The DOI matches its Crossref record; 48 of the 50 references it cites were found in a registry or an index.
Toward a Script Theory of Guidance in Computer-Supported Collaborative Learning
Open accessAbstract
This article presents an outline of a script theory of guidance for computer-supported collaborative learning (CSCL). With its 4 types of components of internal and external scripts (play, scene, role, and scriptlet) and 7 principles, this theory addresses the question of how CSCL practices are shaped by dynamically reconfigured internal collaboration scripts of the participating learners. Furthermore, it explains how internal collaboration scripts develop through participation in CSCL practices. It emphasizes the importance of active application of subject matter knowledge in CSCL practices, and it prioritizes transactive over nontransactive forms of knowledge application in order to facilitate learning. Further, the theory explains how external collaboration scripts modify CSCL practices and how they influence the development of internal collaboration scripts. The principles specify an optimal scaffolding level for external collaboration scripts and allow for the formulation of hypotheses about the fading of external collaboration scripts. Finally, the article points toward conceptual challenges and future research questions.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
(1978) · Medical Entomology and Zoology · Cited by 53,488
Kirschner, P. A., Sweller, J., & Clark, R. E. (2006) · Educational Psychologist · doi:10.1207/s15326985ep4102_1 · Cited by 7,776
(1998) · Cited by 4,875
SCRIPTS, PLANS, GOALS, AND UNDERSTANDING
Schank, R. C., & Abelson, R. P. (1988) · Elsevier eBooks · doi:10.1016/b978-1-4832-1446-7.50019-4 · Cited by 4,544
Active‐Constructive‐Interactive: A Conceptual Framework for Differentiating Learning Activities
Michelene, T. H. (2009) · Topics in Cognitive Science · doi:10.1111/j.1756-8765.2008.01005.x · Cited by 1,799
Boyd, W. L. (2001) · Elsevier eBooks · doi:10.1016/b0-08-043076-7/02360-3 · Cited by 1,083
New Frontiers: Regulating Learning in CSCL
Järvelä, S., & Hadwin, A. F. (2013) · Educational Psychologist · doi:10.1080/00461520.2012.748006 · Cited by 722
Reconceptalizing change in the cognitive construction of knowledge
Dole, J. A., & Sinatra, G. M. (1998) · Educational Psychologist · doi:10.1080/00461520.1998.9653294 · Cited by 672
Schank, R. C. (1999) · Cambridge University Press eBooks · doi:10.1017/cbo9780511527920 · Cited by 669
Collaboration Scripts – A Conceptual Analysis
Kollar, I., Fischer, F., & Hesse, F. W. (2006) · Educational Psychology Review · doi:10.1007/s10648-006-9007-2 · Cited by 559
Self-citation
Flagged first, then by citations
2 of the 50 references couldn’t be matched to a known paper.
Research works printed but not linked: 10
- Dillenbourg P., 2007, Scripting computer-supported collaborative learning: Cognitive, computational, and educational perspectives
- 10.1007/978-0-387-36949-5 · DOI
- 10.1016/j.chb.2004.10.033 · DOI
- 10.1080/00461520.1998.9653294 · DOI
- Stegmann K., 2011, Connecting Computer-Supported Collaborative Learning to Policy and Practice: CSCL2011 Conference Proceedings Volume I—Long Papers, 406
- Stegmann K., 2011, Unterrichtswissenschaft, 39, 231
- 10.1504/IJTEL.2010.031262 · DOI
- Wang X., 2011, Connecting computer-supported collaborative learning to policy and practice: CSCL2011 Conference proceedings volume I—Long papers, 382
- Wecker C., 2010, Learning in the Disciplines: Proceedings of the 9th International Conference of the Learning Sciences—ICLS 2010, 1, 810
- 10.1016/j.chb.2009.08. 007 · DOI
Cited by
Sorted by citations
Items 501–525 of 525
Towards an adaptive AI scaffold for developing student collaborative problem solving
Wong, K., Bulathwela, S., & Cukurova, M. (2026) · Learning and Instruction · doi:10.1016/j.learninstruc.2026.102418 · Cited by 1
Li, D., & Li, H. (2026) · Interactive Learning Environments · doi:10.1080/10494820.2026.2684742
VanLehn’s Two Loops Aren’t Enough: Toward Meta-Adaptive Control of Instructional Form
McLaren, B. M. (2026) · Communications in computer and information science · doi:10.1007/978-3-032-29791-4_28
Jiao, F., Bian, J., Zhang, R., & Zhou, T. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1717440 · Cited by 2
Wang, J., & Li, H. (2026) · Education and Information Technologies · doi:10.1007/s10639-026-14109-7
Nakata, A., Järvenoja, H., Kreijns, K., & Weinberger, A. (2026) · Technology Knowledge and Learning · doi:10.1007/s10758-026-10011-w
