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e‐Learning and the Science of Instruction: Proven Guidelines for Consumers and Designers of Multimedia Learning
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Cited by
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Fabriz, S., Mendzheritskaya, J., & Stehle, S. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.733554 · Cited by 453
Fontaine, G., Cossette, S., Maheu-Cadotte, M.-A., Mailhot, T., Deschênes, M.-F., Mathieu-Dupuis, G., Côté, J., Gagnon, M.-P., & Dubé, V. (2019) · BMJ Open · doi:10.1136/bmjopen-2018-025252 · Cited by 193
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Biomedical and behavioral outcomes of Keep It Up!: an ehealth HIV prevention program RCT.
Mustanski, B., Parsons, J. T., Sullivan, P. S., Madkins, K., Rosenberg, E., & Swann, G. (2018) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2018.04.026 · Cited by 103
Enhancing learning outcomes through self-regulated learning support with an Open Learner Model
Long, Y., & Aleven, V. (2017) · User Modeling and User-Adapted Interaction · doi:10.1007/s11257-016-9186-6 · Cited by 95
Charitopoulos, A., Rangoussi, M., & Koulouriotis, D. (2020) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-020-00200-8 · Cited by 89
Leiker, D., Gyllen, A. R., Eldesouky, I., & Cukurova, M. (2023) · Communications in Computer and Information Science · doi:10.1007/978-3-031-36336-8_81 · Cited by 84
Conceptualizing the Impact of AI on Teacher Knowledge and Expertise: A Cognitive Load Perspective
Rind, I. A. (2026) · Education Sciences · doi:10.3390/educsci16010057 · Cited by 27
Shyr, W.-J., Wei, B.-L., & Liang, Y.-C. (2024) · Sustainability · doi:10.3390/su16052015 · Cited by 26
König, L., & Suhr, R. (2023) · Journal of Medical Internet Research · doi:10.2196/46336 · Cited by 16
Mixed‐methods analysis of videoed expert‐student dialogue supporting clinical competence assessments
Botelho, M., Gao, X., & Bhuyan, S. Y. (2020) · European Journal of Dental Education · doi:10.1111/eje.12515 · Cited by 11
Hammer, S., & Berkel-Otto, L. (2019) · Open Education Studies · doi:10.1515/edu-2019-0018 · Cited by 9
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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.
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.