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-cd4964975-96cn4 Total loading time: 0 Render date: 2023-03-30T00:20:51.315Z Has data issue: true Feature Flags: { "useRatesEcommerce": false } hasContentIssue true

Part VI - Principles Based on Social and Affective Features of 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. 275 - 336
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.)

Purchase

Buy Book

Buy print or eBook[Opens in a new window]

References

References

Atkinson, R. K. (2002). Optimizing learning from examples using animated pedagogical agents. Journal of Educational Psychology, 94, 416–427.CrossRefGoogle Scholar
Atkinson, R. K., Mayer, R. E., & Merrill, M. M. (2005). Fostering social agency in multimedia learning: Examining the impact of an animated agent’s voice. Contemporary Educational Psychology, 30, 117–139.CrossRefGoogle Scholar
Baylor, A. L., & Kim, S. (2009). Designing nonverbal communication for pedagogical agents: When less is more. Computers in Human Behavior, 25, 450–457.CrossRefGoogle Scholar
Brom, C., Bromová, E., Děchtěrenko, F., Buchtová, M., & Pergel, M. (2014). Personalized messages in a brewery educational simulation: Is the personalization principle less robust than previously thought? Computers & Education, 72, 339–366.CrossRefGoogle Scholar
Brom, C., Hannemann, T., Stárková, T., Bromová, E., & Děchtěrenko, F. (2017). The role of cultural background in the personalization principle: Five experiments with Czech learners. Computers & Education, 112, 37–68.CrossRefGoogle Scholar
Brown, P., & Levinson, S. C. (1987). Politeness: Some Universals in Language Usage. New York: Cambridge University Press.CrossRefGoogle Scholar
Chan, K. Y., Lyons, C., Kon, L. L., Stine, K., Manley, M., & Crossley, A. (2020). Effect of on-screen text on multimedia learning with native and foreign-accented narration. Learning and Instruction, 67, 101305.CrossRefGoogle Scholar
Colliot, T., & Jamet, E. (2018). Understanding the effects of a teacher video on learning from a multimedia document: An eye-tracking study. Educational Technology Research and Development, 66(6), 1415–1433.CrossRefGoogle Scholar
Craig, S. D., Gholson, B., & Driscoll, D. M. (2002). Animated pedagogical agent in multimedia educational environments: Effects of agent properties, picture features, and redundancy. Journal of Educational Psychology, 94, 428–434.CrossRefGoogle Scholar
Craig, S. D., & Schroeder, N. L. (2017). Reconsidering the voice effect when learning from a virtual human. Computers & Education, 114, 193–205.CrossRefGoogle Scholar
Domagk, S. (2010). Do pedagogical agents facilitate learner motivation and learning outcomes? The role of the appeal of agent’s appearance and voice. Journal of Media Psychology, 22, 84–97.CrossRefGoogle Scholar
Dunsworth, Q., & Atkinson, R. K. (2010). Fostering multimedia learning of science: Explaining the role of an animated agent’s image. Computers & Education, 49, 677–690.CrossRefGoogle Scholar
Fiorella, L., Stull, A. T., Kuhlmann, S., & Mayer, R. E. (2019). Instructor presence in video lectures: The role of dynamic drawings, eye contact, and instructor visibility. Journal of Educational Psychology, 111(7), 1162–1171.CrossRefGoogle Scholar
Frechette, C., & Moreno, R. (2010). The roles of animated pedagogical agents’ presence and nonverbal communication in multimedia learning environments. Journal of Media Psychology, 22, 61–72.CrossRefGoogle Scholar
Ginns, P., & Fraser, J. (2010). Personalization enhances learning anatomy terms. Medical Teacher, 32(9), 776–778.CrossRefGoogle ScholarPubMed
Ginns, P., Marin, A. J., & Marsh, H. M. (2013). Designing instructional text for conversational style: A meta-analysis. Educational Psychology Review, 25(4), 445–472.CrossRefGoogle Scholar
Grice, H. P. (1975). Logic and conversation. In Cole, P., & Morgan, J. (eds.), Syntax and Semantics (Vol. 3, pp. 41–58). New York: Academic Press.Google Scholar
Guo, Y. R., & Goh, D. H. L. (2015). Affect in embodied pedagogical agents: Meta-analytic review. Journal of Educational Computing Research, 53(1), 124–149.CrossRefGoogle 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
Kartal, G. (2010). Does language matter in multimedia learning? Personalization principle revisited. Journal of Educational Psychology, 102, 615–624.CrossRefGoogle Scholar
Kizilcec, R. F., Bailenson, J. N., & Gomez, C. J. (2015). The instructor’s face in video instruction: Evidence from two large-scale field studies. Journal of Educational Psychology, 107(3), 724–739.CrossRefGoogle Scholar
Kühl, T., & Zander, S. (2017). An inverted personalization effect when learning with multimedia: The case of aversive content. Computers & Education, 108, 71–84.CrossRefGoogle Scholar
Li, J., Kizilcec, R., Bailenson, J., & Ju, W. (2016). Social robots and virtual agents as lecturers for video instruction. Computers in Human Behavior, 55, 1222–1230.CrossRefGoogle Scholar
Li, W., Wang, F., Mayer, R. E., & Liu, H. (2019). Getting the point: Which kinds of gestures by pedagogical agents improve multimedia learning? Journal of Educational Psychology, 111(8), 1382–1395.CrossRefGoogle Scholar
