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A Conceptual Framework for Human–AI Hybrid Adaptivity in Education
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“Continuously interwoven explanation of AI behavior and exploratory adaptation can improve both AI and human learning (Holstein et al. 2020).”
From Keeping the organization in the loop: a socio-technical extension of human-centered artificial intelligence (2023) · cites this paper as Holstein et al. 2020
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Cites
Reinforcement Learning: An Introduction
Sutton, R. S., & Barto, A. (2005) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.2004.842673 · Cited by 25,268
Reinforcement Learning: An Introduction
Johnson, J. D., Li, J., & Chen, Z. (2000) · Neurocomputing · doi:10.1016/s0925-2312(00)00324-6 · Cited by 8,825
(1991) · Choice Reviews Online · doi:10.5860/choice.28-5376 · Cited by 4,218
VanLEHN, K. (2011) · Educational Psychologist · doi:10.1080/00461520.2011.611369 · Cited by 2,323
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
An introduction to human factors engineering
Wickens, C. D. (1997) · Cited by 1,711
Artificial Intelligence: A New Synthesis
(1998) · Elsevier eBooks · doi:10.1016/c2009-0-27773-7 · Cited by 1,211
Intelligent Tutoring Goes To School in the Big City
Koedinger, K. R., Anderson, J. R., Hadley, W. H., & Mark, M. A. (2018) · doi:10.1184/r1/6470153 · Cited by 1,105
Fox, C. (2013) · Routledge eBooks · doi:10.4324/9781315009810-7 · Cited by 1,066
Vinkhuyzen, R. E., Verschure, P. F. M. J., & Newell, A. (1994) · The American Journal of Psychology · doi:10.2307/1422886 · Cited by 831
Research works printed but not linked: 6
- Bransford, J.D., Brown, A.L., Cocking, R.R.: How People Learn, vol. 11. National Academy Press, Washington, DC (2000)
- De-Arteaga, M., Fogliato, R., Chouldechova, A.: A case for humans-in-the-loop: decisions in the presence of erroneous algorithmic scores (2020). arXiv preprint arXiv:2002.08035 · arXiv
- Holstein, K.: Designing real-time teacher augmentation to combine strengths of human and AI instruction. Unpublished doctoral dissertation, Carnegie Mellon University (2019)
- Roll, I., Wiese, E.S., Long, Y., Aleven, V., Koedinger, K.R.: Tutoring self-and co-regulation with intelligent tutoring systems to help students acquire better learning skills. In: Sottilare, R., Graesser, A., Hu, X., Holden, H. (eds.) Design Recommendations for Intelligent Tutoring Systems, vol. 2, pp. 169–182. US Army Research Laboratory, Orlando (2014)
- Simard, P.Y., et al.: Machine teaching: a new paradigm for building machine learning systems (2017). arXiv preprint arXiv:1707.06742 · arXiv
- Zhu, X., Singla, A., Zilles, S., Rafferty, A.N.: An overview of machine teaching (2018). arXiv preprint arXiv:1801.05927 · arXiv
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Baysha, M. H., Ghufron, A., Surjono, H. D., Astuti, E. R. P., Frihastama, R., Helmi, F., & Sangkop, F. I. (2026) · F1000Research · doi:10.12688/f1000research.183470.1
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Strydom, S. C. (2026) · Springer eBooks · doi:10.1007/978-3-031-52643-5_91-1
Chen, G., & Cao, B. (2026) · Asian Journal of Education and Social Studies · doi:10.9734/ajess/2026/v52i93283
Channing, J. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-2600-3840-6.ch006
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Asrifan, A., Muhayyang, M., Sadaruddin, S., Syamsuardi, S., & Octaberlina, L. R. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3693-8382-7.ch003
Yang, J., Wang, H., Chen, M., Chen, X., Wang, J., & Wang, C. (2026) · Interactive Learning Environments · doi:10.1080/10494820.2026.2713873
Basirung, M. R., Nuram, A. S., Hormansyah, R. D., & Mudarris, M. (2026) · Micronic Journal of Multidisciplinary Electrical and Electronics Engineering · doi:10.61220/micronic.v4i3.44
Hoppe, T., Loibl, K., & Leuders, T. (2026) · Frontiers in Education · doi:10.3389/feduc.2026.1857661
Human-AI collaboration for ethical, transparent, and equitable educational practices
Singh, D. (2026) · Journal of Digital Educational Technology · doi:10.29333/jdet/19286
Yan, L., & Kang, J. (2026) · Proceedings. · doi:10.22318/icls2026.814712
Structural signals and role archetypes: The emergence of roles in a distributed epistemic game
Matthews, J. (2026) · Computer-supported collaborative learning/The Computer-Supported Collaborative Learning Conference · doi:10.22318/cscl2026.104106
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Alkhasawneh, S. N., & Hernández‐Leo, D. (2026) · Computer-supported collaborative learning/The Computer-Supported Collaborative Learning Conference · doi:10.22318/cscl2026.633786
Evaluating the Skills Required for ICPC Programming Contest in Palestine: An Analytical Study
Radwan, A. M. (2026) · Lecture notes in networks and systems · doi:10.1007/978-3-032-39783-6_1
Obeng-Nyarko, J. K. (2026) · Discover Education · doi:10.1007/s44217-026-02225-y
Lyu, Q., Alonso-Prieto, V., Jin, Q., Morgus, W., Price, K., Fancsali, S. E., Berman, S., RITTER, S., & Aleven, V. A. W. M. M. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-37979-5_28
Self-citationHorvers, A., Molenaar, I., Snoeijen, K., Costache, O., van der Graaf, J., Kramer, A., de Mooij, S. M. M., Topali, P., Vermeire, Z., & Sleegers, P. J. C. (2026) · Behaviour and Information Technology · doi:10.1080/0144929x.2026.2740744
Diaz-Garcia, J. A., Morcillo-Jiménez, R., Ortiz-Viso, B., & Ruiz, M. D. (2026) · Multidisciplinary Journal for Education Social and Technological Sciences · doi:10.4995/muse.2026.26470
Bleikher, O. (2026) · Педагогика и просвещение · doi:10.7256/2454-0676.2026.4.82890
Álvarez-Rubio, M. N. (2026) · Frontiers in Education · doi:10.3389/feduc.2026.1961346
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Metadata
- Authors
- Holstein, K., Aleven, V., & Rummel, N.
- Affiliations
- Carnegie Mellon University (US)
- Ruhr University Bochum (DE)
- Corresponding author
- Holstein, Kenneth
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2020
- Pages
- 240-254
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- PMC
- PMC7334162
- OpenAlex
- W3038925583
- Cited by
- 168
- References
- 73
- Citations by year
- 2026: 39 · 2025: 35 · 2024: 36 · 2023: 25 · 2022: 21 · 2021: 10 · 2020: 2
- FWCI
- 5.54
- Type
- conference paper
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Lecture notes in computer science (publishedVersion)
- PubMed Central (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Social Sciences › Education › Artificial Intelligence in Education
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Keywords
- artificial intelligence in education, adaptive learning systems, human-AI collaboration, conceptual framework, human-AI augmentation
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