Kurtz, M., Lelardeux, C. P., Benabbou, A., Alamia, A., Iuculano, T., & Broisin, J. (2026) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2026.101203
Pickal, A. J., Engelmann, K., Chinn, C. A., Neuhaus, B. J., Girwidz, R., & Wecker, C. (2026) · International Journal of Computer-Supported Collaborative Learning · doi:10.1007/s11412-026-09494-7
Self-citationThe Dynamics of Cognitive Engagement Process Under Different Scripts in Collaborative Learning
Hong, Z., Yang, X., & Li, X. (2026) · International Conference on Computer Science and Technologies in Education (CSTE) · doi:10.1109/cste69562.2026.11649611
Sui, X., Tian, Z., & Wang, Q. (2026) · International Conference on Computer Science and Technologies in Education (CSTE) · doi:10.1109/cste69562.2026.11649573
Wu, Y., Yang, X., & Li, X. (2026) · International Conference on Computer Science and Technologies in Education (CSTE) · doi:10.1109/cste69562.2026.11649714
Jin, Y., Martínez‐Maldonado, R., Gašević, D., Han, X., & Yan, L. (2026) · Journal of Computer Assisted Learning · doi:10.1002/jcal.70310 · Cited by 1
Peer instruction in chemistry stratified exercises: Cognitive and metacognitive effects
Zheng, Y., Wang, X., Zhang, Y., & Mei, H. (2026) · Learning and Instruction · doi:10.1016/j.learninstruc.2026.102460
Yin, B., Wu, X.-R., & Lian, R. (2026) · Thinking Skills and Creativity · doi:10.1016/j.tsc.2026.102366
Evaluation of Artificial Intelligence Performance in the Mathematical Problem-Solving Process
ASLAN, S. A., Miser, M., & Allison, J. (2026) · SAGE Open · doi:10.1177/21582440261486168
Designprozess 2: Formate und Formatentscheidungen
Niegemann, H., Weinberger, A., Korbach, A., & Malone, S. (2026) · Springer eBooks · doi:10.1007/978-3-662-73355-4_3
Tynnyi, V., & Schukina, E. (2026) · Research Notes · doi:10.31654/2663-4902-2026-pp-3-120-125
Multimodal Subjective Intention Modeling in Social Interactions
Mercier, A. (2026) · INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION · doi:10.1145/3776574.3828968
Clark, S. (2026) · American Journal of Qualitative Research · doi:10.66815/ajqr/19490
Sharma, S., Grajcevci, A., & Weinberger, A. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-37982-5_54
Professional learning communities: a case study on conditions and processes of collaboration
Berger, S., Ripsam, M., Nerdel, C., Fischer, F., & Gräsel, C. (2026) · Learning Research and Practice · doi:10.1080/23735082.2026.2742929
Self-citationEnhancing Cognitive Skills in Online Student Dialogues with a Collaborative Conversational Agent
Papadopoulos, P. M., Stoidis, A., Hogenkamp, L., & de Araujo, A. (2026) · IEEE International Conference on Advanced Learning Technologies (ICALT) · doi:10.1109/icalt68022.2026.00043
Beyond the Zero-Sum Debate: Designing for Agency and Efficiency in the Age of GenAIPreprint
Borge, M., & Shimoda, T. (2026) · Research Square · doi:10.21203/rs.3.rs-11097403/v1
Chen, J., Chen, X., Song, S., Guo, C., Liang, C., & Zhao, R. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1878525
Chen, D., Zhang, Y., Luo, H., Guo, F., Lu, Y., & Guo, X.-G. (2026) · British Journal of Educational Technology · doi:10.1111/bjet.70096
Metadata
- Authors
- Fischer, F., Kollar, I., Stegmann, K., & Wecker, C.
- Affiliations
- Ludwig-Maximilians-Universität München (DE)
- Corresponding author
- Fischer, Frank
- Venue
- Educational Psychologist
- Publisher
- Informa UK Limited
- Published
- 2013-01
- Volume
- 48
- Issue
- 1
- Pages
- 56-66
- ISSN
- 0046-1520 (ISSN-L)
- 1532-6985
- PMC
- PMC3557614
- OpenAlex
- W2131910319
- Cited by
- 525
- References
- 50
- Citations by year
- 2026: 51 · 2025: 41 · 2024: 40 · 2023: 37 · 2022: 52 · 2021: 45 · 2020: 28 · 2019: 26 · 2018: 55 · 2017: 31 · 2016: 42 · 2015: 29 · 2014: 32 · 2013: 16
- FWCI
- 81.77
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Educational Psychologist (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- HAL (submittedVersion, other-oa)
- Open access LMU (Ludwid Maxmilian's Universitat Munchen) (submittedVersion, cc-by-nc-nd)
- OPUS (Augsburg University) (submittedVersion)
- Topics
- Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Visual and Cognitive Learning Processes
- Social Sciences › Education › Innovative Education and Learning Practices
- Keywords
- script theory, computer-supported collaborative learning, cooperative script, scaffolding, content knowledge, learner development
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review