Lusk, M. M., & Atkinson, R. K. (2007). Animated pedagogical agents: Does their degree of embodiment impact learning from static or animated worked examples? Applied Cognitive Psychology, 21, 747–764.CrossRefGoogle Scholar
Mayer, R. E., & DaPra, C. S. (2012). An embodiment effect in computer-based learning with animated pedagogical agent. Journal of Experimental Psychology: Applied, 18, 239–252.Google Scholar
Mayer, R. E., Dow, G., & Mayer, R. E. (2003). Multimedia learning in an interactive self-explaining environment: What works in the design of agent-based microworlds? Journal of Educational Psychology, 95, 806–813.CrossRefGoogle Scholar
Mayer, R. E., Fennell, S., Farmer, L., & Campbell, J. (2004). A personalization effect in multimedia learning: Students learn better when words are in conversational style rather than formal style. Journal of Educational Psychology, 96, 389–395.CrossRefGoogle Scholar
Mayer, R. E., Sobko, K., & Mautone, P. D. (2003). Social cues in multimedia learning: Role of speaker’s voice. Journal of Educational Psychology, 95, 419–425.CrossRefGoogle Scholar
McLaren, B. M., DeLeeuw, K. E., & Mayer, R. E. (2011a). Polite web-based intelligent tutors: Can they improve learning in classrooms? Computers & Education, 56, 574–584.CrossRefGoogle Scholar
McLaren, B. M., DeLeeuw, K. E., & Mayer, R. E. (2011b). A politeness effect in learning with web-based intelligent tutors. International Journal of Human–Computer Studies, 69, 70–79.CrossRefGoogle Scholar
McLaren, B. M., Lim, S., Yaron, D., & Koedinger, K. (2007). Can a polite intelligent tutoring system lead to improved learning outside the lab? In Proceedings of the 13th International Conference on Artificial Intelligence in Education (pp. 433–440). Amsterdam: IOS Press.Google Scholar
Moreno, R., & Mayer, R. E. (2000). Engaging students in active learning: The case for personalized multimedia messages. Journal of Educational Psychology, 92, 724–733.CrossRefGoogle Scholar
Moreno, R., & Mayer, R. E. (2004). Personalized messages that promote science learning invirtual environments. Journal of Educational Psychology, 96, 165–173.CrossRefGoogle Scholar
Moreno, R., Mayer, R. E., Spires, H. A., & Lester, J. C. (2001). The case for social agency in computer-based teaching: Do students learn more deeply when they interact with animated pedagogical agents? Cognition and Instruction, 19, 177–213.CrossRefGoogle Scholar
Moreno, R., Reislein, M., & Ozogul, G. (2010). Using virtual peers to guide visual attention during learning: A test of the persona hypothesis. Journal of Media Psychology, 22, 52–60.CrossRefGoogle Scholar
Nass, C., & Brave, S. (2005). Wired for Speech. Cambridge, MA: MIT Press.Google Scholar
Reeves, B., and Nass, C. (1996). The Media Equation. New York: Cambridge University Press.Google Scholar
Reichelt, M., Kämmerer, F., Niegemann, H. M., & Zander, S. (2014). Talk to me personally: Personalization of language style in computer-based learning. Computers in Human Behavior, 35, 199–210.CrossRefGoogle Scholar
Schneider, S., Nebel, S., Pradel, S., & Rey, G. D. (2015a). Mind your Ps and Qs! How polite instructions affect learning with multimedia. Computers in Human Behavior, 51, 546–555.CrossRefGoogle Scholar
Schneider, S., Nebel, S., Pradel, S., & Rey, G. D. (2015b). Introducing the familiarity mechanism: A unified explanatory approach for the personalization effect and the examination of youth slang in multimedia learning. Computers in Human Behavior, 43, 129–138.CrossRefGoogle Scholar
Schrader, C., Reichelt, M., & Zander, S. (2018). The effect of the personalization principle on multimedia learning: The role of student individual interests as a predictor. Educational Technology Research and Development, 66(6), 1387–1397.CrossRefGoogle Scholar
van Gog, T., Verveer, I., & Verveer, L. (2014). Learning from video modeling examples: Effects of seeing the human model’s face. Computers & Education, 72, 323–327.CrossRefGoogle Scholar
van Wermeskerken, M., Grimmius, B., & van Gog, T. (2018). Attention to the model’s face when learning from video modeling examples in adolescents with and without autism spectrum disorder. Journal of Computer Assisted Learning, 34(1), 32–41.CrossRefGoogle Scholar
van Wermeskerken, M., Ravensbergen, S., & van Gog, T. (2018). Effects of instructor presence in video modeling examples on attention and learning. Computers in Human Behavior, 89, 430–438.CrossRefGoogle Scholar
Wang, F., Li, W., Mayer, R. E., & Liu, H. (2018). Animated pedagogical agents as aids in multimedia learning: Effects on eye-fixations during learning and learning outcomes. Journal of Educational Psychology, 110(2), 250–268.CrossRefGoogle Scholar
Wang, J., & Antonenko, P. D. (2017). Instructor presence in instructional video: Effects on visual attention, recall, and perceived learning. Computers in Human Behavior, 71, 79–89.CrossRefGoogle Scholar
Wang, N., Johnson, W. L., Mayer, R. E., Rizzo, P., Shaw, E., & Collins, H. (2008). The politeness effect: Pedagogical agents and learning outcomes. International Journal of Human–Computer Studies, 66, 98–112.CrossRefGoogle Scholar
