Skip to main content Accessibility help

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
×
Hostname: page-component-cd9895bd7-gvvz8 Total loading time: 0 Render date: 2024-12-27T02:09:16.512Z Has data issue: false hasContentIssue false

Part IV - Principles for Reducing Extraneous Processing in Multimedia Learning

Published online by Cambridge University Press:  19 November 2021

Edited by
Richard E. Mayer  and
Logan Fiorella
Richard E. Mayer
Affiliation:
University of California, Santa Barbara
Logan Fiorella
Affiliation:
University of Georgia
Get access

Summary

A summary is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.
Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Chapter
Information
The Cambridge Handbook of Multimedia Learning , pp. 183 - 240
Publisher: Cambridge University Press
Print publication year: 2021

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

References

Abercrombie, S., Hushman, C. J., & Carbonneau, K. J. (2019). The impact of seductive details and signaling on analogical transfer. Applied Cognitive Psychology, 33(1), 38–47.CrossRefGoogle Scholar
Adesope, O. O., & Nesbit, J. C. (2012). Verbal redundancy in multimedia learning environments: A meta-analysis. Journal of Educational Psychology, 104(1), 250–263.Google Scholar
Alemdag, E., & Cagiltay, K. (2018). A systematic review of eye tracking research on multimedia learning. Computers & Education, 125, 413–428.Google Scholar
Amadieu, F., Marine, C., & Lemay, C. (2011). The attention guiding effect and cognitive load in the comprehension of animations. Computers in Human Behavior, 27, 36–40.CrossRefGoogle Scholar
Ari, F., Flores, R., Inan, F. A., Cheon, J., Crooks, S. M., Paniukov, D., & Kurucay, M. (2014). The effects of verbally redundant information on student learning: An instance of reverse redundancy. Computers & Education, 76, 199–204.CrossRefGoogle Scholar
Arndt, J., Schüler, A., & Scheiter, K. (2019). Investigating the influence of simultaneous – versus sequential – text–picture presentation on text–picture integration. The Journal of Experimental Education, 87(1), 116–127.CrossRefGoogle Scholar
Austin, K. A. (2009). Multimedia learning: Cognitive individual differences and display design techniques predict transfer learning with multimedia learning modules. Computers and Education, 53, 1339–1354.Google Scholar
Bauhoff, V., Huff, M., & Schwan, S. (2012). Distance matters: Spatial contiguity effects as trade‐off between gaze switches and memory load. Applied Cognitive Psychology, 26(6), 863–871.Google Scholar
Bodemer, D., Ploetzner, R., Bruchmüller, K., & Häcker, S. (2005). Supporting learning with interactive multimedia through active integration of representations. Instructional Science, 33(1), 73–95.Google Scholar
Boucheix, J. M., Lowe, R. K., Putri, D. K., & Groff, J. (2013). Cueing animations: Dynamic signaling aids information extraction and comprehension. Learning and Instruction, 25, 71–84.CrossRefGoogle Scholar
Chandler, P., & Sweller, J. (1991). Cognitive load theory and the format of instruction. Cognition and Instruction, 8, 293–332.Google Scholar
Chandler, P., & Sweller, J. (1992). The split-attention effect as a factor in the design of instruction. British Journal of Educational Psychology, 62, 233–246.Google Scholar
Chung, K. K. H. (2007). Presentation factors in the learning of Chinese characters: The order and position of Hanyu pinyin and English translations. Educational Psychology, 27, 1–20.Google Scholar
Cierniak, G., Scheiter, K., & Gerjets, P. (2009). Explaining the split-attention effect: Is the reduction of extraneous cognitive load accompanied by an increase in germane cognitive load? Computers in Human Behavior, 25(2), 315–324.Google Scholar
Congdon, E. L., Novack, M. A., Brooks, N., Hemani-Lopez, N., O’Keefe, L., & Goldin-Meadow, S. (2017). Better together: Simultaneous presentation of speech and gesture in math instruction supports generalization and retention. Learning and Instruction, 50, 65–74.CrossRefGoogle ScholarPubMed
Craig, S. D., Gholson, B., & Driscoll, D. M. (2002). Animated pedagogical agents in multimedia educational environments: Effects of agent properties, picture features and redundancy. Journal of Educational Psychology, 94(2), 428–434.Google Scholar
Craig, S. D., Twyford, J., Irigoyen, N., & Zipp, S. A. (2015). A test of spatial contiguity for virtual human’s gestures in multimedia learning environments. Journal of Educational Computing Research, 53(1), 3–14.Google Scholar
Crooks, S., White, D., Srinivasan, S., & Wang, Q. (2008). Temporal, but not spatial, contiguity effects while studying an interactive geographic map. Journal of Educational Multimedia and Hypermedia, 17(2), 145–169.Google Scholar
de Koning, B. B., Rop, G., & Paas, F. (2020a). Learning from split-attention materials: Effects of teaching physical and mental learning strategies. Contemporary Educational Psychology, 61, 101873.CrossRefGoogle Scholar
de Koning, B. B., Rop, G., & Paas, F. (2020b). Effects of spatial distance on the effectiveness of mental and physical integration strategies in learning from split-attention examples. Computers in Human Behavior, 110, 106379.CrossRefGoogle Scholar
de Koning, B. B., Tabbers, H. K., Rikers, R. M. J. P., & Paas, F. (2007). Attention cueing as a means to enhance learning from an animation. Applied Cognitive Psychology, 21, 731–746.Google Scholar
de Koning, B. B., Tabbers, H. K., Rikers, R. M. J. P., & Paas, F. (2009). Towards a framework for attention cueing in instructional animations: Guidelines for research and design. Educational Psychology Review, 21, 113–140.Google Scholar
de Koning, B. B., Tabbers, H. K., Rikers, R. M. J. P., & Paas, F. (2010). Attention guidance in learning from complex animation: Seeing is understanding? Learning and Instruction, 20(2), 111–122.CrossRefGoogle Scholar
de Koning, B. B., Tabbers, H. K., Rikers, R. M. J. P., & Paas, F. (2011). Improved effectiveness of cueing by self‐explanations when learning from a complex animation. Applied Cognitive Psychology, 25(2), 183–194.Google Scholar
de Koning, B. B., van Hooijdonk, C. M., & Lagerwerf, L. (2017). Verbal redundancy in a procedural animation: On-screen labels improve retention but not behavioral performance. Computers & Education, 107, 45–53.Google Scholar
Doolittle, P. E., & Altstaedter, L. L. (2009). The effect of working memory capacity on multimedia learning: Does attentional control result in improved performance? Journal of Research in Innovative Teaching, 2, 7–23.Google Scholar
Eitel, A., Bender, L., & Renkl, A. (2019). Are seductive details seductive only when you think they are relevant? An experimental test of the moderating role of perceived relevance. Applied Cognitive Psychology, 33(1), 20–30.Google Scholar
Eitel, A., & Scheiter, K. (2015). Picture or text first? Explaining sequence effects when learning with pictures and text. Educational Psychology Review, 27(1), 153–180.Google Scholar
Eitel, A., Scheiter, K., Schüler, A., Nyström, M., & Holmqvist, K. (2013). How a picture facilitates the process of learning from text: Evidence for scaffolding. Learning and Instruction, 28, 48–63.CrossRefGoogle Scholar
Fenesi, B., Heisz, J. J., Savage, P. I., Shore, D. I., & Kim, J. A. (2014). Combining best-practice and experimental approaches: Redundancy, images, and misperceptions in multimedia learning. The Journal of Experimental Education, 82(2), 253–263.Google Scholar
Fiorella, L., & Pilegard, C. (2020). Learner-generated explanations: Effects on restudying and learning from a multimedia lesson. Educational Psychology, 41(1), 45–62.Google Scholar
Fries, L., DeCaro, M. S., & Ramirez, G. (2019). The lure of seductive details during lecture learning. Journal of Educational Psychology, 111(4), 736.CrossRefGoogle Scholar
Ginns, P. (2006). Integrating information: A meta-analysis of the spatial contiguity and temporal contiguity effects. Learning and Instruction, 16(6), 511–525.CrossRefGoogle Scholar
Gordon, C., Tindall‐Ford, S., Agostinho, S., & Paas, F. (2016). Learning from instructor‐managed and self‐managed split‐attention materials. Applied Cognitive Psychology, 30(1), 1–9.CrossRefGoogle Scholar
Harp, S. F., & Mayer, R. E. (1997). The role of interest in learning from scientific text and illustrations: On the distinction between emotional interest and cognitive interest. Journal of Educational Psychology, 89(1), 92–102.CrossRefGoogle Scholar
Harp, S. F., & Mayer, R. E. (1998). How seductive details do their damage: A theory of cognitive interest in science learning. Journal of Educational Psychology, 90(3), 414–434.Google Scholar
Jamet, E. (2014). An eye-tracking study of cueing effects in multimedia learning. Computers in Human Behavior, 32, 47–53.Google Scholar
Jamet, E., Gavota, M., & Quaireau, C. (2008). Attention guiding in multimedia learning. Learning and Instruction, 18, 135–145.CrossRefGoogle Scholar
Jamet, E., & Le Bohec, O. (2007). The effect of redundant text in multimedia instruction. Contemporary Educational Psychology, 32, 588–598.CrossRefGoogle Scholar
Jarosz, A. F., & Jaeger, A. J. (2019). Inconsistent operations: A weapon of math disruption. Applied Cognitive Psychology, 33(1), 124–138.Google Scholar
Jeung, H., Chandler, P., & Sweller, J. (1997). The role of visual indicators in dual sensory mode instruction. Educational Psychology, 17, 329–345.Google Scholar
Johnson, A. M., Ozogul, G., & Reisslein, M. (2015). Supporting multimedia learning with visual signalling and animated pedagogical agent: Moderating effects of prior knowledge. Journal of Computer Assisted Learning, 31(2), 97–115.CrossRefGoogle Scholar
Johnson, C., & Mayer, R. E. (2012). An eye movement analysis of the spatial contiguity effect in multimedia learning. Journal of Experimental Psychology: Applied, 18, 178–191.Google Scholar
Kalyuga, S., Chandler, P., & Sweller, J. (1999). Managing split-attention and redundancy in multimedia instruction. Applied Cognitive Psychology, 13, 351–371.3.0.CO;2-6>CrossRefGoogle Scholar
Kalyuga, S., Chandler, P., & Sweller, J. (2000). Incorporating learner experience into the design of multimedia instruction. Journal of Educational Psychology, 92, 126–136.Google Scholar
Kester, L., Kirschner, P. A., & van Merrienboer, J. J. G. (2005). The management of cognitive load during complex cognitive skill acquisition by means of computer-simulated problem solving. British Journal of Educational Psychology, 75, 71–85.Google Scholar
Khacharem, A., Trabelsi, K., Engel, F. A., Sperlich, B., & Kalyuga, S. (2020). The effects of temporal contiguity and expertise on acquisition of tactical movements. Frontiers in Psychology, 11, 413.CrossRefGoogle ScholarPubMed
Kriz, S., & Hegarty, M. (2007). Top-down and bottom-up influences on learning from animations. International Journal of Human-Computer Studies, 65, 911–930.CrossRefGoogle Scholar
Kühl, T., & Münzer, S. (2019). The moderating role of additional information when learning with animations compared to static pictures. Instructional Science, 47(6), 659–677.Google Scholar
