But what is a skill?

For more than four decades, developmental psychologist Kurt Fischer and his research colleagues investigated this very question. Together, they developed detailed descriptions of how simple actions evolve into complex skills—and why our ability to use these skills naturally ebbs and flows depending on context and support.

Built upon the pioneering work of renowned child psychologist Jean Piaget, their framework—known as Dynamic Skill Theory—offers a modern, rigorous lens to understand the growth of complex skills.1 Today, Dynamic Skill Theory is a cornerstone of the Science of Learning and Development.2

The Bottom Line: Skill is the capacity to think and act in an organized way in a specific context.3 Context has multiple possible dimensions, such as physical environment, emotional state, social support, subject, and the specific demands of a task. Because skill and context are tightly welded together:

• There are no abstract, context-free skills.

• When we change the context, we change the skill.

• Skill mastery comes from developing proficiency in a skill in a variety of contexts.

Want to dive deeper into the research behind the development of complex skills? Check out our series on the Principles of Skill Building, where we unpack key insights from Dynamic Skill Theory.

Works Cited

Cantor, P., Osher, D., Berg, J., Steyer, L., & Rose, T. (2019). Malleability, plasticity, and individuality: How children learn and develop in context. Applied Developmental Science, 23(4), 307–337.

Fischer, K. W., & Bidell, T. R. (2006). Dynamic development of action and thought. In R. M. Lerner & W. Damon (Eds.), Handbook of child psychology: Theoretical models of human development (6th ed., pp. 313–399). John Wiley & Sons, Inc.

Immordino-Yang, M. H., & Fischer, K. W. (2010). Neuroscience bases of learning. In V. G. Aukrust (Ed.), International encyclopedia of education (3rd Edition, pp. 310–316). Elsevier.

Mascolo, M. F. (2020). Dynamic skill theory: An integrative model of psychological development. In M. F. Mascolo & T. R. Bidell (Eds.), Handbook of integrative developmental science (pp. 91–135). Routledge.

Part of the answer lies in understanding that not all learning follows the same path. Skills generally fall into two distinct categories: constrained and unconstrained.

If you are looking to build, fund, or evaluate programs that truly move the needle for kids, understanding the balance between these two types of skills is critical.

Here is a quick summary of the core concepts covered in the video above:

• Constrained Skills (Finite & Measurable): These are skills with a clear ceiling. Once a child learns them, they are mastered. Examples include learning the alphabet, numbers, phonics, and addition. They are straightforward to teach and assess. They are mostly learned in formal classroom settings.

• Unconstrained Skills (Infinite & Deep): These skills have no ceiling. They develop slowly across a lifetime. Examples include executive function, vocabulary, world knowledge, and mathematical reasoning. They develop from experiences and direct and indirect instruction outside and inside the classroom.

The Bottom Line: From the beginning, constrained and unconstrained skills interact with each other to support proficiency in reading, writing, and mathematics. Children do not just need one or the other—they need to develop both simultaneously to thrive in school and beyond.

Want to dive deeper into the research and data and see the long-term implications of this framework? Check out our series on the Importance of Skill Type for reading, writing, and math achievement.

This is an important topic, so this post is longer than usual. Citations and additional commentary is in the footnotes. (Mouse over the footnotes to read them.)

Thanks to Malai Amfahr, Madison Brown, Kristin Droege, Siobhan O’Loughlin-Reardon, and Kara Richardson for providing feedback on an earlier (and lengthier) draft of this post. Any errors or omissions are entirely my own.

First posted: July 15, 2025

Last updated: April 21, 2026

Three Big Ideas

1. Unconstrained skills, which develop from experiences inside and outside of school, quietly drive reading and math success. They’re largely responsible for the achievement gap.

2. Informal learning organizations—such as museums, libraries, zoos, aquariums, afterschool programs, and extracurricular programs—are uniquely positioned to provide out-of-school experiences that help children and youth build and strengthen unconstrained skills. There’s evidence they’ve already been doing this.

3. Strategically aligned efforts between schools, families, and informal learning organizations offers a promising path to raise reading and math achievement overall and close stubborn achievement gaps.

Families and schools are critically important to children’s learning and development.1 They are the foundation of children and youth’s academic growth and achievement. But a third institution also plays an important role–informal learning organizations.2 A third of school children’s weekly lives is spent in activities other than school, meals, and sleep. Families routinely rely upon out-of-school programs and experiences to fill some of this time.

“Children learn best in active, engaged, constructive, and interactive environments, when the material they are learning is meaningful to them, and when they receive consequential feedback and probing questions.”3

This post focuses on the important role that informal learning plays in children and youth’s learning and skill development. At their best, informal learning organizations excel in creating and providing active, engaged, constructive, interactive, and meaningful experiences. These experiences support children and youth’s learning and development across a range of important outcomes.

In this post, I summarize findings from rigorous empirical research studies about the impact of informal learning organizations on academic achievement. I focus specifically on their ability to build unconstrained skills. This particular type of skill depends upon opportunities to develop inside and outside of school. Unconstrained skills are largely responsible for the achievement gap between student groups. I believe a focus on unconstrained skills is a pressing opportunity to improve K-12 reading and math achievement. Informal learning organizations are uniquely positioned to play an important role to improve these outcomes.

Informal learning is a big tent

The time children and youth spend in the classroom is unquestionably important for their learning and development. It’s also relatively limited. On average, school age children in the U.S. spend 31 of 168 hours per week in school. Add to this the average time for meals (about 8 hours) and sleep (about 67 hours), and this leaves about 60 hours a week for other activities.4

Informal learning is a big tent that includes a variety of organizations, program types, and experiences:

• Afterschool programs with a mix of academic (e.g. reading, math) and enrichment activities (e.g. science, arts, games)

• Botanical gardens and arboretums with opportunities to learn about plants and trees and their habitats

• Extracurricular activities with a specific content focus (e.g. sports, music, art lessons, Scouts)

• Libraries with with opportunities to engage in arts and crafts, STEM projects, reading clubs, and special interest groups

• Museums, art galleries, and historical sites with opportunities to learn about science, social studies, and the humanities

• Zoos and aquariums with opportunities to learn about animals and their habitats

Some experiences have aspects of formal learning – a defined curriculum and activities that feel like an extension of the school day. Engagement is structured and managed by adults. Some informal learning experiences are completely unstructured. Engagement is completely driven by children and youth interests and learning is largely incidental. Other experiences fall somewhere in between.5

How informal learning matters for reading and math

A child learns a good number of facts, procedures, and concepts in the process of becoming proficient in reading and math. Despite important differences, all reading and math skills can be boiled down to two types–constrained and unconstrained.8 Each skill type has a distinct developmental pathway.

Constrained skills involve a relatively limited amount of information.9 Everyone works with the same information.10 Skills like the alphabet, word reading, counting, addition, and subtraction. Mastery is clearly defined for constrained skills. The yardstick for mastery is the same for everyone.11 Constrained skills are relatively straightforward to teach and assess. Constrained skills are mostly learned in formal classroom settings. Most typically developing children master constrained skills within relatively limited amounts of time.12

Unconstrained skills involve much broader amounts of information. Everyone doesn’t have access to the same information. Skills like vocabulary, comprehension, relational thinking, word problem solving, perspective taking, and knowledge. There is no universal finish line for mastery of these skills. There is always the opportunity to learn more. It is not as straightforward to teach and assess unconstrained skills. Unconstrained skills are developed inside and outside of formal classroom settings.13 These skills generally take more time to build than constrained skills.

From an early age, constrained and unconstrained skills interact with and reinforce each other’s development. I’ve described elsewhere the constrained and unconstrained skills that research describes as key components for reading and math development. The development of both types of skills at the same time is critical.14 My review of data over the past 25 years shows that the primary challenge with reading and math achievement overwhelmingly lies with unconstrained skills.

Children need repeated and varied experiences to build proficient skills

Up close, the process of skill-building can look messy. It’s a repeated cycle of building, collapse, and rebuilding. Children build specific skills for specific contexts. “Context” means more than the physical environment. It also includes a child’s emotional state, the external support they receive, the domain or subject area, and the specific task involved.15

In the initial stages of skill-building, a small change in the context can rapidly cause one’s skill level to quickly collapse.16 A child might be able to solve a math problem one day or in one situation but not the next day or a different but otherwise similar situation.17 They might be able to exhibit a skill with one person, but not another. Repetition and exposure to multiple opportunities for skill-building across multiple contexts helps children build and rebuild skills towards mastery.

This is particularly important for unconstrained skills. Skills like vocabulary, inference, perspective taking, inhibition control, and knowledge (facts, procedures, concepts) are both “taught and caught.” They are learned through direct instruction in formal learning settings. They are also learned indirectly through less formal learning opportunities.

Unconstrained skills involve more information to acquire, integrate, and master. These slower-building skills don’t develop as readily on school time (weeks, quarters, semesters, years).18 They are built and reinforced over longer periods through experiences inside and outside of school. Children who participate in out-of-school programs have more varied opportunities to build and rebuild these skills outside of the classroom and home.

Research shows informal learning can build unconstrained skills

My review of rigorous empirical studies find that informal learning programs can build unconstrained skills:

• Afterschool programs: self-perception (self-esteem, self-concept, self-efficacy), problem behaviors (inhibition control), social understanding (perspective taking)19

• Extracurricular activities: math problem solving, reading comprehension, and expressive vocabulary20

• Museums: factual knowledge, conceptual knowledge, critical thinking (e.g. interpretation, evaluation, comparison)21

• Zoos and aquariums: factual knowledge, conceptual knowledge, inhibition control22

Impact on skills is not automatic. It depends upon program quality and the design of the experiences. Too many programs and experiences fail to demonstrate impact under rigorous scrutiny. But it is possible.

I don’t mean to suggest that out-of-school organizations shouldn’t help children and youth develop constrained skills like word-reading or arithmetic. But the comparative advantage of informal learning organizations is their opportunity to help children and youth build different skills in different ways from what they experience in formal classroom settings. Different.

Access to informal learning opportunities is a key challenge

Not all of the roughly 50 million school age children and youth in the United States have the same opportunity for these experiences. Most afterschool and extracurricular activities are paid programs. The majority of families who send their children to these programs are middle income families.23 Families in the top-fifth of household incomes spend about $2,200 annually on out-of-school activities. This is just over three times the $700 spent by families in the bottom-fifth of household incomes.24

Between 1998 and 2020, school-age children in high-income households were much more likely than their peers in low-income households to participate in a range of potential skill-building activities: sports (59% vs 24%), music, dance, and language lessons (41% vs 21%), and organized clubs (24% vs 11%). Over this period, 43% of children and youth from low-income households did not participate in any organized extracurricular activities compared to just 14% of children and youth from high-income households.25

These differences also extend to other informal learning settings. Roughly half of school-aged youth in the United States visit a museum, art gallery, or historical site once or more a year. Children in lower socioeconomic households and those who live in rural areas, however, are less likely to visit museums over their entire childhood.26

There are many organizations working to increase access to quality afterschool programs, summer programs, and expanded learning opportunities.27 Like other issues, progress depends upon policy, funding, and willpower. While we advocate for more support, we can also demonstrate what’s possible with the resources currently in hand.

How we can leverage the power of informal learning to improve reading and math

Informal learning plays an important role in learning and skill-building alongside the classroom and home. Each informal learning experience contains the seed of opportunity to build and strengthen a number of unconstrained skills. Here are seven ideas to leverage the superpower of informal learning to improve reading and math achievement.

1: Take skills seriously. We should use research insights from developmental psychologists about how skills work to inform the design of programs and experiences for children and youth. Elsewhere I’ve summarized a set of key principles about skills and skill-building.

2: Take skill-building seriously. Researchers find programs that involve supervised practice – “practicing new skills in the presence of someone who can observe and provide feedback to ensure its optimal adoption and application” – are more effective than programs with unsupervised practice.28 Impactful afterschool programs are active, focused, and explicit regarding skill-building.29 In other words, they use active forms of learning to support skill-building, have at least one component of their program focused on developing skills, and have clear and explicit learning objectives related to skill growth.30 Programs with these components have shown impact on a range of academic and non-academic outcomes.

3: Focus on unconstrained skills. Research studies provide examples of how a single well-designed informal learning experience can boost unconstrained skills:

• Conversation cards that structured a museum visit increased dialogue between preschool children and parents, transfer of knowledge across exhibits, and increased knowledge acquisition up to two weeks afterwards.31

• Guided visits during trips to the zoo supported increased learning and knowledge acquisition.32

• The combination of activities prior to and after field trips to zoos, aquariums, and museums positively impacted student interest and knowledge acquisition.33

• Hands-on activities during visits to zoos and aquariums increased students’ cognitive engagement and knowledge-building.34

• The combination of strategically-designed worksheets, social interaction, and free choice increased knowledge acquisition during a museum visit.35

• Guided discussion about art works during museum visits increased critical thinking skills up to three weeks later.36

And this impact is not necessarily short-lived. For example, researchers find that under the right conditions, the impact of visits to zoos and aquariums on children’s knowledge can last from months to years.37

4: Build systems to support unconstrained skills. Supporting individual organizations is good. Building systems of informal learning is even better. The FrameWorks Institute offers the metaphor of “charging stations” as a way to think about this:

“We want to make sure that people in our community are a part of high wattage, densely networked charging systems that support early childhood development. That’s why we need to build a network of connected charging stations that includes daycares, pre-kindergarten (pre-K), libraries, museums, science centers, and afterschool programs so that young children have lots of opportunities to charge up their development.”38

Some children and youth live in neighborhoods full of charging stations: libraries, sports fields, organized clubs, community centers. Others have less ready access to “charge up.” This means fewer opportunities to build and rebuild skills across multiple settings. The Forum for Youth Investment offers a roadmap for designing community-level systems of support.

5: Let informal learning be informal. Informal learning organizations don’t have to look like school to make an impact. They don’t have to follow a curriculum (though they can if they want). Informal learning organizations don’t have to cover a set of grade-level state standards each year. They can directly engage children and youth’s interests and curiosity. Children and youth can practice hobbies and favorite activities or discover new ones. They can move at their own pace. Let informal learning do what it’s good at. Awe and wonder. Fun and joy. Love of learning. Let the goose lay the golden eggs.

6: Rethink alignment between formal and informal learning. Alignment does not mean that informal learning organizations should replicate the structures and work of school systems. It means combining the strengths of formal education with those of informal learning. In “all-day schools” in European countries such as Germany, Finland, Greece, Spain, and Croatia, learning seamlessly shifts from formal classroom instruction at the end of the academic day to informal extracurricular activities after school.39 The Learn Everywhere initiative in New Hampshire gives academic credit for student experiences outside of school, such as music lessons, karate classes, robotics clubs, and foreign language classes. Creating stronger linkages between formal and informal learning gives more children and youth more opportunities to build constrained and unconstrained skills at the same time.

7: Rethink impact and outcome measurement. Greater focus on unconstrained skills and system-building requires different approaches to impact and outcome measurement. We need to make sure assessments are appropriate for efforts focused on unconstrained skills. We should also include as outcomes key drivers of skill-building, like wonder, awe, interests, motivation, and self-beliefs. We also will need to rethink time; it may take longer to see impact than a semester or academic year.40 Our theories of change should explicitly mention skill-building. For example, the QuEST (Quality, Engagement, Skills, and Transfer) program logic model from the Forum for Youth Investment helps organizations identify which skills they are trying to grow and how likely the qualities of the program experience they provide will grow those skills. There are also multiple observation tools for out-of-school programs that include a review of skill-building program features among other program components.

Unconstrained skill is a powerful lever to improve reading and math achievement

“To move the boulder, you need to be smart and strategic. Because of the complexity you face, you can’t change everything. You can’t change most things. You can’t even change a respectable fraction of things! But with a bit of prodding and catalyzing, you can change something. A well-chosen something. We’ll call that “well-chosen something” a Leverage Point (a term popularized by the systems theorist Donella Meadows).” Dan Heath, Reset: How to change what’s not working

Envisioning K-12 reading and math achievement as a boulder might conjure up the image of poor Sisyphus. Each morning he rolled a boulder up a hill only to see it roll back to the bottom at the end of the day. When it comes to metaphors about moving boulders, I’m more of an Archimedes guy. I am looking for a lever and a place to stand.

The research and data I’ve seen screams out that a focus on building children and youth’s unconstrained skills is a powerful leverage point. In Dan Heath’s words, it’s well-chosen. Families and schools are obvious places to focus this lever.41 But informal learning organizations are important places to focus efforts, too.

Families and schools routinely rely upon informal learning organizations. Families sign up their children for extracurricular activities, after school programs, and summer camps. Families take their children to the zoo, children’s museum, and science center. Schools regularly send classes on field trips to zoos, aquariums, science centers, and museums.

Working together with families and schools, informal learning organizations offer a promising path toward improved reading and math achievement. Each visit to an afterschool program, extracurricular activity, zoo, aquarium, library, or museum has the power to be a transformative, skill-building experience.

But wait, there’s more

• What are skills?

• An overview of constrained and unconstrained skills.

• Two skill types, two developmental pathways

• The science of skill building

Works Cited

After-school Alliance. (2022). America after 3PM: Demand grows, opportunity shrinks. After-School Alliance.

Akiva, T., Cortina, K. S., Eccles, J. S., & Smith, C. (2013). Youth belonging and cognitive engagement in organized activities: A large-scale field study. Journal of Applied Developmental Psychology, 34(5), 208–218.

Andre, L., Durksen, T., & Volman, M. L. (2017). Museums as avenues of learning for children: a decade of research. Learning Environments Research, 20(1), 47–76.

Auger, A., Pierce, K. M., & Vandell, D. L. (2013, April 20). Narrowing the achievement gap: Consistency and intensity of structured activities during elementary school. Biennial meeting of the Society for Research in Child Development, Seattle, WA.

Bowen, D. H., Greene, J. P., & Kisida, B. (2014). Learning to think critically: A visual art experiment. Educational Researcher, 43(1), 37–44.

Caetano, C., Caetano, G., & Nielsen, E. (2020). Should children do more enrichment activities? Leveraging bunching to correct for endogeneity (Nos. 2020–036; Finance and Economics Discussion Series). Board of Governors of the Federal Reserve System.

Cantor, P., Osher, D., Berg, J., Steyer, L., & Rose, T. (2019). Malleability, plasticity, and individuality: How children learn and develop in context. Applied Developmental Science, 23(4), 307–337.

