Scaffolding Complex Learning: The Mechanisms of Structuring and Problematizing Student Work
Abstract
There has been much interest in using software tools to scaffold learners in complex tasks, that is, to provide supports that enable students to deal with more complex content and skill demands than they could otherwise handle. Many different approaches to scaffolding techniques have been presented in a broad range of software tools. I argue that two complementary mechanisms can explain how a diversity of scaffolding approaches in software act to support learners. Software tools can help structure the learning task, guiding learners through key components and supporting their planning and performance. In addition, tools can shape students' performance and understanding of the task in terms of key disciplinary content and strategies and thus problematize this important content. Although making the task more difficult in the short term, by forcing learners to engage with this complexity, such scaffolded tools make this work more productive opportunities for learning. I present arguments for these mechanisms in terms of the obstacles learners face, and I present several brief examples to illustrate their use in design guidelines. Finally, I examine how the mechanisms of structuring and problematizing are sometimes complementary and sometimes in tension in design, discuss design tradeoffs in developing scaffolded investigation tools for learners, and consider the reliance of scaffolding on a classroom system of supports.
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Generic support can be applied across different contexts and domains.
“generic support, as it can be applied across different contexts and domains (Hein & Prediger, 2017;Reiser, 2004).”
From Enhancing the Peer-Feedback Process Through Instructional Support: A Meta-Analysis (2025) · cites this paper as Reiser, 2004
A possible explanation for the positive effect of generic support on subject-matter-related knowledge is that structural support might reduce students' need to overly ponder about how to provide feedback, so they can focus explicitly on the learning content.
“a possible explanation for the positive effect of generic support on subject-matter-related knowledge could be that this structural support might reduce students' need to overly ponder about how to provide feedback (as generic support will explicitly tell them how to do this), so that they can focus explicitly on the learning content (e.g., Hein & Prediger, 2017;Reiser, 2004).”
From Enhancing the Peer-Feedback Process Through Instructional Support: A Meta-Analysis (2025) · cites this paper as Reiser, 2004
Cites
(1978) · Medical Entomology and Zoology · Cited by 53,488 · see citing works
Hutchins, E. (1995) · doi:10.7551/mitpress/1881.001.0001 · Cited by 10,801 · see citing works
THE ROLE OF TUTORING IN PROBLEM SOLVING <sup>*</sup>
Wood, D., Bruner, J. S., & Ross, G. (1976) · Journal of Child Psychology and Psychiatry · doi:10.1111/j.1469-7610.1976.tb00381.x · Cited by 8,851 · cited 6× · see citing works
“This notion of problematizing as supporting learners has its roots in the original analysis of scaffolding presented by Wood et al. (1976).”
BackgroundInfluentialApprenticeship in thinking: cognitive development in social context
(1990) · Choice Reviews Online · doi:10.5860/choice.28-0612 · Cited by 5,420 · see citing works
Categorization and Representation of Physics Problems by Experts and Novices*
Chi, M. T. H., Feltovich, P. J., & Glaser, R. (1981) · Cognitive Science · doi:10.1207/s15516709cog0502_2 · Cited by 5,248 · see citing works
Apprenticeship in Thinking: Cognitive Development in Social Context
Rogoff, B. (1990) · doi:10.1093/oso/9780195059731.001.0001 · Cited by 4,709 · see citing works
(1966) · Medical Entomology and Zoology · Cited by 4,505 · see citing works
Talking science: language, learning, and values
Lemke, J. L. (1991) · Choice Reviews Online · doi:10.5860/choice.28-5211 · Cited by 4,000 · see citing works
Cognitive Apprenticeship: Teaching the Crafts of Reading, Writing, and Mathematics
Collins, A., Brown, J. S., & Newman, S. E. (2018) · Knowing, Learning, and Instruction · doi:10.4324/9781315044408-14 · Cited by 3,674 · see citing works
Motivating Project-Based Learning: Sustaining the Doing, Supporting the Learning
Blumenfeld, P. C., Soloway, E., Marx, R. W., Krajcik, J. S., Guzdial, M., & Palincsar, A. (1991) · Educational Psychologist · doi:10.1080/00461520.1991.9653139 · Cited by 3,594 · see citing works
Hollan, J., Hutchins, E., & Kirsh, D. (2000) · ACM Transactions on Computer-Human Interaction · doi:10.1145/353485.353487 · Cited by 2,300 · cited 1× · see citing works
“The framework of distributed cognition has been used to describe these transformative tools (Collins, 1991; Hollan et al., 2000; Pea, 1992; Pea & Gomez, 1992).”
