The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Will media influence learning? Reframing the debate
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Citations
Cites
Protocol Analysis: Verbal Reports as Data
Ericsson, K. A., & Simon, H. A. (1993) · doi:10.7551/mitpress/5657.001.0001 · Cited by 3,537
Reconsidering Research on Learning from Media
Clark, R. E. (1983) · Review of Educational Research · doi:10.3102/00346543053004445 · Cited by 2,715
Kozma, R. B. (1991) · Review of Educational Research · doi:10.3102/00346543061002179 · Cited by 1,429
Self-citationGuttman, L. (1968) · Psychometrika · doi:10.1007/bf02290164 · Cited by 1,343
The 1987 Presidential Address Learning In School and Out
Resnick, L. B. (1987) · Educational Researcher · doi:10.3102/0013189x016009013 · Cited by 1,035
Partners in Cognition: Extending Human Intelligence with Intelligent Technologies
SALOMON, G., PERKINS, D. N., & GLOBERSON, T. (1991) · Educational Researcher · doi:10.3102/0013189x020003002 · Cited by 948 · cited 1×
“Consequently, we will understand the potential for a relationship between media and learning when we consider it as an interaction between cognitive processes and characteristics of the environment, so mediated (Salomon, 1993; Salomon, Perkins, & Globerson, 1991 ).”
Background
Cited by
Media will never influence learning
Clark, R. E. (1994) · Educational Technology Research and Development · doi:10.1007/bf02299088 · Cited by 1,893
Bernard, R. M., Abrami, P. C., Lou, Y., Borokhovski, E., Wade, A., Wozney, L., Wallet, P. A., Fiset, M., & Huang, B. (2004) · Review of Educational Research · doi:10.3102/00346543074003379 · Cited by 1,761
Multimedia learning: Are we asking the right questions?
Mayer, R. E. (1997) · Educational Psychologist · doi:10.1207/s15326985ep3201_1 · Cited by 1,533
Makransky, G., & Petersen, G. B. (2021) · Educational Psychology Review · doi:10.1007/s10648-020-09586-2 · Cited by 1,438
“Kozma agreed with the lack of evidence, but responded with hopes that future media research would prove more positive, and contended that “ if we can find a relationship between media and learning then we will be able to see how technology influences learning ” (Kozma 1994, p. 8).”
BackgroundMayer, R. E. (2003) · Learning and Instruction · doi:10.1016/s0959-4752(02)00016-6 · Cited by 1,337
Digital Games, Design, and Learning: A Systematic Review and Meta-Analysis
Clark, D. B., Tanner-Smith, E. E., & Killingsworth, S. S. (2016) · Review of Educational Research · doi:10.3102/0034654315582065 · Cited by 1,274
Tamim, R. M., Bernard, R. M., Borokhovski, E., Abrami, P. C., & Schmid, R. F. (2011) · Review of Educational Research · doi:10.3102/0034654310393361 · Cited by 1,029
Cheung, A. C. K., & Slavin, R. E. (2013) · Educational Research Review · doi:10.1016/j.edurev.2013.01.001 · Cited by 792
Animation as an Aid to Multimedia Learning
Mayer, R. E., & Moreno, R. (2002) · Educational Psychology Review · doi:10.1023/a:1013184611077 · Cited by 749
Research Commentary: Technology-Mediated Learning—A Call for Greater Depth and Breadth of Research
Alavi, M., & Leidner, D. E. (2001) · Information Systems Research · doi:10.1287/isre.12.1.1.9720 · Cited by 689
A history of instructional design and technology: Part II: A history of instructional design
Reiser, R. A. (2001) · Educational Technology Research and Development · doi:10.1007/bf02504928 · Cited by 607
Hillmayr, D., Ziernwald, L., Reinhold, F., Hofer, S. I., & Reiss, K. M. (2020) · Computers & Education · doi:10.1016/j.compedu.2020.103897 · Cited by 574
“Despite the potential of using digital tools in mathematics and science classes, teachers should always assess additional benefits in regard to the context they want to use it in, and learning content should still take center stage (e.g., Clark, 1994; Kozma, 1994).”