Le Bohec, O., & Jamet, E. (2008). Levels of verbal redundancy, notetaking and multimedia learning. In Rouet, J.-F., Lowe, R., & Schnotz, W. (eds.), Understanding Multimedia Documents (pp. 79–101). New York: Springer.Google Scholar
Leahy, W., Chandler, P., & Sweller, J. (2003). When auditory presentations should and should not be a component of multimedia instruction. Applied Cognitive Psychology, 17, 401–418.Google Scholar
Lee, H., & Mayer, R. E. (2018). Fostering learning from instructional video in a second language. Applied Cognitive Psychology, 32(5), 648–654.CrossRefGoogle Scholar
Lin, L., & Atkinson, R. K. (2011). Using animations and visual cueing to support learning of scientific concepts and processes. Computers & Education, 56(3), 650–658.Google Scholar
Lowe, R., & Boucheix, J. M. (2011). Cueing complex animations: Does direction of attention foster learning processes? Learning and Instruction, 21(5), 650–663.CrossRefGoogle Scholar
Makransky, G., Terkildsen, T. S., & Mayer, R. E. (2019). Role of subjective and objective measures of cognitive processing during learning in explaining the spatial contiguity effect. Learning and Instruction, 61, 23–34.Google Scholar
Mautone, P. D., & Mayer, R. E. (2001). Signaling as a cognitive guide in multimedia learning. Journal of Educational Psychology, 93, 377–389.CrossRefGoogle Scholar
Mayer, R. E. (1989). Systematic thinking fostered by illustrations in scientific text. Journal of Educational Psychology, 81, 240–246.Google Scholar
Mayer, R. E., & Anderson, R. B. (1991). Animations need narrations: An experimental test of a dual-coding hypothesis. Journal of Educational Psychology, 83, 484–490.Google Scholar
Mayer, R. E., & Anderson, R. B. (1992). The instructive animation: Helping students build connections between words and pictures in multimedia learning. Journal of Educational Psychology, 84, 444–452.CrossRefGoogle Scholar
Mayer, R. E., Bove, W., Bryman, A., Mars, R., & Tapangco, L. (1996). When less is more: Meaningful learning from visual and verbal summaries of science textbook lessons. Journal of Educational Psychology, 88, 64–73.Google Scholar
Mayer, R. E., Heiser, H., & Lonn, S. (2001). Cognitive constraints on multimedia learning: When presenting more material results in less understanding. Journal of Educational Psychology, 93, 187–198.Google Scholar
Mayer, R. E., & Jackson, J. (2005). The case for coherence in scientific explanations: Quantitative details hurt qualitative understanding. Journal of Experimental Psychology: Applied, 11, 256–265.Google Scholar
Mayer, R. E., & Johnson, C. I. (2008). Revising the redundancy principle in multimedia learning. Journal of Educational Psychology, 100, 380–386.Google Scholar
Mayer, R. E., Moreno, R., Boire, M., & Vagge, S. (1999). Maximizing constructivist learning from multimedia communications by minimizing cognitive load. Journal of Educational Psychology, 91, 638–643.Google Scholar
Mayer, R. E., & Sims, V. K. (1994). For whom is a picture worth a thousand words? Extensions of a dual-coding theory of multimedia learning? Journal of Educational Psychology, 86, 389–401.Google Scholar
Mayer, R. E., Steinhoff, K., Bower, G., & Mars, R. (1995). A generative theory of textbook design: Using annotated illustrations to foster meaningful learning of science text. Educational Technology Research and Development, 43, 31–43.Google Scholar
McCrudden, M. T. (2019). The effect of task relevance instructions on memory for text with seductive details. Applied Cognitive Psychology, 33(1), 31–37.Google Scholar
McCrudden, M. T., Hushman, C. J., & Marley, S. C. (2014). Exploring the boundary conditions of the redundancy principle. The Journal of Experimental Education, 82(4), 537–554.Google Scholar
Michas, I. C., & Berry, D. (2000). Learning a procedural task: Effectiveness of multimedia presentations. Applied Cognitive Psychology, 14, 555–575.3.0.CO;2-4>CrossRefGoogle Scholar
Moreno, R., & Mayer, R. E. (1999). Cognitive principles of multimedia learning: The role of modality and contiguity. Journal of Educational Psychology, 91, 358–368.Google Scholar
Moreno, R., & Mayer, R. E. (2000). A coherence effect in multimedia learning: The case for minimizing irrelevant sounds in the design of multimedia messages. Journal of Educational Psychology, 92, 117–125Google Scholar
Moreno, R., & Mayer, R. E. (2002). Verbal redundancy in multimedia learning: When reading helps listening. Journal of Educational Psychology, 94, 156–163.Google Scholar
Mousavi, S. Y., Low, R., & Sweller, J. (1995). Reducing cognitive load by mixing auditory and visual presentation modes. Journal of Educational Psychology, 87, 319–334.Google Scholar
Naumann, J., Richter, T., Flender, J., Cristmann, U., & Groeben, N. (2007). Signaling in expository hypertexts compensates for deficits in reading skill. Journal of Educational Psychology, 99, 791–807.Google Scholar
Ouwehand, K., van Gog, T., & Paas, F. (2015). Designing effective video-based modeling examples using gaze and gesture cues. Educational Technology & Society (online), 18, 78–88.Google Scholar
Owens, P., & Sweller, J. (2008). Cognitive load theory and music instruction. Educational Psychology, 28, 29–45.CrossRefGoogle Scholar
Ozcelik, E., Arslan-Ari, I., & Cagiltay, K. (2010). Why does signaling enhance multimedia learning? Evidence from eye movements. Computers in Human Behavior, 26, 110–117.CrossRefGoogle Scholar
Park, B., Flowerday, T., & Brünken, R. (2015). Cognitive and affective effects of seductive details in multimedia learning. Computers in Human Behavior, 44, 267–278.Google Scholar
Park, B., Moreno, R., Seufert, T., & Brünken, R. (2011). Does cognitive load moderate the seductive details effect? A multimedia study. Computers in Human Behavior, 27(1), 5–10.Google Scholar
Pociask, F. D., & Morrison, G. R. (2008). Controlling split attention and redundancy in physical therapy instruction. Educational Technology Research and Development, 56, 379–399.Google Scholar
Rey, G. D. (2010). Reading direction and signaling in a simple computer simulation. Computers in Human Behavior, 26(5), 1176–1182.Google Scholar
Rey, G. D. (2014). Seductive details and attention distraction – An eye tracker experiment. Computers in Human Behavior, 32, 133–144.CrossRefGoogle Scholar
Richter, J., & Scheiter, K. (2019). Studying the expertise reversal of the multimedia signaling effect at a process level: Evidence from eye tracking. Instructional Science, 47(6), 627–658.Google Scholar
Richter, J., Scheiter, K., & Eitel, A. (2016). Signaling text-picture relations in multimedia learning: A comprehensive meta-analysis. Educational Research Review, 17, 19–36.Google Scholar
Richter, J., Scheiter, K., & Eitel, A. (2018). Signaling text–picture relations in multimedia learning: The influence of prior knowledge. Journal of Educational Psychology, 110(4), 544.CrossRefGoogle Scholar
Roodenrys, K., Agostinho, S., Roodenrys, S., & Chandler, P. (2012). Managing one’s own cognitive load when evidence of split attention is present. Applied Cognitive Psychology, 26(6), 878–886.CrossRefGoogle Scholar
Roscoe, R. D., Jacovina, M. E., Harry, D., Russell, D. G., & McNamara, D. S. (2015). Partial verbal redundancy in multimedia presentations for writing strategy instruction. Applied Cognitive Psychology, 29(5), 669–679.Google Scholar
Sanchez, C. A., & Wiley, J. (2006). An examination of the seductive details effect in terms of working memory capacity. Memory & Cognition, 34(2), 344–355.Google Scholar
Scheiter, K., & Eitel, A. (2015). Signals foster multimedia learning by supporting integration of highlighted text and diagram elements. Learning and Instruction, 36, 11–26.Google Scholar
Schneider, S., Beege, M., Nebel, S., & Rey, G. D. (2018). A meta-analysis of how signaling affects learning with media. Educational Research Review, 23, 1–24.Google Scholar
Schneider, S., Wirzberger, M., & Rey, G. D. (2019). The moderating role of arousal on the seductive detail effect in a multimedia learning setting. Applied Cognitive Psychology, 33(1), 71–84.CrossRefGoogle Scholar
Schroeder, N. L., & Cenkci, A. T. (2018). Spatial contiguity and spatial split-attention effects in multimedia learning environments: A meta-analysis. Educational Psychology Review, 30, 679–701.CrossRefGoogle Scholar
Schroeder, N. L., & Cenkci, A. T. (2020). Do measures of cognitive load explain the spatial split-attention principle in multimedia learning environments? A systematic review. Journal of Educational Psychology, 112(2), 254–270.Google Scholar
Schüler, A., Scheiter, K., Rummer, R., & Gerjets, P. (2012). Explaining the modality effect in multimedia learning: Is it due to a lack of temporal contiguity with written text and pictures? Learning and Instruction, 22(2), 92–102.Google Scholar
Smith, A., & Ayres, P. (2016). Investigating the modality and redundancy effects for learners with persistent pain. Educational Psychology Review, 28(2), 401–424.Google Scholar
Stull, A., & Mayer, R. E. (2007). Learning by doing versus learning by viewing: Three experimental comparisons of learner-generated versus author-provided graphic organizers. Journal of Educational Psychology, 99, 808–820.Google Scholar
Sundararajan, N., & Adesope, O. (2020). Keep it coherent: A meta-analysis of the seductive details effect. Educational Psychology Review, 32, 707–734.Google Scholar
Sweller, J., Chandler, P., Tierney, P., & Cooper, M. (1990). Cognitive load and selective attention as factors in the structuring of technical material. Journal of Experimental Psychology: General, 119, 176–192.CrossRefGoogle Scholar
Tindall-Ford, S., Chandler, P., & Sweller, J. (1997). When two sensory modalities are better than one. Journal of Experimental Psychology: Applied, 3, 257–287.Google Scholar
Um, E., Plass, J. L., Hayward, E. O., & Homer, B. D. (2012). Emotional design in multimedia learning. Journal of Educational Psychology, 104(2), 485–498.Google Scholar
van Wermeskerken, M., & van Gog, T. (2017). Seeing the instructor’s face and gaze in demonstration video examples affects attention allocation but not learning. Computers & Education, 113, 98–107.Google Scholar
Wassenburg, S. I., de Koning, B. B., Bos, L. T., & van der Schoot, M. (2020). Inspecting a picture before reading affects attentional processing but not comprehension. Educational Psychology, 40(1), 4–21.Google Scholar
Xie, H., Mayer, R. E., Wang, F., & Zhou, Z. (2019). Coordinating visual and auditory cueing in multimedia learning. Journal of Educational Psychology, 111(2), 235–255.Google Scholar
Yue, C. L., & Bjork, E. L. (2017). Using selective redundancy to eliminate the seductive details effect. Applied Cognitive Psychology, 31(5), 565–571.Google Scholar
Yue, C. L., Bjork, E. L., & Bjork, R. A. (2013). Reducing verbal redundancy in multimedia learning: An undesired desirable difficulty? Journal of Educational Psychology, 105(2), 266–277.Google Scholar