MethodSelf-explanations: How students study and use examples in learning to solve problems
Chi, M. (1989) · Cognitive Science · doi:10.1016/0364-0213(89)90002-5 · Cited by 2,287 · see citing works
Computer Support for Knowledge-Building Communities
Scardamalia, M., & Bereiter, C. (1994) · Journal of the Learning Sciences · doi:10.1207/s15327809jls0303_3 · Cited by 2,164 · see citing works
Handbook of Human-Computer Interaction
(1988) · Elsevier eBooks · doi:10.1016/c2009-0-12113-x · Cited by 2,057 · see citing works
Cognitive Tutors: Lessons Learned
Anderson, J. R., Corbett, A. T., Koedinger, K. R., & Pelletier, R. (1995) · Journal of the Learning Sciences · doi:10.1207/s15327809jls0402_2 · Cited by 1,982 · see citing works
User Centered System Design: New Perspectives on Human-Computer Interaction
Anderson, N. S., Norman, D. A., & Draper, S. W. (1988) · The American Journal of Psychology · doi:10.2307/1422802 · Cited by 1,851 · see citing works
Knowing, Learning, and Instruction
(2018) · Routledge eBooks · doi:10.4324/9781315044408 · Cited by 1,819 · see citing works
Things That Make Us Smart: Defending Human Attributes in the Age of the Machine
Robinson, R., & Norman, D. (1994) · Design Issues · doi:10.2307/1511661 · Cited by 1,528 · see citing works
Barron, B. (2003) · Journal of the Learning Sciences · doi:10.1207/s15327809jls1203_1 · Cited by 1,446 · see citing works
Inquiry, modeling, and metacognition: making science accessible to all students
White, B. Y., & Frederiksen, J. R. (1998) · Cognition and Instruction · doi:10.1207/s1532690xci1601_2 · Cited by 1,394 · see citing works
Direct Manipulation Interfaces
Hutchins, E. L., Hollan, J. D., & Norman, D. A. (1985) · Human-Computer Interaction · doi:10.1207/s15327051hci0104_2 · Cited by 1,374 · see citing works
Engle, R. A., & Conant, F. R. (2002) · Cognition and Instruction · doi:10.1207/s1532690xci2004_1 · Cited by 1,165 · see citing works
Guided Discovery in a Community of Learners
Brown, A. L., & Campione, J. C. (1994) · Classroom Lessons · doi:10.7551/mitpress/1861.003.0016 · Cited by 1,152 · see citing works
The psychology of everyday things
Norman, D. A. (1988) · Choice Reviews Online · doi:10.5860/choice.26-1204 · Cited by 1,062 · see citing works
Dual space search during scientific reasoning
Klahr, D., & Dunbar, K. (1988) · Cognitive Science · doi:10.1207/s15516709cog1201_1 · Cited by 1,058 · see citing works
Practices of Distributed Intelligence and Designs for Education
(1993) · HAL · Cited by 1,046 · see citing works
Learning by Collaborating: Convergent Conceptual Change
Roschelle, J. (1992) · Journal of the Learning Sciences · doi:10.1207/s15327809jls0203_1 · Cited by 1,015 · see citing works
Inquiry and the National Science Education Standards
Board on Science Education, & Education, D. O. B. A. S. S. A. (2000) · National Academies Press eBooks · doi:10.17226/9596 · Cited by 980 · see citing works
Partners in Cognition: Extending Human Intelligence with Intelligent Technologies
SALOMON, G., PERKINS, D. N., & GLOBERSON, T. (1991) · Educational Researcher · doi:10.3102/0013189x020003002 · Cited by 948 · cited 1× · see citing works
“One clear way that tools change the nature of tasks for learners is in automating aspects of tasks and thereby limiting the part of the task the learners need to perform, potentially enabling them to focus on more productive parts of the tasks ( Salomon, Perkins, & Globerson, 1991 ).”