Wilson, K. E., Martinez, M., Mills, C., D’Mello, S., Smilek, D., & Risko, E. F. (2018). Instructor presence effect: Liking does not always lead to learning. Computers & Education, 122, 205–220.CrossRefGoogle Scholar
Yung, H. I., & Paas, F. (2015). Effects of cueing by a pedagogical agent in an instructional animation: A cognitive load approach. Journal of Educational Technology & Society, 18(3), 153–160.Google Scholar
Zander, S., Wetzel, S., Kühl, T., & Bertel, S. (2017). Underlying processes of an inverted personalization effect in multimedia learning – An eye-tracking study. Frontiers in Psychology, 8, 2202.CrossRefGoogle ScholarPubMed

References

Agostinho, S., Tindall-Ford, S., Ginns, P., Howard, S. J., Leahy, W., & Paas, F. (2015). Giving learning a helping hand: Finger tracing of temperature graphs on an iPad. Educational Psychology Review, 27(3), 427–443.CrossRefGoogle Scholar
Alibali, M. W., & Nathan, M. J. (2012). Embodiment in mathematics teaching and learning: Evidence from learners’ and teachers’ gestures. Journal of the Learning Sciences, 21(2), 247–286.CrossRefGoogle Scholar
Ayres, P., Marcus, N., Chan, C., & Qian, N. (2009). Learning hand manipulative tasks: When instructional animations are superior to equivalent static representations. Computers in Human Behavior, 25(2), 348–353.CrossRefGoogle Scholar
Barrett, T. J., Stull, A. T., Hsu, T. M., & Hegarty, M. (2015). Constrained interactivity for relating multiple representations in science: When virtual is better than real. Computers & Education, 81, 69–81.CrossRefGoogle Scholar
Barsalou, L. W. (2008). Grounded cognition. Annual Review of Psychology, 59, 617–645.CrossRefGoogle ScholarPubMed
Broaders, S. C., Cook, S. W., Mitchell, Z., & Goldin-Meadow, S. (2007). Making children gesture brings out implicit knowledge and leads to learning. Journal of Experimental Psychology: General, 136(4), 539–550.CrossRefGoogle ScholarPubMed
Brooks, N., & Goldin‐Meadow, S. (2016). Moving to learn: How guiding the hands can set the stage for learning. Cognitive Science, 40(7), 1831–1849.CrossRefGoogle ScholarPubMed
Boucheix, J. M., & Forestier, C. (2017). Reducing the transience effect of animations does not (always) lead to better performance in children learning a complex hand procedure. Computers in Human Behavior, 69, 358–370.CrossRefGoogle Scholar
Boucheix, J. M., Gauthier, P., Fontaine, J. B., & Jaffeux, S. (2018). Mixed camera viewpoints improve learning medical hand procedure from video in nurse training? Computers in Human Behavior, 89, 418–429.CrossRefGoogle Scholar
Carbonneau, K. J., Marley, S. C., & Selig, J. P. (2013). A meta-analysis of the efficacy of teaching mathematics with concrete manipulatives. Journal of Educational Psychology, 105(2), 380.CrossRefGoogle Scholar
Castro-Alonso, J. C., Ayres, P., & Paas, F. (2014). Learning from observing hands in static and animated versions of non-manipulative tasks. Learning and Instruction, 34, 11–21.CrossRefGoogle Scholar
Castro-Alonso, J. C., Ayres, P., & Paas, F. (2016). Comparing apples and oranges? A critical look at research on learning from statics versus animations. Computers & Education, 102, 234–243.CrossRefGoogle Scholar
Cherdieu, M., Palombi, O., Gerber, S., Troccaz, J., & Rochet-Capellan, A. (2017). Make gestures to learn: Reproducing gestures improves the learning of anatomical knowledge more than just seeing gestures. Frontiers in Psychology, 8, 1689.CrossRefGoogle ScholarPubMed
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
Cook, S. W., Duffy, R. G., & Fenn, K. M. (2013). Consolidation and transfer of learning after observing hand gesture. Child Development, 84(6), 1863–1871.CrossRefGoogle ScholarPubMed
Cook, S. W., Mitchell, Z., & Goldin-Meadow, S. (2008). Gesturing makes learning last. Cognition, 106(2), 1047–1058.CrossRefGoogle ScholarPubMed
de Koning, B. B., & Tabbers, H. K. (2011). Facilitating understanding of movements in dynamic visualizations: An embodied perspective. Educational Psychology Review, 23(4), 501–521.CrossRefGoogle Scholar
de Koning, B. B., & Tabbers, H. K. (2013). Gestures in instructional animations: A helping hand to understanding non‐human movements? Applied Cognitive Psychology, 27(5), 683–689.Google Scholar
de Koning, B. B., Tabbers, H. K., Rikers, R. M., & Paas, F. (2010). Attention guidance in learning from a complex animation: Seeing is understanding? Learning and Instruction, 20(2), 111–122.CrossRefGoogle Scholar
Du, X., & Zhang, Q. (2019). Tracing worked examples: Effects on learning in geometry. Educational Psychology, 39(2), 169–187.CrossRefGoogle Scholar
Fiorella, L., & Mayer, R. E. (2015). Learning As a Generative Activity. New York: Cambridge University Press.CrossRefGoogle Scholar
Fiorella, L., & Mayer, R. E. (2016a). Eight ways to promote generative learning. Educational Psychology Review, 28(4), 717–741.CrossRefGoogle Scholar
Fiorella, L., & Mayer, R. E. (2016b). Effects of observing the instructor draw diagrams on learning from multimedia messages. Journal of Educational Psychology, 108(4), 528.CrossRefGoogle Scholar