BackgroundMeyer, O. A., Omdahl, M. K., & Makransky, G. (2019) · Computers & Education · doi:10.1016/j.compedu.2019.103603 · Cited by 515
Meta-analysis of the impact of Augmented Reality on students’ learning gains
Garzón, J., & Acevedo, J. (2019) · Educational Research Review · doi:10.1016/j.edurev.2019.04.001 · Cited by 491
Web-based learning: pros, cons and controversies
Cook, D. A. (2007) · Clinical Medicine · doi:10.7861/clinmedicine.7-1-37 · Cited by 437
Effective Programs in Elementary Mathematics: A Best-Evidence Synthesis
Slavin, R. E., & Lake, C. (2008) · Review of Educational Research · doi:10.3102/0034654308317473 · Cited by 407
How College Affects Students: Ten Directions for Future Research
Pascarella, E. T. (2006) · Journal of College Student Development · doi:10.1353/csd.2006.0060 · Cited by 355
Impact of podcasting on student motivation in the online learning environment
Bolliger, D. U., Supanakorn, S., & Boggs, C. (2010) · Computers & Education · doi:10.1016/j.compedu.2010.03.004 · Cited by 337
The effects of technology use in postsecondary education: A meta-analysis of classroom applications
Schmid, R. F., Bernard, R. M., Borokhovski, E., Tamim, R. M., Abrami, P. C., Surkes, M. A., Wade, C. A., & Woods, J. (2014) · Computers & Education · doi:10.1016/j.compedu.2013.11.002 · Cited by 313
The roles of the formal and informal sectors in the provision of effective science education
Stocklmayer, S. M., Rennie, L. J., & Gilbert, J. K. (2010) · Studies in Science Education · doi:10.1080/03057260903562284 · Cited by 314
Fishman, B., Konstantopoulos, S., Kubitskey, B. W., Vath, R., Park, G., Johnson, H., & Edelson, D. C. (2013) · Journal of Teacher Education · doi:10.1177/0022487113494413 · Cited by 311
How features of educational technology applications affect student reading outcomes: A meta-analysis
Cheung, A. C. K., & Slavin, R. E. (2012) · Educational Research Review · doi:10.1016/j.edurev.2012.05.002 · Cited by 307
Garzón, J., Kinshuk, Baldiris, S., Gutiérrez, J., & Pavón, J. (2020) · Educational Research Review · doi:10.1016/j.edurev.2020.100334 · Cited by 291
Design and Use of a Rubric to Assess and Encourage Interactive Qualities in Distance Courses
Roblyer, M. D., & Wiencke, W. R. (2003) · American Journal of Distance Education · doi:10.1207/s15389286ajde1702_2 · Cited by 280
Cao, X., Masood, A., Luqman, A., & Ali, A. (2018) · Computers in Human Behavior · doi:10.1016/j.chb.2018.03.023 · Cited by 257
The Self-Explanation Principle in Multimedia Learning
Roy, M., & Chi, M. T. H. (2005) · The Cambridge Handbook of Multimedia Learning · doi:10.1017/cbo9780511816819.018 · Cited by 219
Effective virtual patient simulators for medical communication training: A systematic review
Lee, J., Kim, H., Kim, K. H., Jung, D., Jowsey, T., & Webster, C. S. (2020) · Medical Education · doi:10.1111/medu.14152 · Cited by 210
(2001) · AUSpace (Athabasca University) · Cited by 208
Lou, Y., Bernard, R. M., & Abrami, P. C. (2006) · Educational Technology Research and Development · doi:10.1007/s11423-006-8252-x · Cited by 197
Looking Beyond the Hype: Understanding the Effects of AI on Learning
Bauer, E., Greiff, S., Graesser, A. C., Scheiter, K., & Sailer, M. (2025) · Educational Psychology Review · doi:10.1007/s10648-025-10020-8 · Cited by 153
Lusk, D. L., Evans, A. D., Jeffrey, T. R., Palmer, K. R., Wikstrom, C. S., & Doolittle, P. E. (2009) · British Journal of Educational Technology · doi:10.1111/j.1467-8535.2008.00848.x · Cited by 135
Media comparison studies dominate comparative research on augmented reality in education
Buchner, J., & Kerres, M. (2023) · Computers & Education · doi:10.1016/j.compedu.2022.104711 · Cited by 133
Yadav, A., Phillips, M. M., Lundeberg, M. A., Koehler, M. J., Hilden, K., & Dirkin, K. H. (2011) · Journal of Computing in Higher Education · doi:10.1007/s12528-011-9042-y · Cited by 127
Should self-regulated learning be integrated with cognitive load theory? A commentary
Sweller, J., & Paas, F. (2017) · Learning and Instruction · doi:10.1016/j.learninstruc.2017.05.005 · Cited by 54
ChatGPT in Education: An Effect in Search of a Cause
Weidlich, J., Gašević, D., Drachsler, H., & Kirschner, P. (2025) · Journal of Computer Assisted Learning · doi:10.1111/jcal.70105 · Cited by 52
AI in essay-based assessment: Student adoption, usage, and performance
Smerdon, D. (2024) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2024.100288 · Cited by 43
Evens, M., Larmuseau, C., Dewaele, K., Van Craesbeek, L., Elen, J., & Depaepe, F. (2017) · Journal of Digital Learning in Teacher Education · doi:10.1080/21532974.2017.1314779 · Cited by 18
Metadata
- Authors
- Kozma, R. B.
- Venue
- Educational Technology Research and Development
- Published
- 1994-06
- Volume
- 42
- Issue
- 2
- Pages
- 7-19
- ISSN
- 1042-1629 (ISSN-L)
- 1556-6501
- OpenAlex
- W2064083597
- Cited by
- 1,142
- References
- 6
- FWCI
- 20.88
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