BackgroundScience as argument: Implications for teaching and learning scientific thinking
Kuhn, D. (1993) · Science Education · doi:10.1002/sce.3730770306 · Cited by 918 · see citing works
Addressing the Challenges of Inquiry-Based Learning Through Technology and Curriculum Design
Edelson, D. C., Gordin, D. N., & Pea, R. D. (1999) · HAL · doi:10.1207/s15327809jls0803 · Cited by 875 · see citing works
Group Processes in the Classroom
Berliner, D. C., & Calfee, R. C. (2013) · Routledge eBooks · doi:10.4324/9780203053874-35 · Cited by 842 · see citing works
Internet Environments for Science Education
(2013) · Routledge eBooks · doi:10.4324/9781410610393 · Cited by 767 · see citing works
Explanation‐driven inquiry: Integrating conceptual and epistemic scaffolds for scientific inquiry
Sandoval, W. A., & Reiser, B. J. (2004) · Science Education · doi:10.1002/sce.10130 · Cited by 718 · see citing works
Self-citationInquiry in Project-Based Science Classrooms: Initial Attempts by Middle School Students
Krajcik, J. S., Blumenfeld, P. C., Marx, R. W., Bass, K. M., Fredricks, J. A., & Soloway, E. M. (1998) · Journal of the Learning Sciences · doi:10.1080/10508406.1998.9672057 · Cited by 689 · see citing works
Scientific arguments as learning artifacts: designing for learning from the web with KIE
Bell, P., & Linn, M. C. (2000) · International Journal of Science Education · doi:10.1080/095006900412284 · Cited by 657 · see citing works
Problem Solving as a Basis for Reform in Curriculum and Instruction: The Case of Mathematics
Hiebert, J., Carpenter, T. P., Fennema, E. H., Fuson, K. C., Human, P., Murray, H., Olivier, A., & Wearne, D. (1996) · Educational Researcher · doi:10.3102/0013189x025004012 · Cited by 636 · see citing works
Norman, D. A. (1991) · Cited by 585 · see citing works
Designing to Learn About Complex Systems
Hmelo, C. E., Holton, D. L., & Kolodner, J. L. (2000) · Journal of the Learning Sciences · doi:10.1207/s15327809jls0903_2 · Cited by 578 · see citing works
Scaffolding students' knowledge integration: prompts for reflection in KIE
Davis, E. A. (2000) · International Journal of Science Education · doi:10.1080/095006900412293 · Cited by 531 · see citing works
Appropriating Scientific Discourse: Findings From Language Minority Classrooms
Rosebery, A. S., Warren, B. M., & Conant, F. R. (1992) · Journal of the Learning Sciences · doi:10.1207/s15327809jls0201_2 · Cited by 499 · see citing works
Cognitive Apprenticeship and Instructional Technology
Collins, A. (1988) · doi:10.21236/ada203609 · Cited by 485 · see citing works
Soloway, E. M., Guzdial, M., & Hay, K. E. (1994) · interactions · doi:10.1145/174809.174813 · Cited by 478 · see citing works
Exploring science: the cognition and development of discovery processes
(2001) · Choice Reviews Online · doi:10.5860/choice.38-2703 · Cited by 471 · see citing works
Discourse Patterns and Collaborative Scientific Reasoning in Peer and Teacher-Guided Discussions
Hogan, K., Nastasi, B. K., & Pressley, M. (1999) · Cognition and Instruction · doi:10.1207/s1532690xci1704_2 · Cited by 460 · see citing works
Conceptual and Epistemic Aspects of Students' Scientific Explanations
Sandoval, W. A. (2003) · Journal of the Learning Sciences · doi:10.1207/s15327809jls1201_2 · Cited by 459 · see citing works
How Students Understand Physics Equations
Sherin, B. L. (2001) · Cognition and Instruction · doi:10.1207/s1532690xci1904_3 · Cited by 457 · see citing works
Prompting Middle School Science Students for Productive Reflection: Generic and Directed Prompts
Davis, E. A. (2003) · Journal of the Learning Sciences · doi:10.1207/s15327809jls1201_4 · Cited by 429 · see citing works
Heuristics for Scientific Experimentation: A Developmental Study
Klahr, D., Fay, A. L., & Dunbar, K. (1993) · Cognitive Psychology · doi:10.1006/cogp.1993.1003 · Cited by 397 · see citing works
“Maestro, what is ‘quality’?”: Language, literacy, and discourse in project‐based science
Moje, E. B., Collazo, T., Carrillo, R., & Marx, R. W. (2001) · Journal of Research in Science Teaching · doi:10.1002/tea.1014 · Cited by 381 · see citing works
Putting Case-Based Instruction Into Context: Examples From Legal and Medical Education
Williams, S. M. (1992) · Journal of the Learning Sciences · doi:10.1207/s15327809jls0204_2 · Cited by 367 · see citing works
