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Scaffolding Self-regulated Learning and Metacognition – Implications for the Design of Computer-based Scaffolds
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THE ROLE OF TUTORING IN PROBLEM SOLVING *
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 1×
“Scaffolding involves providing assistance to students on an as-needed basis, fading the assistance as learner competence increases (Wood et al., 1976).”
BackgroundChi, M. T. H., Siler, S. A., Jeong, H., Yamauchi, T., & Hausmann, R. G. (2001) · Cognitive Science · doi:10.1207/s15516709cog2504_1 · Cited by 855
The Metaphor of Scaffolding: Its Utility for the Field of Learning Disabilities
Stone, C. A. (1998) · Journal of Learning Disabilities · doi:10.1177/002221949803100404 · Cited by 465
Flagged first, then by citations
Research works printed but not linked: 42
- J.R. Anderson, 1995, The Journal of the Learning Sciences, 4, 167, 10.1207/s15327809jls0402_2 · DOI · Paper page
- V. Aleven, 2002, Cognitive Science, 26, 147, 10.1207/s15516709cog2602_1 · DOI · Paper page
- Azevedo, R. Computers as metacognitive tools for enhancing learning. Educational Psychologist (in press).
- Azevedo, R. (2003). Metacognition and self-regulation in learning with MetaCognitive tools. Proceedings of the workshop on metacognition and self-regulation in learning with Metacognitive tool held at the 11th International Conference on Artificial Intelligence in Education. Amsterdam: IOS press.
- R. Azevedo, 2002, Instructional Science, 30, 31, 10.1023/A:1013592216234 · DOI
- R. Azevedo, 2004, Journal of Educational Psychology, 96, 523, 10.1037/0022-0663.96.3.523 · DOI · Paper page
- R. Azevedo, 2004, Contemporary Educational Psychology, 29, 344, 10.1016/j.cedpsych.2003.09.002 · DOI
- R. Azevedo, 2005, Instructional science, 33, 381, 10.1007/s11251-005-1273-8 · DOI · Paper page
- A. L. Baylor, 2002, Journal of Educational Computing Research, 26, 249, 10.2190/PH2K-6P09-K8EC-KRDK · DOI
- T. Brush, 2001, Journal of Educational Multimedia and Hypermedia, 10, 333
- M.T.H. Chi de, 1994, Cognitive Science, 18, 439
- I. Choi, 2005, Instructional science, 33, 483, 10.1007/s11251-005-1277-4 · DOI
- C. Conati, 2000, International Journal of Artificial Intelligence in Education, 11, 389
- N. Dabbagh, 2005, Instructional Science, 33, 513, 10.1007/s11251-005-1278-3 · DOI
- Graesser, A., McNamara, D. & VanLehn, K. Scaffolding deep comprehension strategies through Pint&Query, AuthTutor and iSTRAT. Educational Psychologist (in press).
- Graesser, A., Wiemer-Hastings, K., Wiemer-Hastings, P., Kruez, R., The Tutoring Research Group. (2000). AutoTutor: A simulation of a human tutor. Journal of Cognitive Systems Research 1: 35–51. · DOI
- B. Greene, 2000, Journal of Educational Computing Research, 23, 151, 10.2190/1GUB-8UE9-NW80-CQAD · DOI
- A. Hadwin, 2001, Educational Research and Evaluation, 7, 313, 10.1076/edre.7.2.313.3868 · DOI · Paper page
- A.F. Hadwin, 2005, Instructional Science, 33, 413, 10.1007/s11251-005-1274-7 · DOI
- M. Hannafin, 1999, Contemporary Education, 68, 94
- M.J. Hannafin, 1997, Instructional Science, 25, 167, 10.1023/A:1002997414652 · DOI
- J. Hill, 1997, Educational Technology Research & Development, 45, 37, 10.1007/BF02299682 · DOI
- K. Hogan, 1997, Scaffolding Student Learning: Instructional Approaches and Issues
- M. Jacobson, 2000, Journal of the Learning Sciences, 9, 149, 10.1207/s15327809jls0902_2 · DOI
- K. Koedinger, 2001, Smart Machines in Education, 145
- Lajoie, S.P. & Azevedo, R. Teaching and learning in technology-rich environments. In P. Alexander & P. Winne eds., Handbook of educational psychology (2nd edn.). Mahwah, NJ: Erlbaum (in press). · DOI