References

Agostinho, S., Tindall-Ford, S., & Bokosmaty, S. (2014). Adaptive diagrams: A research agenda to explore how learners can manipulate online diagrams to self-manage cognitive load. In Huang, W. (ed.). Human Centric Visualization: Theories, Methodologies and Case Studies (pp. 529–550). New York: Springer.Google Scholar
Agostinho, S., Tindall-Ford, S., & Roodenrys, K. (2013). Adaptive diagrams: Handing control over to the learner to manage split-attention online. Computers & Education, 64, 52–62.Google Scholar
Altmeyer, K., Kapp, S., Thees, M., Malone, S., Kuhn, J., & Brünken, R. (2020). The use of augmented reality to foster conceptual knowledge acquisition in STEM laboratory courses – Theoretical background and empirical results. British Journal of Educational Technology, 51(3), 611–628.Google Scholar
Ayres, P. (2018). Subjective measures of cognitive load: What can they reliably measure? In Zheng, R. (ed.), Cognitive Load Measurement and Application: A Theoretical Framework for Meaningful Research and Practice (pp. 9–28). New York: Routledge.Google Scholar
Ayres, P. (2020). Something old, something new from cognitive load theory. Computers in Human Behavior, 113, 106503.Google Scholar
Ayres, P. & Paas, F. (2012). Some answers to the challenges of cognitive load theory. Applied Cognitive Psychology, 26, 827–832.Google Scholar
Ayres, P. & Sweller, J. (2013). The worked example effect. In Hattie, J. A. C., & Anderman, E. M. (eds.). International Guide to Student Achievement (pp. 408–410). Oxford: Routledge.Google Scholar
Ayres, P. & Sweller, J. (2014). The split-attention principle in multimedia learning. In Mayer, R. E. (ed.), The Cambridge Handbook of Multimedia Learning (2nd ed., pp. 206–226). New York: Cambridge University Press.Google Scholar
Baggett, P. (1984). Role of temporal overlap of visual and auditory material in forming dual media associations. Journal of Educational Psychology, 76, 408–417.CrossRefGoogle Scholar
Bauhoff, V., Huff, M., & Schwan, S. (2011). The effect of temporal distance on comparative visual search. Journal of Vision, 11, 1325.Google Scholar
Bauhoff, V., Huff, M., & Schwan, S. (2012). Distance matters: Spatial contiguity effects as trade-off between gaze-switches and memory load. Applied Cognitive Psychology, 26, 863–871.Google Scholar
Beege, M., Wirzberger, M., Nebel, S., Schneider, S., Schmidt, N., & Rey, G. D. (2019). Spatial contiguity effect vs. spatial contiguity failure. Revising the effects of spatial proximity between related and unrelated representations. Frontiers in Education, 4, 86.Google Scholar
Bétrancourt, M., & Bisseret, A. (1998). Integrating textual and pictorial information via pop-up windows: An experimental study. Behaviour & Information Technology, 17, 263–273.Google Scholar
Bobis, J., Sweller, J., & Cooper, M. (1993). Cognitive load effects in a primary-school geometry task. Learning and Instruction, 3, 1–21.Google Scholar
Bodemer, D., & Faust, U. (2006). External and mental referencing of multiple representations. Computers in Human Behavior, 22, 27–42.Google Scholar
Bodemer, D., Ploetzner, R., Feuerlein, I., & Spada, H. (2004). The active integration of information during learning with dynamic and interactive visualisations. Learning and Instruction, 14, 325–341.Google Scholar
Cammeraat, S., Rop, G., & de Koning, B. B. (2020). The influence of spatial distance and signaling on the split-attention effect. Computers in Human Behavior, 105, 106203.Google Scholar
Cerpa, N., Chandler, P., & Sweller, J. (1996). Some conditions under which integrated computer-based training software can facilitate learning. Journal of Educational Computing Research, 15, 345–367.Google Scholar
Chandler, P., & Sweller, J. (1991). Cognitive load theory and the format of instruction. Cognition and Instruction, 8, 293–332.Google Scholar
Chandler, P., & Sweller, J. (1996). Cognitive load while learning to use a computer program. Applied Cognitive Psychology, 10, 151–170.Google Scholar
Chen, C.-M., & Wu, C.-H. (2015). Effects of different video lecture types on sustained attention, emotion, cognitive load, and learning performance. Computers & Education, 80, 108–121.Google Scholar
Chung, K. K. H. (2007). Presentation factors in the learning of Chinese characters: The order and position of Hanyu pinyin and English translations. Educational Psychology, 27, 1–20.Google Scholar
Cierniak, G., Scheiter, K., & Gerjets, P. (2009). Explaining the split-attention effect: Is the reduction of extraneous cognitive load accompanied by an increase in germane cognitive load? Computers in Human Behavior, 25, 315–324.Google Scholar
Cooper, G., & Sweller, J. (1987). The effects of schema acquisition and rule automation on mathematical problem-solving transfer. Journal of Educational Psychology, 79, 347–362.Google Scholar
Craig, S. D., Twyford, J., Irigoyen, N., & Zipp, S. A. (2015). A test of spatial contiguity for virtual human’s gestures in multimedia learning environments. Journal of Educational Computing, 53(1), 3–14.Google Scholar
de Koning, B. B., Rop, G., & Paas, F. (2020a). Effects of spatial distance on the effectiveness of mental and physical integration strategies in learning from split-attention examples. Computers in Human Behavior, 110, 106379.Google Scholar
de Koning, B. B., Rop, G., & Paas, F. (2020b). The self-management effect in learning from split-attention materials: Mental versus physical integration. Contemporary Educational Psychology, 61, 101873.Google Scholar
Erhel, S., & Jamet, E. (2006). Using pop-up windows to improve multimedia learning. Journal of Computer Assisted Learning, 22, 137–147.Google Scholar
Florax, M., & Ploetzner, R. (2010). What contributes to the split-attention effect? The role of text segmentation, picture labelling, and spatial proximity. Learning and Instruction, 20, 216–224.Google Scholar
Fraser, K. L., Ayres, P., & Sweller, J. (2015). Cognitive load theory for the design of medical simulations. Simulation in Healthcare, 10, 295–307.Google Scholar
Ginns, P. (2006). Integrating information: A meta-analysis of the spatial contiguity and temporal contiguity effects. Learning and Instruction, 16, 511–525.Google Scholar
Gordon, C., Tindall-Ford, S., Agostinho, S., & Paas, F. (2016). Learning from instructor-managed and self-managed split-attention materials. Applied Cognitive Psychology, 30, 1–9.Google Scholar
Holsanova, J. (2014). Reception of multimodality: Applying eye tracking methodology in multimodal research. In Jewitt, C. (ed.), Routledge Handbook of Multimodal Analysis (2nd ed., pp. 285–296). London: Routledge.Google Scholar
Jarodzka, H., Janssen, N., Kirschner, P. A., & Erkens, G. (2015). Avoiding split attention in computer-based testing: Is neglecting additional information facilitative? British Journal of Educational Technology, 46(5), 803–817.Google Scholar
Johnson, C., & Mayer, R. E. (2012). An eye movement analysis of the spatial contiguity effect in multimedia learning. Journal of Experimental Psychology: Applied, 18, 178–191.Google Scholar
Kalyuga, S., Ayres, P., Chandler, P., & Sweller, J. (2003). The expertise reversal effect. Educational Psychologist, 38, 23–31.Google Scholar
Kalyuga, S., Chandler, P., & Sweller, J. (1998). Levels of expertise and instructional design. Human Factors, 40, 1–17.Google Scholar
Kalyuga, S., Chandler, P., & Sweller, J. (1999). Managing split-attention and redundancy in multimedia instruction. Applied Cognitive Psychology, 13, 351–371.Google Scholar
Kirschner, P. A., Ayres, P., & Chandler, P. (2011). Contemporary cognitive load theory research: The good, the bad and the ugly. Computers in Human Behavior, 27(1), 99–105.Google Scholar
Leahy, W., & Sweller, J. (2008). The imagination effect increases with an increased intrinsic cognitive load. Applied Cognitive Psychology, 22, 273–283.Google Scholar
Leahy, W., & Sweller, J. (2019). The centrality of element interactivity to cognitive load theory. In Tindall-Ford, S., Agostinho, S., & Sweller, J. (eds.), Advances in Cognitive Load Theory: Rethinking Teaching (pp. 221–232). Abingdon: Routledge.Google Scholar