Christensen, K. M., Assink, M., van Dam, L., Stams, G.-J., Poon, C. Y. S., Astesano, J., & Rhodes, J. E. (2024). Youth interventions with and without supervised practice: A second-order meta-analysis. Child and Adolescent Social Work Journal, 41(5), 769–780.

Christensen, K. M., Kremer, K. P., Poon, C. Y. S., & Rhodes, J. E. (2023). A meta-analysis of the effects of after-school programmes among youth with marginalized identities. Journal of Community and Applied Social Psychology, 33(4), 882–913.

Clark, R. E., & Saxberg, B. (2018). Engineering motivation using the belief-expectancy-control framework. Interdisciplinary Education and Psychology, 2(1), 1–26.

Collins, C. (2024). Maximizing zoological education and learning experiences. In Human-animal interactions in zoos (pp. 180–191).

Collins, C., Corkery, I., McKeown, S., McSweeney, L., Flannery, K., Kennedy, D., & O’Riordan, R. (2020). An educational intervention maximizes children’s learning during a zoo or aquarium visit. The Journal of Environmental Education, 51(5), 361–380.

Collins, C., McKeown, S., McSweeney, L., Flannery, K., Kennedy, D., & O’Riordan, R. (2021). Children’s conversations reveal in-depth learning at the zoo. Anthrozoös, 34(1), 17–32.

Collins, C., Quirke, T., McKeown, S., Flannery, K., Kennedy, D., & O’Riordan, R. (2019). Zoological education: Can it change behaviour? Applied Animal Behaviour Science, 220, 104857.

Collins, C., & O’Riordan, R. (2022). Data triangulation confirms learning in the zoo environment. Environmental Education Research, 28(2), 295–317.

Crispin, L. M., & Beck, M. I. (2025). Disparities in museum attendance among youth over two decades: an empirical analysis of who attends and how often. Arts Education Policy Review, 126(1), 25–37.

Durlak, J. A., & Weissberg, R. P. (2007). The impact of after-school programs that promote personal and social skills. Collaborative for Academic, Social, and Emotional Learning.

Durlak, J. A., Weissberg, R. P., & Pachan, M. (2010). A meta-analysis of after-school programs that seek to promote personal and social skills in children and adolescents. American Journal of Community Psychology, 45(3), 294–309.

Eccles, J., & Gootman, J. A. (2002). Community programs to promote youth development. National Academy Press.

Fischer, K. W., & Bidell, T. R. (2006). Dynamic development of action and thought. In R. M. Lerner & W. Damon (Eds.), Handbook of child psychology: Theoretical models of human development (6th ed., pp. 313–399). John Wiley & Sons, Inc.

Fischer, K. W., & Immordino-Yang, M. H. (2002). Cognitive development and education: From dynamic general structure to specific learning and teaching. In E. Lagemann (Ed.), Traditions of scholarship in education. Spencer Foundation.

Fredricks, J. A., Naftzger, N., Smith, C., & Riley, A. (2017). Measuring youth participation, program quality, and social and emotional skills in after-school programs. In N. L. Deutsch (Ed.), After-school programs to promote positive youth development: Integrating research into practice and policy, volume 1 (pp. 23–43). Springer International Publishing.

Granger, R. C., Durlak, J., Yohalem, N., & Reisner, E. (2007). Improving after-school program quality. William T. Grant Foundation.

Granger, R. C. (2010). Understanding and improving the effectiveness of after-school practice. American Journal of Community Psychology, 45(3), 441–446.

Greene, J. P., Kisida, B., & Bowen, D. H. (2014). The educational value of field trips. Education Next, 14(1), 78–86.

Heath, D. (2025). Reset: How to change what’s not working. Simon & Schuster.

Hofferth, S. L., & Sandberg, J. F. (2001). How American children spend their time. Journal of Marriage and Family, 63(2), 295–308.

Hutton, R., & Nalamada, P. (2020). Shaping positive summertime experiences for all

youth to promote healthy development. Journal of Youth Development, 15(3).

Immordino-Yang, M. H., & Fischer, K. W. (2010). Neuroscience bases of learning. In V. G. Aukrust (Ed.), International encyclopedia of education (3rd Edition, pp. 310–316). Elsevier.

Jant, E. A., Haden, C. A., Uttal, D. H., & Babcock, E. (2014). Conversation and object manipulation influence children’s learning in a museum. Child Development, 85(5), 2029–2045.

Jensen, E. (2014). Evaluating children’s conservation biology learning at the zoo. Conservation Biology, 28(4), 1004–1011.

Jensen, E. A., Moss, A., & Gusset, M. (2017). Quantifying long-term impact of zoo and aquarium visits on biodiversity-related learning outcomes. Zoo Biology, 36(4), 294–297.

Johnson, M., & Majewska, D. (2022). Formal, non-formal, and informal learning: What are they, and how can we research them? Cambridge University Press & Assessment Research Report.

Kahneman, D. (2011). Thinking, fast and slow. Farrar, Straus and Giroux.

Kim, J. S., Gilbert, J. B., Relyea, J. E., Rich, P., Scherer, E., Burkhauser, M. A., & Tvedt, J. N. (2024). Time to transfer: Long-term effects of a sustained and spiraled content literacy intervention in the elementary grades. Developmental Psychology, 60(7), 1279–1297.

Kim, J., Gilbert, J., Yu, Q., & Gale, C. (2021). Measures matter: A meta-analysis of the effects of educational apps on preschool to grade 3 children’s literacy and math skills. AERA Open, 7(1), 1–19.

Kisida, B., Bowen, D. H., & Greene, J. P. (2016). Measuring Critical Thinking: Results From an Art Museum Field Trip Experiment. Journal of Research on Educational Effectiveness, 9, 171–187.

Krombaβ, A., & Harms, U. (2008). Acquiring knowledge about biodiversity in a museum — are worksheets effective? Journal of Biological Education, 42(4), 157–163.

Lauer, P. A., Akiba, M., Wilkerson, S. B., Apthorp, H. S., Snow, D., & Martin-Glenn, M. L. (2006). Out-of-school-time programs: A meta-analysis of effects for at-risk students. Review of Educational Research, 76(2), 275–313.

Lee, H., Stern, M. J., & Powell, R. B. (2020). Do pre-visit preparation and post-visit activities improve student outcomes on field trips? Environmental Education Research, 26(7), 989–1007.

Leftwich, M., & Haywood, C. (2016). The littlest historians: Early years programming in history museums. Journal of Museum Education, 41(3), 152–164.

Lynch, K., An, L., & Mancenido, Z. (2023). The impact of summer programs on student mathematics achievement: A meta-analysis. Review of Educational Research, 93(2), 275–315.

Lynch, K., Lanteri, L., An, L., Mancenido, Z., & Richardson, J. (2025). The effects of summer learning on social-emotional and behavioral outcomes: A meta-analysis. Social and Emotional Learning: Research, Practice, and Policy, 5.

Mahoney, J. L., Parente, M. E., & Zigler, E. F. (2010). After-school program participation and children’s development. In Handbook of research on schools, schooling and human development (pp. 379–397). Routledge.

McCombs, J. S., Augustine, C. H., Unlu, F., Ziol-Guest, K. M., Naftel, S., Gomez, C. J., Marsh, T., Akinniranye, G., & Todd, I. (2019). Investing in successful summer programs: A review of evidence under the every student succeeds act.

McCormick, M. P., Weissman, A. K., Weiland, C., Hsueh, J., Sachs, J., & Snow, C. (2020). Time well spent: Home learning activities and gains in children’s academic skills in the prekindergarten year. Developmental Psychology, 56(4), 710.

Muir, D., Orlando, C., & Newton, B. (2024). Impact of summer programmes on the outcomes of disadvantaged or ‘at risk’ young people: A systematic review. Campbell Systematic Reviews, 20(2), e1406.

National Academies of Sciences, Engineering, and Medicine. (2019). Shaping summertime experiences: Opportunities to promote healthy development and well-being for children and youth. National Academies Press.

National Institute of Child Health and Human Development Early Child Care Research Network. (2004). Are child developmental outcomes related to before- and after-school care arrangements? Results from the NICHD study of early child care. Child Development, 75(1), 280–295.

Neild, R. C., Wilson, S. J., & McClanahan, W. (2019). Afterschool programs: A review of evidence under the every student succeeds act. Research for Action.

O’Neil, M., Pineau, M. G., Moyer, J., & Stevens, A. (2019). Framing family, school, and community engagement in early childhood: A FrameWorks brief.

Paris, S. G. (2005). Reinterpreting the development of reading skills. Reading Research Quarterly, 40(2), 184–202.

Payton, J., Weissberg, R. P., Durlak, J. A., Dymnicki, A. B., Taylor, R. D., Schellinger, K. B., & Pachan, M. (2008). The positive impact of social and emotional learning for kindergarten to eighth-grade students: Findings from three scientific reviews. Collaborative for Academic, Social, and Emotional Learning.

Peterson, T. K., & Vandell, D. L. (2021). The evidence base for summer enrichment and comprehensive afterschool opportunities. Collaborative Communications.

Pianta, R., Purtell, K., McCormick, M., Knoche, L., Burchinal, M., Ludvik, D., & Peisner-Feinberg, E. (2021). Sustaining the pre-k boost: Skill type matters. Early Learning Network-University of Nebraska-Lincoln.

Rock, D. A., & Pollack, J. M. (2002). Early childhood longitudinal study-kindergarten class of 1998–99 (ECLS–K), psychometric report for kindergarten through first grade (NCES 2002–05). National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education.

Rogoff, B., Callanan, M., Gutiérrez, K. D., & Erickson, F. (2016). The organization of Informal learning. Review of Research in Education, 40(1), 356–401.

Roth, J. L., & Brooks-Gunn, J. (2003). What exactly is a youth development program? Answers from research and practice. Applied Developmental Science, 7(2), 94–111.

Roth, J. L., & Brooks-Gunn, J. (2016). Evaluating youth development programs: Progress and promise. Applied Developmental Science, 20(3), 188–202.

Russell, J. L., Knutson, K., & Crowley, K. (2013). Informal learning organizations as part of an educational ecology: Lessons from collaboration across the formal-informal divide. Journal of Educational Change, 14(3), 259–281.

Schilbert, J., & Scheersoi, A. (2023). Learning outcomes measured in zoo and aquarium conservation education. Conservation Biology, 37(1), e13891.

Shernoff, D. J. (2010). Engagement in after-school programs as a predictor of social competence and academic performance. American Journal of Community Psychology, 45(3), 325–337.

Smith, C., Akiva, T., McGovern, G., & Peck, S. C. (2014). Afterschool quality. New Directions for Youth Development, 2014(144), 31–44.

Smith, C., & McGovern, G. (2014). The QuEST model: Out-of-school time contexts and individual-level change. Forum for Youth Investment.

Snow, C. E., & Matthews, T. J. (2016). Reading and language in the early grades. The Future of Children, 57–74.

Song, L., Golinkoff, R. M., Stuehling, A., Resnick, I., Mahajan, N., Hirsh-Pasek, K., & Thompson, N. (2017). Parents’ and experts’ awareness of learning opportunities in children’s museum exhibits. Journal of Applied Developmental Psychology, 49, 39–45.

Souto-Otero, M. (2024). Bringing formal and nonformal learning closer together: A reflection on crossovers in curriculum, pedagogy, assessment and learning environments. In M. Pilz (Ed.), Informal learning in vocational education and training (pp. 65–89). Springer Fachmedien Wiesbaden.

Stafford-Brizard, K. B. (2016). Nonacademic skills are the necessary foundation for learning. Education Week. Retrieved from http://www.edweek.org/ew/articles/2016/

07/21/nonacademic-skills-are-the-necessary-foundationfor.html

Stahl, K. A. D. (2011). Applying new visions of reading development in today’s classrooms. The Reading Teacher, 65(1), 52–56.

Vandell, D. L., & Gülseven, Z. (2023). The study of early child care and youth development (SECCYD): Studying development from infancy to adulthood. Annual Review of Developmental Psychology, 5, 331–354.

Vandell, D. L., Lee, K. T. H., Whitaker, A. A., & Pierce, K. M. (2020). Cumulative and differential effects of early child care and middle childhood out-of-school time on adolescent functioning. Child Development, 91(1), 129–144.

Vandell, D. L., & Simpkins, S. D. (2024). Organized afterschool activities as a developmental context for children and adolescents. In J. J. Lockman (Ed.), Advances in child development and behavior (Vol. 67). Academic Press.

Weisberg, D. S., Hirsh-Pasek, K., & Golinkoff, R. M. (2013). Guided play: Where curricular goals meet a playful pedagogy. Mind, Brain, and Education, 7(2), 104–112.

Whitesell, E. R. (2016). A day at the museum: The impact of field trips on middle school science achievement. Journal of Research in Science Teaching, 53(7), 1036–1054.

Xie, C., Neitzel, A., Cheung, A., & Slavin, R. E. (2020). The effects of summer programs on K-12 students’ reading and mathematics achievement: A meta-analysis.

Yohalem, N., & Wilson-Ahlstrom, A. (2010). Inside the black box: Assessing and improving quality in youth programs. American Journal of Community Psychology, 45(3), 350–357.

Yohalem, N., Wilson-Ahlestrom, A., Fischer, S., & Shinn, M. (2009). Measuring youth program quality: A guide to assessment tools, Second Edition. The Forum for Youth Investment.

Young, S., Eadie, T., Suda, L., & Church, A. (2022). LEARN: Essential elements of museum education programs for young children. Curator: The Museum Journal, 65(1), 209–223.

I am also in the planning stages of developing a standalone site of the same name that will provide open-source resources to support the development of unconstrained skills inside and outside of the classroom. I will make updates as needed.

First posted: July 24, 2026

[Backdated to June 14, 2025 so this post appears first in the series.]

First posted: June 4, 2025

Last updated: July 24, 2026

Key Takeaway

Skill is the capacity to think and act in an organized way in a specific context (Immordino-Yang and Fischer, 2010). Building new skills is a journey. The terrain is full of growth spurts, drops, and plateaus. While new learners have the most ups and downs, even experts will experience the occasional drops in skill levels as they acquire new knowledge and skills. Skill building is a cycle of building, collapse, and rebuilding. Skills develop on two simultaneous tracks: short-term changes that can appear more chaotic and long-term changes that appear as sudden jumps in ability. There is no single way to build skills.

Skill building is messy. It doesn’t follow a single, tidy pathway. Instead, skill development moves in a continuous cycle of construction, collapse, and reconstruction. As we saw in Principle 1, skills are organized in a hierarchy from simpler lower-level skills to more complex higher-level skills. When we develop new skills we rebuild the very structure of skills.

“People build a skill and then repeatedly rebuild it in a wavelike pattern of construction and reconstruction, not in a straight line or monotonic upward progression. Encountering a new task or situation, people first move down to a low level of complexity…They then gradually build a more complex skill for coping with the task by repeatedly rebuilding it with variations” (Fischer & Bidell, 2006).

Since skills are so tightly welded to context, even a minor disturbance—a dip in motivation, a spike in frustration, or a change in scenery—can cause a newly formed skill to temporarily collapse. For beginners, this process looks incredibly chaotic. But even seasoned experts experience drops when they learn something new. The difference is that these drops tend to be smaller and short-lived (Fischer & Bidell, 2006; Fischer, 2008). Regardless of age, domain, or expertise, everyone experiences this pattern of construction and reconstruction when learning new skills.

Growth curves for learning a new task. Source: Fischer (2008).

Short-and long-term skill building

Watching children and youth develop skills can sometimes look like climbing a ladder. At other times it can look like a wild roller coaster ride. This conflicting picture appears because we build skills simultaneously on two parallel tracks:

• Moment-to-Moment Construction: This is the rapid, real-time process of skill building that occurs in increments as small as minutes or hours when a child actively tackles a specific problem. Small scale changes stem from developing skills for specific contexts, tasks, or problems (Fischer and Granott, 1995; Fischer and Bidell, 2006). On this track, skill is highly unstable. We can see the looped roller coaster ride of quick jumps in ability followed by sudden drops of competence.

• Long-Term Growth: This is the large-scale change in ability that unfolds gradually over months and years, shaping a child’s overall capability as they grow up. This long-term progress quietly gathers all those tiny, moment-to-moment changes and weaves them together. Skill building often shows up as sudden, massive leaps up a ladder in broad skill mastery across multiple environments (Fischer and Yan 2002; Fischer and Bidell, 2006).

Long-term skill mastery isn’t a separate process from short-term changes—it is the sum total of those smaller moments built up over time (Granott, 2002). At the same time, a child’s overall skill bandwidth (as described in Principle 6) sets the boundaries for how they perform in specific real-world contexts. Every time a child struggles in real-time, steps backward, and tries a new strategy, they are laying the foundation for a larger, more complex skill down the road.

No single approach for skill building

There is no single “right” approach for skill building, no standardized method for twisting individual threads into thick, versatile skill ropes. Multiple paths lie open to every child (Cantor et al., 2019; Immordino-Yang and Fischer, 2010). While there may be popular ways of teaching, the science of learning and development proves that children can arrive at the exact same destination of mastery using entirely different pathways.1

Children and youth benefit from a variety of opportunities to build skills in formal and informal learning settings, across the classroom, community, and home. Without these varied opportunities, children easily fall behind what they are truly capable of achieving, and their progress stalls. This is particularly important for unconstrained skills, which develop from direct and indirect instruction and experiences inside and outside of the classroom.

But wait, there’s more

• Insights about the other 6 principles of skill building.

• The skills that quietly drive PK-12 math and reading achievement.

Works Cited

Cantor, P., Osher, D., Berg, J., Steyer, L., & Rose, T. (2019). Malleability, plasticity, and individuality: How children learn and develop in context. Applied Developmental Science, 23(4), 307-337.

Fischer, K. W. (2008). Dynamic cycles of cognitive and brain development: Measuring growth in mind, brain, and education. In A. M. Battro, K. W. Fischer, & P. Léna (Eds.), The educated brain (pp. 127–150). Cambridge University Press.

Fischer, K. W., & Bidell, T. R. (2006). Dynamic development of action and thought. In R. M. Lerner & W. Damon (Eds.), Handbook of child psychology: Theoretical models of human development (6th ed., pp. 313–399). John Wiley & Sons, Inc.

