The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.
Thirty years of research on online learning
Abstract
Summary: This paper presents a personal account of developments in research on online learning over the past 30 years. Research on how to design online instruction represents an example of applying the science of learning to education. It contributes to the science of learning (as exemplified by developments in cognitive load theory, the cognitive theory of multimedia learning, and incorporating metacognitive, motivational, and affective aspects of learning), the science of instruction (as exemplified by the continuing development of research‐based principles of instructional design), and the science of assessment (as exemplified by supplementing self‐report surveys and retention tests with multilevel transfer tests, log file data during learning, and cognitive neuroscience measures of cognitive processing during learning). Some recurring themes are that learning is caused by instructional methods rather than instructional media, so research should focus on features that are uniquely afforded by digital learning environments; instructional practice should be grounded in rigorous and systematic research, including value‐added experiments aimed at pinpointing the active ingredients in online instruction; research in online learning should identify boundary conditions under which instructional techniques are most effective; and research in online learning should test and contribute to learning theory.
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Citations
Cites
Mayer, R. E. (2009) · doi:10.1017/cbo9780511811678 · Cited by 7,800
Self-citationMayer, R. (2020) · doi:10.1017/9781316941355 · Cited by 7,777
Self-citationKirschner, P. A., Sweller, J., & Clark, R. E. (2006) · Educational Psychologist · doi:10.1207/s15326985ep4102_1 · Cited by 7,776 · cited 1×
“Instructional design goal description”
Sweller, J., Ayres, P., & Kalyuga, S. (2011) · doi:10.1007/978-1-4419-8126-4 · Cited by 5,531
Nine Ways to Reduce Cognitive Load in Multimedia Learning
Mayer, R. E., & Moreno, R. (2003) · Educational Psychologist · doi:10.1207/s15326985ep3801_6 · Cited by 4,207
Self-citationMayer, R. E. (2001) · doi:10.1017/cbo9781139164603 · Cited by 2,304
Self-citationCognitive Theory of Multimedia Learning
Mayer, R. E. (2014) · The Cambridge Handbook of Multimedia Learning · doi:10.1017/cbo9781139547369.005 · Cited by 1,976
Self-citationCognitive Theory of Multimedia Learning
Mayer, R. E. (2005) · The Cambridge Handbook of Multimedia Learning · doi:10.1017/cbo9780511816819.004 · Cited by 1,602
Self-citationMayer, R. E., & Moreno, R. (1998) · Journal of Educational Psychology · doi:10.1037/0022-0663.90.2.312 · Cited by 1,315 · cited 2×
“An important advance is the recognition that the key to meaningful instructional methods rests not necessarily in the learner's behavioral activity during learning but in the learner's cognitive processing during learning.”
BackgroundSelf-citationLearning science in immersive virtual reality.
Parong, J., & Mayer, R. E. (2018) · Journal of Educational Psychology · doi:10.1037/edu0000241 · Cited by 1,088 · cited 1×
“In the last few years, the pace has continued for research on the instructional design of online instruction, including emerging research on instructional design to enhance learning in virtual reality (Parong & Mayer, 2018).”
BackgroundSelf-citation
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Cited by
Skulmowski, A., & Xu, K. M. (2022) · Educational Psychology Review · doi:10.1007/s10648-021-09624-7 · Cited by 678
Future research recommendations for transforming higher education with generative AI
Chiu, T. K. F. (2024) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2023.100197 · Cited by 511
Money, W. H., & Dean, B. P. (2019) · Computers & Education · doi:10.1016/j.compedu.2019.03.013 · Cited by 53
Mindset matters: Fostering teachers’ responsible AI use through professional development
Huynh, L., Le, T. H., Dang, B., An, B. T., Vu, C. T., & Nguyen, A. (2025) · Journal of New Approaches in Educational Research · doi:10.1007/s44322-025-00043-y · Cited by 22
System design for using multimodal trace data in modeling self-regulated learning
Cloude, E. B., Azevedo, R., Winne, P. H., Biswas, G., & Jang, E. E. (2022) · Frontiers in Education · doi:10.3389/feduc.2022.928632 · Cited by 23
Metadata
- Authors
- Mayer, R. E.
- Venue
- Applied Cognitive Psychology
- Publisher
- Wiley
- Published
- 2018-11-08
- Volume
- 33
- Issue
- 2
- Pages
- 152-159
- ISSN
- 0888-4080 (ISSN-L)
- 1099-0720
- OpenAlex
- W2897920637
- Cited by
- 337
- References
- 17
- FWCI
- 70.58
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Funders
- Office of Naval Research (N00014‐16‐2046)
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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