Lee, C. H., & Kalyuga, S. (2011). Effectiveness of different pinyin presentation formats in learning Chinese characters: A cognitive load perspective. Language Learning, 61, 1099–1118.Google Scholar
Leppink, J., Paas, F., van der Vleuten, C. P. M., van Gog, T., & van Merriënboer, J. J. G. (2013). Development of an instrument for measuring different types of cognitive load. Behavior Research Methods, 45, 1058–1072.Google Scholar
Lin, J. J. H., Lee, Y. H., Wang, D. Y., & Lin, S. S. J. (2016). Reading subtitles and taking Enotes while learning scientific materials in a multimedia environment: Cognitive load perspectives on EFL students. Educational Technology & Society, 19(4), 47–58.Google Scholar
Macken, L., & Ginns, P. (2014). Pointing and tracing gestures may enhance anatomy and physiology learning. Medical Teacher, 36, 596–601.Google Scholar
Makransky, G., Terkildsen, T. S., & Mayer, R. E. (2019). Role of subjective and objective measures of cognitive processing during learning in explaining the spatial contiguity effect. Learning and Instruction, 61, 23–34.Google Scholar
Mayer, R. E. (1989). Systematic thinking fostered by illustrations in scientific text. Journal of Educational Psychology, 81, 240–246.CrossRefGoogle Scholar
Mayer, R. E. (2001). Multimedia Learning. New York: Cambridge University Press.Google Scholar
Mayer, R. E. (2020a). Multimedia Learning (3rd ed.). New York: Cambridge University Press.Google Scholar
Mayer, R. E. (2020b). Designing multimedia instruction in anatomy: An evidence-based approach. Clinical Anatomy, 33, 2–11.Google Scholar
Mayer, R., & Anderson, R. (1991). Animations need narrations: An experimental test of a dual-coding hypothesis. Journal of Educational Psychology, 83, 484–490.Google Scholar
Mayer, R., & Anderson, R. (1992). The instructive animation: Helping students build connections between words and pictures in multimedia learning. Journal of Educational Psychology, 84, 444–452.Google Scholar
Mayer, R. E., & Sims, V. K. (1994). For whom is a picture worth a thousand words? Extensions of a dual-coding theory of multimedia learning. Journal of Educational Psychology, 86, 389–401.Google Scholar
Mayer, R. E., Steinhoff, K., Bower, G., & Mars, R. (1995). A generative theory of textbook design: Using annotated illustrations to foster meaningful learning of science text. Educational Technology Research, & Development, 43, 31–43.Google Scholar
Moreno, R., & Mayer, R.E. (1999). Cognitive principles of multimedia learning: The role of modality and contiguity. Journal of Educational Psychology, 91, 358–368.Google Scholar
Owens, P., & Sweller, J. (2008). Cognitive load theory and music instruction. Educational Psychology, 28, 29–45.Google Scholar
Paas, F. G., & Sweller, J. (2012). An evolutionary upgrade of cognitive load theory: Using the human motor system and collaboration to support the learning of complex cognitive tasks. Educational Psychology Review, 24, 27–45.Google Scholar
Pi, Z., Xu, K., Liu, C., & Yang, J. (2020). Instructor presence in video lectures: Eye gaze matters, but not body orientation. Computers & Education, 144, 103713.CrossRefGoogle Scholar
Pociask, F. D., & Morrison, G. R. (2008). Controlling split attention and redundancy in physical therapy instruction. Educational Technology Research and Development, 56, 379–399.Google Scholar
Pouw, W., Rop, G., de Koning, B., & Paas, F. (2019). The cognitive basis for the split-attention effect. Journal of Experimental Psychology: General, 148, 2058–2075.Google Scholar
Purnell, K. N., Solman, R. T., & Sweller, J. (1991). The effects of technical illustrations on cognitive load. Instructional Science, 20, 443–462.Google Scholar
Roodenrys, K., Agostinho, S., Roodenrys, S., & Chandler, P. (2012). Managing one’s own cognitive load when evidence of split attention is present. Applied Cognitive Psychology, 26, 878–886.Google Scholar
Rose, J. M., & Wolfe, C. J. (2000). The effects of system design alternatives on the acquisition of tax knowledge from a computerized tax decision aid. Accounting, Organizations and Society, 25, 285–306.Google Scholar
Scheiter, K., & Eitel, A. (2015). Signals foster multimedia learning by supporting integration of highlighted text and diagram elements. Learning and Instruction, 36, 11–26.Google Scholar
Schmidt-Weigand, F., Kohnert, A., & Glowalla, U. (2010). A closer look at split visual attention in system- and self-paced instruction in multimedia learning. Learning and Instruction, 20(2), 100–110.Google Scholar
Schroeder, N. L., & Cenkci, A. T. (2018). Spatial contiguity and spatial split-attention effects in multimedia learning environments: A meta-analysis. Educational Psychology Review, 30, 679–701.Google Scholar
Schroeder, N. L., & Cenkci, A. T. (2019). Do measures of cognitive load explain the spatial split-attention principle in multimedia learning environments? A systematic review. Journal of Educational Psychology, 112(2), 254–270.Google Scholar
Sithole, S. T. M., Chandler, P., Abeysekera, I., & Paas, F. (2017). Benefits of guided self-management of attention on learning accounting. Journal of Educational Psychology, 109(2), 220–232.Google Scholar
Strzys, M., Kapp, S., Thees, M., Klein, P., Lukowicz, P., Knierim, P., Schmidt, A., & Kuhn, J. (2018). Physics holo.lab learning experience: Using smartglasses for augmented reality labwork to foster the concepts of heat conduction. European Journal of Physics, 39, 035703.Google Scholar
Strzys, M. P., Thees, M., Kapp, S., & Kuhn, J. (2019). Smartglasses in STEM laboratory courses – the augmented thermal flux experiment. In Traxler, A., Cao, Y., & Wolf, S. (eds.), 2018 Physics Education Research Conference Proceedings (pp. 411–414). Washington, DC: American Association of Physics Teachers.Google Scholar
Sweller, J. (2010). Element interactivity and intrinsic, extraneous and germane cognitive load. Educational Psychology Review, 22, 123–138.Google Scholar
Sweller, J., Ayres, P., & Kalyuga, S. (2011). Cognitive Load Theory. New York: Springer.Google Scholar
Sweller, J., & Chandler, P. (1994). Why some material is difficult to learn. Cognition and Instruction, 12, 185–233.Google Scholar
Sweller, J., Chandler, P., Tierney, P., & Cooper, M. (1990). Cognitive load and selective attention as factors in the structuring of technical material. Journal of Experimental Psychology: General, 119, 176–192.Google Scholar
Sweller, J., & Cooper, G. A. (1985). The use of worked examples as a substitute for problem solving in learning algebra. Cognition and Instruction, 2, 59–89.Google Scholar
Sweller, J., van Merriënboer, J. J. G., & Paas, F. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10, 251–296.Google Scholar
Sweller, J., van Merriënboer, J. J. G., & Paas, F. (2019). Cognitive architecture and instructional design: 20 years later. Educational Psychology Review, 31(2), 261–292.Google Scholar
Tarmizi, R. & Sweller, J. (1988). Guidance during mathematical problem-solving. Journal of Educational Psychology, 80, 424–436.Google Scholar
Thees, M., Kapp, S., Strzys, M. P., Beil, F., Lukowicz, P., & Kuhn, J. (2020). Effects of augmented reality on learning and cognitive load in university physics laboratory courses. Computers in Human Behavior, 108, 106316.Google Scholar
van Gog, T., & Scheiter, K. (2010). Eye tracking as a tool to study and enhance multimedia learning. Learning and Instruction, 20, 95–99.Google Scholar
Wang, J., Antonenko, P., & Dawson, K. (2020). Does visual attention to the instructor in online video affect learning and learner perceptions? An eye-tracking analysis. Computers & Education, 146, 103779.Google Scholar
Ward, M., & Sweller, J. (1990). Structuring effective worked examples. Cognition and Instruction, 7, 1–39.Google Scholar
Yeung, A. S., Jin, P., & Sweller, J. (1998). Cognitive load and learner expertise: Split-attention and redundancy effects in reading with explanatory notes. Contemporary Educational Psychology, 23, 1–21.Google Scholar
Zhu, X., & Simon, H. (1987). Learning mathematics from examples and by doing. Cognition and Instruction, 4, 137–166.Google Scholar