Fischer, K. W., & Granott, N. (1995). Beyond one-dimensional change: Parallel, concurrent, socially distributed processes in learning and development. Human Development, 38(6), 302-314.

Fischer, K. W., & Yan, Z. (2002). Darwin's construction of the theory of evolution: Microdevelopment of explanations of variation and change in species. In N. Granott & J. Parziale (Eds.), Microdevelopment: Transition processes in development and learning. Cambridge University Press.

Granott, N. (2002). How microdevelopment creates macrodevelopment: Reiterated sequences, backward transitions, and the Zone of Current Development. In N. Granott & J. Parziale (Eds.), Microdevelopment: Transition processes in development and learning. Cambridge University Press.

Immordino-Yang, M. H., & Fischer, K. W. (2010). Neuroscience bases of learning. In V. G. Aukrust (Ed.), International encyclopedia of education (3rd Edition, pp. 310–316). Elsevier.

First posted: June 4, 2025

Last updated: July 24, 2026

Key Takeaway

Skill is the capacity to think and act in an organized way in a specific context (Immordino-Yang and Fischer, 2010). The developmental range is the difference in a person’s skill level with social support (optimal level) and without support (independent level). It is the elastic ability to use a wider range of skill that ultimately distinguishes children and youth with highly proficient skills. With the right amount of challenge, rigor, feedback, and support, we can intentionally help children expand their developmental range (Cantor et al., 2019).

As we saw in Principle 1, skill is the capacity to think and act in an organized way in a specific context (Immordino-Yang and Fischer, 2010). Context involves many factors at once, such as the environment, emotional state, and activity. One of the key features of context is the degree of support to engage in an activity. We routinely demonstrate different levels of ability depending upon the support we receive. For example, consider the difference in ability in cooking an unfamiliar dish. Our skill is drastically different with a well-written recipe or video on YouTube than fumbling around on our own.

This difference between a person’s ability with and without support is known as the developmental range (Fischer & Bidell, 2006). This is the space between the dotted blue line (independent skill level) and the solid red line (optimal skill level) in this graphic.

Everything up to the blue line represents skills the person can already perform effortlessly on their own. The range between the blue and red lines highlights the power of environmental support to stretch performance to its upper limit. This is one of the most important ideas in skill building. Our skill level constantly moves across this range.

“Skills are not all or none: A person does not suddenly move from not being able to perform a task to performing it well. Instead, a person’s skills vary frequently between two upper limits – a functional level, the most complex performance that a child or adult performs without support, and an optimal level, the most complex performance that she or he performs with explicit support, such as through modeling or priming.” (Fischer and Immordino-Yang, 2002)

Educators will recognize shades of Lev Vygotsky’s classic Zone of Proximal Development (ZPD) here, but there is an important difference. The ZPD focuses primarily on the potential for growth–the “sweet spot” for instruction that exists at the space a learner cannot do alone but can master with help from a more knowledgeable person. The developmental range, however, focuses on the variability of performance across different contexts. A person’s skill level isn’t a fixed point but a range that fluctuates based on support and familiarity.

Elevating the developmental range

When children and youth have the opportunity to build and practice skills in conditions of high support—emotional engagement, structured activities, familiar tasks, high motivation, co-development of skills with others—their ability is closer to the red line. They are able to experience a level of skill complexity that they could not accomplish on their own. In the right circumstances, well-designed instructional materials and resources can provide this type of external support.

When this support is removed, however, their skill level falls down towards the blue line. Repeated exposure to this type of experience over time raises their independent skill levels. In other words, lots of experience closer to the red line helps pull up the skill level of the blue line.

When children take standardized tests, we are measuring their ability at their independent level–the blue line. In conditions of stress or gripped with negative emotions, it’s possible to perform below this level. Not every task or everyday problem requires the absolute ceiling of our capabilities. Yet, it is the elastic ability to use a wider range of skill that ultimately distinguishes children and youth who have higher levels of reading and mathematics achievement from their peers. In other words, their abilities are woven together tightly—giving them thicker, more resilient “skill ropes” that don’t easily snap under pressure (Fischer et al., 1993; Fischer, 2008; Mascolo & Fischer, 2010; Cantor et al., 2019).

Elevating this developmental range—and accelerating a youth's growth within it—is one of the most critical responsibilities shared by schools, out-of-school programs, and families alike. Children need opportunities to build, practice, and refine skills in a variety of contexts to build durable, flexible skills. By engineering the right mixture of challenge, rigor, feedback, and support, we can help children develop these skills to meet a wide range of demands in a rapidly changing world (Cantor et al., 2019).

But wait, there’s more

• Insights about the other 6 principles of skill building.

• The skills that quietly drive PK-12 math and reading achievement.

Works Cited

Cantor, P., Osher, D., Berg, J., Steyer, L., & Rose, T. (2019). Malleability, plasticity, and individuality: How children learn and develop in context. Applied Developmental Science, 23(4), 307–337.

Fischer, K. W. (2008). Dynamic cycles of cognitive and brain development: Measuring growth in mind, brain, and education. In A. M. Battro, K. W. Fischer, & P. Léna (Eds.), The educated brain (pp. 127–150). Cambridge University Press.

Fischer, K. W., & Bidell, T. R. (2006). Dynamic development of action and thought. In R. M. Lerner & W. Damon (Eds.), Handbook of child psychology: Theoretical models of human development (6th ed., pp. 313–399). John Wiley & Sons, Inc.

Fischer, K. W., Bullock, D. H., Rotenberg, E. J., & Raya, P. (1993). The dynamics of competence: How context contributes directly to skill. In R. Wozniak & K. Fischer (Eds.), Development in context: Acting and thinking in specific environments. Lawrence Erlbaum Associates.

Fischer, K. W., & Immordino-Yang, M. H. (2002). Cognitive development and education: From dynamic general structure to specific learning and teaching. In E. Lagemann (Ed.), Traditions of scholarship in education. Spencer Foundation.

Immordino-Yang, M. H., & Fischer, K. W. (2010). Neuroscience bases of learning. In V. G. Aukrust (Ed.), International encyclopedia of education (3rd Edition, pp. 310–316). Elsevier.

Mascolo, M. F., & Fischer, K. W. (2010). The dynamic development of thinking, feeling, and acting over the lifespan. In R. M. Lerner (Ed.), Handbook of life-span development (Vol. 1, pp. 149–194). Wiley.

First posted: June 4, 2025

Last updated: July 24, 2026

Key Takeaway

Skill is the capacity to think and act in an organized way in a specific context (Immordino-Yang and Fischer, 2010). It is impossible to learn or build skills if we are not motivated. Motivation is deeply intertwined with emotion, which is the body’s fuel for learning and skill building. Motivation stems from positive emotions about the value of an activity, personal expectations for success, and belief that we can influence the outcome. Motivation is an important part of the context for skill building.

Three core acts are required to build a new skill (Clark & Saxberg, 2018):

1. First, we have to start. We have to take the initial, crucial steps to begin to learn something new. This requires overcoming the immediate friction that stands between us and a new skill. The barrier could be external—like finding the right program, a mentor, or transportation. Or the barrier could be internal—hesitance, doubt, or simple inertia.

2. Second, once we start we have to persist. We have to continue our efforts to build the skill once the initial novelty wears off. This involves protecting our attention in the face of distractions or challenges, such as resisting the urge to check our smartphone or pushing past the immediate frustration of hitting a wall or an unexpected setback.

3. Finally, we have to invest sufficient mental effort. We don’t build skills by merely going through the motions. Building automated skills requires deliberate practice (Willingham, 2004). We have to learn from successes and failures to wire and rewire our mental circuitry.

In other words, we have to be motivated to build skill. Motivation is the process of starting, persisting, and investing sufficient mental effort to achieve a goal in a reasonable time (Clark & Saxberg, 2018).

For adolescents and adults, it’s conservatively estimated that motivation accounts for at least 30% of learning (Cantor et al., 2019). Motivation is described as “indispensable” for school success. It is suggested that motivation possibly matters more than intellectual ability (Dweck et al., 2011; Sternberg, 2017). As psychologist Richard Clark explains, “without motivation, even the most capable expert will fail” (Clark, 2006).

Motivation is deeply entwined with emotions (Meyer and Turner, 2006; Immordino-Yang and Damasio, 2007; Hardway, 2020). Our beliefs about the value of a task, our expectations for success, and how much control we feel we have–key components of motivation–are deeply connected to our feelings.

Strong negative emotions can overwhelm our mental capacity needed to build and practice skills (Clark & Saxberg, 2018). Negative emotions like anger, fear, and depression can lead to focus on past failures and lower beliefs about what’s possible in future attempts. As Richard Clark warns us, this is “one of the biggest killers of motivation” (Clark, 2003).

“Motivation nudges us to convert intention into action. It pushes us to start doing something new or to restart something that we have stopped. It controls our decision to persist at a specific work goal in the face of distractions and competing priorities. It leads us to invest more or less mental and physical effort to enhance both the quality and quantity of our work.” (Clark, 2006)

Motivation operates differently for children and youth

A trap we must avoid is assuming that motivation for children and youth operates the same as adults. For adults in a workplace setting, financial incentives and other tangible rewards are a highly effective way to drive performance (Clark, 2003). But children and youth appear to operate differently.

A major experimental study in three large urban districts paid students for reading books, performance on interim exams, or for classroom grades. All three approaches failed to make an impact on student achievement (Fryer, 2011). Psychologist David Yeager suggests that young people ages 10 to 25 are heavily motivated by non-financial incentives: status and respect (Yeager, 2024).

Both of these rewards are heavily social in nature, rooted in the interactions we discussed in Principle 3 and emotional connections described in Principle 4. Having a sense of control over success or failure is an important part of motivation for children, youth, and adults.

To help children and youth generate and maintain motivation for skill building involves helping them develop positive answers to three key questions (Clark & Saxberg, 2018):1

• Why do I care? (Value of the activity)

• Can I do this? (Personal expectation of success)

• Do I dictate the outcome? (Sense of control or autonomy)

But wait, there’s more

• Insights about the other 6 principles of skill building.

• The skills that quietly drive PK-12 math and reading achievement.

Works Cited

Cantor, P., Osher, D., Berg, J., Steyer, L., & Rose, T. (2019). Malleability, plasticity, and individuality: How children learn and develop in context. Applied Developmental Science, 23(4), 307–337.

Clark, R. E. (2003). Fostering the work motivation of individuals and teams. Performance Improvement, 42(3), 21–29.

Clark, R. E. (2006). Motivating individuals, teams, and organizations. In J. A. Pershing (Ed.), Handbook of human performance technology: Principles, practices, and potential (Third, pp. 478–497). Pfeiffer.

Clark, R. E., & Saxberg, B. (2018). Engineering motivation using the belief-expectancy-control framework. Interdisciplinary Education and Psychology, 2(1).

Dweck, C. S., Walton, G. M., & Cohen, G. L. (2011). Academic tenacity: Mindsets and skills that promote long-term learning. Gates Foundation.

Fryer, R. G., Jr. (2011). Financial incentives and student achievement: Evidence from randomized trials. The Quarterly Journal of Economics, 126(4), 1755–1798.

Hardway, C. (2020). Of interest and engagement: The emotional force of learning and development. In M. F. Mascolo & T. R. Bidell (Eds.), Handbook of integrative developmental science: Essays in honor of Kurt W. Fischer (pp. 232-261). Routledge.

Immordino-Yang, M. H., & Damasio, A. (2007). We feel, therefore we learn: The relevance of affective and social neuroscience to education. Mind, Brain, and Education, 1(1), 3–10.

Immordino-Yang, M. H., & Fischer, K. W. (2010). Neuroscience bases of learning. In V. G. Aukrust (Ed.), International encyclopedia of education (3rd Edition, pp. 310–316). Elsevier.

Meyer, D. K., & Turner, J. C. (2006). Re-conceptualizing emotion and motivation to learn in classroom contexts. Educational Psychology Review, 18(4), 377–390.

Sternberg, R. J. (2017). Intelligence and competence in theory and practice. In A. J. Elliot, C. S. Dweck, & D. S. Yeager (Eds.), Handbook of competence and motivation: Theory and application (Second). The Guilford Press.

Willingham, D. T. (2004). Ask the cognitive scientist: Practice makes perfect—But only if you practice beyond the point of perfection. American Educator, 28(1), 31–39.

Yeager, D. S. (2024). 10 to 25: The science of motivating young people: A groundbreaking approach to leading the next generation-and making your own life easier. Avid Reader Press.

First posted: June 4, 2025

Last updated: July 24, 2026

Key Takeaway

Skill is the capacity to think and act in an organized way in a specific context (Immordino-Yang and Fischer, 2010). Emotion is the body’s fuel for skill building. We do not pay attention to things we do not feel something about. And if we do not pay attention, we cannot build skill. We can help children and youth build complex skills by connecting facts and procedures we want them to learn with “intrinsically emotional, subjective and meaningful experiences” (Immordino-Yang, 2016).

It is biologically impossible to build skills without emotion.

The brain’s primary job is not thinking. It is regulating the body’s use of energy. When it comes to consuming these calories, the brain puts itself first in line. For the first decade of a child’s life, their developing brain consumes more than half of their body’s energy supply. Even in adulthood, this three pound organ devours 20 percent of our metabolic resources.

Because energy resources are finite, the human brain cannot afford to build expensive neural connections for every interaction and encounter. It needs a filter to decide which incoming information is worth the expense of building new neural pathways–the type of pathways that build skills. This biological filter is emotion.

“The brain is metabolically expensive. We don’t waste energy and oxygen thinking about things that don’t matter to us. We only think deeply about things we care about.” (Immordino-Yang, 2016)

If an activity lacks emotional significance or context, the brain flags it as an energy waste. We simply do not pay attention to things we do not feel something about (Immordino-Yang, 2016). What we do not pay attention to, we cannot remember. And what we do not remember, we cannot transform into skill.

Success in subjects we tend to think of as purely rational – like science, technology, engineering, and mathematics – depends upon making emotional connections between concepts. Emotion helps engage the brain networks that manage attention, motivation, and evaluation of potential solutions (Immordino-Yang & Faeth, 2010; Immordino-Yang, 2011). Emotion helps build skills by serving as a “rudder” for thinking (Immordino-Yang and Damasio, 2007). It helps guide and direct our attention, thoughts, and behavior (Fischer & Bidell, 2006; Mascolo & Fischer, 2010; Mascolo, 2020; Hardway, 2020).

This is not the same as social-emotional learning

The idea that emotion is the body’s fuel for skill building is distinct from “social-emotional learning” (SEL). This is not about self-regulation, self-awareness, or relationship skills. Rather, we are describing the powerful role that emotions play in building and using skills.

As we saw in Principle 1, skill and context are welded together. “Emotions such as interest, anxiety, frustration, excitement, or a sense of awe in beholding beauty become a dimension of the skill itself” (Immordino-Yang, 2016). Emotion is not only the fuel for learning. It is a persistent feature of the context in which skill is developed. Thus, it is impossible to separate emotion from skill. Emotion does not sit outside of the learning process; it dictates the boundary lines of skill itself.

When we say “emotion is a feature of context,” it means that a child’s internal feelings are a direct, active component of the setting in which their skills must perform. Emotions of course can be positive or negative. They are both internally-driven and externally triggered in response to real, anticipated, or even imagined experiences (Immordino-Yang, 2011; Pekrun, 2017; Hareli & Parkinson, 2008).

Because skill is bound to context, a child’s capacity for building skills will always be connected to their emotions. When the emotional context changes—say, moving from a low-stakes peer collaboration to a high-stakes, isolated assessment—the skill itself changes because the context has shifted.

A context rich in trust, safety, and positive adult and peer interactions shifts a child’s internal chemistry. This relational safety changes the emotional context from one of high alert to one of open exploration. We don’t engineer emotion directly, but rather shift the relational context, which in turn adjusts a child’s internal emotional thermostat. When we change the emotional context, we adjust the brain’s readiness for skill building.

But wait, there’s more

• Insights about the other 6 principles of skill building.

• The skills that quietly drive PK-12 math and reading achievement.

Works Cited

Fischer, K. W., & Bidell, T. R. (2006). Dynamic development of action and thought. In R. M. Lerner & W. Damon (Eds.), Handbook of child psychology: Theoretical models of human development (6th ed., pp. 313–399). John Wiley & Sons, Inc.

Hardway, C. (2020). Of interest and engagement: The emotional force of learning and development. In M. F. Mascolo & T. R. Bidell (Eds.), Handbook of integrative developmental science: Essays in honor of Kurt W. Fischer (pp. 232-261). Routledge.

Hareli, S., & Parkinson, B. (2008). What’s Social About Social Emotions? Journal for the Theory of Social Behaviour, 38(2), 131–156.

Immordino‐Yang, M. H. (2011). Implications of affective and social neuroscience for educational theory. Educational Philosophy and Theory, 43(1), 98–103.

Immordino-Yang, M. H. (2016). Emotions, learning, and the brain: Exploring the educational implications of affective neuroscience. W. W. Norton & Company.

Immordino-Yang, M. H., & Damasio, A. (2007). We feel, therefore we learn: The relevance of affective and social neuroscience to education. Mind, Brain, and Education, 1(1), 3–10.

Immordino-Yang, M. H., & Faeth, M. (2010). The role of emotion and skilled intuition in learning. In D. A. Sousa (Ed.), Mind, brain, and education: Neuroscience implications for the classroom (pp. 67–81). Solution Tree Press.

Immordino-Yang, M. H., & Fischer, K. W. (2010). Neuroscience bases of learning. In V. G. Aukrust (Ed.), International encyclopedia of education (3rd Edition, pp. 310–316). Elsevier.

Mascolo, M. F. (2020). Dynamic skill theory: An integrative model of psychological development. In M. F. Mascolo & T. R. Bidell (Eds.), Handbook of integrative developmental science: Essays in honor of Kurt W. Fischer (pp. 91–135). Routledge.

Mascolo, M. F., & Fischer, K. W. (2010). The dynamic development of thinking, feeling, and acting over the lifespan. In R. M. Lerner (Ed.), Handbook of life-span development (Vol. 1, pp. 149–194). Wiley.

Pekrun, R. (2017). Achievement emotions. In A. J. Elliot, C. S. Dweck, & D. S. Yeager (Eds.), Handbook of competence and motivation: Theory and application (Second). The Guilford Press.