Addressing the Challenges of Inquiry-Based Learning Through Technology and Curriculum Design
Edelson, D. C., Gordin, D. N., & Pea, R. D. (1999) · Journal of the Learning Sciences · doi:10.1080/10508406.1999.9672075 · Cited by 366 · see citing works
Exploring Science: The Cognition and Development of Discovery Processes
Klahr, D. (2000) · doi:10.7551/mitpress/2939.001.0001 · Cited by 325 · see citing works
Software‐Realized Scaffolding to Facilitate Programming for Science Learning
Guzdial, M. (1994) · Interactive Learning Environments · doi:10.1080/1049482940040101 · Cited by 320 · see citing works
Constructing a Joint Problem Space: The Computer as a Tool for Sharing Knowledge
Teasley, S. D. (1993) · Cited by 307 · see citing works
Students' Understanding of the Objectives and Procedures of Experimentation in the Science Classroom
Schauble, L., Glaser, R. A., Duschl, R. A., Schulze, S. K., & John, J. (1995) · Journal of the Learning Sciences · doi:10.1207/s15327809jls0402_1 · Cited by 305 · see citing works
Direct Manipulation Interfaces
(2011) · SpringerReference · doi:10.1007/springerreference_64794 · Cited by 295 · see citing works
The Computer as a Tool for Learning Through Reflection
Collins, A., & Brown, J. S. (1988) · Springer eBooks · doi:10.1007/978-1-4684-6350-7_1 · Cited by 293 · see citing works
Motivational techniques of expert human tutors: Lessons for the design of computer-based tutors.
Lepper, M. R., Woolverton, M., Mumme, D. L., & Gurtner, J. (1993) · Cited by 293 · see citing works
Designing the Knowledge Integration Environment
Linn, M. C. (2000) · International Journal of Science Education · doi:10.1080/095006900412275 · Cited by 257 · see citing works
Kelly, J. L. (1990) · The American Biology Teacher · doi:10.2307/4449146 · Cited by 250 · see citing works
Beyond the Interface: Encountering Artifacts in Use
Bannon, L. J., & Bødker, S. (1989) · DAIMI Report Series · doi:10.7146/dpb.v18i288.6666 · Cited by 248 · see citing works
A modeling approach to teaching evolutionary biology in high schools*
Passmore, C., & Stewart, J. (2002) · Journal of Research in Science Teaching · doi:10.1002/tea.10020 · Cited by 237 · see citing works
Cognition in scientific and everyday domains: Comparison and learning implications
Reif, F., & Larkin, J. H. (1991) · Journal of Research in Science Teaching · doi:10.1002/tea.3660280904 · Cited by 232 · see citing works
de Vries, E., Lund, K., & Baker, M. J. (2002) · Journal of the Learning Sciences · doi:10.1207/s15327809jls1101_3 · Cited by 227 · see citing works
Using Explanatory Knowledge During Collaborative Problem Solving in Science
Coleman, E. B. (1998) · Journal of the Learning Sciences · doi:10.1080/10508406.1998.9672059 · Cited by 210 · see citing works
Toth, E. E., Suthers, D. D., & Lesgold, A. M. (2002) · Science Education · doi:10.1002/sce.10004 · Cited by 205 · see citing works
The design of guided learner-adaptable scaffolding in interactive learning environments
Jackson, S. L., Krajcik, J. S., & Soloway, E. M. (1998) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/274644.274672 · Cited by 203 · see citing works
Phelps, E., & Damon, W. (1989) · Journal of Educational Psychology · doi:10.1037/0022-0663.81.4.639 · Cited by 190 · see citing works
Causal Models and Experimentation Strategies in Scientific Reasoning
Schauble, L., Glaser, R. A., Raghavan, K., & Reiner, M. (1991) · Journal of the Learning Sciences · doi:10.1207/s15327809jls0102_3 · Cited by 156 · see citing works
Tutoring: Guided Learning by Doing
Merrill, D. C., Reiser, B. J., Merrill, S. K., & Landes, S. (1995) · Cognition and Instruction · doi:10.1207/s1532690xci1303_1 · Cited by 156 · see citing works
Self-citationReflective discourse: developing shared understandings in a physics classroom
Zee, E. H. V., & Minstrell, J. (1997) · International Journal of Science Education · doi:10.1080/0950069970190206 · Cited by 152 · see citing works
Banet, E., & Fernández, G. E. A. (2000) · Science Education · doi:10.1002/(sici)1098-237x(200005)84:3 · Cited by 141 · see citing works
Learning science: A Deweyan perspective
Wong, D., & Pugh, K. J. (2001) · Journal of Research in Science Teaching · doi:10.1002/1098-2736(200103)38:3 · Cited by 128 · see citing works
Distributed Multimedia Learning Environments: Why and How?