Fiorella, L., Stull, A. T., Kuhlmann, S., & Mayer, R. E. (2019). Instructor presence in video lectures: The role of dynamic drawings, eye contact, and instructor visibility. Journal of Educational Psychology, 111(7), 1162.CrossRefGoogle Scholar
Fiorella, L., Stull, A. T., Kuhlmann, S., & Mayer, R. E. (2020). Fostering generative learning from video lessons: Benefits of instructor-generated drawings and learner-generated explanations. Journal of Educational Psychology, 112(5), 895–906.CrossRefGoogle Scholar
Fiorella, L., van Gog, T., Hoogerheide, V., & Mayer, R. E. (2017). It’s all a matter of perspective: Viewing first-person video modeling examples promotes learning of an assembly task. Journal of Educational Psychology, 109, 653–665.CrossRefGoogle Scholar
Fujimura, N. (2001). Facilitating children’s proportional reasoning: A model of reasoning processes and effects of intervention on strategy change. Journal of Educational Psychology, 93(3), 589–603.CrossRefGoogle Scholar
Fyfe, E. R., McNeil, N. M., Son, J. Y., & Goldstone, R. L. (2014). Concreteness fading in mathematics and science instruction: A systematic review. Educational Psychology Review, 26(1), 9–25.CrossRefGoogle Scholar
Ganier, F., & de Vries, P. (2016). Are instructions in video format always better than photographs when learning manual techniques? The case of learning how to do sutures. Learning and Instruction, 44, 87–96.CrossRefGoogle Scholar
Garland, T. B., & Sanchez, C. A. (2013). Rotational perspective and learning procedural tasks from dynamic media. Computers & Education, 69, 31–37.CrossRefGoogle Scholar
Ginns, P., Hu, F. T., Byrne, E., & Bobis, J. (2016). Learning by tracing worked examples. Applied Cognitive Psychology, 30(2), 160–169.CrossRefGoogle Scholar
Glenberg, A. M. (2008). Embodiment for education. In Calvo, P., & Gamila, T. (eds.), Handbook of Cognitive Science (pp. 355–372). Amsterdam: Elsevier.CrossRefGoogle Scholar
Glenberg, A. M., Goldberg, A. B., & Zhu, X. (2011). Improving early reading comprehension using embodied CAI. Instructional Science, 39(1), 27–39.CrossRefGoogle Scholar
Glenberg, A. M., Gutierrez, T., Levin, J. R., Japuntich, S., & Kaschak, M. P. (2004). Activity and imagined activity can enhance young children’s reading comprehension. Journal of Educational Psychology, 96(3), 424–436.CrossRefGoogle Scholar
Glenberg, A. M., & Kaschak, M. P. (2002). Grounding language in action. Psychonomic Bulletin & Review, 9(3), 558–565.CrossRefGoogle ScholarPubMed
Glenberg, A. M., Witt, J. K., & Metcalfe, J. (2013). From the revolution to embodiment: 25 years of cognitive psychology. Perspectives on Psychological Science, 8(5), 573–585.CrossRefGoogle ScholarPubMed
Goldin-Meadow, S., Cook, S. W., & Mitchell, Z. A. (2009). Gesturing gives children new ideas about math. Psychological Science, 20(3), 267–272.CrossRefGoogle ScholarPubMed
Goldin‐Meadow, S., Levine, S. C., Zinchenko, E., Yip, T. K., Hemani, N., & Factor, L. (2012). Doing gesture promotes learning a mental transformation task better than seeing gesture. Developmental Science, 15(6), 876–884.CrossRefGoogle ScholarPubMed
Höffler, T. N., & Leutner, D. (2007). Instructional animation versus static pictures: A meta-analysis. Learning and Instruction, 17(6), 722–738.CrossRefGoogle Scholar
Hu, F. T., Ginns, P., & Bobis, J. (2015). Getting the point: Tracing worked examples enhances learning. Learning and Instruction, 35, 85–93.CrossRefGoogle Scholar
Johnson-Glenberg, M. C., Birchfield, D. A., Tolentino, L., & Koziupa, T. (2014). Collaborative embodied learning in mixed reality motion-capture environments: Two science studies. Journal of Educational Psychology, 106(1), 86–104.CrossRefGoogle Scholar
Kontra, C., Lyons, D. J., Fischer, S. M., & Beilock, S. L. (2015). Physical experience enhances science learning. Psychological Science, 26(6), 737–749.CrossRefGoogle ScholarPubMed
Korbach, A., Ginns, P., Brünken, R., & Park, B. (2020). Should learners use their hands for learning? Results from an eye‐tracking study. Journal of Computer Assisted Learning, 36(1), 102–113.CrossRefGoogle Scholar
Lakoff, G., & Johnson, M. (1980). Metaphors We Live By. Chicago, IL: University of Chicago Press.Google Scholar
Laski, E. V., & Siegler, R. S. (2014). Learning from number board games: You learn what you encode. Developmental Psychology, 50(3), 853–864.CrossRefGoogle ScholarPubMed
Leopold, C., Mayer, R. E., & Dutke, S. (2019). The power of imagination and perspective in learning from science text. Journal of Educational Psychology, 111(5), 793–808.CrossRefGoogle Scholar
Lindgren, R. (2012). Generating a learning stance through perspective-taking in a virtual environment. Computers in Human Behavior, 28(4), 1130–1139.CrossRefGoogle Scholar
Macken, L., & Ginns, P. (2014). Pointing and tracing gestures may enhance anatomy and physiology learning. Medical Teacher, 36(7), 596–601.CrossRefGoogle ScholarPubMed
Marley, S. C., Levin, J. R., & Glenberg, A. M. (2010). What cognitive benefits does an activity-based reading strategy afford young Native American readers? The Journal of Experimental Education, 78(3), 395–417.CrossRefGoogle Scholar