First posted: June 4, 2025

Last updated: July 24, 2026

Key Takeaway

Skill is the capacity to think and act in an organized way in a specific context (Immordino-Yang and Fischer, 2010). Children develop skills from active engagement in meaningful activities. This is likely to be more successful when children interact with others. We develop skills from what we do—particularly what we do with other people.

Highly automated, proficient skills are the direct result of wiring and rewiring of connections in our brain. Neurons that fire together, wire together.1 The neural pathways connecting individual brain cells and synapses are physically built and strengthened through repetition and deliberate practice. This constant structural change is what creates a skill.

When we actively engage with the world, we literally shape our brain structure—changing the neurons, synapses, and overall brain activity. Mere exposure is not enough to change our brain or to build skills. Learning facts is important but not enough. We have to be actively involved to build skills (Fischer, 2009).

“Skills do not spring up fully grown from preformed rules or logical structures. They are built up gradually through the practice of real activities in real contexts, and they are gradually extended to new contexts through this same constructive process.” (Fischer & Bidell, 2006)

“Action” is not limited to physical activity. Skills are developed and organized to support real mental activities, too. Thinking is a form of internalized action. Feeling involves the experience of activity (Mascolo, 2009). The documented impact of mindfulness interventions on executive and self-regulation skills is one positive example of “mental action.”

Skills are built with others

We don’t acquire skills and knowledge entirely on our own. Skills are learned partly from other people–whether directly or vicariously by watching them (Immordino-Yang, 2008). We imitate other people’s actions–including their thoughts and beliefs. In this way, social learning is a major driver of skill building.

Children and youth rely upon trusted adults–parents, caregivers, teachers, mentors–and peers for emotional clues about how they should behave. “They imagine how other people feel and think, and those thoughts in turn influence how they feel and think” (Immordino‐Yang, 2011).

“Individuals learn what they do, and particularly what they do with others. Social interaction—especially exchanges that are scaffolded by more accomplished others—has the effect of raising an individual’s performance to levels beyond that which can be sustained while working alone.” (Mascolo, 2020)

Social support is an important part of the context in which skills are built (See Principle 2). Interaction with others is critical to social emotions. (See Principle 4.). “We are influenced by not only our own emotions, but also by others’ emotions, behaviors, and mental states” (Immordino-Yang, 2007).

Social interaction is important for both intrinsic and extrinsic motivation. (See Principle 5.) Skills are developed and practiced with others. In situations of high support, a mentor, coach, or teacher can help a child achieve levels of competence they couldn’t reach on their own. The presence or absence of social support can have dramatic effects on the skill level a child is able to produce (Fischer et al., 1993).

If an environment starves a child of personal action or isolates them from social support, skill development suffers. The research is clear that throwing children into the deep end of the skill pool and waiting for them to learn to swim doesn’t work (Christensen et al., 2024). Active engagement and social interaction are not optional elements—they are foundational pillars of effective skill building.

But wait, there’s more

• Insights about the other 6 principles of skill building.

• The skills that quietly drive PK-12 math and reading achievement.

Works Cited

Barrett, L. F. (2020). Seven and a half lessons about the brain. Houghton Mifflin.

Fischer, K. W. (2009). Mind, brain, and education: Building a scientific groundwork for learning and teaching. Mind, Brain, and Education, 3(1), 3–16.

Fischer, K. W., & Bidell, T. R. (2006). Dynamic development of action and thought. In R. M. Lerner & W. Damon (Eds.), Handbook of child psychology: Theoretical models of human development (6th ed., pp. 313–399). John Wiley & Sons, Inc.

Immordino-Yang, M. H., & Fischer, K. W. (2010). Neuroscience bases of learning. In V. G. Aukrust (Ed.), International encyclopedia of education (3rd Edition, pp. 310–316). Elsevier.

Mascolo, M. F. (2009). Beyond student-centered and teacher-centered pedagogy: Teaching and learning as guided participation. Pedagogy and the Human Sciences, 1(1), 3–27.

First posted: June 4, 2025

Last updated: July 24, 2026

Key Takeaway

Skill is the capacity to think and act in an organized way in a specific context (Immordino-Yang and Fischer, 2010). Skill is welded to its context, and context means many things at once, like environment, emotion, and social support. We can intentionally engineer rich, high-support environments where skills have no choice but to grow. Cultivating generalized skills usually requires prolonged time and effort. Shortcuts to skill transfer, however, are possible through the intentional leverage of existing skills, adaptive challenges, and reflective practice.

There is no such thing as running.1

There is running up a hill. There is running down a hill. There is running in a pair of Brooks shoes. There is running in bare feet. There is running on the beach. There is running cross country in the woods. There is running by yourself and there is running with a group.

While each instance of running shares common skill elements, each environment demands an entirely distinct set of mental and physical abilities. Skill is the ability to think and act in an organized way in a specific context (Immordino-Yang and Fischer, 2010). Just as there is no abstract capability called “running,” there are no context-free academic skills.

“In ordinary English usage, skill implies both person and context simultaneously. People have a skill for riding a bicycle, a skill for listening to their friends, a skill for repairing Toyota engines, a skill for doing analysis of variance. A person cannot have a skill independent of context. Skill requires a collaboration between person and context. This conception means that skills vary not only between people but also across contexts for a given person” (Fischer et al, 1993).

“Context” means many things at once: the physical environment, emotional state, social support, domain or subject area, and the specific task involved (Fischer & Immordino-Yang, 2002). Since skills are welded to their contexts, and context can change in multiple ways from moment to moment, human performance is inherently variable. Context helps explain why a child who is able to solve a math problem one day or in a particular situation is unable to repeat this performance the next day or in a different or similar situation (Fischer & Bidell, 2006).

Context and the challenge of skill transfer

The transfer of knowledge and learning from one setting or domain to another is a well-established challenge in education (Barnett & Ceci, 2002). Near transfer involves the application of skills or knowledge learned in one context (task, activity, domain) to a similar context. Far transfer involves the use of knowledge or skills very different from the original context, task, or activity (Fischer & Bidell, 2006).

Researchers repeatedly fail to find evidence of far transfer of skills from playing chess (Sala & Gobet, 2017; Blanch, 2022), video games (Sala et al., 2018), brain games (Simons et al., 2016), music training (Sala & Gobet, 2020), or cognitive training (e.g. working memory) (Gobet & Sala, 2023). Researchers find that children who are adept in complex mental math calculation in street markets in Kolkata and Delhi are not able to successfully apply the same math concepts in classroom settings. Moreover, children who are able to successfully complete these same calculations in classroom settings struggle to apply these concepts to real-world situations like the street markets (Banerjee et al., 2025).

Skills developed in one context have to be completely reconstructed in a new context (Fischer & Farrar, 1987; Fischer & Bidell, 2006).2 Skill and context are tightly welded. While certain elements are similar (think about running on the beach versus running in the woods), skills have to be constructed for each specific context. Proficiency in multiple contexts leads to generalized skill mastery. Since context is comprised of multiple factors (environment, emotional state, etc.), this can be a winding, messy process that usually takes a long time (see Principle 7).

Accordingly, some researchers argue we should focus on building skills in the specific context in which the skills are to be used. If you want children to get better at math, teach them math skills not chess.3 This is a sensible argument. Yet, we also want children to develop broad, durable skills that can help them be successful in multiple contexts in school and life.

Fortunately, research suggests three possible shortcuts to accelerate the development of generalized skills:

1. Leverage Familiar Frameworks. Help children develop new skills in new contexts by building upon their existing knowledge and skills. In other words, create a “shortcut” in the ordinary time-intensive process of skill building. One example is how the Fraction Ball math program helps children learn factions and decimals using interactive play on a basketball court.4

2. Use Adaptive Tasks. Help children expand their skill repertoire in two ways. One, by avoiding repetition and intentionally introducing novelty, complexity, and diversity in the tasks involved in a single context.5 Two, by practicing and reinforcing the same skill in different contexts. This forces the core targeted skill to adapt and develop. (See Principle 6.)

3. Embed Reflective Practice. Have children pause and think about their experiences. Reflecting on what they learn, what worked and didn’t, can help them learn about the purpose and utility of skills. This can help them learn how to use these abilities in new situations and accelerate the growth of the targeted skill (Zelazo and Carlson, 2020).

The dependency of skills on context is not just a feature–it’s a potential leverage point. We can intentionally engineer rich, high-support environments where these abilities have no choice but to grow. Cultivating generalized skills usually requires prolonged time and effort. Shortcuts to transfer, however, are possible through the intentional leverage of existing skills, adaptive challenges, and reflective practice.

But wait, there’s more

• Insights about the other 6 principles of skill building.

• The skills that quietly drive PK-12 math and reading achievement.

Works Cited

Banerjee, A. V., Bhattacharjee, S., Chattopadhyay, R., Duflo, E., Ganimian, A. J., Rajah, K., & Spelke, E. S. (2025). Children’s arithmetic skills do not transfer between applied and academic mathematics. Nature, 639(8055), 673–681.

Barnett, S. M., & Ceci, S. J. (2002). When and where do we apply what we learn?: A taxonomy for far transfer. Psychological Bulletin, 128(4), 612.

Blanch, A. (2022). Chess instruction improves cognitive abilities and academic performance: Real effects or wishful thinking? Educational Psychology Review, 34(3), 1371–1398.

Bustamante, A., Begolli, K., Alvarez-Vargas, D., Bailey, D., & Richland, L. E. (2022). Fraction ball: Playful and physically active fraction and decimal learning. Journal of Educational Psychology, 114(6), 1307–1320.

Cantor, P., Osher, D., Berg, J., Steyer, L., & Rose, T. (2019). Malleability, plasticity, and individuality: How children learn and develop in context. Applied Developmental Science, 23(4), 307–337.

Fischer, K. W., & Bidell, T. R. (2006). Dynamic development of action and thought. In R. M. Lerner & W. Damon (Eds.), Handbook of child psychology: Theoretical models of human development (6th ed., pp. 313–399). John Wiley & Sons, Inc.

Fischer, K. W., Bullock, D. H., Rotenberg, E. J., & Raya, P. (1993). The dynamics of competence: How context contributes directly to skill. In R. Wozniak & K. Fischer (Eds.), Development in context: Acting and thinking in specific environments. Lawrence Erlbaum Associates.

Fischer, K. W., & Farrar, M. J. (1987). Generalizations about generalization: How a theory of skill development explains both generality and specificity. International Journal of Psychology, 22, 643–677.

Fischer, K. W., & Immordino-Yang, M. H. (2002). Cognitive development and education: From dynamic general structure to specific learning and teaching. In E. Lagemann (Ed.), Traditions of scholarship in education. Spencer Foundation.

Gobet, F., & Sala, G. (2023). Cognitive training: A field in search of a phenomenon. Perspectives on Psychological Science, 18(1), 125–141.

Immordino-Yang, M. H., & Fischer, K. W. (2010). Neuroscience bases of learning. In V. G. Aukrust (Ed.), International encyclopedia of education (3rd Edition, pp. 310–316). Elsevier.

Sala, G., & Gobet, F. (2017). Does chess instruction improve mathematical problem-solving ability? Two experimental studies with an active control group. Learning Behavior, 45(4), 414–421.

Sala, G., & Gobet, F. (2020). Cognitive and academic benefits of music training with children: A multilevel meta-analysis. Memory & Cognition, 48(8), 1429–1441.

Sala, G., Tatlidil, K. S., & Gobet, F. (2018). Video game training does not enhance cognitive ability: a comprehensive meta-analytic investigation. Psychological Bulletin, 144(2), 111–139.

Simons, D. J., Boot, W. R., Charness, N., Gathercole, S. E., Chabris, C. F., Hambrick, D. Z., & Stine-Morrow, E. A. L. (2016). Do “brain-training” programs work? Psychological Science in the Public Interest, 17(3), 103–186.

Zelazo, P. D., & Carlson, S. M. (2020). The neurodevelopment of executive function skills: Implications for academic achievement gaps. Psychology & Neuroscience, 13(3), 273–298.

First posted: June 4, 2025

Last updated: July 24, 2026

Key Takeaway

Skill is the capacity to think and act in an organized way in a specific context (Immordino-Yang and Fischer, 2010). Skill is like a rope made of many individual fibers (Erard, 2013). Weaving a skill rope is an active process. Children need help to weave thick, durable skill ropes. Skills can be intentionally developed with positive social relationships, rich learning environments, and well-designed learning experiences. Despite different starting points and individual developmental pathways, all children share a similar capacity to develop basic and complex skills under the right conditions (Cantor et al., 2019). There are many ways to weave a strong, thick skill rope.

One of the many remarkable features of the human brain is its capacity for self-organization. In response to stimuli and experiences, the brain’s internal processes organize its functioning and development. The brain reorganizes itself multiple times between when a child is born and when she graduates high school.1 This reorganization supports progressively complex skill development (Fischer 2008; Fischer 2009).

Skills mirror this ability. Skills developed for specific purposes combine with other skills developed for other purposes to create new, integrated skills. In this way, simple skills self-organize into more complex skills that can be used to support an increasingly wider range of activities. This architecture of higher-level skills built upon a foundation of simpler skills is a distinctive feature of complex skills.

“Skills are self-organizing. Part of the natural functioning of skills is that they organize and reorganize themselves. These self-organizing properties go beyond maintenance to include growth of new, more complex skills (Fischer & Bidell, 2006).”

For example, the ability to count objects is a skill we develop in early childhood. This basic skill, which starts with concrete objects, becomes more complex when it’s applied to abstract representations of numbers (numerals). This ability eventually supports even more complex skills such as adding numbers together.

Addition later supports multiplication (which is really multiple addition). Addition and multiplication in turn support even more complex (and abstract) skills such as word problem solving and algebraic thinking. These skills support even more advanced math skills such as probability and calculus.

To help children and youth develop complex skills, we should take advantage of how skills naturally develop and grow. Developmentally and interpersonally rich experiences are the breeding grounds for skills. Decades of research show that the most impactful learning environments—from structured school curricula to youth development programs—utilize an intentional, sequenced progression of skill development (Durlak and Weisberg, 2007; Durlak et al., 2010, Kim et al., 2024, Cabell et al., 2025). Well-designed learning experiences help build progressively complex skills on top of each other.

But wait, there’s more

• Insights about the other 13 principles of skill building.

• The skills that quietly drive PK-12 math and reading achievement.

Works Cited

Barrett, L. F. (2020). Seven and a half lessons about the brain. Houghton Mifflin.

Cabell, S. Q., Kim, J. S., White, T. G., Gale, C. J., Edwards, A. A., Hwang, H., Petscher, Y., & Raines, R. M. (2025). Impact of a content-rich literacy curriculum on kindergarteners’ vocabulary, listening comprehension, and content knowledge. Journal of Educational Psychology, 117(2), 153–175.

Cantor, P., Osher, D., Berg, J., Steyer, L., & Rose, T. (2019). Malleability, plasticity, and individuality: How children learn and develop in context. Applied Developmental Science, 23(4), 307–337.

Christensen, K. M., Assink, M., van Dam, L., Stams, G.-J., Poon, C. Y. S., Astesano, J., & Rhodes, J. E. (2024). Youth interventions with and without supervised practice: A second-order meta-analysis. Child and Adolescent Social Work Journal, 41(5), 769–780.

Erard, M. (2013). Weaving skill ropes: Using metaphor to enhance understanding of what skills are and how they develop. FrameWorks Institute.

Fischer, K. W. (2008). Dynamic cycles of cognitive and brain development: Measuring growth in mind, brain, and education. In A. M. Battro, K. W. Fischer, & P. Léna (Eds.), The educated brain (pp. 127–150). Cambridge University Press.

Fischer, K. W. (2009). Mind, brain, and education: Building a scientific groundwork for learning and teaching. Mind, Brain, and Education, 3(1), 3–16.

Fischer, K. W., & Bidell, T. R. (2006). Dynamic development of action and thought. In R. M. Lerner & W. Damon (Eds.), Handbook of child psychology: Theoretical models of human development (6th ed., pp. 313–399). John Wiley & Sons, Inc.

Immordino-Yang, M. H., & Fischer, K. W. (2010). Neuroscience bases of learning. In V. G. Aukrust (Ed.), International encyclopedia of education (3rd Edition, pp. 310–316). Elsevier.

Kim, J. S., Gilbert, J. B., Relyea, J. E., Rich, P., Scherer, E., Burkhauser, M. A., & Tvedt, J. N. (2024). Time to transfer: Long-term effects of a sustained and spiraled content literacy intervention in the elementary grades. Developmental Psychology, 60(7), 1279–1297.

First posted: June 4, 2025

Last updated: July 24, 2026

I’m obsessed with skills. What they are. How they develop. I’m particularly interested in understanding the factors that support or inhibit the growth of unconstrained skills that quietly drive PK-12 math and reading achievement.

Check out this post for a basic primer on skills:

The brain has a fundamental biological need to develop proficient skills to help it efficiently manage the body’s finite energy resources. Proficient skills are virtually automatic; their use requires little attention or conscious awareness (Mascolo, 2020). Hence, the development and refinement of skills to support goal-oriented action is an essential part of human life.

I’ve read dozens of academic articles, reports, and books about skills since spring 2024. Although “skill” is one of the most common words in the English language,1 it is not a well understood concept. Parents, educators, policymakers, and employers want to ensure that children and youth develop the skills they need to succeed in school and in life. The general public assumes skills are a natural result of growth and aging (Erard, 2013).

In PK-12 education, “skill” is not always consistently defined. Among educators “skills” and “strategies” are often used interchangeably (Afflerbach et al., 2008). It is no wonder education commentators sometimes argue that reading comprehension isn’t a skill or that it’s a myth that we need to focus on skills at all. I believe these arguments stem from a misunderstanding of what skills are and how they develop.

