The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Animation and learning: selective processing of information in dynamic graphics
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
Mayer, R. E., & Moreno, R. (1998) · Journal of Educational Psychology · doi:10.1037/0022-0663.90.2.312 · Cited by 1,315 · cited 1×
“An important theoretical consideration underlying much of this work is the issue of minimising split-attention effects, in which attention to one type of presentation component may result in information being missed in a different, accompanying presentation component (Mayer & Moreno, 1998).”
BackgroundMayer, R. E., & Anderson, R. B. (1992) · Journal of Educational Psychology · doi:10.1037/0022-0663.84.4.444 · Cited by 1,000 · cited 1×
“Such exclusive direction of attention would probably also prejudice learners' capacities to build the connections between various parts of the display that are necessary for relating the individual fragments of information into a coherent, meaningful whole (cf. Mayer & Anderson, 1992).”
BackgroundAnimations need narrations: an experimental test of a dual-coding hypothesis.
Mayer, R. E., & Anderson, R. B. (1991) · Journal of Educational Psychology · doi:10.1037/0022-0663.83.4.484 · Cited by 883 · cited 1×
“Investigations with both conventional print materials and the newer forms of presentation such as multimedia have examined the effects of various spatial and temporal arrangements on learning outcomes (e.g., Mayer, 1994, 1997; Mayer & Anderson, 1991).”
BackgroundExtracting information from an animation during complex visual learning
Lowe, R. K. (1999) · European Journal of Psychology of Education · doi:10.1007/bf03172967 · Cited by 381
Self-citationMayer, R. E. (1994) · Advances in Psychology · doi:10.1016/s0166-4115(09)60112-6 · Cited by 36
Cited by
DeFT: A conceptual framework for considering learning with multiple representations
Ainsworth, S. (2006) · Learning and Instruction · doi:10.1016/j.learninstruc.2006.03.001 · Cited by 1,673
Instructional animation versus static pictures: A meta-analysis
Höffler, T. N., & Leutner, D. (2007) · Learning and Instruction · doi:10.1016/j.learninstruc.2007.09.013 · Cited by 992
Cook, M. P. (2006) · Science Education · doi:10.1002/sce.20164 · Cited by 538
de Koning, B. B., Tabbers, H. K., Rikers, R. M. J. P., & Paas, F. (2009) · Educational Psychology Review · doi:10.1007/s10648-009-9098-7 · Cited by 428
Interrogation of a dynamic visualization during learning
Lowe, R. (2004) · Learning and Instruction · doi:10.1016/j.learninstruc.2004.06.003 · Cited by 312
Self-citationHow to Optimize Learning From Animated Models: A Review of Guidelines Based on Cognitive Load
Wouters, P., Paas, F., & van Merriënboer, J. J. G. (2008) · Review of Educational Research · doi:10.3102/0034654308320320 · Cited by 224
Instructional animations can be superior to statics when learning human motor skills
Wong, A., Marcus, N., Ayres, P., Smith, L., Cooper, G. A., Paas, F., & Sweller, J. (2009) · Computers in Human Behavior · doi:10.1016/j.chb.2008.12.012 · Cited by 193
A meta-analysis of signaling principle in multimedia learning environments
Alpizar, D., Adesope, O. O., & Wong, R. M. (2020) · Educational Technology Research and Development · doi:10.1007/s11423-020-09748-7 · Cited by 157
The attention-guiding effect and cognitive load in the comprehension of animations
Amadieu, F., Mariné, C., & Laimay, C. (2011) · Computers in Human Behavior · doi:10.1016/j.chb.2010.05.009 · Cited by 137
Song, H. S., Pusic, M., Nick, M. W., Sarpel, U., Plass, J. L., & Kalet, A. L. (2014) · Computers & Education · doi:10.1016/j.compedu.2013.09.017 · Cited by 69
Seeing Change in Time: Video Games to Teach about Temporal Change in Scientific Phenomena
Corredor, J., Gaydos, M., & Squire, K. (2014) · Journal of Science Education and Technology · doi:10.1007/s10956-013-9466-4 · Cited by 67
A proposed multimedia cone of abstraction: updating a classic instructional design theory
Baukal, C. E. (2013) · i-manager's Journal of Educational Technology · doi:10.26634/jet.9.4.2129 · Cited by 41
Representation control increases task efficiency in complex graphical representations
Moritz, J., Meyerhoff, H. S., Meyer-Dernbecher, C., & Schwan, S. (2018) · PLOS ONE · doi:10.1371/journal.pone.0196420 · Cited by 11
Metadata
- Authors
- Lowe, R. K.
- Venue
- Learning and Instruction
- Publisher
- Elsevier BV
- Published
- 2003-04
- Volume
- 13
- Issue
- 2
- Pages
- 157-176
- ISSN
- 0959-4752 (ISSN-L)
- OpenAlex
- W2087622072
- Cited by
- 551
- References
- 5
- FWCI
- 20.85
- Type
- journal article
- Language
- en
- Open access
- closed
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
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.