Cognitive Apprenticeship

doi:10.1017/9781108888295.010

8 - Cognitive Apprenticeship

from Part I - Foundations

Published online by Cambridge University Press: 14 March 2022

Allan Collins and

Manu Kapur

Edited by

R. Keith Sawyer

Show author details

R. Keith Sawyer: Affiliation:
University of North Carolina, Chapel Hill

Book contents

Get access

Summary

This chapter reviews how people learn during apprenticeships, ways of guiding beginners while they engage in authentic situated activity with more experienced people. Apprenticeship practices are found throughout the world both in cultures with formal schooling and in those without. Traditional apprenticeship practices tend to focus on physical and visible activities, but most schooling is directed toward conceptual learning outcomes which are usually not physical and visible – like formulas in mathematics or theories in physics. This chapter extends apprenticeship research to cognitive apprenticeship, and describes apprenticeships that are designed to lead to abstract or conceptual knowledge. These involve scaffolding, metacognitive reflection, problem-based learning, and situated social practices. Effective apprenticeship often involves productive failure, when learners initially develop potential solutions that are wrong but that can be productively guided toward conceptually correct answers.

Keywords

apprenticeship situated learning community of practice modeling guided participation productive failure

Information

Type: Chapter
Information: The Cambridge Handbook of the Learning Sciences , pp. 156 - 174
DOI: https://doi.org/10.1017/9781108888295.010 [Opens in a new window]
Publisher: Cambridge University Press
Print publication year: 2022

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Book purchase

Temporarily unavailable

References

Aronson, E. (1978). The jigsaw classroom. Beverly Hills, CA: Sage Publications.Google Scholar

Bielaczyc, K., & Collins, A. (1999). Learning communities in classrooms: A reconceptualization of educational practice. In Reigeluth, C. M. (Ed.), Instructional-design theories and models: A new paradigm of instructional theory (pp. 269–292). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar

Bransford, J. D., Brown, A. L., & Cocking, R. (2000). How people learn: Brain, mind, experience and school (expanded ed.) Washington, DC: National Academy Press.Google Scholar

Bransford, J. D., Franks, J. J., Vye, N. J., & Sherwood, R. D. (1989). New approaches to instruction: Because wisdom can’t be told. In Vosniadou, S. & Ortony, A. (Eds.), Similarity and analogical reasoning (pp. 470–497). New York, NY: Cambridge University Press.CrossRef Google Scholar

Brown, A., & Campione, J. (1996). Psychological theory and the design of innovative learning environments: On procedures, principles, and systems. In Schauble, L. & Glaser, R. (Eds.), Innovations in learning: New environments for education (pp. 289–325). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar

Brown, J. S., Collins, A., & Duguid, P. (1989). Situated cognition and the culture of learning. Educational Researcher, 18(1), 32–42.CrossRef Google Scholar

Burton, R., Brown, J. S., & Fischer, G. (1984). Skiing as a model of instruction. In Rogoff, B. & Lave, J. (Eds.), Everyday cognition: Its developmental and social context (pp. 139–150). Cambridge, MA: Harvard University Press.Google Scholar

Chi, M. T. H., Bassok, M., Lewis, M. W., Reimann, P., & Glaser, R. (1989). Self-explanations: How students study and use examples in learning to solve problems. Cognitive Science, 13(2), 145–182.Google Scholar

Cobb, P., & Bauersfeld, H. (Eds.). (1995). The emergence of mathematical meaning: Interaction in classroom cultures. Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar

Cognition and Technology Group at Vanderbilt. (1997). The Jasper Project: Lessons in curriculum, instruction, assessment, and professional development. Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar

Collins, A., & Brown, J. S. (1988). The computer as a tool for learning through reflection. In Mandl, H. & Lesgold, A. (Eds.), Learning issues for intelligent tutoring systems (pp. 1–18). New York, NY: Springer.Google Scholar

Collins, A., Brown, J. S., & Newman, S. E. (1989). Cognitive apprenticeship: Teaching the craft of reading, writing, and mathematics. In Resnick, L. B. (Ed.), Knowing, learning, and instruction: Essays in honor of Robert Glaser (pp. 453–494). Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar

Collins, A., & Smith, E. E. (1982). Teaching the process of reading comprehension. In Detterman, D. K. & Sternberg, R. J. (Eds.), How much and how can intelligence be increased? (pp. 173–185). Norwood, NJ: Ablex.Google Scholar

