Problem solving is an important skill in the knowledge economy. Research indicates that the development of problem solving skills works better in the context of instructional approaches centered on real-world problems. But students need scaffolding to be successful in such instruction. In this paper I present a conceptual framework for understanding the effects of scaffolding. First, I discuss the ultimate goal of scaffolding—the transfer of responsibility—and one way that scholars have conceptualized promoting this outcome (fading). Next, I describe an alternative way to conceptualize transfer of responsibility through the lens of distributed cognition and discuss how this lens informs how to promote transfer of responsibility. Then I propose guidelines for the creation of problem solving scaffolds to support transfer of responsibility and discuss them in light of the literature.
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Aleven, V., Stahl, E., Schworm, S., Fischer, F., & Wallace, R. (2003). Help seeking and help design in interactive learning environments. Review of Educational Research, 73(3), 277–320.
Azevedo, R. (2005). Using hypermedia as a metacognitive tool for enhancing student learning? The role of self-regulated learning. Educational Psychologist, 40(4), 199–209.
Azevedo, R., & Hadwin, A. F. (2005). Scaffolding self-regulated learning and metacognition—Implications for the design of computer-based scaffolds. Instructional Science, 33, 367–379.
Azevedo, R., Cromley, J. G., & Siebert, D. (2004). Does adaptive scaffolding facilitate students’ ability to regulate their learning with hypermedia? Contemporary Educational Psychology, 29(3), 344–370.
Azevedo, R., Cromley, J. G., Winters, F. I., Moos, D. C., & Greene, J. A. (2005). Adaptive human scaffolding facilitates adolescents’ self-regulated learning with hypermedia. Instructional Science, 33, 381–412.
Barab, S. A., & Dodge, T. (2008). Strategies for designing embodied curriculum. In J. M. Spector, M. D. Merrill, J. van Merrienboër, & M. P. Driscoll (Eds.), Handbook of research on educational communications and technology (pp. 97–110). New York: Routledge.
Barrows, H. S. (1985). How to design a problem-based curriculum for the preclinical years. New York: Springer.
Bell, B., Bareiss, R., & Beckwith, R. (1993/1994). Sickle cell counselor: A prototype goal-based scenario for instruction in a museum environment. The Journal of the Learning Sciences, 3(4), 347–386.
Belland, B. R. (2010). Portraits of middle school students constructing evidence-based arguments during problem-based learning: The impact of computer-based scaffolds. Educational Technology Research and Development, 58(3), 285–309.
Belland, B. R., Glazewski, K. D., & Richardson, J. C. (2008). A scaffolding framework to support the construction of evidence-based arguments among middle school students. Educational Technology Research and Development, 56, 401–422.
Belland, B., Glazewski, K., & Ertmer, P. (2009). Inclusion and problem-based learning: Roles of students in a mixed-ability group. Research on Middle Level Education Online, 32(9), 1–19.
Belland, B. R., Glazewski, K. D., & Richardson, J. C. (2011). Problem-based learning and argumentation: Testing a scaffolding framework to support middle school students’ creation of evidence-based arguments. Instructional Science, 39, 667–694.
Bereiter, C., & Scardamalia, M. (1993). Surpassing ourselves: An inquiry into the nature and implications of expertise. Chicago: Open Court.
Berkowitz, M. W. (1980). Moral peers to the rescue! A critical appraisal of the “Plus 1” convention in moral education. ERIC document reproduction service Number ED193138.
Bibok, M. B., Carpendale, J. I. M., & Müller, M. (2009). Parental scaffolding and the development of the executive function. New Directions in Child and Adolescent Development, 123, 17–34.
Bodner, G. M. (1991). A view from chemistry. In M. U. Smith (Ed.), Toward a unified theory of problem solving: Views from the content domains (pp. 21–33). Hillsdale: Lawrence Erlbaum.
Bransford, J. D., & Schwartz, D. L. (1999). Rethinking transfer: A simple proposal with multiple implications. Review of Research in Education, 24, 61–100.
Bransford, J. D., Brown, A. L., & Cocking, R. R. (1999). How people learn: Brain, experience, and school. Washington: National Academies Press.