References

Acarturk, C., & Ozcelic, E. (2017). Secondary-task effects on learning with multimedia: An investigation through eye-movement analysis. The Journal of Experimental Education, 85, 126–141.Google Scholar
Ari, F., Flores, R., Inan, F. A., Cheon, J., Crooks, S. M., Paniukov, D., & Kurucay, M. (2014). The effects of verbally redundant information on student learning: An instance of reverse redundancy. Computers & Education, 76, 199–204.Google Scholar
Berninger, V., Raskind, W., Richards, T., Abbott, R., & Stock, P. (2008). A multidisciplinary approach to understanding developmental dyslexia within working-memory architecture: Genotypes, phenotypes, brain, and instruction. Developmental Neuropsychology, 33, 707–744.Google Scholar
Bobis, J., Sweller, J., & Cooper, M. (1993). Cognitive load effects in a primary school geometry task. Learning and Instruction, 3, 1–21.Google Scholar
Brown, V., Lewis, D., & Toussaint, M. (2016). The redundancy effect on retention and transfer for individuals with high symptoms of ADHD. Journal of the American Academy of Special Education Professionals, Fall 2016, 34–46.Google Scholar
Carroll, J. M. (1990). The Nurnberg Funnel: Designing Minimalist Instruction for Practical Computer Skill. Cambridge, MA: MIT Press.Google Scholar
Carroll, J. M., Smith-Kerker, P., Ford, J., & Mazur-Rimetz, S. (1987). The minimal manual. Human–Computer Interaction, 3, 123–153.Google Scholar
Cerpa, N., Chandler, P., & Sweller, J. (1996). Some conditions under which integrated computer-based training software can facilitate learning. Journal of Educational Computing Research, 15, 345–367.Google Scholar
Chandler, P., & Sweller, J. (1991). Cognitive load theory and the format of instruction. Cognition and Instruction, 8, 293–332.Google Scholar
Chandler, P., & Sweller, J. (1996). Cognitive load while learning to use a computer program. Applied Cognitive Psychology, 10, 151–170.Google Scholar
Craig, S., Gholson, B., & Driscoll, D. (2002). Animated pedagogical agents in multimedia educational environments: Effects of agent properties, picture features, and redundancy. Journal of Educational Psychology, 94, 428–434.Google Scholar
de Koning, B. B., van Hooijdonk, C. M. J., & Lagerverf, L. (2017). Verbal redundancy in a procedural animation: On-screen labels improve retention but not behavioral performance. Computers & Education, 107, 45–53.Google Scholar
Diao, Y., Chandler, P., & Sweller, J. (2007). The effect of written text on comprehension of spoken English as a foreign language. The American Journal of Psychology, 120, 237–262.Google Scholar
Diao, Y., & Sweller, J. (2007). Redundancy in foreign language reading comprehension instruction: Concurrent written and spoken presentations. Learning and Instruction, 17, 78–88.Google Scholar
Fenesi, B., Kramer, E., & Kim, J. A. (2016). Split‐attention and coherence principles in multimedia instruction can rescue performance for learners with lower working memory capacity. Applied Cognitive Psychology, 30, 691–699.Google Scholar
Gerjets, P., Scheiter, K., Opfermann, M., Hesse, F. W., & Eysink, T. H.S. (2009). Learning with hypermedia: The influence of representational formats and different levels of learner control on performance and learning behaviour. Computers in Human Behavior, 25, 360–370.Google Scholar
Holliday, W. G. (1976). Teaching verbal chains using flow diagrams and texts. AV Communication Review, 24, 63–78.CrossRefGoogle Scholar
Jamet, E., & Le Bohec, O. (2007). The effect of redundant text in multimedia instruction. Contemporary Educational Psychology, 32, 588–598.Google Scholar
Jiang, D., Kalyuga, S., & Sweller, J. (2018). The curious case of improving foreign language listening skills by reading rather than listening: An expertise reversal effect. Educational Psychology Review, 30, 1139–1165.Google Scholar
Kalyuga, S., Chandler, P., & Sweller, J. (1999). Managing split-attention and redundancy in multimedia instruction. Applied Cognitive Psychology, 13, 351–371.Google Scholar
Kalyuga, S., Chandler, P. & Sweller, J. (2000). Incorporating learner experience into the design of multimedia instruction. Journal of Educational Psychology, 92, 126–136.Google Scholar
Kalyuga, S., Chandler, P., & Sweller, J. (2004). When redundant on-screen text in multimedia technical instruction can interfere with learning. Human Factors, 46, 567–581.Google Scholar
Knoop‐van Campen, C. A. N., Segers, E., & Verhoeven, L. (2018). The modality and redundancy effects in multimedia learning in children with dyslexia. Dyslexia, 24(2), 140–155.Google Scholar
Knoop-van Campen, C. A. N., Segers, E., & Verhoeven, L. (2019). The modality and redundancy effects, and their relation to executive functioning in children with dyslexia. Research in Developmental Disabilities, 90, 41–50.Google Scholar
Larkin, J., & Simon, H. (1987). Why a diagram is (sometimes) worth a thousand words. Cognitive Science, 11, 65–69.Google Scholar
Lazonder, A., & Van der Meij, H. (1993). The minimal manual: Is less really more? International Journal of Man-Machine Studies, 39, 729–752.Google Scholar
Lee, H., & Mayer, R. (2015). Visual aids to learning in a second language: Adding redundant video to an audio lecture. Applied Cognitive Psychology, 29, 445–454.Google Scholar
Lesh, R., Behr, M., & Post, T. (1987). Rational number relations and proportions. In Janvier, C. (ed.). Problems of Representation in the Teaching and Learning of Mathematics (pp. 41–58). Hillsdale, NJ: Erlbaum.Google Scholar
Li, J., & Tong, F. (2019). Multimedia-assisted self-learning materials: The benefits of E-flashcards for vocabulary learning in Chinese as a foreign language. Reading and Writing, 32, 1175–1195.Google Scholar
Liu, Y., Jang, B. G., & Roy-Campbell, Z. (2018). Optimum input mode in the modality and redundancy principles for university ESL students’ multimedia learning. Computers & Education, 127, 190–200.Google Scholar
Liu, T.-C., Lin, Y.-C., Gao, Y., Yeh, S.-C, & Kalyuga, S. (2015). Does the redundancy effect exist in electronic slideshow assisted lecturing? Computers & Education, 88, 303–314.Google Scholar
Liu, T.-C., Lin, Y.-C., Tsai, M.-J., & Paas, F. (2012). Split-attention and redundancy effects on mobile learning in physical environments. Computers & Education, 58, 172–180.CrossRefGoogle Scholar
Luchini, P. L. (2015) Simultaneous reading and listening is less effective than reading alone: A study based on cognitive load theory. In Piechurska-Kuciel, E., & Szyszka, M. (eds.), The Ecosystem of the Foreign Language Learner: Second Language Learning and Teaching (pp. 71–80). Cham: Springer.Google Scholar
Machado, C., & Luchini, P. L. (2018). Cognitive load theory, redundancy effect and language learning. In Ponniah, R., & Venkatesan, S. (eds.), The Idea and Practice of Reading (pp. 177–190). Singapore: Springer.Google Scholar
Majooni, A., Masood, M., & Akhavan, A. (2016). An eye tracking experiment on strategies to minimize the redundancy and split attention effects in scientific graphs and diagrams. In Di Bucchianico, G., & Kerscher, P. (eds.), Advances in Design for Inclusion: Advances in Intelligent Systems and Computing (Vol. 500, pp. 529–540). Cham: Springer.Google Scholar
Makransky, G., Terkildsen, T. S., & Mayer, R. E. (2019). Adding immersive virtual reality to a science lab simulation causes more presence but less learning. Learning and Instruction, 60, 225–236.Google Scholar
Mayer, R., Bove, W., Bryman, A., Mars, R., & Tapangco, L. (1996). When less is more: Meaningful learning from visual and verbal summaries of science textbook lessons. Journal of Educational Psychology, 88, 64–73.Google Scholar
Mayer, R., Heiser, J., & Lonn, S. (2001). Cognitive contraints on multimedia learning: When presenting more material results in less understanding. Journal of Educational Psychology, 93, 187–198.Google Scholar
Miller, W. (1937). The picture crutch in reading. Elementary English Review, 14, 263–264.Google Scholar
Mohamad Ali, A. Z., Segaran, K., & Wee Hoe, T. (2015). Effects of verbal components in 3D talking-head on pronunciation learning among non-native speakers. Journal of Educational Technology & Society, 18, 313–322.Google Scholar
Molina, A. I., Navaro, O., Ortega, M., & Lacruz, M. (2018). Evaluating multimedia learning materials in primary education using eye tracking. Computer Standards & Interfaces, 59, 45–60.Google Scholar
Moreno, R., & Mayer, R. (2002a). Learning science in virtual reality multimedia environments: Role of methods and media. Journal of Educational Psychology, 94, 598–610.Google Scholar
Moreno, R., & Mayer, R. (2002b). Verbal redundancy in multimedia learning: When reading helps listening. Journal of Educational Psychology, 94, 156–163.Google Scholar
Moussa-Inaty, J., Ayres, P., & Sweller, J. (2012). Cognitive load and the impact of spoken English on learning English as a foreign language. Applied Cognitive Psychology, 63, 391–402.Google Scholar
Pachman, M., & Ke, F. (2012). Environmental support hypothesis in designing multimedia training for older adults: Is less always more? Computers & Education, 58, 100–110.Google Scholar
Paoletti, G., Bortolotti, E., & Zanon, F. (2012). Effects of redundancy and paraphrasing in university lessons: Multitasking and cognitive load in written-spoken PowerPoint presentation. International Journal of Digital Literacy and Digital Competence, 3, 1–11.Google Scholar
Pociask, F. D., & Morrison, G. R. (2008). Controlling split attention and redundancy in physical therapy instruction. Educational Technology Research and Development, 56, 379–399.Google Scholar
Reder, L., & Anderson, J. R. (1980). A comparison of texts and their summaries: Memorial consequences. Journal of Verbal Learning and Verbal Behavior, 19, 121–134.Google Scholar
Reder, L., & Anderson, J. R. (1982). Effects of spacing and embellishment on memory for main points of a text. Memory & Cognition, 10, 97–102.Google Scholar
Roscoe, R. D., Jacovina, M. E., Harry, D., Russel, D. G., & McNamara, D. S. (2015). Partial verbal redundancy in multimedia presentations for writing strategy instruction. Applied Cognitive Psychology, 29, 669–679.Google Scholar
Saunders, R., & Solman, R. (1984). The effect of pictures on the acquisition of a small vocabulary of similar sight-words. British Journal of Educational Psychology, 54, 265–275.Google Scholar
Schooler, J., & Engstler-Schooler, T. (1990). Verbal overshadowing of visual memories: Some things are better left unsaid. Cognitive Psychology, 22, 36–71.Google Scholar
Smith, A., & Ayres, P. (2016). Investigating the modality and redundancy effects for learners with persistent pain. Educational Psychology Review, 28, 401–424.Google Scholar
Solman, R., Singh, N., & Kehoe, E. J. (1992). Pictures block the learning of sight words. Educational Psychology, 12, 143–153.Google Scholar
Swanson, H. L., Zheng, X., & Jerman, O. (2009). Working memory, short-term memory, and reading disabilities: A selective meta-analysis of the literature. Journal of Learning Disabilities, 42(3), 260–287.Google Scholar
Sweller, J., & Chandler, P. (1994) Why some material is difficult to learn. Cognition & Instruction, 12, 185–233.Google Scholar
Torcasio, S., & Sweller, J. (2010). The use of illustrations when learning to read: A cognitive load theory approach. Applied Cognitive Psychology, 24, 659–672.Google Scholar
Wang, C.-Y., Tsai, M.-J., & Tsai, C.-C. (2016). Multimedia recipe reading: Predicting learning outcomes and diagnosing cooking interest using eye-tracking measures. Computers in Human Behavior, 62, 9–18.Google Scholar
Yue, C. L., Bjork, E. L., & Bjork, R. A. (2013). Reducing verbal redundancy in multimedia learning: An undesired desirable difficulty? Journal of Educational Psychology, 105, 266–277.Google Scholar
Zheng, R., Smith, D., Luptak, M., Hill, R. D., Hill, J., & Rupper, R. (2016). Does visual redundancy inhibit older persons’ information processing in learning? Educational Gerontology, 42, 635–645.Google Scholar