Marley, S. C., & Szabo, Z. (2010). Improving children’s listening comprehension with a manipulation strategy. The Journal of Educational Research, 103(4), 227–238.CrossRefGoogle Scholar
Marley, S. C., Szabo, Z., Levin, J. R., & Glenberg, A. M. (2011). Investigation of an activity-based text-processing strategy in mixed-age child dyads. The Journal of Experimental Education, 79(3), 340–360.CrossRefGoogle Scholar
Martin, T., & Schwartz, D. L. (2005). Physically distributed learning: Adapting and reinterpreting physical environments in the development of fraction concepts. Cognitive Science, 29(4), 587–625.CrossRefGoogle ScholarPubMed
Mayer, R. E., & DaPra, C. S. (2012). An embodiment effect in computer-based learning with animated pedagogical agents. Journal of Experimental Psychology: Applied, 18(3), 239–252.Google ScholarPubMed
Mayer, R. E., Hegarty, M., Mayer, S., & Campbell, J. (2005). When static media promote active learning: Annotated illustrations versus narrated animations in multimedia instruction. Journal of Experimental Psychology: Applied, 11(4), 256.Google ScholarPubMed
McNeil, N. M., & Fyfe, E. R. (2012). “Concreteness fading” promotes transfer of mathematical knowledge. Learning and Instruction, 22(6), 440–448.CrossRefGoogle Scholar
McNeil, N. M., Uttal, D. H., Jarvin, L., & Sternberg, R. J. (2009). Should you show me the money? Concrete objects both hurt and help performance on mathematics problems. Learning and Instruction, 19(2), 171–184.CrossRefGoogle Scholar
Novack, M. A., Congdon, E. L., Hemani-Lopez, N., & Goldin-Meadow, S. (2014). From action to abstraction: Using the hands to learn math. Psychological Science, 25(4), 903–910.CrossRefGoogle Scholar
Novack, M., & Goldin-Meadow, S. (2015). Learning from gesture: How our hands change our minds. Educational Psychology Review, 27(3), 405–412.CrossRefGoogle ScholarPubMed
Olympiou, G., & Zacharia, Z. C. (2012). Blending physical and virtual manipulatives: An effort to improve students’ conceptual understanding through science laboratory experimentation. Science Education, 96(1), 21–47.CrossRefGoogle 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
Paas, F., & 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(1), 27–45.CrossRefGoogle Scholar
Padalkar, S., & Hegarty, M. (2015). Models as feedback: Developing representational competence in chemistry. Journal of Educational Psychology, 107(2), 451–467.CrossRefGoogle Scholar
Post, L. S., van Gog, T., Paas, F., & Zwaan, R. A. (2013). Effects of simultaneously observing and making gestures while studying grammar animations on cognitive load and learning. Computers in Human Behavior, 29(4), 1450–1455.CrossRefGoogle Scholar
Pouw, W. T., van Gog, T., & Paas, F. (2014). An embedded and embodied cognition review of instructional manipulatives. Educational Psychology Review, 26(1), 51–72.CrossRefGoogle Scholar
Schroeder, N. L., & Traxler, A. L. (2017). Humanizing instructional videos in physics: When less is more. Journal of Science Education and Technology, 26(3), 269–278.CrossRefGoogle Scholar
Sepp, S., Howard, S. J., Tindall-Ford, S., Agostinho, S., & Paas, F. (2019). Cognitive load theory and human movement: Towards an integrated model of working memory. Educational Psychology Review, 31, 293–317.CrossRefGoogle Scholar
Siegler, R. S., & Ramani, G. B. (2009). Playing linear number board games – but not circular ones – improves low-income preschoolers’ numerical understanding. Journal of Educational Psychology, 101(3), 545.CrossRefGoogle Scholar
Singer, M. A., & Goldin-Meadow, S. (2005). Children learn when their teacher’s gestures and speech differ. Psychological Science, 16(2), 85–89.CrossRefGoogle ScholarPubMed
Sommerville, J. A., Woodward, A. L., & Needham, A. (2005). Action experience alters 3-month-old infants’ perception of others’ actions. Cognition, 96(1), B1–B11.CrossRefGoogle ScholarPubMed
Stull, A. T., Gainer, M. J., & Hegarty, M. (2018). Learning by enacting: The role of embodiment in chemistry education. Learning and Instruction, 55, 80–92.CrossRefGoogle Scholar
Stull, A. T., & Hegarty, M. (2016). Model manipulation and learning: Fostering representational competence with virtual and concrete models. Journal of Educational Psychology, 108(4), 509–527.CrossRefGoogle Scholar
Stull, A. T., Hegarty, M., Dixon, B., & Stieff, M. (2012). Representational translation with concrete models in organic chemistry. Cognition and Instruction, 30(4), 404–434.CrossRefGoogle Scholar
Tang, M., Ginns, P., & Jacobson, M. J. (2019). Tracing enhances recall and transfer of knowledge of the water cycle. Educational Psychology Review, 31(2), 439–455.CrossRefGoogle Scholar
Türkay, S. (2016). The effects of whiteboard animations on retention and subjective experiences when learning advanced physics topics. Computers & Education, 98, 102–114.CrossRefGoogle Scholar
Uttal, D. H., Scudder, K. V., & DeLoache, J. S. (1997). Manipulatives as symbols: A new perspective on the use of concrete objects to teach mathematics. Journal of Applied Developmental Psychology, 18(1), 37–54.CrossRefGoogle Scholar