Developmental psychologist Kurt Fischer and his research colleagues spent decades developing detailed descriptions of how simple actions evolve into complex skills. Built upon the pioneering work of renowned child psychologist Jean Piaget, this framework is known as Dynamic Skill Theory and is a core pillar of what’s known as the Science of Learning and Development.2

I think about skills the way Fischer and his colleagues describe them: the ability to think and act in an organized way in a specific context (Immordino-Yang and Fischer, 2010). Dynamic Skill Theory is a powerful framework to understand how we build complex skills, and why our ability to use them naturally ebbs and flows depending on our environment. This series translates these important insights into seven core principles of skill building.3

Seven Principles of Skill Building

1. Skills self-organize and increase in complexity over time.

2. Skills are built in specific contexts.

3. Skills are built through action and interaction.

4. Emotion is the body’s fuel for skill building.

5. It is impossible to build skill without motivation.

6. Skill is not a single fixed ability.

7. Skill building is messy and never occurs in a straight line.

I’ve written a post with key insights for each principle. These principles apply to development of any type of skill, including those that are the focus of this Substack: PK-12 reading, writing, math, and durable skills. Although each principle stands on its own, the seven principles are highly interconnected. My read of the research suggests that experiences, instruction, interventions, and programs informed by these principles are better positioned to support successful skill building.

But wait, there’s more

• The skills that quietly drive PK-12 math and reading achievement.

Works Cited

Afflerbach, P., Pearson, P. D., & Paris, S. G. (2008). Clarifying differences between reading skills and reading strategies. The Reading Teacher, 61(5), 364–373.

Cantor, P., Osher, D., Berg, J., Steyer, L., & Rose, T. (2019). Malleability, plasticity, and individuality: How children learn and develop in context. Applied Developmental Science, 23(4), 307–337.

Erard, M. (2013). Weaving skill ropes: Using metaphor to enhance understanding of what skills are and how they develop. FrameWorks Institute.

Fischer, K. W., & Immordino-Yang, M. H. (2002). Cognitive development and education: From dynamic general structure to specific learning and teaching. In E. Lagemann (Ed.), Traditions of scholarship in education. Spencer Foundation.

Immordino-Yang, M. H., & Fischer, K. W. (2010). Neuroscience bases of learning. In V. G. Aukrust (Ed.), International encyclopedia of education (3rd Edition, pp. 310–316). Elsevier.

Mascolo, M. F. (2020). Dynamic skill theory: An integrative model of psychological development. In M. F. Mascolo & T. R. Bidell (Eds.), Handbook of integrative developmental science (pp. 91–135). Routledge.

Osher, D., Cantor, P., Berg, J., Steyer, L., & Rose, T. (2020). Drivers of human development: How relationships and context shape learning and development. Applied Developmental Science, 6–36.

First posted: March 15, 2025

Last updated: April 21, 2026

What I’m doing now

This Substack is part of a larger project. I am working to bring a powerful 20-year-old insight from academia into the mainstream. The current focus here is WHAT constrained and unconstrained skills are and WHY they matter. I am in the throes of research and writing a book on HOW to improve them. My focus (the “dependent variable”) is improvement of PreK-12 reading and math achievement. I am particularly concerned about closing gaps in slow-growing unconstrained skills.

This requires thoughtful approaches to building and repairing skills. I am focused on the nature and nurture of skills, how kids learn to read and think mathematically, and how personal systems support or inhibit skill development. This includes careful attention to the challenge of how skills developed in one context transfer to another. We need to understand what works, for whom, and under what conditions. I intentionally use the term “kids” so that people and organizations outside of the schoolhouse (where “students” learn) know that I am talking to you, too. My goal is to help people who run, fund, and assist organizations that teach and serve kids.

I have a full-time day job; research and writing will be a slow process. But you don’t have to wait to start paying attention to unconstrained skills for the kids that you teach or serve. Academic researchers strongly encourage you to do so.

What you can do now

Constrained skills are largely developed in the classroom. Unconstrained skills are built in formal and informal learning environments: the schoolhouse, at home, and in the community. My advice is to look at how you can put more focus on unconstrained skills wherever you serve kids. But this does not mean sacrificing support for constrained skills. Kids need both.

One potential place to start is your data. Examine patterns of constrained reading and math skills. (You can’t do this with composite scores that combine constrained and unconstrained skills!) Point-in-time data can give you snapshots of relative levels of skill proficiency. Longitudinal data can show you trajectories of skill growth over time. Compare the patterns in your data to the data I’ve collected so far.

Ask questions about how your school or program is organized to build unconstrained reading, math, and executive skills. And don’t forget knowledge building; it is the ultimate unconstrained skill. And don’t let anyone convince you that you can’t measure unconstrained skills. Anything can be measured.

TeamCraft

How to Measure Anything

A common scenario faced by a data middle manager is to field questions from execs and peers about something that, in their perception, is intangible (i.e. it cannot be measured…

Read more

3 years ago · Gokhan Ciflikli

Schools

Schools have a crucial role to play. They have the resources, materials, and people to build kids’ constrained and unconstrained skills. Schools make critical decisions about how to spend time and money on curriculum, assessments, and interventions. Researchers have long advocated for educators to give more attention to unconstrained skills starting as early as Pre-K.

As important as schools are, they can’t build unconstrained skills alone. Snow and Matthews (2016) succinctly describe the challenge:

The research on effective schools by researchers and writers such as Tony Bryk and Karin Chenoweth show that schools never “beat the odds” on their own. They always have help. This is especially true for schools serving our most vulnerable children. We need to help schools build “exoskeletons” of additional support.

Home and community

Kids spend 80% or more of their waking hours outside of school. Children from higher socioeconomic families routinely receive active support at home. They participate in enrichment activities outside of school. They get extra academic tutoring when they need it. There are many families on the other end of the socioeconomic ladder who also make sure their kids get similar opportunities. This often happens with great sacrifice and determination. But too many kids from less advantaged households don’t receive a fair chance to fully develop their skills.

Although schools and families are critical, I believe that community organizations and institutions are especially well-suited to help kids build unconstrained skills. Think libraries, museums, zoos, aquaria, science centers, Scouts, 4-H, YMCAs, Boys and Girls Clubs, and the like. Mentoring programs could also play an important role in helping children build unconstrained skills.

Unconstrained skills are key leverage points for change

In his new book, Reset, Dan Heath suggests that the solution to solving tough problems is to realign (“restack”) existing resources behind strategically selected leverage points. Unconstrained skills is such a leverage point for education. This aligns with the recommendation of Bailey et al. (2017) to focus interventions on “trifecta skills”—skills that (1) are malleable, (2) fundamental for later success, and (3) would not have developed anyway in the absence of intervention. I believe many of the unconstrained skills identified by academic researchers meet these criteria. The challenge is finding strategies to repair unconstrained skills that are effective, pragmatic, and scalable for PreK-12 kids.

Studies dating to the 1980s repeatedly demonstrate that dialogic reading builds children’s vocabulary, language, and comprehension skills. The Home Literacy Model and the Home Numeracy Model document how activities at home contribute to classroom gains in reading and math (Sénéchal & LeFevre, 2002; Sénéchal, 2006; LeFevre et al., 2009; Skwarchuk et al. 2014). Research by McCormick et al. (2020) suggests home activities supporting unconstrained skills can positively support classroom reading and math achievement. Although the term “unconstrained skills” might be new, encouraging families to talk, read, sing, and play with their kids is not.

Share this Substack with others whom you think should read it. I would love to hear your thoughts about how to put more focus on unconstrained skills in the schoolhouse, at home, and in community organizations. Let me know if there are studies, programs, or interventions you think I should know about. I’m open to comments, suggestions, or alternative viewpoints. In the meantime, I’ll keep reading, thinking, and writing.

But wait, there’s more

If you’d like to learn more about constrained and unconstrained skills, check out these other topics:

• A basic primer on skills.

• What are constrained and unconstrained skills?

• Two skill types, two developmental pathways

• A secret hiding in plain sight?

• The science of skill building

Works cited

Bailey, D., Duncan, G. J., Odgers, C. L., & Yu, W. (2017). Persistence and fadeout in the impacts of child and adolescent interventions. Journal of Research on Educational Effectiveness, 10(1), 7-39.

LeFevre, J. A., Skwarchuk, S. L., Smith-Chant, B. L., Fast, L., Kamawar, D., & Bisanz, J. (2009). Home numeracy experiences and children’s math performance in the early school years. Canadian Journal of Behavioural Science, 41(2), 55.

McCormick, M. P., Weissman, A. K., Weiland, C., Hsueh, J., Sachs, J., & Snow, C. (2020). Time well spent: Home learning activities and gains in children’s academic skills in the prekindergarten year. Developmental Psychology, 56(4), 710.

Sénéchal, M. (2006). Testing the home literacy model: Parent involvement in kindergarten is differentially related to grade 4 reading comprehension, fluency, spelling, and reading for pleasure. Scientific Studies of Reading, 10(1), 59-87.

Sénéchal, M., & LeFevre, J. A. (2002). Parental involvement in the development of children’s reading skill: A five‐year longitudinal study. Child Development, 73(2), 445-460.

Skwarchuk, S. L., Sowinski, C., & LeFevre, J. A. (2014). Formal and informal home learning activities in relation to children’s early numeracy and literacy skills: The development of a home numeracy model. Journal of Experimental Child Psychology, 121, 63-84.

Snow, C. E., & Matthews, T. J. (2016). Reading and language in the early grades. The Future of Children, 57-74.

First posted: March 7, 2025

Last updated: April 21, 2026

Three big ideas

1. Constrained skill theory is one of the most influential ideas proposed over the past 20 years among academic researchers in education.

2. For at least 15 years, academic researchers have called for more explicit focus on building kids’ unconstrained skills to improve reading and math achievement.

3. Academic researchers to date have proposed consideration of differences between constrained and unconstrained skills have implications for family engagement, Pre-K programs, educational apps, curricula, assessments, and interventions.

An influential idea in education research

A 2014 article in the journal Nature observed that less than 1% of academic papers receive 1,000 or more citations in other academic publications (Van Noorden et al., 2014). Just 100 citations gets a paper in the top 2% overall. According to Google Scholar, the three articles that often get cited for constrained skill theory — Paris (2005), Stahl (2011), and Snow and Matthews (2016) — currently have over 1,300, nearly 100, and 470 citations, respectively. For academics, this is rare air. This signifies the influence that constrained skill theory has achieved among academic researchers over the past 20 years.

Advocacy for policy and practice change

Academic researchers use the constrained skill framework to advocate for change in classroom instruction and assessment.

Classroom instruction

• Stahl (2011): “Teaching constrained skills explicitly and systematically and matching instruction to students’ developmental needs should ensure that the largest portion of the literacy block can be allocated to the more complex unconstrained abilities throughout the elementary years.”

• Snow and Matthews (2016): “[M]any prekindergarten through third-grade classrooms, particularly those serving low-income children, still focus on constrained skills, which are easy to teach and easy to test…our schools may be focusing too much on constrained skills—and too little on unconstrained ones—in the early grades.”

• Pianta et al. (2021): “The advantages children gain from enrolling in formal pre-K programs are evident, but it will require continued work to ensure that planned large-scale investments in pre-K deliver on their promise to improve children’s learning and development in the long-term. Balancing instruction between more constrained and more unconstrained instruction in pre-K and early elementary school programming — and measuring children’s progress in both types of skills — shows promise for making progress on this goal.”

• Whittingham et al. (2024): “When constrained skills (i.e., print-centric skills including alphabetic knowledge and phonics) taught in isolation dominate instructional time, critically important unconstrained skills (i.e., meaning-centric skills including comprehension and composition) and reading-adjacent skills (i.e., interest, motivation) that underlie long-term literacy development are compromised.”

Assessment

• Pianta et al. (2021): “Invest in developing a broader set of assessments that capture more unconstrained skills —competencies that are admittedly more difficult to assess — in addition to more constrained skills, which are more typically used by schools and researchers because they are easier to assess and directly aligned with standards.”

• McCormick and Mattera (2022): “As investments in publicly funded pre-K expand, policymakers and localities are increasingly looking to use assessments of children’s skills to understand whether programs effectively support learning and development. Recent research examining constrained and unconstrained skills points to the value of expanding the types of skills measured to understand more fully the effects of pre-K on children over time.”

• Whittingham et al. (2024): “Whereas assessment and accountability are essential to documenting student growth and proficiency, prioritizing assessments that emphasize constrained skills overestimates a readers’ ability to make sense of text. Instead, they are simply demonstrating accurate decoding…Changing instructional practices to emphasize both constrained and unconstrained skills requires refining and reconceptualizing schools’ assessment systems.”

• Hanno et al. (2025): “Overcoming the complexities of capturing unconstrained skills is central to fostering stronger pedagogical practices that build on children's strengths and identifying programs that are most effective in promoting these important skills. One way to deepen domain measurement to include more unconstrained skills is to align assessment content to developmental trajectories rather than focus on discrete skills.”

Research into effects on student achievement

Researchers in recent years published studies about the relationship between constrained and unconstrained skills and student achievement.

Family engagement

• McCormick et al. (2020) conducted a correlational study of 307 parents of Pre-K children to evaluate the relationship between constrained and unconstrained learning activities at home and student growth in reading and math. Accounting for a range of child and family variables to isolate the effects of at-home learning, they found extra growth in children’s vocabulary (about 2-3 months) and math problem solving (about 2 months) from increasing unconstrained activities at home from 1-2 times to 3-6 times a week. The gains were greater for families with lower levels of education. Conversely, additional time spent on constrained learning activities at home did not affect these skills.

Classroom

• In a study of 470 students and 51 classrooms in Boston Public Schools, researchers (Weiland et al., 2023) found increased exposure during Pre-K to unconstrained language and literacy instruction is a significant predictor of larger learning gains for all students (Maier et al., 2022). While these gains support the potential of high-quality Pre-K instruction to reduce initial disparities in school readiness, research shows that gains in unconstrained skills are significantly more persistent than those in constrained skills (McCormick et al., 2021). However, the long-term impact of these early gains depends on continued high-quality unconstrained instruction in kindergarten and beyond (McCormick et al., 2022).

Interventions

• Kim et al. (2021) evaluated 36 studies and nearly 300 outcomes on the effectiveness of educational apps on constrained and unconstrained PK-3 reading and math skills. Controlling for differences between types of assessment and student grade level, they find that education apps make greater gains on constrained skills.1 In fact, the impact is more than twice as large as unconstrained skills.

• Thomas et al. (2025) conducted a quasi-experimental study with a literacy-focused educational application (AppLINOU) in 32 schools with just over 500 French students. The research was conducted over two years in Pre-K and kindergarten.2 The study explicitly used the constrained skill framework. The researchers found statistically significant effects for constrained literacy skills (letter knowledge and phonological awareness) but none for unconstrained oral language skills.

High-quality research always comes with careful caveats of the limitations of the studies. The study design also has important relevance. The research design of these studies include random experiments, meta-analysis, and correlational analysis. And some papers more explicitly use the constrained skill framework to test the impact of changes in practice than others. Another challenge is the lack of consistency in definition and frameworks (Chia et al., 2026).

A largely unknown idea in PK-12 education and youth development

Since early 2024, I’ve directly engaged with hundreds of people in PK-12 education and youth development about constrained and unconstrained skills. The bulk of these engagements occurred through presentations and workshops I delivered in late 2025 and early 2026. The people I interacted with are knowledgeable people who are deeply invested in creating brighter futures for children and youth. Many focus on disrupting general poverty through closing the achievement gap. I’ve repeatedly found that educators and practitioners inside and outside of schools had never heard of constrained and unconstrained skills.

This does not appear to be limited to adults working directly with children and youth in schools and out-of-school programs. I pored through reports and webinars in 2024 and 2025 about learning loss in the wake of COVID 19-related school closures. I failed to find references to skill type in any of these analyses or policy recommendations. There was no discussion of constrained and unconstrained skills. Yet, my analysis of national data finds that the decline in reading and math performance was greater for unconstrained than constrained skills.3

This first chart shows proficiency levels of U.S. nine-year-olds eligible for free- and reduced-price meals on the NAEP Long-Term Trend Assessment.4 The chart focuses on constrained math and reading skills, showing proficiency before (early 2020) and after the outbreak of the COVID-19 pandemic. As you can see, there was a relatively small two percentage point decline for math and four percentage points for reading.

By comparison there was no decline for U.S. nine-year olds not eligible for free- and reduced-price meals in schools. (The difference in reading proficiency is not statistically significant.)

The overall decline in reading and math scores was due to lower proficiency in unconstrained math and reading skills. This next chart shows changes in proficiency for different levels of unconstrained math and reading skills for these same cohorts of nine-year-olds in 2020 and 2022. The declines were between 6-8 percentage points — about double those of constrained skills.

In contrast to the lack of change in constrained skill proficiency, U.S. nine-year-olds not eligible for free- and reduced-lunch did experience declines in unconstrained reading and math skills.

Hadley et al. (2025) found similar patterns of the impact of the pandemic on constrained and unconstrained skill in a two-year longitudinal study of Pre-K and kindergarten students. They conclude this difference may be due to the nature of instruction during the pandemic: “Some evidence suggests that instruction during the pandemic, especially remote instruction, may have emphasized discrete, constrained skills such as letter knowledge that could be more easily taught through resources such as apps and worksheets and required scaffolding from adults.”

But wait, there’s more

If you’d like to learn more about constrained and unconstrained skills, check out these other topics:

• A basic primer on skills.

• What are constrained and unconstrained skills?

• Two skill types, two developmental pathways

• An annotated summary of the major research papers behind constrained skill theory

• The importance of skill type

Works cited

Chia, J., Levickis, P., & McFarland, L. (2026). Unconstrained and Constrained Literacy Skills in Early Childhood Education: A Scoping Review. Australasian Journal of Early Childhood, 18369391261421725.

Hadley, E. B., Liu, S., Kim, E., McKenna, M., & Hull, K. (2025). Tracing the impact of COVID-19 on early language and literacy development from Pre-K through first grade. AERA Open, 11(1), 1–22.

Hanno, E. C., Portilla, X. A., & Hsueh, J. (2025). Designing equity-centered early learning assessments for today’s young children. Child Development Perspectives, 19(2), 92–98.

Kim, J., Gilbert, J., Yu, Q., & Gale, C. (2021). Measures matter: A meta-analysis of the effects of educational apps on preschool to grade 3 children’s literacy and math skills. AERA Open, 7(1), 1-19.

Maier, M. F., McCormick, M. P., Xia, S., Hsueh, J., Weiland, C., Morales, A., Boni, M., Tonachel, M., Sachs, J., & Snow, C. (2022). Content-rich instruction and cognitive demand in prek: Using systematic observations to predict child gains. Early Childhood Research Quarterly, 60, 96–109.