Collins, A., & Stevens, A. L. (1983). A cognitive theory of interactive teaching. In Reigeluth, C. M. (Ed.), Instructional design theories and models: An overview (pp. 247–278). Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar

Cuban, L. (1984). How teachers taught. New York, NY: Longman.Google Scholar

Davis, E. A., & Miyake, N. (Eds.). (2004). Special issue: Scaffolding. Journal of the Learning Sciences, 13(3), 265–451.Google Scholar

Gardner, H. (1989). Zero-based arts education: An introduction to Arts Propel. Studies in Art Education, 30(2), 71–83.Google Scholar

Hatano, G., & Inagaki, K. (1991). Sharing cognition through collective comprehension activity. In Resnick, L., Levin, J., & Teasley, S. D. (Eds.), Perspectives on socially shared cognition (pp. 331–348). Washington, DC: American Psychological Association.Google Scholar

Kapur, M. (2008). Productive failure. Cognition and Instruction, 26(3), 379–424.Google Scholar

Kapur, M. (2012). Productive failure in learning the concept of variance. Instructional Science, 40(4), 651–672.Google Scholar

Kapur, M. (2014). Productive failure in learning math. Cognitive Science, 38(5), 1008–1022. doi: 10.1111/cogs.12107 Google Scholar

Kapur, M. (2015). The preparatory effects of problem solving versus problem posing on learning from instruction. Learning and Instruction, 39, 23–31.CrossRef Google Scholar

Kapur, M. (2016). Examining productive failure, productive success, unproductive failure, and unproductive success in learning. Educational Psychologist, 51(2), 289–299.CrossRef Google Scholar

Kapur, M., & Bielaczyc, K. (2012). Designing for productive failure. Journal of the Learning Sciences, 21(1), 45–83.Google Scholar

Kapur, M., & Rummel, N. (2012). Productive failure in learning and problem solving. Instructional Science, 40(4), 645–650.Google Scholar

Kolodner, J. L., Camp, P. J., Crismond, D., et al. (2003). Problem-based learning meets case-based reasoning in the middle-school classroom: Putting learning by design into practice. Journal of the Learning Sciences, 12(4), 495–547.Google Scholar

Lampert, M., Rittenhouse, P., & Crumbaugh, C. (1996). Agreeing to disagree: Developing sociable mathematical discourse. In Olson, D. & Torrance, N. (Eds.), Handbook of education and human development (pp. 731–764). Oxford, England: Blackwell.Google Scholar

Lave, J. (1988). The culture of acquisition and the practice of understanding (Report No. IRL88–0007). Palo Alto, CA: Institute for Research on Learning.Google Scholar

Lave, J., & Wenger, E. (1991). Situated learning: Legitimate peripheral participation. New York, NY: Cambridge University Press.Google Scholar

Lepper, M. R., & Greene, D. (1979). The hidden costs of reward. Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar

Loibl, K., Roll, I., & Rummel, N. (2017). Towards a theory of when and how problem solving followed by instruction supports learning. Educational Psychology Review, 29(4), 693–715. doi:10.1007/s10648-016-9379-x Google Scholar

Norman, D. A. (1973). Memory, knowledge, and the answering of questions. In Solso, R. L. (Ed.), Contemporary issues in cognitive psychology: The Loyola symposium (pp. 135–165). Washington, DC: Winston.Google Scholar

Nowakowski, A., Campbell, R., Monson, D., et al. (1994). Goal-based scenarios: A new approach to professional education. Educational Technology, 34(9), 3–32.Google Scholar

Palincsar, A. S., & Brown, A. L. (1984). Reciprocal teaching of comprehension-fostering and monitoring activities. Cognition and Instruction, 1(2), 117–175.Google Scholar

Quintana, C., Reiser, B. J., Davis, E. A., et al. (2004). A scaffolding design framework for software to support science inquiry. Journal of the Learning Sciences, 13(3), 337–386.CrossRef Google Scholar

Reiser, B. J. (2004). Scaffolding complex learning: The mechanisms of structuring and problematizing student work. Journal of the Learning Sciences, 13(3), 273–304.Google Scholar

Sandoval, W. A., & Reiser, B. J. (2004). Explanation-driven inquiry: Integrating conceptual and epistemic scaffolds for scientific inquiry. Science Education, 88(3), 345–372.Google Scholar

Scardamalia, M., & Bereiter, C. (1994). Computer support for knowledge-building communities. Journal of the Learning Sciences, 3(3), 265–283.Google Scholar