Bravo, C., van Joolingen, W., & de Jong, T. (2009). Using Co-lab to build systems dynamics models: Students’ actions and online tutorial advice. Computers & Education, 53, 243–251.
Chi, M. T. H., & Glaser, R. (1985). Problem solving ability [Eric document reproduction number 257630]. Pittsburgh: Pittsburgh University.
Coleman, E. B. (1998). Using explanatory knowledge during collaborative problem solving in science. The Journal of the Learning Sciences, 7(3&4), 387–427.
Collins, A., Brown, J. S., & Newman, S. E. (1989). Cognitive apprenticeship: Teaching the crafts of reading, writing, and mathematics. In L. B. Resnick (Ed.), Knowing, learning, and instruction: Essays in honor of Robert Glaser (pp. 453–494). Hillsdale: Lawrence Erlbaum Associates.
Conner, D. B., & Cross, D. R. (2003). Longitudinal analysis of the presence, efficacy and stability of maternal scaffolding during informal problem-solving interactions. British Journal of Developmental Psychology, 21, 315–334.
Davis, E. A., & Linn, M. C. (2000). Scaffolding students’ knowledge integration: Prompts for reflection in KIE. International Journal of Science Education, 22(8), 819–837.
Derry, S. J., DuRussel, L. A., & O’Donnell, A. M. (1998). Individual and distributed cognitions during interdisciplinary teamwork: A developing case study and emerging theory. Educational Psychology Review, 10(1), 25–56.
Detterman, D. K. (1993). The case for the prosecution: Transfer as an epiphenomenon. In D. K. Detterman & R. J. Sternberg (Eds.), Transfer on trial: Intelligence, cognition, and instruction (pp. 1–24). Norwood: Ablex.
Dillenbourg, P. (2002). Over-scripting CSCL: The risks of blending collaborative learning with instructional design. In P. A. Kirschner (Ed.), Three worlds of CSCL. Can we support CSCL (pp. 61–91). Heerlen: Open Universiteit Nederland.
Diziol, D., Walker, E., Rummel, N., & Koedinger, K. R. (2010). Using intelligent tutor technology to implement adaptive support for student collaboration. Educational Psychology Review, 22, 89–102.
Eisenberg, M. B., & Berkowitz, R. E. (1991). Information problem solving: The Big Six skills approach to library and information skills instruction. Norwood: Ablex.
Ellis, A. B. (2007). A taxonomy for categorizing generalizations: Generalizing actions and reflection generalizations. The Journal of the Learning Sciences, 16(2), 221–262.
Fernandez-Duque, D., Baird, J. A., & Posner, M. I. (2000). Executive attention and metacognitive regulation. Consciousness and Cognition, 9, 288–307.
Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new area of cognitive-developmental inquiry. American Psychologist, 34(10), 906–911.
Gagné, R. M. (1965). The conditions of learning (1st ed.). New York: Holt, Rinehart, & Winston.
Gagné, R. M. (1968). Contributions of learning to human development. Psychological Review, 75(3), 177–191.
Gallagher, S. A., Stepien, W. J., & Rosenthal, H. (1992). The effects of problem-based learning on problem solving. Gifted Child Quarterly, 36(4), 195–200.
Ge, X., Chen, C., & Davis, K. A. (2005). Scaffolding novice instructional designers’ problem-solving processes using question prompts in a web-based learning environment. Journal of Educational Computing Research, 33(2), 219–248.
Genor, M. (2005). A social reconstructionist framework for reflection: The “problematizing” of teaching. Issues in Teacher Education, 14(2), 45–62.
Gentner, D., Loewenstein, J., & Thompson, L. (2003). Learning and transfer: A general role for analogical encoding. Journal of Educational Psychology, 95(2), 393–408.
Gick, M. L., & Holyoak, M. J. (1980). Analogical problem solving. Cognitive Psychology, 12, 306–355.
Giere, R. N. (2004). The problem of agency in scientific distributed cognitive systems. Journal of Cognition and Culture, 4(3), 759–774.
Giere, R. N. (2006). The role of agency in distributed cognitive systems. Philosophy of Science, 73, 710–719.
Gijlers, H., Saab, N., Van Joolingen, W. R., De Jong, T., & Van Hout-Wolters, B. H. A. M. (2009). Interaction between tool and talk: How instruction and tools support consensus building in inquiry-learning environments. Journal of Computer-Assisted Learning, 25, 252–267.