McCormick, M., & Mattera, S. (2022). Learning more by measuring more: Building better evidence on pre-k programs by assessing the full range of children's skills. MDRC: New York, NY.

McCormick, M., Weiland, C., Hsueh, J., Pralica, M., Weissman, A. K., Moffett, L., ... & Sachs, J. (2021). Is skill type the key to the preK fadeout puzzle? Differential associations between enrollment in preK and constrained and unconstrained skills across kindergarten. Child Development, 92(4), e599-e620.

McCormick, M. P., Weissman, A. K., Weiland, C., Hsueh, J., Sachs, J., & Snow, C. (2020). Time well spent: Home learning activities and gains in children’s academic skills in the prekindergarten year. Developmental Psychology, 56(4), 710.

Pianta, R., Purtell, K., McCormick, M., Knoche, L., Burchinal, M., Ludvik, D. & Peisner-Feinberg, E. “Sustaining the pre-k boost: Skills type matters,” Spring (Lincoln, NE: Early Learning Network, 2021).

Snow, C. E., & Matthews, T. J. (2016). Reading and language in the early grades. The Future of Children, 57-74.

Stahl, K. A. D. (2011). Applying new visions of reading development in today's classrooms. The Reading Teacher, 65(1), 52-56.

Thomas, A., Hoareau, L., Jarlégan, A., Hubert, B., Luxembourger, C., & Tazouti, Y. (2025). Enhancing French preschoolers’ early literacy skills with a new educational classroom application. Early Education and Development, 36(4), 886–911.

Van Noorden, R., Maher, B., & Nuzzo, R. (2014). The top 100 papers. Nature, 514, 550-553.

Weiland, C., Moffett, L., Rosada, P. G., Weissman, A., Zhang, K., Maier, M., Snow, C., McCormick, M., Hsueh, J., & Sachs, J. (2023). Learning experiences vary across young children in the same classroom: Evidence from the individualizing student instruction measure in the Boston Public Schools. Early Childhood Research Quarterly, 63, 313–326.

Whittingham, C. E., Hoffman, E. B., & Paciga, K. A. (2024). Assessment, accountability, and access: Constrained skill mastery as instructional gatekeeper. Journal of Early Childhood Literacy, 24(1), 69-95.

First posted: March 7, 2025

Last updated: April 21, 2026

Three big ideas

1. Knowledge is the ability to use facts, principles, and ideas to decide and do complex tasks. There are many types of knowledge.

2. Knowledge about the natural and social world shapes children’s abilities in reading, writing, and mathematics.

3. Meaningful gaps in knowledge across socioeconomic groups are already present by early elementary school. These differences are shaped by experiences inside and outside of the classroom.

About the data in this post

In this post, I use data from the Early Childhood Longitudinal Study, Kindergarten Class of 1998-99 (ECLS-K). The ECLS-K tracked roughly 22,000 U.S. children from kindergarten (fall 1998) through grade 8 (spring 2007). It’s the best dataset I’ve found to dig deep into individual K-8 reading and math skills. It’s also unique in that it directly assessed children’s general knowledge in kindergarten and first grade. I’ve organized the data by household socioeconomic status. The data are organized by household socioeconomic status.1

What is knowledge?

Knowledge is the ability to use facts, ideas, and principles to decide and do complex tasks (Cantor et al., 2021). This definition comes from what’s known as the “science of learning and development.” This definition has three parts. First, there are things to learn: facts, ideas, principles. Second, there are things to do: decide and do complex tasks. Third, there is capacity: the ability to use what we learn to make decisions and take action. Knowledge is active and dynamic.

This definition parallels that of skill: the capacity to think and act in an organized way in a specific context (Immordino-Yang & Fischer, 2010). Sometimes knowledge itself is referred to as a skill in the context of reading or mathematics (Kim, 2023; Rittle-Johnson et al., 2001). Indeed, the ability to access and use facts, principles, and ideas to engage in goal-oriented behavior is an important part of skill development. Children’s knowledge about the world around them is an essential part of skill building.

There are many types of knowledge.2 The rules of baseball and the strategies of the game. How dinosaurs lived and died. Multi-layered subjects like biology or history. The facts, procedures, and concepts embodied in mathematics. How things work, like the parts of a book or what happens when you go to a restaurant. How different elements of the world — people, objects, ideas — relate to each other, and why. The meanings of words and how they connect to other words, ideas, and principles.

Knowledge is a “caught and taught” skill, developing from both informal and formal learning experiences. Unlike constrained skills, any assessment of knowledge will only give us a partial glimpse of a child’s ability to use facts, principles, and ideas to decide and do complex tasks.

Knowledge, reading, writing, and mathematics

In a 2003 article, E.D. Hirsch offers this sentence as an example of the role of general knowledge to reading comprehension:

“Gigantic and luminous, the earliest star formed like a pearl inside shells of swirling gas.”

To comprehend this sentence, Hirsch notes that you rely upon prior knowledge about multiple concepts at once: the Big Bang, pearl formation, the use of metaphor in language, and gasses (Hirsch, 2003). A child who learns to read the words in this sentence will be limited in their understanding if they don’t also understand what the words mean and the embedded concepts and ideas. In other words, they need to understand the world around them.

Although there are many types of knowledge, in this post I focus on what’s alternatively referred to as world knowledge, general knowledge, or background knowledge. These are facts and concepts about the natural and social world. Although there is a distinction between knowledge building and knowledge activation, to keep things simple I refer to both simply as knowledge.

General knowledge represents children’s breadth and depth of understanding of their social and physical environment (i.e., the social, physical and natural world) and their ability to draw inferences and comprehend implications (West et al., 2000). Knowledge about the natural and social world is critical for reading comprehension (Hirsch, 2003; Pearson, et al., 2020; Kim & Cao, 2025), written composition (Graham & Aitken, 2025; Kim, 2025), and mathematical thinking (Grissmer et al., 2010).

General knowledge is an unconstrained skill

The ECLS-K study includes an assessment of K-1 children’s general knowledge of basic natural science and social studies concepts.3 Children were assessed first with a battery of 12 questions, which then determined which of two subsequent versions of the assessment (higher-level or lower-level) they received at the second stage.4

This first chart shows the average number of questions answered correctly by kids on the first-stage assessment. Kids are organized by household income status (quintiles). The dots represent assessments at three points in time: fall kindergarten, spring kindergarten, and spring first grade. Clear gaps existed across social groups in children’s general knowledge, which did not narrow by the end of their second full year in elementary school. (Mouse over the chart.)

To put these data in perspective, this next chart shows the growth pattern for a constrained math skill (relative size) for this same group of kids over the same time period. Early gaps in fall kindergarten are largely closed by the end of first grade. Kids across all socioeconomic groups on average are at or close to full proficiency.

We see similar gap closing for a constrained reading skill (letter-sound correspondence) for the same kids over the same time period.

The knowledge gap is an opportunity gap

The researchers behind the ECLS-K noted the differences in these growth patterns, suggesting that growth in knowledge was also influenced by experiences outside of school in addition to learning in the classroom (Rock & Pollack, 2002). A key difference between constrained and unconstrained skills is opportunity. After all, a constrained skill involves a relatively limited amount of information. All kids who attend school get access to the same information. Mastery is clearly defined and the same for everyone. But unconstrained skills depend more upon opportunities to develop these slower-growing skills inside and outside of school.

For example, children in different socioeconomic groups have different experiences outside of school. This next chart hows participation levels in extracurricular activities for the kids in top and bottom socioeconomic groups in the ECLS-K study during their kindergarten year. These children have vastly different experiences outside of school.

Later surveys in this study also show that children in lower socioeconomic households visit zoos, aquariums, museums, and libraries at significantly lower levels. These differences in opportunity are made more plain by examining differences in general knowledge across socioeconomic levels within a single racial group.5 This next chart shows correct responses to the first-stage general knowledge questions by Black students across five socioeconomic groups. Once again, we see the same stair-step pattern across SES groups and even a further widening by the end of the second year of school.

There is greater use today of knowledge-building curricula in schools compared to 25 years ago. It’s unclear if a similar study today would yield the same results as we see in these late 1990s data. The key point is that knowledge is caught and taught. Kids’ experiences inside and outside of school contribute to the growth of their world knowledge. It plays a complex and vital role in building constrained and unconstrained reading and math skills. Knowledge is the ultimate unconstrained skill.

But wait, there’s more

If you’d like to see more data about constrained and unconstrained skills, check out these other posts on Unconstrained Kids:

• A basic primer on skills

• What are constrained and unconstrained skills?

• Two skill types, two developmental pathways

• How informal learning can help grow unconstrained skills

Works Cited

Cantor, P., Osher, D., Berg, J., Steyer, L., & Rose, T. (2021). Malleability, plasticity, and individuality: How children learn and develop in context. In P. Cantor & D. Osher (Eds.), The science of learning and development: Enhancing the lives of all young people (pp. 3-54). New York: Routledge.

Fischer, K.W. & Immordino-Yang, M.H. (2002). Cognitive development and education: From dynamic general structure to specific learning and teaching. In E. Lagemann (Ed.), Traditions of scholarship in education. Chicago: Spencer Foundation.

Graham, S., & Aitken, A. (2025). The Writer(s)-within-Community Model. In C. A. MacArthur, S. Graham, & J. Fitzgerald (Eds.), Handbook of writing research (Third). The Guilford Press.

Hattan, C., & Lupo, S. M. (2020). Rethinking the role of knowledge in the literacy classroom. Reading Research Quarterly, 55, S283-S298.

Hirsch, E. D. (2003). Reading comprehension requires knowledge of words and the world. American Educator, 27(1), 10-13.

Kim, Y. S. G. (2023). Simplicity meets complexity: Expanding the simple view of reading with the direct and indirect effects model of reading. In Cabell, S. Q., Neuman, S. B. & Patton Terry, N. (Eds.), Handbook on the Science of Early Literacy, New York: The Guilford Press, pp. 9-22.

Kim, Y.-S. G. (2025). The Science of Reading-Writing Connections. In C. A. MacArthur, S. Graham, & J. Fitzgerald (Eds.), Handbook of writing research (Third). The Guilford Press.

Kim, Y.-S. G., & Cao, Y. (2025). Content knowledge and comprehension: A meta-analytic review of correlational and causal associations. Psychological Bulletin, 151(10), 1219.

Pearson, P. D., Palincsar, A. S., Biancarosa, G., & Berman, A. I. (Eds.). (2020). Reaping the Rewards of the Reading for Understanding Initiative. Washington, DC: National Academy of Education.

Rittle-Johnson, B., Siegler, R. S., & Alibali, M. W. (2001). Developing conceptual understanding and procedural skill in mathematics: An iterative process. Journal of Educational Psychology, 93(2), 346-362.

Rock, D.A. & Pollack, J.M. (2002). Early childhood longitudinal study-kindergarten class of 1998–99 (ECLS–K), psychometric report for kindergarten through first grade (NCES 2002–05). National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education. Washington, DC.

Stahl, S. A. (2005). Four problems with teaching word meanings. In E. H. Hiebert & M. L. Kamil (Eds.), Teaching and learning vocabulary: Bringing research to practice, (pp. 95-116). Mahwah, NJ: Lawrence Erlbaum Associates, Inc.

West, J., Denton, K., & Reaney, L. M. (2000). The kindergarten year: Findings from the early childhood longitudinal study, kindergarten class of 1998-99. NCES 2001-023. National Center for Education Statistics.

First posted: March 7, 2025

Last updated: April 21, 2026

Three big ideas

1. Executive skills help us control and shift our attention, manage distractions, and use and organize information. Self-regulation skills help us manage our thoughts, emotions, and actions.

2. Longitudinal studies of reading, writing, and mathematics show executive skills support the development of reading and math skills. Some studies show the relative contributions of executive function skills are on par with those of domain-specific reading and math component skills.

3. Early gaps in executive skills by household socioeconomic status do not appear to close through elementary school.

About these data

The data in these charts come from the Early Childhood Longitudinal Study, Kindergarten Class of 2010-11 (ECLS-K:2011). The ECLS-K:2011 data were collected between Fall 2010 and Spring 2016. The ECLS-K:2011 tracked a statistically representative group of about 18,000 children in the U.S. from kindergarten (fall 2010) through fifth grade (spring 2016). It’s the best dataset I’ve found to dig deep into executive function skills. The data are organized by household socioeconomic status.

Executive skills

Executive skills are like the “air traffic control” in our brain. They help us control and shift our attention, manage distractions, and use and organize information (Dawson and Guare, 2018). Executive skills help us coordinate the use of other skills to achieve goals and take intentional actions. There is plenty of research that shows executive skills directly and indirectly support the development of reading, writing, and math skills (Sowinski et al., 2015; Cragg et al., 2017; Kim, 2020; Kim & Graham, 2022; Graham & Aitken, 2025).

Although precise definitions vary, researchers often describe a core group of three foundational executive skills: working memory, cognitive flexibility, and inhibition control (Cuevas et al., 2018). Like some researchers, I prefer to break these out into four skills and describe them in more plain language:1

• Attention control: the ability to focus attention and override the desire to pay attention to distractions

• Attention shifting: the ability to shift attention while ignoring distracting information

• Impulse control: the ability to override automatic responses

• Working memory: the ability to maintain and manipulate information over a relatively short period of time

This core group provides the foundation for more advanced executive skills like metacognition, reasoning, and perspective taking. Researchers sometimes distinguish between “cool” executive skills that are used in emotionally neutral situations like reading and math, and “hot” executive skills that involve effortful control (e.g., social regulation, social understanding). Collectively, these foundational executive skills also lay the foundation for more advanced thinking and reasoning skills (i.e. “durable skills”) like collaboration, critical thinking, communication, creativity, adaptability, and leadership.

Working memory

Working memory is the ability to hold and process information in our minds while performing complex tasks (Dawson & Guare, 2018). There are two types of working memory – visual and verbal. Working memory helps us to do a wide range of daily tasks. Working memory has been shown to have an indirect effect on reading and math achievement (Cragg et al., 2017; Kim, 2020). The environments in which children grow up – positive and negative – can significantly shape the development of their working memory.

This first chart shows the percentage of kids by household income with average or higher scores for verbal working memory from kindergarten through fifth grade.2 The chart shows a staggering 46 point gap (32% to 78%) for working memory at the start of kindergarten between the lowest and highest household socioeconomic groups at the start of elementary school. Although the gap closes by two-third by the end of elementary school, a significant disparity remains. (Mouse over the chart.) Throughout this period working memory is having a direct and indirect effect on the development of reading and math skills (Cragg et al., 2017; Kim, 2020).

Cognitive flexibility (attention shifting)

Cognitive flexibility is the ability to consider multiple pieces of information or ideas at one time and switch between them while engaging in a task (Cartwright, 2023). This ability helps us to adjust our plans or actions in the face of obstacles or changing conditions (Dawson & Guare, 2018).

Cognitive flexibility is developed through consistent practice in everyday routines and experiences. Differences in children’s environments and experiences affect their ability to adjust their thought patterns, look at issues from alternative perspectives, and learn to adapt to change. In reading, cognitive flexibility is thought to help, for example, in actively shifting our attention back and forth between sounds and meanings of printed words (Duke & Cartwright, 2021; Cartwright, 2023). Cognitive flexibility can also help students evaluate different strategies and approaches for solving math problems.

This next chart shows the percentage of kids by household socioeconomic status with passing scores on an assessment of their cognitive flexibility from kindergarten through fifth grade.3 The chart shows an astounding 27 point gap (22% vs. 49%) for cognitive flexibility at the start of kindergarten between the lowest and highest household socioeconomic groups at the start of elementary school. Although the spread of the gap is cut roughly in half by fifth grade, like working memory it doesn’t fully close by the end of elementary school.

There are real consequences for these differences in cognitive flexibility. In reading, cognitive flexibility is thought to help, for example, in actively shifting our attention back and forth between sounds and meanings of printed words (Duke & Cartwright, 2021; Cartwright, 2023). Cognitive flexibility can also help students evaluate different strategies and approaches for solving math problems.

Impulse (inhibition) control

Researchers describe inhibition control in different ways. Inhibition control involves the ability to ignore distractions (Cartwright, 2023). Inhibition control is the capacity to think before you act. It is the ability to override or delay a dominant response in order to achieve a goal (Dawson & Guare, 2018). Inhibition control develops from infancy over the course of a lifetime. Children’s experiences starting from birth affect their capacity to manage distractions and control emotional impulses.

This next chart shows the percentage of kids by household socioeconomic status with average or higher scores for inhibition control between in fourth and fifth grade.4 The chart shows a roughly 20 point gap for inhibition control in fourth and fifth grade between the lowest and highest household socioeconomic groups. (Mouse over the chart.)

These differences in children’s ability to manage distractions have real consequences for their reading and math achievement. Inhibition control assists readers to stay focused on a reading task (e.g. ignore distractions, avoid daydreaming) and inhibit or suppress irrelevant details in the text while reading for understanding (Cartwright, 2023).

Inhibition control has also been found to support math achievement through its connection to factual knowledge and procedural skills (Cragg et al., 2017). Math procedural knowledge has an interactive relationship with math conceptual knowledge, which supports mathematical thinking and problem solving.

Although data for working memory, cognitive flexibility and inhibition control are presented separately, in reality all three skills are highly interactive and co-dependent with each other (Dawson & Gaure, 2018). The ECLS-K:2011 provides a unique window into the development of this important set of unconstrained skills.

But wait, there’s more

If you’d like to see more data about constrained and unconstrained skills, check out these other posts on Unconstrained Kids:

• What are skills? A basic primer

• What are constrained and unconstrained skills?

• Two skill types, two developmental pathways

• World knowledge in kindergarten and first grade

Works Cited

Cartwright, K. B. (2023). Executive skills and reading comprehension: A guide for educators. New York: The Guilford Press.

Cragg, L., Keeble, S., Richardson, S., Roome, H. E., & Gilmore, C. (2017). Direct and indirect influences of executive functions on mathematics achievement. Cognition, 162, 12-26.

Cuevas, K., Rajan, V., & Bryant, L. J. (2017). Emergence of executive function in infancy. In S. A. Wiebe and J. Karbach (Eds.), Executive function: Development across the life span. (pp. 11-28). New York: Routledge.

Dawson, P., & Guare, R. (2018). Executive skills in children and adolescents: A practical guide to assessment and intervention. New York: The Guilford Press.