References

Alpizar, D., Adesope, O. O., & Wong, R. M. (2020). A meta-analysis of signaling principle in multimedia learning environments. Educational Technology Research and Development, 68, 2095–2119.Google Scholar
Amadieu, F., Mariné, C., & Laimay, C. (2011). The attention-guiding effect and cognitive load in the comprehension of animations. Computers in Human Behavior, 27, 36–40.Google Scholar
Boucheix, J.-M., & Lowe, R. K. (2010). An eye tracking comparison of external pointing cues and internal continuous cues in learning with complex animations. Learning and Instruction, 20(2), 123–135.Google Scholar
Boucheix, J.-M., Lowe, R. K., Putri, D. K., & Groff, J. (2013). Cueing animations: Dynamic signaling aids information extraction and comprehension. Learning and Instruction, 25(1), 71–84.Google Scholar
Canham, M., & Hegarty, M. (2010). Effects of knowledge and display design on comprehension of complex graphics. Learning and Instruction, 20(2), 155–166.Google Scholar
Charness, N., Reingold, E. M., Pomplun, M., & Stampe, D. M. (2001). The perceptual aspect of skilled performance in chess: Evidence from eye movements. Memory and Cognition, 29(8), 1146–1152.Google Scholar
Crooks, S. M., Cheon, J., Inan, F., Ari, F., & Flores, R. (2012). Modality and cueing in multimedia learning: Examining cognitive and perceptual explanations for the modality effect. Computers in Human Behavior, 28(3), 1063–1071.Google Scholar
de Koning, B. B., & Jarodzka, H. (2017). Attention guidance strategies for supporting learning from dynamic visualizations. In Lowe, R., & Ploetzner, R. (ed.), Learning from Dynamic Visualizations: Innovations in Research and Practice (pp. 255–278). Berlin: Springer.Google Scholar
de Koning, B. B., Tabbers, H. K., Rikers, R. M. J. P., & Paas, F. (2007). Attention cueing as a means to enhance learning from an animation. Applied Cognitive Psychology, 21(6), 731–746.Google Scholar
de Koning, B. B., Tabbers, H. K., Rikers, R. M. J. P., & Paas, F. (2009). Towards a framework for attention cueing in instructional animations: Guidelines for research and design. Educational Psychology Review, 21(2), 113–140.Google Scholar
de Koning, B. B., Tabbers, H. K., Rikers, R. M. J. P., & Paas, F. (2010a). Attention guidance in learning from a complex animation: Seeing is understanding? Learning and Instruction, 20(2), 111–122.Google Scholar
de Koning, B. B., Tabbers, H. K., Rikers, R. M. J. P., & Paas, F. (2010b). Learning by generating vs. receiving instructional explanations: Two approaches to enhance attention cueing in animations. Computers & Education, 55(2), 681–691.Google Scholar
de Koning, B. B., Tabbers, H. K., Rikers, R. M. J. P., & Paas, F. (2011). Attention cueing in an instructional animation: The role of presentation speed. Computers in Human Behavior, 27(1), 41–45.Google Scholar
Fischer, S., & Schwan, S. (2010). Comprehending animations: Effects of spatial cueing versus temporal scaling. Learning and Instruction, 20(6), 465–475.Google Scholar
Folker, S., Ritter, H., & Sichelschmidt, L. (2005). Processing and integrating multimodal material: The influence of color coding. In Bara, B. G., Barsalou, L., & Bucciarelli, M. (eds.), Proceedings of 27th Annual Conference of the Cognitive Science Society (pp. 690–695). Mahwah, NJ: Erlbaum.Google Scholar
Gegenfurtner, A., Lehtinen, E., Jarodzka, H., & Säljö, R. (2017). Effects of eye movement modeling examples on adaptive expertise in medical image diagnosis. Computers and Education, 113, 212–225.Google Scholar
Grant, E. R., & Spivey, M. J. (2003). Eye movements and problem solving: Guiding attention guides thought. Psychological Science, 14(5), 462–466.Google Scholar
Haider, H., & Frensch, P. A. (1999). Eye movement during skill acquisition: More evidence for the information reduction hypothesis. Journal of Experimental Psychology: Learning, Memory and Cognition, 25(1), 172–190.Google Scholar
Harp, S. F., & Mayer, R. E. (1998). How seductive details do their damage: A theory of cognitive interest in science learning. Journal of Educational Psychology, 90(3), 414–434.Google Scholar
Hayes, D. A., & Reinking, D. (1991). Good and poor readers’ use of graphic aids cued in texts and adjunct study materials. Contemporary Educational Psychology, 16(4), 391–398.Google Scholar
Hegarty, M., Canham, M. S., & Fabrikant, S. I. (2010). Thinking about the weather: How display salience and knowledge affect performance in a graphic inference task. Journal of Experimental Psychology: Learning, Memory and Cognition, 36(1), 37–53.Google Scholar
Holmqvist, K., Nyström, M., Andersson, R., Dewhurst, R., Jarodzka, H., & van de Weijer, J. (2011). Eye Tracking A Comprehensive Guide to Methods and Measures. Oxford: Oxford University Press.Google Scholar
Jairam, D., Kiewra, K. A., Kauffman, D. F., & Zhao, R. (2012). How to study a matrix. Contemporary Educational Psychology, 37(2), 128–135.Google Scholar
Jamet, E., Gavota, M., & Quaireau, C. (2008). Attention guiding in multimedia learning. Learning and Instruction, 18(2), 135–145.Google Scholar
Jarodzka, H., Balslev, T., Holmqvist, K., Nyström, M., Scheiter, K., Gerjets, P., & Eika, B. (2012). Conveying clinical reasoning based on visual observation via eye-movement modelling examples. Instructional Science, 40(5), 813–827.Google Scholar
Jarodzka, H., Scheiter, K., Gerjets, P., & van Gog, T. (2010). In the eyes of the beholder: How experts and novices interpret dynamic stimuli. Learning and Instruction, 20(2), 146–154.Google Scholar
Jarodzka, H., van Gog, T., Dorr, M., Scheiter, K., & Gerjets, P. (2013). Learning to see: Guiding students’ attention via a model’s eye movements fosters learning. Learning and Instruction, 25, 62–70.Google Scholar
Jeung, H., Chandler, P., & Sweller, J. (1997). The role of visual indicators in dual sensory mode instruction. Educational Psychology, 17(3), 329–343.CrossRefGoogle Scholar
Kalyuga, S., Ayres, P., Chandler, P., & Sweller, J. (2003). The expertise reversal effect. Educational Psychologist, 38, 23–31.Google Scholar
Kalyuga, S., Chandler, P., & Sweller, J. (1999). Managing split-attention and redundancy in multimedia instruction. Applied Cognitive Psychology, 13(4), 351–371.Google Scholar
Lin, L., & Atkinson, R. K. (2011). Using animations and visual cueing to support learning of scientific concepts and processes. Computers & Education, 56(3), 650–658.Google Scholar
Lin, L., Atkinson, R. K., Savenye, W. C., & Nelson, B. C. (2016). The effects of visual cues and self-explanation prompts: Empirical evidence in a multimedia environment. Interactive Learning Environments, 24(4), 799–813.Google Scholar
Litchfield, D., & Ball, L. J. (2011). Using another’s gaze as an explicit aid to insight problem solving. Quarterly Journal of Experimental Psychology, 64, 649–656.Google Scholar
Litchfield, D., Ball, L. J., Donovan, T., Manning, D. J., & Crawford, T. (2010). Viewing another person’s eye movements improves identification of pulmonary nodules in chest x-ray inspection. Journal of Experimental Psychology: Applied, 16(3), 251–262.Google Scholar
Loman, N. L., & Mayer, R. E. (1983). Signaling techniques that increase the understandability of expository prose. Journal of Educational Psychology, 75(3), 402–412.Google Scholar
Lorch, R. F. Jr., & Lorch, E. P. (1995). Effects of organizational signals on text-processing strategies. Journal of Educational Psychology, 87(4), 537–544.Google Scholar
Lorch, R. F. Jr., & Lorch, E. P. (1996). Effects of organizational signals on free recall of expository text. Journal of Educational Psychology, 88(1), 34–48.Google Scholar
Lorch, R. F. Jr., Lorch, E. P., & Klusewitz, M. A. (1995). Effects of typographical cues on reading and recall of text. Contemporary Educational Psychology, 20(1), 51–64.Google Scholar