- S.P. Lajoie, 2000, Computers as Cognitive Tools II: No More Walls: Theory Change, Paradigm Shifts and Their Influence on the Use of Computers for Instructional Purposes, 247
- S. Land, 2000, Educational Technology Research Development, 48, 61, 10.1007/BF02319858 · DOI
- R. Luckin, 1999, International Journal of Artificial Intelligence in Education, 10, 198
- K. Oliver, 2000, Journal of Educational Research, 94, 75, 10.1080/00220670009598746 · DOI
- A.S. Palinscar, 1998, Journal of the Learning Disabilities, 31, 371
- R.D. Pea, 2004, Journal of the Learning Sciences, 13, 423, 10.1207/s15327809jls1303_6 · DOI · Paper page
- P. Pintrich, 2002, Development of Achievement Motivation, 249, 10.1016/B978-012750053-9/50012-7 · DOI
- S. Puntambekar, 2005, Educational Psychologist, 40, 1, 10.1207/s15326985ep4001_1 · DOI · Paper page
- S. Puntambekar, 2005, Instructional Science, 33, 451, 10.1007/s11251-005-1276-5 · DOI
- Quitana, C., Zhang, X. & Krajcik, J. A framework for supporting metacognitive aspects of on-line inquiry through software-based scaffolding. Educational Psychologist (in press).
- B. Reiser, 2004, Journal of the Learning Sciences, 13930, 273, 10.1207/s15327809jls1303_2 · DOI · Paper page
- Reiser, B.J. (2002). Why scaffolding should sometimes make tasks more difficult for learners. Proceedings of the annual meeting of the CSCL (pp. 255–264). · DOI
- V. Shute, 1996, Handbook of Research for Educational Communications and Technology, 570
- Vye, N., Schwartz, D., Bransford, J., Barron, B., Zech, L. & CTGV. (1998). SMART environments that support monitoring, reflection, and revision. In D. Hacker, J.␣Dunlosky & A. Graesser, eds., Metacognition in Educational Theory and Practice (pp. 305–346). Mahwah, NJ: Erlbaum.
- White, B. & Frederiksen, J. A theoretical framework and approach for fostering metacognitive development. Educational Psychologist (in press). · DOI
- B. White, 2000, Computers as Cognitive Tools Volume Two: No More Walls, 97
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“Customised learning environments, ranging from fixed to dynamic adaptive scaffolds, enable educators to effectively implement SRL interventions and provide meta-cognitive support (Azevedo & Hadwin, 2005).”
BackgroundAzevedo, R., Moos, D. C., Greene, J. A., Winters, F. I., & Cromley, J. G. (2008) · Educational Technology Research and Development · doi:10.1007/s11423-007-9067-0 · Cited by 380
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Evagorou, M., Korfiatis, K., Nicolaou, C., & Constantinou, C. (2009) · International Journal of Science Education · doi:10.1080/09500690701749313 · Cited by 216
Kim, N. J., Belland, B. R., & Walker, A. E. (2018) · Educational Psychology Review · doi:10.1007/s10648-017-9419-1 · Cited by 220
Effects of real-time analytics-based personalized scaffolds on students’ self-regulated learning
Lim, L., Bannert, M., van der Graaf, J., Singh, S., Fan, Y., Surendrannair, S., Rakovic, M., Molenaar, I., Moore, J., & Gašević, D. (2023) · Computers in Human Behavior · doi:10.1016/j.chb.2022.107547 · Cited by 198
Self-regulated Learning with MetaTutor: Advancing the Science of Learning with MetaCognitive Tools
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Self-citationHovardas, T., Tsivitanidou, O. E., & Zacharia, Z. C. (2014) · Computers & Education · doi:10.1016/j.compedu.2013.09.019 · Cited by 176
Guo, L. (2022) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12650 · Cited by 141
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Metadata
- Authors
- Azevedo, R., & Hadwin, A. F.
- Venue
- Instructional Science
- Published
- 2005-11
- Volume
- 33
- Issue
- 5-6
- Pages
- 367-379
- ISSN
- 0020-4277
- 1573-1952
- Cited by
- 469
- References
- 3
- Language
- en
- Licence
- www.springer.com/tdm (tdm)
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