Pea, R. D., & Gomez, L. M. (1992) · Interactive Learning Environments · doi:10.1080/1049482920020201 · Cited by 120 · see citing works
Scaffolding scientific competencies within classroom communities of inquiry.
Hogan, K., & Pressley, M. G. (1997) · Cited by 97 · see citing works
The case of Carla: Dilemmas of helpingallstudents to understand science
Kurth, L. A., Anderson, C., & Palincsar, A. S. (2002) · Science Education · doi:10.1002/sce.10009 · Cited by 68 · see citing works
Combining general and domain-specific strategic support for biological inquiry
Tabak, I., Smith, B. K., Sandoval, W. A., & Reiser, B. J. (1996) · Lecture notes in computer science · doi:10.1007/3-540-61327-7_126 · Cited by 60 · see citing works
Self-citationTabak, I., & Reiser, B. J. (1997) · doi:10.3115/1599773.1599809 · Cited by 54 · see citing works
Self-citationQuintana, C., Eng, J., Carra, A., et al. (1999) · doi:10.1145/302979.303136 · Cited by 54 · see citing works
Smith, B. K., & Reiser, B. J. (1998) · ACM SIGCHI Conference on Human Factors in Computing Systems (CHI) · doi:10.1145/274644.274702 · Cited by 30 · see citing works
Self-citationSoftware support for students engaging in scientific activity and scientific controversy
Cavalli‐Sforza, V., Weiner, A. W., & Lesgold, A. M. (1994) · Science Education · doi:10.1002/sce.3730780604 · Cited by 28 · see citing works
(2013) · Routledge eBooks · doi:10.4324/9780203052594-6 · Cited by 28 · see citing works
Hollan, J. D., Bederson, B. B., & Helfman, J. I. (1997) · Elsevier eBooks · doi:10.1016/b978-044481862-1.50068-6 · Cited by 27 · see citing works
Developing Reflective Inquiry Practices: A Case Study of Software, the Teacher, and Students
Crowley, K., Schunn, C. D., & Okada, T. (2001) · Psychology Press eBooks · doi:10.4324/9781410600318-18 · Cited by 19 · see citing works
Phelps, E., & Damon, W. (1989) · Journal of Educational Psychology · doi:10.1037//0022-0663.81.4.639 · Cited by 17 · see citing works
Kyza, E. Α., Golan, R., Reiser, B. J., & Edelson, D. C. (2002) · Computer-supported collaborative learning/The Computer-Supported Collaborative Learning Conference · doi:10.3115/1658616.1658648 · Cited by 10 · see citing works
Self-citationLoh, B. (2003) · PhDT · Cited by 7 · see citing works
Sandoval, W. A. (1998) · PhDT · Cited by 6 · see citing works
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HMELO-SILVER, C. E., DUNCAN, R. G., & CHINN, C. A. (2007) · Educational Psychologist · doi:10.1080/00461520701263368 · Cited by 2,641 · see citing works
Designing for Productive Failure
Kapur, M., & Bielaczyc, K. (2012) · Journal of the Learning Sciences · doi:10.1080/10508406.2011.591717 · Cited by 674 · see citing works
Higher Education Future in the Era of Digital Transformation
Akour, M., & Alenezi, M. (2022) · Education Sciences · doi:10.3390/educsci12110784 · Cited by 378 · see citing works
Synthesizing Results From Empirical Research on Computer-Based Scaffolding in STEM Education
Belland, B. R., Walker, A. E., Kim, N. J., & Lefler, M. (2017) · Review of Educational Research · doi:10.3102/0034654316670999 · Cited by 346 · see citing works
“Generic Versus Context-Specific Scaffolding researchers often argue whether scaffolding should be generic or context-specific (Davis, 2003; McNeill & Krajcik, 2009; Reiser, 2004).”