Glaser, R., Raghavan, K., & Baxter, G. P. (1992). Cognitive theory as the basis for design of innovative assessment: Design characteristics of science assessments. CSE Technical Report No. 349. Los Angeles: National Center for Research on Evaluation, Standards, and Student Testing. [Eric Document Reproduction Service No. ED357038].
Greeno, J. G., & van de Sande, C. (2007). Perspectival understanding of conceptions and conceptual growth in interaction. Educational Psychologist, 42(1), 9–23.
Hall, R. (2005). Reconstructing the learning sciences. The Journal of the Learning Sciences, 14(1), 139–155.
Halverson, C. A. (2002). Activity theory and distributed cognition: Or what does CSCW need to DO with theories? Computer Supported Cooperative Work, 11, 243–267.
Hannafin, M., Land, S., & Oliver, K. (1999). Open-ended learning environments: Foundations, methods, and models. In C. M. Reigeluth (Ed.), Instructional design theories and models: Volume II: A new paradigm of instructional theory (pp. 115–140). Mahwah: Lawrence Erlbaum.
Hestenes, D. (1987). Toward a modeling theory of physics instruction. American Journal of Physics, 55, 440–454.
Hewitt, J., & Scardamalia, M. (1998). Design principles for distributed knowledge building processes. Educational Psychology Review, 10(1), 75–96.
Hiebert, J., Carpenter, T. P., Fennema, E., Fuson, K., Human, P., Murray, H., et al. (1996). Problem solving as a basis for reform in curriculum and instruction: The case of mathematics. Educational Researcher, 25(4), 12–21.
Hmelo-Silver, C. E. (2004). Problem-based learning: What and how do students learn? Educational Psychology Review, 16(3), 235–266.
Hmelo-Silver, C. E., Duncan, R. G., & Chinn, C. A. (2007). Scaffolding and achievement in problem-based learning and inquiry learning: A response to Kirschner, Sweller, & Clark (2006). Educational Psychologist, 42(2), 99–107.
Hollan, J., Hutchins, E., & Kirsh, D. (2000). Distributed cognition: Toward a new foundation for human-computer interaction research. ACM Transactions on Computer-Human Interaction, 7(2), 174–196.
Hutchins, E. (1995). Cognition in the wild. Cambridge: MIT.
Johnson, D. W., & Johnson, R. T. (1974). Instructional goal structure: Cooperative, competitive, and individualistic. Review of Educational Research, 44(2), 213–240.
Johnson, D. W., & Johnson, R. T. (2009). An educational psychology success story: Social interdependence theory and cooperative learning. Educational Researcher, 38, 365–379.
Johnson-Laird, P. N. (1980). Mental models in cognitive science. Cognitive Science, 4, 71–115.
Jonassen, D. H. (2000). Toward a design theory of problem solving. Educational Technology Research and Development, 48(4), 63–85.
Jonassen, D. H. (2003). Using cognitive tools to represent problems. Journal of Research on Technology in Education, 35(3), 362–381.
Jonassen, D. H., & Hernandez-Serrano, J. (2002). Case-based reasoning and instructional design: Using stories to support problem-solving. Educational Technology Research and Development, 50(2), 65–77.
Kali, Y., & Linn, M. C. (2008). Technology-enhanced support strategies for inquiry learning. In J. M. Spector, M. D. Merrill, J. J. G. van Merriënboer, & M. P. Driscoll (Eds.), Handbook of research on educational communications and technology (3rd ed., pp. 145–161). New York: Lawrence Erlbaum Associates.
Kauffman, D. F., Ge, X., Xie, K., & Chen, C. (2008). Prompting in web-based environments: Supporting self-monitoring and problem-solving skills in college students. Journal of Educational Computing Research, 38(2), 115–137.
Kayluga, S. (2007). Enhancing instructional efficiency of interactive e-learning environments: A cognitive load perspective. Educational Psychology Review, 19, 387–399.
Kayluga, S., & Sweller, J. (2005). Rapid dynamic assessment of expertise to improve the efficiency of adaptive e-learning. Educational Technology Research and Development, 53(3), 83–93.