Valenzeno, L., Alibali, M. W., & Klatzky, R. (2003). Teachers’ gestures facilitate students’ learning: A lesson in symmetry. Contemporary Educational Psychology, 28(2), 187–204.CrossRefGoogle Scholar
van Gog, T., Paas, F., Marcus, N., Ayres, P., & Sweller, J. (2009). The mirror neuron system and observational learning: Implications for the effectiveness of dynamic visualizations. Educational Psychology Review, 21(1), 21–30.CrossRefGoogle Scholar
van Wermeskerken, M., Fijan, N., Eielts, C., & Pouw, W. T. (2016). Observation of depictive versus tracing gestures selectively aids verbal versus visual–spatial learning in primary school children. Applied Cognitive Psychology, 30(5), 806–814.CrossRefGoogle 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.CrossRefGoogle Scholar
Wakefield, E. M., Congdon, E. L., Novack, M. A., Goldin-Meadow, S., & James, K. H. (2019). Learning math by hand: The neural effects of gesture-based instruction in 8-year-old children. Attention, Perception, & Psychophysics, 81(7), 2343–2353.CrossRefGoogle ScholarPubMed
Willingham, D. T. (2017). Ask the cognitive scientist: Do manipulatives help students learn? American Educator, 6(2017), 7.Google Scholar
Wilson, M. (2002). Six views of embodied cognition. Psychonomic Bulletin & Review, 9(4), 625–636.CrossRefGoogle ScholarPubMed
Wittrock, M. C. (1989). Generative processes of comprehension. Educational Psychologist, 24(4), 345–376.CrossRefGoogle Scholar
Wong, A., Marcus, N., Ayres, P., Smith, L., Cooper, G. A., Paas, F., & Sweller, J. (2009). Instructional animations can be superior to statics when learning human motor skills. Computers in Human Behavior, 25(2), 339–347.CrossRefGoogle Scholar

References

Alhalabi, W. (2016). Virtual reality systems enhance students’ achievements in engineering education. Behaviour & Information Technology, 35(11), 919–925.CrossRefGoogle Scholar
Baceviciute, S., Mottelson, A., Terkildsen, T., & Makransky, G. (2020). Investigating representation of text and audio in educational VR using learning outcomes and EEG. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (CHI’20) (pp. 1–9). New York: ACM.Google Scholar
Baceviciute, S., Terkildsen, T. S., & Makransky, G. (in press). Investigating the Redundancy Principle in Immersive Virtual Reality Environments: An Eye-tracking and EEG Study. Journal of Computer Assisted Learning.Google Scholar
Bailenson, J. (2018). Experience on Demand: What Vrtual Reality Is, How it Works, and What it Can Do. New York: Norton & Company.Google Scholar
Barfield, W., Zeltzer, D., Sheridan, T. B., & Slater, M. (1995). Presence and performance within virtual environments. In Barfield, W., & Furness, T. A. (eds.), Virtual Environments and Advanced Interface Design (pp. 473–541). Oxford: Oxford University Press.CrossRefGoogle Scholar
Checa, D., & Bustillo, A. (2020). A review of immersive virtual reality serious games to enhance learning and training. Multimedia Tools and Applications, 79(9), 5501–5527.CrossRefGoogle Scholar
Chittaro, L., & Buttussi, F. (2015). Assessing knowledge retention of an immersive serious game vs. a traditional education method in aviation safety. IEEE Transactions on Visualization and Computer Graphics, 21(4), 529–538.CrossRefGoogle Scholar
Cummings, J. J., & Bailenson, J. N. (2016). How immersive is enough? A meta-analysis of the effect of immersive technology on user presence. Media Psychology, 19(2), 272–309.CrossRefGoogle Scholar
Dalgarno, B., & Lee, M. J. W. (2010). What are the learning affordances of 3-D virtual environments? British Journal of Educational Technology, 41(1), 10–32.CrossRefGoogle Scholar
Ferguson, C., van den Broek, E. L., & van Oostendorp, H. (2020). On the role of interaction mode and story structure in virtual reality serious games. Computers & Education, 143, 1–10.CrossRefGoogle Scholar
Jensen, L., & Konradsen, F. (2018). A review of the use of virtual reality head-mounted displays in education and training. Education and Information Technologies, 23(4), 1515–1529.CrossRefGoogle Scholar
Johnson-Glenberg, M. C. (2019). The necessary nine: Design principles for embodied VR and active stem education. In Díaz, P., Ioannou, A., Bhagat, K., & Spector, J. (eds.), Learning in a Digital World. Smart Computing and Intelligence (pp. 83–112). Singapore: Springer.CrossRefGoogle Scholar
Klingenberg, S., Jørgensen, M. L., Dandanell, G., Skriver, K., Mottelson, A., & Makransky, G. (2020). Investigating the effect of teaching as a general learning strategy when learning through desktop and immersive VR: A media and methods experiment. British Journal of Educational Technology, 51(6), 2115–2138.CrossRefGoogle Scholar
Leahy, W., & Sweller, J. (2011). Cognitive load theory, modality of presentation and the transient information effect. Applied Cognitive Psychology, 25(6), 943–951.CrossRefGoogle Scholar
Lee, E. A.-L., Wong, K. W., & Fung, C. C. (2010). How does desktop virtual reality enhance learning outcomes? A structural equation modeling approach. Computers and Education, 55(4), 1424–1442.Google Scholar