Duke, N. K., & Cartwright, K. B. (2021). The science of reading progresses: Communicating advances beyond the simple view of reading. Reading Research Quarterly, 56, S25-S44.

Graham, S., & Aitken, A. (2025). The Writer(s)-within-Community Model. In C. A. MacArthur, S. Graham, & J. Fitzgerald (Eds.), Handbook of writing research (Third). The Guilford Press.

Jacob, R., & Parkinson, J. (2015). The Potential for School-Based Interventions That Target Executive Function to Improve Academic Achievement: A Review. Review of Educational Research, 85(4), 512–552.

Kim, Y. S. G. (2020). Hierarchical and dynamic relations of language and cognitive skills to reading comprehension: Testing the direct and indirect effects model of reading (DIER). Journal of Educational Psychology, 112(4), 667.

Kim, Y. S. G., & Graham, S. (2022). Expanding the Direct and Indirect Effects Model of Writing (DIEW): Reading–writing relations, and dynamic relations as a function of measurement/ dimensions of written composition. Journal of Educational Psychology, 114(2), 215.

Najarian, M., Tourangeau, K., Nord, C., & Wallner-Allen, K. (2018). Early Childhood Longitudinal Study, Kindergarten Class of 2010–11 (ECLS-K: 2011), first-and second-grade psychometric report (NCES 2018-183). National Center for Education Statistics, Institute of Education Sciences, US Department of Education

Slotkin, J., Kallen, M., Griffith, J., Magasi, S., Salsman, J., & Nowinski, C. (2012). NIH toolbox. Technical Manual.

Sowinski, C., LeFevre, J. A., Skwarchuk, S. L., Kamawar, D., Bisanz, J., & Smith-Chant, B. (2015). Refining the quantitative pathway of the Pathways to Mathematics model. Journal of Experimental Child Psychology, 131, 73-93.

Stafford-Brizard, K. B. (2016). Nonacademic skills are the necessary foundation for learning. Education Week. Retrieved from http://www.edweek.org/ew/articles/2016/07/21/nonacademic-skills-are-the-necessary-foundation-for.html.

First posted: March 7, 2025

Last updated: April 21, 2026

Three big ideas

1. Scott Paris, a former University of Michigan professor, first proposed Constrained Skill Theory in a peer-reviewed article published in 2005. He wrote a total of seven articles and edited book chapters on this topic. His primary focus was the challenge posed by constrained reading skills to statistical analyses of reading.

2. Two articles were published by other researchers in 2011 and 2016 that built upon the constrained skill framework for early literacy. Writing directly to educators and policymakers, they sought to expand the audience beyond academic researchers.

3. Between 2020 and 2023, multiple groups of researchers published articles and research briefs expanding the constrained skill framework to include mathematics and nonacademic (executive) skills. The intended audience appears to be largely policymakers and academic researchers.

Literacy skills

Scott Paris, a former University of Michigan professor, in 2005 published the first academic paper to describe two types of reading skills—constrained and unconstrained.

Paris, S. G. (2005). Reinterpreting the development of reading skills. Reading Research Quarterly, 40(2), 184-202.

This paper largely focused on statistical methods. Paris argued that constrained reading skills go from no ability to proficiency in a relatively brief period of time. Unconstrained skills develop slowly over longer periods of time. Paris argued that these characteristics and differences affect statistical analyses and interpretation. When researchers cite Paris, this is typically the paper they refer to. According to Google Scholar, this paper has been cited over 1,200 times. You can find this paper online.

The same year, Paris and three co-authors published a chapter in an edited book.

Paris, S. G., Carpenter, R. D., Paris, A. H., & Hamilton, E. E. (2005). Spurious and genuine correlates of children’s reading comprehension. In S. Paris & S. Stahl (Eds.), Children's Reading Comprehension and Assessment (pp. 149-178). New York: Routledge.

This chapter also had a heavy statistical methods focus. Interestingly, it included a vignette on the origin story for the discovery of constrained skill theory. The paper analyzed the relationships between oral reading fluency and print knowledge (both constrained skills) and reading comprehension (unconstrained). The paper discussed temporary relationships (correlations) between constrained and unconstrained reading skills. It described challenges with aggregated data and sampling related to interpreting results involving constrained and unconstrained skills. The paper concluded with a discussion of long-run relationships (correlations) between reading comprehension and (individually) language skills, vocabulary, and narrative reasoning skills. These four literacy skills are all unconstrained.

Two years later, Paris co-authored another chapter on constrained skill theory in an edited book.

Paris, S. G., & Paris, A. H. (2007). Assessments of early reading. In Damon, W., Lerner, R. M., Renninger, K. A., & Sigel, I. E. (Eds.). Handbook of Child Psychology, Volume Four: Child Psychology in Practice. (pp. 48-74) Hoboken, NJ: John Wiley & Sons.

This chapter focused on assessments of early reading skills. There was more limited statistical methods discussion in this chapter. It featured a notable shift toward implications of constrained skill theory for application, practice, and policy compared to the two previous papers. The chapter discussed reading assessments, the five parts of reading, and reading interventions. It also mentioned that constrained skill theory might also be applied to mathematics and other skills. In my opinion, this is one of the better — if not the best — papers authored by Paris on constrained skill theory.

Two years later, Paris authored a chapter in an edited book on constrained skill theory.

Paris, S. G. (2009). Constrained skills–So what? In K. M. Leander, D. W. Rowe, D. K. Dickinson, M. K. Hundley, R. T. Jimenez, & V. J. Risko (Eds.), 58th Yearbook of the National Reading Conference (pp. 34-44). Oak Creek, WI: National Reading Conference.

This chapter revisited the methodological argument behind constrained skill theory. It explained the nature of constrained and unconstrained skills. It discussed how the “shape of skill development” challenged prevailing theories of reading development. The chapter concluded with a discussion about the challenges that constrained skills in particular pose to common statistical analyses of reading development.

The same year, Paris and Hamilton published a chapter in an edited book.

Paris, S. G., & Hamilton, E. E. (2009). The development of children’s reading comprehension. In S. E. Israel & G. G. Duffy (Eds.), Handbook of Research on Reading Comprehension (pp. 56-77). New York: Routledge.

The first part of the chapter reviewed major models of reading comprehension. It highlighted three key research issues regarding the relationship between working memory, self-regulation, and oral reading fluency with reading comprehension. The chapter focused heavily on one methodological aspect of constrained skill theory: proficiency thresholds. The core idea was that the mastery level of different component skills required to support reading comprehension varied by skill type.

The following year, Paris and Luo published an article critiquing statistical analyses in the National Early Literacy Panel report.

Paris, S. G., & Luo, S. W. (2010). Confounded statistical analyses hinder interpretation of the NELP report. Educational Researcher, 39(4), 316-322.

NELP was convened in 2002. Its charge was to produce a synthesis of scientific research on the development of early literacy skills in children birth to five. This article applied the arguments developed in the previous three papers to the NELP report. Paris and Luo argued that the combination of constrained and unconstrained skills challenged the statistical analyses, interpretations, and recommendations in the report. (The report’s authors responded: they disagreed. Interestingly, one of authors of this response would later co-author a paper that expanded constrained skill theory beyond literacy.) In this paper, Paris and Luo suggested that longitudinal studies were better than cross-sectional studies for understanding the developmental dynamics of constrained and unconstrained skills from low to high mastery. You can read this paper online.

A year later, Paris published a chapter on constrained skill theory in an edited book. As far as I can tell, this appears to be Paris’s seventh and final publication on constrained skill theory.

Paris, S. G. (2011). Developmental differences in early reading skills. In S. Neuman & D. Dickinson (Eds.), Handbook of early literacy research (Vol. 3, pp. 228-241). New York: Guilford Press.

This chapter focused on differences in developmental trajectories of early reading skills. It made three claims: 1) some skills are mastered universally to the same end point; 2) some skills do not exhibit regular and steady growth; and 3) some skills are temporarily co-dependent on other skills. The chapter highlighted developmental trajectories of a set of reading skills to argue its case: alphabetic principle, concepts of print, phonological awareness, phonemic awareness, and oral reading fluency. The chapter concluded with two suggestions for the field. First, it proposed that new theories of reading development be generated that take these constraints into account. Second, it suggested reanalyses of data derived from constrained skills in previous studies. Next to the 2007 paper, I think this is arguably the second best in the Paris canon.

Up to this point, the arguments posed by Paris for constrained skill theory were largely centered on statistical analyses of differences in skill trajectories. Moreover, only two of the seven publications appeared in academic journals that offered greater potential visibility than edited books. In 2011, Katherine A. Dougherty Stahl published the first paper on constrained skill theory written for classroom educators.

Stahl, K. A. D. (2011). Applying new visions of reading development in today's classrooms. The Reading Teacher, 65(1), 52-56.

Stahl described constrained skill theory as “a reconceptualization of reading development that has important implications for classroom practice, curricula, and assessment.” This paper emphasized the varying levels of constraint across skills (“a continuum of constraint”). It defined highly constrained skills (name writing, alphabet knowledge, concepts of print, high-frequency words, phonics), moderately constrained skills (phonological awareness and reading fluency), and unconstrained skills (vocabulary and comprehension). This paper emphasized implications for classroom instruction and assessment. It acknowledged that unconstrained skills were more complex and time consuming to teach and assess than constrained skills. The paper discussed limits of assessments and classroom practices that support the development of unconstrained literacy skills. At the conclusion, Stahl thanked Scott Paris for providing feedback on the development of this paper. You can read this paper online.

Five years later, Catherine Snow and Timothy Matthews co-authored a paper on constrained skill theory targeted at policymakers.

Snow, C. E., & Matthews, T. J. (2016). Reading and language in the early grades. The Future of Children, 57-74.

This article used constrained skill theory to explain trends in early literacy development among American children. It expanded the framework to print-related and sound-related skills (constrained) and language- and knowledge-related skills (unconstrained). The article described unconstrained skills as key predictors of long-term literacy outcomes, i.e. “outcomes measured after third grade.” It drew a direct line between proficiency in unconstrained skills and socioeconomic status. The paper also directly addressed the key challenges of shifting educational practice: “[Constrained skills] are easy to teach and easy to test. Ensuring that teachers pay appropriate attention to unconstrained skills in early childhood and primary classrooms is a serious challenge.” The article discussed practices, programs, and interventions that support both constrained and unconstrained skill development. You can read this paper online.

Whenever constrained skill theory is cited in academic research, it most often includes one or more of three articles: Paris (2005), Stahl (2011), and/or Snow and Matthews (2016).

Mathematics and Non-academic skills

Researchers built upon this foundation over the last decade to go beyond literacy skills. The first paper to add mathematics to the constrained skills framework was published in 2020 by Meghan McCormick and colleagues. One of the co-authors was Catherine Snow.

McCormick, M. P., Weissman, A. K., Weiland, C., Hsueh, J., Sachs, J., & Snow, C. (2020). Time well spent: Home learning activities and gains in children’s academic skills in the prekindergarten year. Developmental Psychology, 56(4), 710.

This article examined the impact of constrained and unconstrained learning activities at home on Pre-K children’s academic skills in the classroom. The paper explicitly defined constrained and unconstrained math skills along with literacy skills. It also developed a list of constrained and unconstrained activities that support reading and math development.

The following year, Robert Pianta and colleagues from the Early Learning Network published a research brief that added math and executive skills to the constrained skills framework.

Pianta, R., Purtell, K., McCormick, M., Knoche, L., Burchinal, M., Ludvik, D. & Peisner-Feinberg, E. “Sustaining the pre-k boost: Skills type matters,” Spring (Lincoln, NE: Early Learning Network, 2021).

This research brief described constrained skills as “rote” or “basic” and unconstrained skills as “abstract.” It listed math and literacy skills in both categories, which it described as a continuum of skills. It also explicitly named executive functioning as an unconstrained skill. You can read this research brief online.

That same year, Jamie Spiegel and colleagues published an meta-analysis on the relationship between executive skills and reading, math, and oral language academic achievement.

Spiegel, J. A., Goodrich, J. M., Morris, B. M., Osborne, C. M., & Lonigan, C. J. (2021). Relations between executive functions and academic outcomes in elementary school children: A meta-analysis. Psychological Bulletin, 147(4), 329.

This meta-study examined the relationship between executive function skills — working memory, attention shifting, and inhibition control — and reading, math, and oral language achievement. The paper explicitly defined various reading, math, and oral language component skills as constrained or unconstrained. Unlike Pianta et al. (2021), the authors did not apply the framework to executive skills themselves.

The following year, Meghan McCormick and Shira Mattera published a research brief calling for assessment of both constrained and unconstrained skills in Pre-K programs.

McCormick, M., & Mattera, S. (2022). Learning more by measuring more: Building better evidence on pre-k programs by assessing the full range of children's skills. MDRC: New York, NY.

This research brief included a table that listed “more constrained” and “more unconstrained” language/literacy and math skills. Like Pianta et al. (2021), the research brief referenced executive function as an unconstrained skill. With echoes of Paris & Paris (2007), the research brief called for Pre-K assessments to include both constrained and unconstrained skills. You can read this paper online.

The following year, Arya Ansari and colleagues published an article that used constrained skill theory to analyze the relationship between participation in Pre-K programs and academic achievement in first grade.

Ansari, A., Zimmermann, K., Pianta, R. C., Whittaker, J. V., Vitiello, V. E., Yang, Q., & Ruzek, E. A. (2023). The first-grade outcomes of pre-k attendees: Examining benefits as a function of skill type, environments, and subgroups. American Educational Research Journal, 60(6), 1139-1173.

This article explicitly used the constrained skill framework to analyze the convergence in early elementary school in ability between students who did and did not attend Pre-K programs. The study included four types of skills: reading, math, executive function, and socioemotional. It divided reading and math skills that were assessed into constrained (rote) and unconstrained (abstract) skills. It described both executive function and socioemotional skills as unconstrained. You can read this paper online.

Collectively, these research papers provide the research framework for constrained and unconstrained skills applied to reading and math achievement.

But wait, there’s more

If you’d like to learn more about constrained and unconstrained skills, check out these other posts:

• A basic primer on skills (they are essential to human life)

• What are constrained and unconstrained skills?

• A secret hiding in plain sight?

First posted: March 7, 2025

Last updated: April 18, 2026

Three Big Ideas

1. Two types of skills support reading, writing, and math achievement—constrained and unconstrained skills.

2. Most children reach relatively high levels of proficiency in constrained skills in elementary and middle school. By contrast, significant gaps in proficiency in unconstrained skills persist across socioeconomic groups.

3. Constrained and unconstrained skills follow distinct developmental pathways. Constrained skills are largely developed in formal classroom settings. Unconstrained skills are developed both inside and outside of classrooms.

Two types of skills; two developmental pathways

In a previous post, we introduced the idea that there are two types of skills that support reading, writing, and math achievement — constrained and unconstrained skills. I suggest you read this post before diving into this one.

Constrained skills

Constrained skills are mostly learned in formal classroom settings. Constrained skills are relatively straightforward to teach. Constrained skills tend to be more visibly. You can actually see whether a child knows their letters, can decode a word, or add 2 +2. In fact, much of the interventions and tutoring children receive to support reading and math focus on constrained skills. Given the limited amount of information involved and universal finish line for mastery, they are also relatively straightforward to assess. Popular reading assessments like DIBELS overwhelmingly focus on constrained skills. Most typically developing children master constrained skills within relatively limited amounts of time.

Unconstrained skills

By contrast, unconstrained skills are developed outside and inside formal classroom settings. Given the broader amounts of information involved, it is not as straightforward to teach unconstrained skills. These skills traditionally are harder (but not impossible) to assess.1 For the most part, these unconstrained skills are not assessed as frequently as constrained skills, if at all.2 These “taught and caught” skills generally take more time to build than constrained skills.

Data

The best way to see differences in how constrained and unconstrained skills develop is to track students over time (Paris & Luo, 2010). In this post, I use data from the Early Childhood Longitudinal Study, Kindergarten Class of 1998-99 (ECLS-K). The ECLS-K tracked roughly 22,000 U.S. children from kindergarten (fall 1998) through grade 8 (spring 2007). It’s the best dataset I’ve found to dig deep into individual K-8 reading and math skills. I’ve organized the data by household socioeconomic status.3

Constrained reading skills

Let’s start with constrained reading skills.4 There are roughly 240 ways that we combine the 26 letters in the English alphabet to represent combinations of the 44 basic sounds in the English language. Kids learn the rules for how to read words mainly in school. This first chart shows that despite early differences between students across socioeconomic groups, virtually all children learn basic phonics and decoding rules in elementary school.

Of course, not all words in English follow phonics rules. Kids need to learn to recognize 200-300 irregularly spelled words in order to read proficiently. Again, despite early differences across socioeconomic groups, most kids learn to recognize sight words by third grade. The remaining gap is completely closed by the end of elementary school.

Constrained math skills

In math, children have to master roughly 20 symbols to decode almost any math problem they will encounter in elementary and middle school. Half of these are the ten digits between 0 to 9. The other half are the symbols used in mathematical operations. The standard addition table (from 0 to 9) has 100 facts to learn. The multiplication table (through 12s) has 144 facts (12 x 12) to learn. But when we account for the simple ones for each (like 0s, 1s, and turnarounds like 7 x 3 and 3 x 7) we’re left with about 30 unique addition facts and 36 unique multiplication facts to learn.

This next chart shows proficiency in addition and subtraction from kindergarten through fifth grade. Despite early differences in proficiency by the end of elementary school virtually all kids have reached high proficiency in these constrained math skills.

Proficiency in multiplication and division takes longer.5 There are still meaningful differences across socioeconomic groups at the end of fifth grade. But these gaps largely narrow by the end of middle school.

To sum up, despite early gaps we find that children across socioeconomic groups generally reach a high degree of proficiency in constrained reading and math skills in elementary school. The story looks differently, however, for unconstrained skills.

Unconstrained reading skills

The goal of reading is comprehension: the ability to process written text, understand its meaning, and integrate it with what the reader already knows. Only the first part of that three part definition is constrained — processing written text (i.e. word reading). The other two parts — language comprehension (processing meaning) and conceptual and world knowledge — are unconstrained. When we mix one part constrained skill with two parts unconstrained skill, we get an unconstrained skill: reading comprehension.