Koedinger, K. R., & Corbett, A. (2006). Cognitive tutors: Technology bringing learning sciences to the classroom. In K. Sawyer (Ed.), The Cambridge handbook of the learning sciences (pp. 61–78). New York: Cambridge University Press.
Kollar, I., Fischer, F., & Hesse, F. W. (2006). Collaboration scripts: A conceptual analysis. Educational Psychology Review, 18, 159–185.
Kollar, I., Fischer, F., & Slotta, J. D. (2007). Internal and external scripts in computer-supported collaborative inquiry learning. Learning and Instruction, 17, 708–721.
Kolodner, J. L. (1993). Case-based reasoning. San Mateo: Morgan Kaufmann.
Kolodner, J. L., Gray, J. T., & Fasse, B. B. (2003). Promoting transfer through case-based reasoning: Rituals and practices in Learning by Design classrooms. Cognitive Science Quarterly, 3(2), 183–232.
Krause, U., Stark, R., & Mandl, H. (2009). The effects of cooperative learning and feedback on e-learning in statistics. Learning and Instruction, 19, 158–170.
Kuhn, D. (2005). Education for thinking. Cambridge: Harvard University Press.
l’Anson, Rodrigues, S., & Wilson, G. (2003). Mirrors, reflections, and refractions: The contribution of microteaching to reflective practice. European Journal of Teacher Education, 26(2), 189–199.
Lajoie, S. P., Lavigne, N. C., Guerrera, C., & Munsie, S. D. (2001). Constructing knowledge in the context of BioWorld. Instructional Science, 29, 155–186.
Landry, S. H., Smith, K. E., & Swank, P. R. (2009). New directions in evaluating social problem solving in childhood: Early precursors and links to adolescent social competence. New Directions in Child and Adolescent Development, 123, 51–68.
Langer, E. J. (1989). Mindfulness. Reading: Addison-Wesley.
Langer, E. J. (1993). A mindful education. Educational Psychologist, 28(1), 43–50.
Lebeau, R. B. (1998). Cognitive tools in a clinical encounter in medicine: Supporting empathy and success in distributed cognition. Educational Psychology Review, 10(1), 3–24.
Lee, H., & Songer, N. B. (2003). Making authentic science accessible to students. International Journal of Science Education, 25(8), 923–948.
Lin, X., Hmelo, C., Kinzer, C. K., & Secules, T. J. (1999). Designing technology to support reflection. Educational Technology Research and Development, 47(3), 43–62.
Linn, M. C. (2000). Designing the knowledge integration environment. International Journal of Science Education, 22(8), 781–796.
Liu, M., & Bera, S. (2005). An analysis of cognitive tool use patterns in a hypermedia learning environment. Educational Technology Research and Development, 53(1), 5–21.
Lobato, J. (2003). How design experiments can inform a rethinking of transfer and vice versa. Educational Researcher, 32(1), 17–20.
Manlove, S., Lazonder, A. W., & de Jong, T. (2009). Trends and issues of regulative support use during inquiry learning: Patterns from three studies. Computers in Human Behavior, 25, 795–803.
Mayer, R. E. (1995). The search for insight: Grappling with Gestalt psychology’s unanswered questions. In R. J. Sternberg & J. E. Davidson (Eds.), The nature of insight (pp. 3–32). Cambridge: MIT.
Mayer, R. E. (1998). Cognitive, metacognitive, and emotional aspects of problem solving. Instructional Science, 26, 49–63.
McNeill, K. L., Lizotte, D. J., Krajcik, J., & Marx, R. W. (2006). Supporting students’ construction of scientific explanations by fading scaffolds in instructional materials. The Journal of the Learning Sciences, 15(2), 153–191.
Meichenbaum, D., & Biemiller, A. (1992). In search of student expertise in the classroom: A metacognitive analysis. In M. Pressley, K. R. Harris, & J. T. Guthrie (Eds.), Promoting academic competency and literacy in school (pp. 3–56). San Diego: Academic.
Metcalf, S. J. (1999). The design of guided learner-adaptable scaffolding in interactive learning environments. Unpublished doctoral dissertation, University of Michigan. UMI number 99598281.