Lowe, R. K. (1999). Extracting information from an animation during complex visual learning. European Journal of Psychology of Education, 14(2), 225–244.Google Scholar
Lowe, R. K. (2003). Animation and learning: Selective processing of information in dynamic graphics. Learning and Instruction, 13(2), 157–176.Google Scholar
Lowe, R. K., & Boucheix, J.-M. (2011). Cueing complex animations: Does direction of attention foster learning processes? Learning and Instruction, 21(5), 650–663.Google Scholar
Mason, L., Pluchino, P., & Tornatora, M. C. (2015). Eye-movement modeling of integrative reading of an illustrated text: Effects on processing and learning. Contemporary Educational Psychology, 41, 172–187.Google Scholar
Mason, L., Pluchino, P., & Tornatora, M. C. (2016). Using eye-tracking technology as an indirect instruction tool to improve text and picture processing and learning. British Journal of Educational Technology, 47(6), 1083–1095.Google Scholar
Mason, L., Scheiter, K., & Tornatora, M. C. (2017). Using eye movements to model the sequence of textpicture processing for multimedia comprehension. Journal of Computer Assisted Learning, 33(5), 443–460.Google Scholar
Mautone, P. D., & Mayer, R. E. (2001). Signaling as a cognitive guide in multimedia learning. Journal of Educational Psychology, 93(2), 377–389.Google Scholar
Mautone, P. D., & Mayer, R. E. (2007). Cognitive aids for guiding graph comprehension. Journal of Educational Psychology, 99(3), 640–652.Google Scholar
Mayer, R. E. (2020). Multimedia Learning (3rd ed.). New York: Cambridge University Press.Google Scholar
Mayer, R. E., Dyck, J. L., & Cook, L. K. (1984). Techniques that help readers build mental models from scientific text: Definitions pretraining and signaling. Journal of Educational Psychology, 76(6), 1089–1105.Google Scholar
Mayer, R. E., & Johnson, C. I. (2008). Revising the redundancy principle in multimedia learning. Journal of Educational Psychology, 100(2), 380–386.Google Scholar
McTigue, E. M. (2009). Does multimedia learning theory extend to middle-school students? Contemporary Educational Psychology, 34(2), 143–153.Google Scholar
Moreno, R., & Abercrombie, S. (2010). Promoting awareness of learner diversity in prospective teachers: Signaling individual and group differences within classroom cases. Journal of Technology and Teacher Education, 18(1), 111–130.Google Scholar
Ozcelik, E., Arslan-Arib, I., & Cagiltay, K. (2010). Why does signaling enhance multimedia learning? Evidence from eye movements. Computers in Human Behavior, 26(1), 110–117.Google Scholar
Ozcelik, E., Karakus, T., Kursun, E., & Cagiltay, K. (2009). An eye-tracking study of how color coding affects multimedia learning. Computers & Education, 53(1), 445–453.Google Scholar
Richter, J., & Scheiter, K. (2019). Studying the expertise reversal of the multimedia signaling effect at a process level: Evidence from eye tracking. Instructional Science, 47(6), 627–658.Google Scholar
Richter, J., Scheiter, K., & Eitel, A. (2016). Signaling text-picture relations in multimedia learning: A comprehensive meta-analysis. Educational Research Review, 17, 19–36.Google Scholar
Richter, J., Scheiter, K., & Eitel, A. (2018). Signaling text–picture relations in multimedia learning: The influence of prior knowledge. Journal of Educational Psychology, 110(4), 544–560.Google Scholar
Rouet, J.-F., Ros, C., Goumi, A., Macedo-Rouet, M., & Dinet, J. (2011). The influence of surface and deep cues on primary and secondary school students’ assessment of relevance in Web menus. Learning and Instruction, 21(2), 205–219.Google Scholar
Salmerón, L., & Llorens, A. (2019). Instruction of digital reading strategies based on eye-movements modeling examples. Journal of Educational Computing Research, 57(2), 343–359.Google Scholar
Scerbo, M. W., Warm, J. S., Dember, W. N., & Grasha, A. F. (1992). The role of time and cuing in a college lecture. Contemporary Educational Psychology, 17(4), 312–328.Google Scholar
Scheiter, K., & Eitel, A. (2015). Signals foster multimedia learning by supporting integration of highlighted text and diagram elements. Learning and Instruction, 36, 11–26.Google Scholar
Scheiter, K., Schubert, C., & Schüler, A. (2018). Self-regulated learning from illustrated text: Eye movement modelling to support use and regulation of cognitive processes during learning from multimedia. British Journal of Educational Technology, 88(1), 80–94.Google Scholar
Scheiter, K., Schubert, C., Schüler, A., Schmidt, H., Zimmermann, G., Wassermann, B., … Eder, T. (2019). Adaptive multimedia: Using gaze-contingent instructional guidance to provide personalized processing support. Computers & Education, 139, 31–47.Google Scholar
Schneider, S., Beege, M., Nebel, S., & Rey, G. D. (2018). A meta-analysis of how signaling affects learning with media. Educational Research Review, 23, 1–24.Google Scholar
Schwonke, R., Berthold, K., & Renkl, A. (2009). How multiple external representations are used and how they can be made more useful. Applied Cognitive Psychology, 23(9), 1227–1243.Google Scholar
Shah, P., Mayer, R. E., & Hegarty, M. (1999). Graphs as aids to knowledge construction. Journal of Educational Psychology, 91(4), 690–702.Google Scholar
Skuballa, I. T., Schwonke, R., & Renkl, A. (2012). Learning from narrated animations with different support procedures: Working memory capacity matters. Applied Cognitive Psychology, 26(6), 840–847.Google Scholar
Sung, E., & Mayer, R. E. (2012). Affective impact of navigational and signaling aids to e-learning. Computers in Human Behavior, 28(2), 473–483.Google Scholar
Sweller, J., Ayres, P., & Kalyuga, S. (2011). Cognitive Load Theory. New York: Springer.Google Scholar
Tabbers, H. K., Martens, R. L., & van Merriënboer, J. J. G. (2004). Multimedia instructions and cognitive load theory: Effects of modality and cueing. British Journal of Educational Psychology, 74(1), 71–81.Google Scholar
Titsworth, B. S., & Kiewra, K. A. (2004). Spoken organizational lecture cues and student notetaking as facilitators of student learning. Contemporary Educational Psychology, 29(4), 447–461.Google Scholar
Underwood, G., Chapman, P., Brocklehurst, N., Underwood, J., & Crundall, D. (2003). Visual attention while driving: Sequences of eye fixations made by experienced and novice drivers. Ergonomics, 46(6), 629–646.Google Scholar
van Gog, T. (2006). Uncovering the Problem-Solving Process to Design Effective Worked Examples [Doctoral Dissertation]. Open University of The Netherlands.Google Scholar
van Gog, T., Jarodzka, H., Scheiter, K., Gerjets, P., & Paas, F. (2009). Attention guidance during example study via the model’s eye movements. Computers in Human Behavior, 25(3), 785–791.Google Scholar
van Gog, T., Paas, F., & van Merriënboer, J. J. G. (2005). Uncovering expertise-related differences in troubleshooting performance: Combining eye movement and concurrent verbal protocol data. Applied Cognitive Psychology, 19(2), 205–221.Google Scholar
van Gog, T., & Scheiter, K. (2010). Eye tracking as a tool to study and enhance multimedia learning. Learning and Instruction, 20(2), 95–99.Google Scholar
van Marlen, T., van Wermeskerken, M., Jarodzka, H., & van Gog, T. (2016). Showing a model’s eye movements in examples does not improve learning of problem-solving tasks. Computers in Human Behavior, 65, 448–459.Google Scholar
van Marlen, T., van Wermeskerken, M., Jarodzka, H., & van Gog, T. (2018). Effectiveness of eye movement modeling examples in problem solving: The role of verbal ambiguity and prior knowledge. Learning and Instruction, 58, 274–283.Google Scholar
Yarbus, A. L. (1967). Eye Movements and Vision. New York: Plenum Press.Google Scholar