This next chart shows proficiency in literal inference (comprehension) from kindergarten through eighth grade.6 As we would expect, few kids in any socioeconomic group are proficient in this reading skill at the end of kindergarten. By the end of first grade, however, a large gap emerges. Although proficiency increases for all students groups across elementary and middle school, the gaps across socioeconomic groups does not significantly narrow like the constrained reading skills.

We see similar patterns for increasingly complex levels of reading comprehension.

Unconstrained math skills

The goal of mathematics is mathematical thinking: the ability to process quantitative situations, understand their underlying structures, and flexibly apply reasoning to make sense of the world. Only the first part of that definition is constrained—processing the quantity (e.g., identifying numbers and basic facts). The other two parts—relational thinking (understanding how numbers relate) and mathematical reasoning (applying logic to new problems)—are unconstrained. When we mix one part constrained procedural skill with two parts unconstrained reasoning, we get an unconstrained skill: mathematical thinking.

This next chart shows proficiency in understanding place value from first through eighth grade.7 This next chart shows proficiency in understanding place value from first through eighth grade. Proficiency here depends upon a child’s “mental number line”—the spatial representation of quantity. This mental number line acts as an “internal map” that allows a child to visualize and locate where a number sits relative to other numbers. It is the core of relational thinking: the ability to see the structure behind the symbols.

Early gaps across socioeconomic groups in this skill appear by first grade. The gaps widen in elementary school and are still meaningfully present by the end of eight grade.

A very common math task in school is solving word problems. Solving a word problem is the “reading comprehension” of mathematics. It requires one part constrained skill (calculation and decoding) and two parts unconstrained skill (relational thinking and linguistic logic). You cannot solve the problem by just “reading” the numbers; you have to understand the “story” of the quantities. This next chart shows proficiency in solving word problems involving rate and measurement from third through eighth grade.8 Significant proficiency gaps are present across socioeconomic groups by third grade that persist through middle school.

Is “unconstrained” an overly complicated way of saying “harder”?

Looking at these charts, it’s reasonable to wonder whether we can simply use the word “harder” or “complex” to describe “unconstrained” skills?9 Indeed, many unconstrained skills are clearly more complex than constrained skills. There is more information to be acquired, consolidated, and integrated to (eventually) use automatically. Proficiency in unconstrained skills often requires mastery of a mix of other constrained and unconstrained skills. In this sense, it is accurate to describe more complex unconstrained skills as “harder” to develop.

But unconstrained skills are distinguished from constrained skills in other ways:

• Constrained skills involve information that everyone has virtually equal access to—letters, numbers, high frequency words, numerical operations, etc.

• Not everyone has equal access to the information involved with unconstrained skills—vocabulary, comprehension, background knowledge, etc.

• Unconstrained skills tend to be “caught and taught,” developing in informal learning environments (e.g. home, community) as well as formal learning environments (e.g. the classroom).

• Unconstrained skills such as working memory, cognitive flexibility, vocabulary, and background knowledge develop from learning experiences in and outside of the classroom. Not all kids enjoy the same opportunities for these experiences.

Two distinct developmental pathways

This table offers a summary of the characteristics of constrained and unconstrained skills. It is derived from descriptions of constrained and unconstrained skills in research papers about constrained skill theory. Both skill types follow distinct developmental pathways. Children and youth are likely to have more common opportunities and experiences to develop constrained skills than unconstrained skills.

But wait, there’s more

If you’d like to learn more about constrained and unconstrained skills, check out these other posts:

• A basic primer on skills

• The importance of skill type

• The science of skill building

• A secret hiding in plain sight?

• How informal learning can help grow unconstrained skills

Works cited

Kim, Y.-S. G., & Pilcher, H. (2016). What is listening comprehension and what does it take to to improve listening comprehension? In R. Schiff & M. Joshi (Eds.), Handbook of Interventions in Learning Disabilities (pp. 159–174). Springer.

McCormick, M., & Mattera, S. (2022). Learning more by measuring more: Building better evidence on pre-k programs by assessing the full range of children’s skills. MDRC.

Paris, S. G., & Luo, S. W. (2010). Confounded statistical analyses hinder interpretation of the NELP report. Educational Researcher, 39(4), 316-322.

Whittingham, C. E., Hoffman, E. B., & Paciga, K. A. (2024). Assessment, accountability, and access: Constrained skill mastery as instructional gatekeeper. Journal of Early Childhood Literacy, 24(1), 69–95.

Subscribe now

First posted: March 7, 2025

Last updated: June 10, 2026

Three Big Ideas

1. Two types of skills support reading, writing, and math achievement —constrained and unconstrained skills.

2. These two skill types differ in the amount of information involved, access to this information, clarity of the definition of mastery, and the universality of measures of mastery.

3. Most typically developing children reach relatively high levels of proficiency in constrained skills. By contrast, more children achieve lower levels of proficiency in unconstrained skills.

Two types of skills support reading, writing, and math achievement

In 2005, Scott Paris, a former University of Michigan professor, published the first of a series of academic papers describing differences in relationships between various reading skills over time.1 He divided reading skills into two categories based largely upon features related to their mastery: constrained and unconstrained.

Over the next 20 years, other researchers built upon this Constrained Skill Theory. Initial contributors continued to focus on early literacy, adding implications for instruction and policy. Later researchers added math skills and executive function skills.

Today, researchers suggest skills differ in four fundamental ways:

• The amount of information associated with learning a particular skill.

• The definition of mastery of a skill and whether it’s the same for everyone.

• The amount of time typically needed to reach mastery of a skill.

• The manner in which a skill is learned or acquired.

Constrained skills

Constrained skills involve a relatively limited amount of information.2 Everyone works with the same information.3 Mastery is clearly defined. The yardstick for mastery is the same for everyone.4 These constrained skills support reading, writing, and mathematics.

Data

I review student proficiency in reading and math skills using a nationally representative dataset of U.S. nine-year-olds: the National Assessment of Educational Progress Long-Term Trend Assessment (LTT).5 The NAEP LTT comes from the National Center for Education Statistics. This long-term trend version of the NAEP dates to the early 1970s. Performance levels in reading and math on the NAEP LTT can readily be ordered from more to less constrained. Roughly 7,400 nine-year-olds for each subject in each testing round. LTT is assessed for nine-year-olds during the school year from January through March.

Figure 1 shows the percentage of U.S. nine-year-olds across racial subgroups who were proficient in a constrained math skill: simple arithmetic.6 Between 2008 and 2020 virtually all American nine-year-olds were highly proficient in this constrained math skill.7 The closing of schools and community spaces due to the COVID-19 global pandemic caused a temporary widening of skill performance, but this gap narrowed in 2025.

Figure 1

Now, let’s turn to reading. Figure 2 shows the percent of U.S. nine-year-olds who were proficient in simple reading tasks.8 Proficiency is not as universally high as math skills. However, the gap between student racial groups was limited to 6 to 8 points prior to the pandemic. (Mouse over the chart to see the percentages.) And all student groups were generally 90% proficient or higher.9 Similar to math, the drop in skill performance in 2022 due to the global pandemic was effectively erased in 2025.

Figure 2

Unconstrained skills

Unconstrained skills involve much broader amounts of information. Everyone doesn’t have access to the same information. Unlike constrained skills, there is no universal finish line for mastery. There is always the opportunity to learn more.

I’ve identified four groups of unconstrained skills from a review of research on unconstrained skills, as well as reading, writing, and math cognition.

Figure 3 looks at math proficiency again on the NAEP LTT for U.S. nine-year-olds, this time for an unconstrained math skill: math operations and reasoning.10 Unlike the constrained math skill in Figure 1, we see significant and persistent gaps across student racial groups over nearly two decades.

Figure 3

Figure 4 shows the same information for an unconstrained reading skill: simple inferential comprehension.11 Once again, we see significant and persistent gaps in skills across student groups for nearly 20 years.

Figure 4

A continuum of constraint

So far, I’ve described skills as either “constrained” or “unconstrained.” In reality skills fall along a “continuum of constraint” (Paris, 2005; Stahl, 2011; McCormick & Mattera, 2022). Constrained skills sometimes are divided into “highly constrained” and “moderately constrained.” But unconstrained skills have degrees of constraint, too. For example, comprehension is an unconstrained skill. Yet, literal comprehension (without inference) of simple text is more constrained than inferential comprehension of complex text.

As skills become less constrained, they require the acquisition, consolidation, integration, and generalization of more information. This “information” sometimes takes the form of proficiency in earlier component skills. For example, proficiency in letter identification becomes integrated into word reading, just as number identification is absorbed into skill in addition.

Not another way to say “simple” versus “complex”

One might be tempted to think that constrained and unconstrained skills is an overly complicated way of describing “simple” versus “complex” skills. To some degree, this is true for some skills. For example, letter knowledge (constrained) is clearly much simpler than reading comprehension (unconstrained).

Many unconstrained skills, however, defy this simple categorization. For example, unconstrained skills such as vocabulary and background knowledge — critical for reading and math — can’t be categorized as merely more “complex” than constrained skills such as reading fluency or addition. Executive function skills such as working memory, impulse control, or attention shifting don’t fit into the “simple versus complex” classification.

So far, we’ve addressed the first two of four defining characteristics of constrained and unconstrained skills at the beginning of this post. A review of the other two features — the time needed for mastery and the manner in which skills are developed — offers a greater appreciation of the importance of skill type for reading, writing, and math achievement. This is the topic of the next post in this series.

But wait, there’s more

If you’d like to learn more about constrained and unconstrained skills, check out these other posts:

• A basic primer on skills (they are essential to human life)

• Two skill types, two developmental pathways

• A secret hiding in plain sight?

• How informal learning can help grow unconstrained skills

Works cited

McCormick, M., & Mattera, S. (2022). Learning more by measuring more: Building better evidence on pre-k programs by assessing the full range of children’s skills. MDRC.

Paris, S. G. (2005). Reinterpreting the development of reading skills. Reading Research Quarterly, 40(2), 184-202.

Stahl, K. A. D., & García, G. E. (2022). Expanding reading comprehension in grades 3–6: Effective instruction for all students. New York: The Guilford Press.

Subscribe now

First posted: March 7, 2025

Last updated: April 21, 2026

Three Big Ideas

1. The limitations of the human brain create a biological imperative to act with limited effort. In other words, we must develop highly efficient, automatic skills.

2. Skill is the capacity to think and act in an organized way in a specific context. When we change the context, we change the skill.

3. Skills are gradually built and mastered through repeated practice in real activities across a variety of contexts. Skill building takes time, effort, and support.

We have a biological need for skill

It might surprise you to learn that the primary job of our brains is not thinking. It’s anticipating and adjusting energy use for our bodies (Barrett, 2020).1 Although adult human brains make up only about two percent of our body weight, they use about 20% of our energy. For a newborn it’s at least 65%, which explains why they sleep all the time (Bryson, 2019). Unlike other organs, our brain burns calories at a steady rate no matter what the rest of our body is doing. We have a strong biological incentive to efficiently use precious resources. This requires the ability to act with limited effort. In other words, we must develop skills.

Skill is essential for goal-oriented behavior

The human brain has limited capacity for actively holding information. A key aspect of skill development is automaticity. Highly developed, automatic skills enable us to take actions without the conscious awareness of the steps or control involved (Afflerbach et al., 2008). We use automatic actions all the time – from simple tasks like tying our shoes or chopping a vegetable to more complex activities like playing a musical instrument or driving a car. The development and refinement of automatic skills to support goal-oriented action is an essential part of human life.

Skill building takes time and effort

Skill is the capacity to think and act in an organized way in a specific context (Immordino-Yang & Fischer, 2010). This definition comes from developmental psychologists. It might be useful to think about skill as a rope.2

What we commonly refer to as “skill” generally is a collection of “mini-skills” (Khaneman, 2011). In other words, individual strands in a skill rope. For example, a basketball player has to successfully coordinate and integrate discrete running, jumping, and visual-motor skills to be successful on the court. As you read the written text in this paragraph, you are coordinating an array of skills all at once: basic executive function skills, word reading skills, language-based skills, and high-level thinking skills life inference and reasoning.

The initial phases of skill development involve active control, focus on achieving a goal, and explicit awareness of our actions. Simpler skills like learning the alphabet support the learning and development of more sophisticated and complex ones like word reading (Bailey et al., 2017). In other words, “skills beget skills” (Cunha & Heckman, 2007; Heckman, 2008).

Skills are hierarchical (they build on each other), interactive (they work together), and dynamic (they are used differently in various situations) (Fischer & Bidell, 2006; Kim, 2020). Skill building is a cycle of learning, forgetting, re-learning, consolidation, and re-consolidation (Fischer & Bidell, 2006).

Skill building requires support

Skill ropes don’t weave themselves. Skill building is an active process. And skill building doesn’t happen alone. Children and youth need help to build skill ropes. Each of the strands needs to be woven by hand. Skill building happens best in stable, predictable environments. And because skill building is messy (building, collapse, rebuilding), kids need opportunity to weave tight, strong skill ropes through repeated practice (Khaneman, 2011).

Skills develop from the interactions between children’s personal characteristics (skills, interests, motivation, etc.), their environment, and the people and organizations they interact with (Bronfenbrenner & Morris, 2006). Academic achievement is shaped by the opportunities children and youth have to develop skills within their personal systems of support (Byrnes & Miller, 2007). This at once describes the opportunity and challenge of helping children and youth develop skills to support reading, writing, and math achievement.

Context matters for skill building

Skill is the capacity to think and act in an organized way in a specific context. We don’t build general, abstract skills. We build skills in specific contexts. “Context” means many things at once: the physical environment, emotional state, social support, domain or subject area, and the specific task involved (Fischer & Immordino-Yang, 2002).

When we change the context, we change the skill.

Take running for example. From a skill perspective, there is no such thing as running. There is running on a treadmill, on a track, cross-country, or running on sand. These are not the same exact activity. Running up a hill is not the same as running down a hill. Running in bare feet is different from running in running shoes which is different yet from running in cleats (Mascolo, 2022).

A general skill for running “emerges” from learning to run in specific contexts. This means some aspects of running are transferable across contexts. But different contexts require developing specific abilities to be successful. A successful basketball player may draw upon skills that are used in other sports, but that does not mean they would be successful in football, soccer, or tennis.

When we change the context, we change the skill.

Children and youth develop proficiency in skills in specific contexts and mastery of skills across contexts. Developing complex skills that can be used across a variety of contexts requires time and effort (Fischer & Bidell, 2006). This means lots of practice. In a wide variety of settings. Children who have the opportunity to build, practice, and reinforce skills in a variety of contexts have an advantage over those who do not.

Skinny and fat skill ropes

The fibers in our skill ropes are not all the same. Some strands are easier to weave. Others are harder to handle and take more time and effort to twist together. For some skills, we all work with the same materials. These fibers of our skill rope are largely woven in school. These parts of our skill rope look most similar to other people’s ropes. But some strands are more special. We don’t all work with the same materials. These strands are woven from individual experiences and opportunities inside and outside of school settings.

This difference in access and opportunity means that our skill ropes look different. Some children and youth have skinny skill ropes. Others get to work with additional skill fibers and the supports to weave them. These kids get the chance to build strong, fat skill ropes.

A child or youth with a fatter skill rope is able to engage in deeper, more complex levels of reading comprehension without “breaking.” Conversely, a child with a skinny skill rope can only bear so much weight. If we want to help children and youth be successful in school and in life, we have to intentionally help them build thick, fat skill ropes. This is more likely to come from experiences inside and outside of school.

Check out the Seven Principles of Skill Building for even more about skill building:

But wait, there’s more

If you’d like to learn more about constrained and unconstrained skills, check out these other posts:

• Constrained and unconstrained skills drive achievement in reading and math

• Two skill types, two developmental pathways

• A secret hiding in plain sight?

Works cited

Afflerbach, P., Pearson, P. D., & Paris, S. G. (2008). Clarifying differences between reading skills and reading strategies. The Reading Teacher, 61(5), 364-373.

Bailey, D., Duncan, G. J., Odgers, C. L., & Yu, W. (2017). Persistence and fadeout in the impacts of child and adolescent interventions. Journal of Research on Educational Effectiveness, 10(1), 7-39.

Barrett, L. F. (2020). Seven and a half lessons about the brain. New York: Houghton Mifflin.

Bronfenbrenner, U., & Morris, P. A. (2006). The bioecological model of human development. In R. M. Lerner & W. Damon (Eds.), Handbook of child psychology: Theoretical models of human development (6th ed., pp. 793–828). Hoboken, NJ: John Wiley & Sons, Inc.

Bryson, B. (2019). The body: a guide for occupants. New York, Anchor Books.

Byrnes, J. P., & Miller, D. C. (2007). The relative importance of predictors of math and science achievement: An opportunity–propensity analysis. Contemporary Educational Psychology, 32(4), 599-629.

Cantor, P., Osher, D., Berg, J., Steyer, L., & Rose, T. (2021). Malleability, plasticity, and individuality: How children learn and develop in context. In P. Cantor & D. Osher (Eds.), The science of learning and development: Enhancing the lives of all young people (pp. 3-54). New York: Routledge.

Cunha, F., & Heckman, J. (2007). The technology of skill formation. American Economic Review, 97(2), 31-47.

Fischer, K. W., & Bidell, T. R. (2006). Dynamic Development of Action and Thought. In R. M. Lerner & W. Damon (Eds.), Handbook of child psychology: Theoretical models of human development (pp. 313–399). New York: John Wiley & Sons, Inc.

Fischer, K.W. & Immordino-Yang, M.H. (2002). Cognitive development and education: From dynamic general structure to specific learning and teaching. In E. Lagemann (Ed.), Traditions of scholarship in education. Chicago: Spencer Foundation.

Heckman, J. J. (2008). Schools, skills, and synapses. Economic Inquiry, 46(3), 289-324.

Immordino-Yang, M. H., & Fischer, K. W. (2010). Neuroscience bases of learning. In V. G. Aukrust (Ed.), International encyclopedia of education (3rd Edition, pp. 310–316). Elsevier.

Khaneman, D. (2011). Thinking, fast and slow. New York: Farrar, Straus and Giroux.

Kim, Y. S. G. (2020). Hierarchical and dynamic relations of language and cognitive skills to reading comprehension: Testing the direct and indirect effects model of reading (DIER). Journal of Educational Psychology, 112(4), 667.

Mascolo, M. (2022, July 20). Dynamic skill theory and Piaget's theory: Some basics [Video]. YouTube. Video link.