Makransky, G., Andreasen, N. K, Baceviciute, S., & Mayer, R. M. (2020). Immersive virtual reality increases liking but not learning with a science simulation and generative learning strategies promote learning in immersive virtual reality. Journal of Educational Psychology. DOI: 10.1037/edu0000473.CrossRefGoogle Scholar
Makransky, G., Borre-Gude, S., & Mayer, R. E. (2019). Motivational and cognitive benefits of training in immersive virtual reality based on multiple assessments. Journal of Computer Assisted Learning, 35(6), 691–707.CrossRefGoogle Scholar
Makransky, G., & Lilleholt, L. (2018). A structural equation modeling investigation of the emotional value of immersive virtual reality in education. Educational Technology Research and Development, 66, 1141–1164.CrossRefGoogle Scholar
Makransky, G., Mayer, R., Nøremølle, A., Cordoba, A. L., Wandall, J., & Bonde, M. (2020). Investigating the feasibility of using assessment and explanatory feedback in desktop virtual reality simulations. Educational Technology Research and Development, 68(1), 293–317.CrossRefGoogle Scholar
Makransky, G., & Petersen, G. B. (2019). Investigating the process of learning with desktop virtual reality: A structural equation modeling approach. Computers & Education, 134, 15–30.CrossRefGoogle Scholar
Makransky, G., & Petersen, G. B. (2021). The Cognitive Affective Model of Immersive Learning (CAMIL): A theoretical research-based model of learning in immersive virtual reality. Educational Psychology Review, DOI: 10.1007/s10648-020-09586-2.CrossRefGoogle 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.CrossRefGoogle Scholar
Makransky, G., Wismer, P., & Mayer, R. E. (2019). A gender matching effect in learning with pedagogical agents in an immersive virtual reality science simulation. Journal of Computer Assisted Learning, 35(3), 349–358.CrossRefGoogle Scholar
Marsh, T., & Smith, S. P. (2001). Guiding user navigation in virtual environments using awareness of virtual off-screen space. In Proceedings of the Workshop on Guiding Users through Interactive Experiences – Usability Centred Design and Evaluation of Virtual 3D Environments, 149–154.Google Scholar
Mayer, R. E. (2014). Principles based on social cues in multimedia learning: Personalization, voice, image, and embodiment principles. In Mayer, R. E. (ed.), The Cambridge Handbook of Multimedia Learning (2nd ed., pp. 345–370). New York: Cambridge University Press.CrossRefGoogle Scholar
Meyer, O. A., Omdahl, M. K., & Makransky, G. (2019). Investigating the effect of pre-training when learning through immersive virtual reality and video: A media and methods experiment. Computers & Education, 140, 1–17.CrossRefGoogle Scholar
Mikropoulos, T. A., & Natsis, A. (2011). Educational virtual environments: A ten- year review of empirical research (1999–2009). Computers and Education, 56(3), 769–780.CrossRefGoogle Scholar
Moreno, R., & Mayer, R. E. (2002). Learning science in virtual reality multimedia environments: Role of methods and media. Journal of Educational Psychology, 94(3), 598–610.CrossRefGoogle Scholar
Moreno, R., & Mayer, R. E. (2004). Personalized messages that promote science learning in virtual environments. Journal of Educational Psychology, 96(1), 165–173.CrossRefGoogle Scholar
Parong, J., & Mayer, R. E. (2018). Learning science in immersive virtual reality. Journal of Educational Psychology, 110, 785–797.CrossRefGoogle Scholar
Pedaste, M., Mäeots, M., Siiman, L. A., de Jong, T., van Riesen, S. A. N., Kamp, E. T., Manoli, C. C., Zacharia, Z. C., & Tsourlidaki, E. (2015). Phases of inquiry-based learning: Definitions and the inquiry cycle. Educational Research Review, 14, 47–61.CrossRefGoogle Scholar
Pekrun, R. (2006). The control-value theory of achievement emotions: Assumptions, corollaries, and implications for educational research and practice. Educational Psychology Review, 18(4), 315–341.CrossRefGoogle Scholar
Petersen, G. B., Klingenberg, S., Mayer, R. E., & Makransky, G. (2020). The virtual field trip: Investigating how to optimize immersive virtual learning in climate change education. British Journal of Educational Technology, 51(6), 2099–2115.CrossRefGoogle Scholar
Rothe, S., & Hußmann, H. (2018). Guiding the viewer in cinematic virtual reality by diegetic cues. In International Conference on Augmented Reality, Virtual Reality and Computer Graphics (pp. 101–117). Cham: Springer.CrossRefGoogle Scholar
Slater, M., & Wilbur, S. (1997). A framework for immersive virtual environments (FIVE): Speculations on the role of presence in virtual environments. Presence: Teleoperators & Virtual Environments, 6(6), 603–616.CrossRefGoogle Scholar
Snelson, C., & Hsu, Y. C. (2020). Educational 360-degree videos in virtual reality: A scoping review of the emerging research. TechTrends, 64, 404–412.CrossRefGoogle Scholar
Terkildsen, T. S., & Makransky, G. (2019). Measuring presence in video games: An investigation of the potential use of physiological measures as indicators of presence. International Journal of Human Computer Studies, 126, 64–80.CrossRefGoogle Scholar