Nardi, B. A. (1996). Studying context: A comparison of activity theory, situated action models, and distributed cognition. In B. A. Nardi (Ed.), Context and consciousness: Activity theory and human-computer interaction (pp. 69–102). Cambridge: Massachusetts Institute of Technology.
National Science Teachers Association. (2009). NSTA position statement: Beyond 2000—teachers of science speak out. Retrieved 9/16/2009 from: http://www.nsta.org/about/positions/beyond2000.aspx
Nückles, M., Hübner, S., Dümer, S., & Renkl, A. (2010). Expertise reversal effects in writing to learn. Instructional Science, 38, 237–258.
Oliver, K., & Hannafin, M. J. (2000). Student management of web-based hypermedia resources during open-ended problem solving. Journal of Educational Research, 94(2), 75–92.
Palincsar, A. S., & Brown, A. L. (1984). Reciprocal teaching of comprehension-fostering and comprehension-monitoring activities. Cognition & Instruction, 1(2), 117–175.
Pea, R. D. (1993). Distributed intelligence and designs for education. In G. Salomon (Ed.), Distributed cognitions: Psychological and educational considerations (pp. 47–87). Cambridge: Cambridge University Press.
Pea, R. D. (2004). The social and technological dimensions of scaffolding and related theoretical concepts for learning, education, and human activity. The Journal of the Learning Sciences, 13(3), 423–451.
Perkins, D. (1995). Outsmarting IQ: The emerging science of learnable intelligence. New York: Free.
Perkins, D. N. (1996). Person-plus: A distributed view of thinking and learning. In G. Salomon (Ed.), Distributed cognitions: Psychological and educational considerations (pp. 88–109). Cambridge: Cambridge University Press.
Pinkwart, N., Ashley, K., Lynch, C., & Aleven, V. (2009). Evaluating an intelligent tutoring system for making legal arguments with hypotheticals. International Journal of Artificial Intelligence in Education, 19, 401–424.
Pintrich, P. R., & de Groot, E. V. (1990). Motivational and self-regulated learning components of classroom academic performance. Journal of Educational Psychology, 82(1), 33–40.
Puntambekar, S., & Hübscher, R. (2005). Tools for scaffolding students in a complex learning environment: What have we gained and what have we missed? Educational Psychologist, 40(1), 1–12.
Puntambekar, S., & Kolodner, J. L. (2005). Toward implementing distributed scaffolding: Helping students learn science from design. Journal of Research in Science Teaching, 42(2), 185–217.
Putnam, R. T., & Borko, H. (2000). What do new views of knowledge and thinking have to say about research on teacher learning? Educational Researcher, 29(1), 4–15.
Quintana, C., Reiser, J., Davis, E. A., Krajcik, J., Fretz, E., Duncan, R. G., et al. (2004). A scaffolding design framework for software to support science inquiry. The Journal of the Learning Sciences, 13(3), 337–386.
Quintana, C., Zhang, M., & Krajcik, J. (2005). A framework for supporting metacognitive aspects of online inquiry through software scaffolding. Educational Psychologist, 40(4), 235–244.
Reiser, B. J. (2004). Scaffolding complex learning: The mechanisms of structuring and problematizing student work. The Journal of the Learning Sciences, 13(3), 273–304.
Resnick, L. B. (1987). The 1987 presidential address: Learning in school and out. Educational Researcher, 16(9), 13-20+54.
Rosengrant, D., van Heuvelen, A., & Etkina, E. (2006). Case study: Students’ use of multiple representations in problem solving. Physics Education Research Conference, 2005, 49–52.
Salden, R. J. C. M., Aleven, V., Schwonke, R., & Renkl, A. (2010). The expertise reversal effect and worked examples in tutored problem solving. Instructional Science, 38, 289–307.
Salomon, G. (1993). No distribution without individuals’ cognition. In G. Salomon (Ed.), Distributed cognitions: Psychological and educational considerations (pp. 111–138). Cambridge: Cambridge University Press.
Salomon, G., Perkins, D. N., & Globerson, T. (1991). Partners in cognition: Extending human intelligence with intelligent technologies. Educational Researcher, 20(3), 2–9.