BackgroundDirect instruction vs. discovery: The long view
Dean Jr., D., & Kuhn, D. (2007) · Science Education · doi:10.1002/sce.20194 · Cited by 325 · see citing works
Jumping the PBL Implementation Hurdle: Supporting the Efforts of K–12 Teachers
Ertmer, P. A., & Simons, K. D. (2006) · Interdisciplinary Journal of Problem-Based Learning · doi:10.7771/1541-5015.1005 · Cited by 262 · see citing works
Kim, N. J., Belland, B. R., & Walker, A. E. (2018) · Educational Psychology Review · doi:10.1007/s10648-017-9419-1 · Cited by 220 · see citing works
Lusk, D. L., Evans, A. D., Jeffrey, T. R., Palmer, K. R., Wikstrom, C. S., & Doolittle, P. E. (2009) · British Journal of Educational Technology · doi:10.1111/j.1467-8535.2008.00848.x · Cited by 135 · see citing works
Guo, L. (2022) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12650 · Cited by 141 · see citing works
Moè, A., Katz, I., & Alesi, M. (2018) · British Journal of Educational Psychology · doi:10.1111/bjep.12216 · Cited by 118 · see citing works
Belland, B. R. (2011) · Educational Psychology Review · doi:10.1007/s10648-011-9176-5 · Cited by 64 · see citing works
MetaWriter: Exploring the Potential and Perils of AI Writing Support in Scientific Peer Review
Sun, L., Tao, S., Hu, J., & Dow, S. P. (2024) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3637371 · Cited by 37 · see citing works
Raković, M., Winne, P. H., Marzouk, Z., & Chang, D. (2021) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12531 · Cited by 26 · see citing works
Huang, H.-W., Teng, D. C.-E., & Tiangco, J. A. N. Z. (2025) · Journal of Science Education and Technology · doi:10.1007/s10956-024-10179-9 · Cited by 23 · see citing works
Enhancing the Peer-Feedback Process Through Instructional Support: A Meta-Analysis
Hornstein, J., Keller, M. V., Greisel, M., Dresel, M., & Kollar, I. (2025) · Educational Psychology Review · doi:10.1007/s10648-025-10017-3 · Cited by 18 · see citing works
“That way, the complexity of the task of providing feedback is reduced through breaking it down into smaller aspects to mitigate the danger of potential cognitive overload (Hein & Prediger, 2017; Reiser, 2004; Sweller, 1999).”
Puech, R., Macina, J., Chatain, J., Sachan, M., & Kapur, M. (2025) · Findings of the Association for Computational Linguistics: ACL 2025 · doi:10.18653/v1/2025.findings-acl.1348 · Cited by 11 · see citing works
- Authors
- Reiser, B. J.
- Affiliations
- Northwestern University (US)
- Corresponding author
- Reiser, Brian J.
- ORCID
- Reiser, Brian J.
- Venue
- Journal of the Learning Sciences
- Publisher
- Informa UK Limited
- Published
- 2004-07
- Volume
- 13
- Issue
- 3
- Pages
- 273-304
- ISSN
- 1050-8406 (ISSN-L)
- 1532-7809
- OpenAlex
- W1999626445
- Cited by
- 1,054
- References
- 90
- Citations by year
- 2026: 71 · 2025: 48 · 2024: 51 · 2023: 43 · 2022: 61 · 2021: 57 · 2020: 62 · 2019: 71 · 2018: 84 · 2017: 58 · 2016: 52 · 2015: 61 · 2014: 61 · 2013: 50 · 2012: 45
- FWCI
- 26.58
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of the Learning Sciences (publishedVersion)
- Topics
- Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Visual and Cognitive Learning Processes
- Keywords
- scaffolding, problematization, design guidelines, design trade-offs
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