Scardamalia, M., Bereiter, C., & Steinbach, R. (1984). Teachability of reflective processes in written composition. Cognitive Science, 8(2), 173–190.Google Scholar

Schank, R. C., Fano, A., Bell, B., & Jona, M. (1994). The design of goal-based scenarios. Journal of the Learning Sciences, 3(4), 305–346.Google Scholar

Schoenfeld, A. H. (1985). Mathematical problem solving. Orlando, FL: Academic Press.Google Scholar

Schon, D. A. (1983). The reflective practitioner: How professionals think in action. New York, NY: Basic Books.Google Scholar

Schwartz, D. L., & Martin, T. (2004). Inventing to prepare for future learning: The hidden efficiency of encouraging original student production in statistics instruction. Cognition and Instruction, 22(2), 129–184.Google Scholar

Sinha, T., & Kapur, M. (2021). When problem-solving followed by instruction works: Evidence for productive failure. Review of Educational Research, 91(5), 761–798.CrossRef Google Scholar

Sinha, T., Kapur, M., West, R., Catasta, M., Hauswirth, M., & Trninic, D. (2020). Differential benefits of explicit failure-driven and success-driven scaffolding in problem-solving prior to instruction. Journal of Educational Psychology. doi:10.1037/edu0000483 CrossRef Google Scholar

Smith, F. (1988). Joining the literacy club. Portsmouth, NH: Heinemann.Google Scholar

Stigler, J., & Hiebert, J. (1999). The teaching gap: Best ideas from the world’s teachers for improving education in the classroom. New York, NY: Free Press.Google Scholar

VanLehn, K., Siler, S., Murray, C., Yamauchi, T., & Baggett, W. B. (2003). Why do only some events cause learning during human tutoring? Cognition and Instruction, 21(3), 209–249.CrossRef Google Scholar

Vygotsky, L. S. (1978). Mind in society: The development of higher mental processes (Cole, M., John-Steiner, V., Scribner, S., & Souberman, E., Eds.), Cambridge, MA: Harvard University Press.Google Scholar

Wenger, E. (1998). Communities of practice: Learning, meaning, and identity. New York, NY: Cambridge University Press.Google Scholar

White, B. Y. (1984). Designing computer games to help physics students understand Newton’s laws of motion. Cognition and Instruction, 1(1), 69–108.Google Scholar

White, B. Y., & Frederiksen, J. R. (1998). Inquiry, modeling, and metacognition: Making science accessible to all students. Cognition and Instruction, 16(1), 3–118.Google Scholar

Wood, D., Bruner, J. S., & Ross, G. (1976). The role of tutoring in problem solving. Journal of Child Psychology and Psychiatry and Allied Disciplines, 17(2), 89–100.CrossRef Google Scholar PubMed

Accessibility standard: WCAG 2.2 AAA

Why this information is here

This section outlines the accessibility features of this content - including support for screen readers, full keyboard navigation and high-contrast display options. This may not be relevant for you.

Accessibility Information

The HTML of this chapter complies with version 2.2 of the Web Content Accessibility Guidelines (WCAG), offering more comprehensive accessibility measures for a broad range of users and attains the highest (AAA) level of WCAG compliance, optimising the user experience by meeting the most extensive accessibility guidelines.

Content Navigation

Table of contents navigation
Allows you to navigate directly to chapters, sections, or non‐text items through a linked table of contents, reducing the need for extensive scrolling.

Index navigation
Provides an interactive index, letting you go straight to where a term or subject appears in the text without manual searching.

Reading Order & Textual Equivalents

Single logical reading order
You will encounter all content (including footnotes, captions, etc.) in a clear, sequential flow, making it easier to follow with assistive tools like screen readers.

Short alternative textual descriptions
You get concise descriptions (for images, charts, or media clips), ensuring you do not miss crucial information when visual or audio elements are not accessible.

Full alternative textual descriptions
You get more than just short alt text: you have comprehensive text equivalents, transcripts, captions, or audio descriptions for substantial non‐text content, which is especially helpful for complex visuals or multimedia.

Visualised data also available as non-graphical data
You can access graphs or charts in a text or tabular format, so you are not excluded if you cannot process visual displays.

Visual Accessibility

Use of high contrast between text and background colour
You benefit from high‐contrast text, which improves legibility if you have low vision or if you are reading in less‐than‐ideal lighting conditions.