References

Atkinson, R. K., Renkl, A., & Merrill, M. M. (2003). Transitioning from studying examples to solving problems: Combining fading with prompting fosters learning. Journal of Educational Psychology, 95, 774–783.Google Scholar
Barbieri, C. A., & Booth, J. L. (2020). Mistakes on display: Incorrect examples refine equation solving and algebraic feature knowledge. Applied Cognitive Psychology, 34, 862–878.Google Scholar
Bentley, B., & Yates, G. C. R. (2017). Facilitating proportional reasoning through worked examples: Two classroom-based experiments. Cogent Education, 4, 1297213.Google Scholar
Berthold, K., & Renkl, A. (2009). Instructional aids to support a conceptual understanding of multiple representations. Journal of Educational Psychology, 101, 70–87.Google Scholar
Catrambone, R. (1996). Generalizing solution procedures learned from examples. Journal of Experimental Psychology: Learning, Memory, & Cognition, 22, 1020–1031.Google Scholar
Cooper, G., Tindall-Ford, S., Chandler, P., & Sweller, J. (2001). Learning by imagining procedures and concepts. Journal of Experimental Psychology: Applied, 7, 68–82.Google Scholar
Eitel, A., Endres, T., & Renkl, A. (2020). Self-management as a bridge between cognitive load and self-regulated learning: The illustrative case of seductive details. Educational Psychology Review, 32, 1073–1087.Google Scholar
Fiorella, L., & Mayer, R. E. (2016). Eight ways to promote generative learning. Educational Psychology Review, 28, 717–741.Google Scholar
Gentner, D., Loewenstein, J., & Thompson, L. (2003). Learning and transfer: A general role for analogical encoding. Journal of Educational Psychology, 95, 393–408.Google Scholar
Ginns, P., Chandler, P., & Sweller, J. (2003). When imagining information is effective. Contemporary Educational Psychology, 28, 229–251.Google Scholar
Ginns, P., Hu, F.-T., & Bobis, J. (2020). Tracing enhances problem‐solving transfer, but without effects on intrinsic or extraneous cognitive load. Applied Cognitive Psychology, 34, 1522–1529.Google Scholar
Glogger-Frey, I., Fleischer, C., Grüny, L., Kappich, J., & Renkl, A. (2015). Inventing a solution and studying a worked solution prepare differently for learning from direct instruction. Learning & Instruction, 39, 72–87.Google Scholar
Glogger-Frey, I., Gaus, K., & Renkl, A. (2017). Learning from direct instruction: Best prepared by several self-regulated or guided invention activities? Learning & Instruction, 51, 26–35.Google Scholar
Große, C. S., & Renkl, A. (2007). Finding and fixing errors in worked examples: Can this foster learning outcomes? Learning & Instruction, 17, 612–634.Google Scholar
Hallinen, N. R., & Booth, J. L. (2018). Don’t just do it, explain it: A 5th grade worked examples curriculum supports transfer to algebra content. Proceedings of International Conference of the Learning Sciences (pp. 1647–1648). London: ICLS.Google Scholar
Hartmann, C., van Gog, T., & Rummel, N. (2020). Do examples of failure effectively prepare students for learning from subsequent instruction? Applied Cognitive Psychology, 34, 879–889.Google Scholar
Hattie, J. A. C. (2009). Visible Learning: A Synthesis of over 800 Meta-Analyses Relating to Achievement. London: Routledge.Google Scholar
Hefter, M. H., Renkl, A., Riess, W., Schmid, S., Fries, S., & Berthold, K. (2018). Training interventions to foster skill and will of argumentative thinking. Journal of Experimental Education, 86, 325–343.Google Scholar
Hilbert, T. S., Renkl, A., Schworm, S., Kessler, S., & Reiss, K. (2008). Learning to teach with worked-out examples: A computer-based learning environment for teachers. Journal of Computer-Assisted Learning, 24, 316–332.Google Scholar
Hiller, S., Rumann, S., Berthold, K., & Roelle, J. (2020). Example‑based learning: Should learners receive closed‑book or open‑book self‑explanation prompts? Instructional Science, 48, 623–649.Google Scholar
Holyoak, K. J. (2012). Analogy and relational reasoning. In Holyoak, K. J., & Morrison, R. G. (eds.), The Oxford Handbook of Thinking and Reasoning (pp. 234–259). New York: Oxford University Press.Google Scholar
Hoogerheide, V., Van Wermeskerken, M., Loyens, S. M. M., & Van Gog, T. (2016). Learning from video modeling examples: Content kept equal, adults are more effective models than peers. Learning & Instruction, 44, 22–30.Google Scholar
Kapur, M. (2008). Productive failure. Cognition & Instruction, 26, 379–424.Google Scholar
Krebs, M.-C., Schüler, A., & Scheiter, K. (2019). Just follow my eyes: The influence of model-observer similarity on eye movement modeling examples. Learning & Instruction, 61, 126–137.Google Scholar
Mason, L., Pluchino, P., & Tornatora, M. C. (2015). Eye-movement modeling of integrative reading of an illustrated text: Effects on processing and learning. Contemporary Educational Psychology, 41, 172–187.Google Scholar
Mayer, R. E. (2021). Multimedia Learning (3rd ed.). Cambridge: Cambridge University Press.Google Scholar
Newman, P. M., & DeCaro, M. S. (2019). Learning by exploring: How much guidance is optimal? Learning & Instruction, 62, 49–63.Google Scholar
Nokes-Malach, T. J., VanLehn, K., Belenky, D., Lichtenstein, M., & Cox, G. (2013). Coordinating principles and examples through analogy and self-explanation. European Journal of Education of Psychology, 28, 1237–1263.Google Scholar
Paas, F., & van Merriënboer, J. J. G. (1994). Variability of worked examples and transfer of geometrical problem-solving skills: A cognitive-load approach. Journal of Educational Psychology, 86, 122–133.Google Scholar
Pant, H. A. (2014). Aufbereitung von Evidenz für bildungspolitische und pädagogische Entscheidungen: Metaanalysen in der Bildungsforschung [Synthesizing evidence for educational policy and educational decisions: Meta-analyses in educational sciences]. Zeitschrift für Erziehungswissenschaft, 17, 79–99.Google Scholar
Quilici, J. L., & Mayer, R. E. (1996). Role of examples in how students learn to categorize statistics word problems. Journal of Educational Psychology, 88, 144–161.Google Scholar
Reiss, K., Heinze, A., Renkl, A., & Groß, C. (2008). Reasoning and proof in geometry: Effects of a learning environment based on heuristic worked-out examples. ZDM – Mathematics Education, 40, 455–467.Google Scholar
Renkl, A. (1997). Learning from worked-out examples: A study on individual differences. Cognitive Science, 21, 1–29.Google Scholar
Renkl, A. (2014). Towards an instructionally-oriented theory of example-based learning. Cognitive Science, 38, 1–37.Google Scholar
Renkl, A. (2015). Different roads lead to Rome: The case of principle-based cognitive skills. Learning: Research & Practice, 1, 79–90.Google Scholar
Renkl, A. (2017). Learning from worked examples in mathematics: Students relate procedures to principles. ZDM Mathematics Education, 49, 571–584.Google Scholar
Renkl, A., & Atkinson, R. K. (2003). Structuring the transition from example study to problem solving in cognitive skills acquisition: A cognitive load perspective. Educational Psychologist, 38, 15–22.Google Scholar
Renkl, A., Hilbert, T., & Schworm, S. (2009). Example-based learning in heuristic domains: A cognitive load theory account. Educational Psychology Review, 21, 67–78.Google Scholar
Richey, J. E., & Nokes-Malach, T. J. (2013). How much is too much? Explanatory text effects on conceptual learning and motivation. Learning & Instruction, 25, 104–121.Google Scholar
Rittle-Johnson, B., Star, J. R., & Durkin, K. (2009). The importance of prior knowledge when comparing examples: Influences on conceptual and procedural knowledge of equation solving. Journal of Educational Psychology, 101, 836–852.Google Scholar
Roelle, J., Hiller, S., Berthold, K., & Rumann, S. (2017). Example-based learning: The benefits of prompting organization before providing examples. Learning and Instruction, 49, 1–12.Google Scholar
Roelle, J., & Renkl, A. (2020). Does an option to review instructional explanations enhance example-based learning? It depends on learners’ academic self-concept. Journal of Educational Psychology, 112, 131–147.Google Scholar
Rummel, N., Spada, H., & Hauser, S. (2009). Learning to collaborate while being scripted or by observing a model. International Journal of Computer-Supported Collaborative Learning, 4, 69–92.Google Scholar
Salden, R., Aleven, V., Schwonke, R., & Renkl, A. (2010). The expertise-reversal effect and worked examples in tutored problem solving. Instructional Science, 38, 289–307.Google Scholar
Salden, R., Koedinger, K. R., Renkl, A., Aleven, V., & McLaren, B. M. (2010). Accounting for beneficial effects of worked examples in tutored problem solving. Educational Psychology Review, 22, 379–392.Google Scholar
Scheiter, K. (2020). Embracing complexity in research on learning from examples and from problem solving. Applied Cognitive Psychology, 34, 906–911.Google Scholar
Schwonke, R., Berthold, K., & Renkl, A. (2009). How multiple external representations are used and how they can be made more useful. Applied Cognitive Psychology, 23, 1227–1243.Google Scholar
Schwonke, R., Ertelt, A., Otieno, C., Renkl, A., Aleven, V., & Salden, R. (2013). Metacognitive support promotes an effective use of instructional resources in intelligent tutoring. Learning & Instruction, 23, 136–150.Google Scholar
Schwonke, R., Renkl, A., Krieg, K., Wittwer, J., Aleven, V., & Salden, R. (2009). The worked-example effect: Not an artefact of lousy control conditions. Computers in Human Behavior, 25, 258–266.Google Scholar
Spanjers, I. A. E., van Gog, T., & van Merriënboer, J. J. G. (2012). Segmentation of worked examples: Effects on cognitive load and learning. Applied Cognitive Psychology, 26, 352–358.Google Scholar
Sweller, J., & Cooper, G. A. (1985). The use of worked examples as a substitute for problem solving in learning algebra. Cognition & Instruction, 2, 59–89.Google Scholar
Sweller, J., van Merriënboer, J. J. G., & Paas, F. (2019). Cognitive architecture and instructional design: 20 years later. Educational Psychology Review, 31, 261–292.Google Scholar
Tarmizi, R. A., & Sweller, J. (1988). Guidance during mathematical problem solving. Journal of Educational Psychology, 80, 424–436.Google Scholar
Tindall-Ford, S., Agostinho, S., Bokosmaty, S., Paas, F., & Chandler, P. (2015). Computer-based learning of geometry from integrated and split-attention worked examples: The power of self-management. Educational Technology & Society, 18, 89–99.Google Scholar
van Gog, T., Rummel, N., & Renkl, A. (2019). Learning how to solve problems by studying examples. In Dunlosky, J., & Rawson, K. (eds.), Cambridge Handbook on Cognition and Education (pp. 183–208). Cambridge: Cambridge University Press.Google Scholar
van Harsel, M., Hoogerheide, V., Verkoeijen, P., & van Gog, T. (2019). Effects of different sequences of examples and problems on motivation and learning. Contemporary Educational Psychology, 58, 260–275.Google Scholar
Wittrock, M. C. (1989). Generative processes of comprehension. Educational Psychologist, 24, 345–376.Google Scholar
Wittwer, J., & Renkl, A. (2010). How effective are instructional explanations in example-based learning? A meta-analytic review. Educational Psychology Review, 22, 393–409.Google Scholar
Wouters, P., Paas, F., & van Merriënboer, J. J. G. (2009). Observational learning from animated models: Effects of modality and reflection on transfer. Contemporary Educational Psychology, 34, 1–8.Google Scholar
Yeo, L., & Tzeng, Y. (2020). Cognitive effect of tracing gesture in the learning from mathematics worked examples. International Journal of Science and Mathematics Education, 18, 733–751.Google Scholar
Ziegler, E., & Stern, E. (2014). Delayed benefits of learning elementary algebraic transformations through contrasted comparisons. Learning & Instruction, 33, 131–146.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×