Sandoval, W. A., & Reiser, B. J. (2004). Explanation-driven inquiry: Integrating conceptual and epistemic scaffolds for scientific inquiry. Science Education, 88, 345–372.
Saye, J., & Brush, T. (2002). Scaffolding critical reasoning about history and social issues in multimedia-supported learning environments. Educational Technology Research and Development, 50(3), 77–96.
Scandura, J. M. (1977). Problem solving: A structural/process approach with instructional implications. New York: Academic.
Schoenfeld, A. H. (1985). Mathematical problem solving. Orlando: Academic.
Schoenfeld, A. H. (1992). Learning to think mathematically: Problem solving, metacognition, and sense-making in mathematics. In D. Grouws (Ed.), Handbook for research on mathematics teaching and learning (pp. 334–370). New York: Macmillan.
Simons, K. D., & Ertmer, P. A. (2006). Scaffolding disciplined inquiry in problem-based learning environments. International Journal of Learning, 12(6), 297–305.
Slavin, R. E. (1980). Cooperative learning. Review of Educational Research, 50(2), 315–342.
Stratford, S. J., Krajcik, J., & Soloway, E. (1998). Secondary students’ dynamic modeling processes: Analyzing, reasoning about, synthesizing, and testing models of stream ecosystems. Journal of Science Education and Technology, 7(3), 215–234.
Susswein, N., & Racine, T. P. (2009). Wittgenstein and not-just-in-the-head cognition. New Ideas in Psychology, 27, 184–196.
Sutton, M. J. (2003). Problem representation, understanding, and learning transfer: Implications for technology education research. Journal of Industrial Teacher Education, 40(4), 47–63.
Thompson, E., & Stapleton, M. (2009). Making sense of sense-making: Reflections on enactive and extended mind theories. Topoi, 28, 23–30.
Tyler, R. W. (1942). Adventure in American education. Vol. 1. The story of the eight-year study. New York: Harper & Brothers. Accessed 6/1/11 at http://www.archive.org/stream/storyoftheeighty009637mbp/storyoftheeighty009637mbp_djvu.txt
U.S. Department of Education, National Center for Education Statistics. (2006). The Condition of Education 2006 (NCES 2006-071). Washington, DC: U.S. Government Printing Office.
Vosniadou, S. (2007). The cognitive-situative divide and the problem of conceptual change. Educational Psychologist, 42(1), 55–66.
Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. M. Cole, V. John-Steiner, S. Scribner, & E. Souberman (Eds.). Cambridge, MA: Harvard University Press.
Weisburg, R. W. (1993). Creativity: Beyond the myth of genius. New York: Freeman.
White, B. Y., & Frederiksen, J. R. (1998). Inquiry, modeling, and meta-cognition: Making science accessible for all students. Cognition and Instruction, 16(1), 3–118.
Williams, M. D. (1996). Learner-control and instructional technologies. In D. H. Jonassen (Ed.), Handbook of research for educational communications and technology (pp. 112–142). New York: MacMillan Library Reference.
Wolf, S. E., Brush, T., & Saye, J. (2003). Using an information problem-solving model as a metacognitive scaffold for multimedia-supported information-based problems. Journal of Research on Technology in Education, 35(3), 321–341.
Wood, D., Bruner, J., & Ross, G. (1976). The role of tutoring in problem-solving. Journal of Child Psychology and Psychiatry, 17, 89–100.
Woolf, B., Burleson, W., Arroyo, I., Dragon, T., Cooper, D., & Picard, R. (2009). Affect-aware tutors: Recognizing and responding to student affect. International Journal of Learning Technology, 4(3/4), 129–164.
Zhang, B., Liu, X., & Krajcik, J. S. (2006). Expert models and modeling processes associated with a computer-modeling tool. Science Education, 90(4), 579–604.
This work was supported by National Science Foundation Early CAREER grant 0953046 to the author. However, the opinions expressed in this paper do not necessarily represent those of the Foundation.
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Belland, B.R. Distributed Cognition as a Lens to Understand the Effects of Scaffolds: The Role of Transfer of Responsibility. Educ Psychol Rev 23, 577–600 (2011). https://doi.org/10.1007/s10648-011-9176-5
- Transfer of responsibility
- Problem solving
- Computer-based scaffolds
- Distributed cognition