van der Heijden, H. (2004). User acceptance of hedonic information systems. MIS Quarterly, 28(4), 695–704.CrossRefGoogle Scholar
Webster, R. (2016). Declarative knowledge acquisition in immersive virtual learning environments. Interactive Learning Environments, 24(6), 1319–1333.CrossRefGoogle Scholar
Wu, B.., Yu, X., & Gu, X. (2020). Effectiveness of immersive virtual reality using head-mounted displays on learning performance: A meta-analysis. British Journal of Educational Technology, 51(6), 1991–2005.CrossRefGoogle Scholar

References

Aronson, E., Blaney, N., Stephan, C., Sikes, J., & Snapp, M. (1978). The Jigsaw Classroom. Beverly Hills, CA: Sage.Google Scholar
Asterhan, C. S. C., & Schwarz, B. B. (2016). Argumentation for learning: Well-trodden paths and unexplored territories. Educational Psychologist, 51(2), 164–187.CrossRefGoogle Scholar
Atkinson, R. K., Derry, S. J., Renkl, A., & Wortham, D. (2000). Learning from examples: Instructional principles from the worked examples research. Review of Educational Research, 70(2), 181–214.CrossRefGoogle Scholar
Barron, B. (2003). When smart groups fail. Journal of the Learning Sciences, 12(3), 307–359.CrossRefGoogle Scholar
Buchs, C., & Butera, F. (2009). Is a partner’s competence threatening during dyadic cooperative work? It depends on resource interdependence. European Journal of Psychology of Education, 24, 145–154.CrossRefGoogle Scholar
Chen, J., Wang, M., Kirschner, P. A., & Tsai, C.-C. (2018). The role of collaboration, computer use, learning environments, and supporting strategies in CSCL: A meta-analysis. Review of Educational Research, 88(6), 799–843.CrossRefGoogle Scholar
Ciborra, C., & Olson, M. H. (1988). Encountering electronic work groups: A transaction costs perspective. In Proceedings of the 1988 ACM Conference on Computer-Supported Cooperative Work (pp. 94–101). Portland, OR: ACM.Google Scholar
Ellis, C. A., Gibbs, S. J., & Rein, G. (1992). Groupware: Some issues and experiences. In Marca, D., & Bock, G. (eds.), Groupware: Software for Computer-Supported Cooperative Work (pp. 23–43). Los Alamitos, CA: IEEE Computer Society Press.Google Scholar
Erkens, M., & Bodemer, D. (2019). Improving collaborative learning: Guiding knowledge exchange through the provision of information about learning partners and learning contents. Computers & Education, 128, 452–472.CrossRefGoogle Scholar
Fiorella, L., & Mayer, R. E. (2014). Role of expectations and explanations in learning by teaching. Contemporary Educational Psychology, 39(2), 75–85.CrossRefGoogle Scholar
Fitzsimons, G. M., Finkel, E. J., & vanDellen, M. R. (2015). Transactive goal dynamics. Psychological Review, 122(4), 648–673.CrossRefGoogle ScholarPubMed
Hinsz, V. B., Tindale, R. S., & Vollrath, D. A. (1997). The emerging conceptualization of groups as information processors. Psychological Bulletin, 121(1), 43–64.CrossRefGoogle ScholarPubMed
Hollingshead, A. B. (2001). Cognitive interdependence and convergent expectations in transactive memory. Journal of Personality and Social Psychology, 81(6), 1080–1089.CrossRefGoogle ScholarPubMed
Janssen, J., Erkens, G., Kanselaar, G., & Jaspers, J. (2007). Visualization of participation: Does it contribute to successful computer-supported collaborative learning? Computers & Education, 49(4), 1037–1065.CrossRefGoogle Scholar
Janssen, J., Erkens, G., Kirschner, P. A., & Kanselaar, G. (2012). Task-related and social regulation during online collaborative learning. Metacognition and Learning, 7, 25–43.CrossRefGoogle Scholar
Janssen, J., Kirschner, F., Erkens, G., Kirschner, P. A., & Paas, F. (2010). Making the black box of collaborative learning transparent: Combining process-oriented and cognitive load approaches. Educational Psychology Review, 22, 139–154.CrossRefGoogle Scholar
Janssen, J., & Kirschner, P. A. (2020). Applying collaborative cognitive load theory to computer-supported collaborative learning: Towards a research agenda. Educational Technology Research and Development, 68, 783–805.CrossRefGoogle Scholar
Järvelä, S., Kirschner, P. A., Panadero, E., Malmberg, J., Phielix, C., Jaspers, J., Koivuniemi, M., & Järvenoja, H. (2015). Enhancing socially shared regulation in collaborative learning groups: Designing for CSCL regulation tools. Educational Technology Research and Development, 63, 125–142.CrossRefGoogle Scholar
Johnson, D. W., & Johnson, R. T. (2009). An educational psychology success story: Social interdependence theory and cooperative learning. Educational Researcher, 38, 365–379.CrossRefGoogle Scholar
Johnson, D. W., & Johnson, R. T. (2014). Using technology to revolutionize cooperative learning: An opinion. Frontiers in Psychology, 5, 1156.CrossRefGoogle Scholar
Johnson, D. W., Johnson, R. T., & Stanne, M. B. (1989). Impact of goal and resource interdependence on problem-solving success. The Journal of Social Psychology, 129(5), 621–629.CrossRefGoogle Scholar
Kalyuga, S., Chandler, P., & Sweller, J. (1998). Levels of expertise and instructional design. Human Factors: The Journal of the Human Factors and Ergonomics Society, 40(1), 1–17.CrossRefGoogle Scholar
Kirschner, F., Paas, F., & Kirschner, P. A. (2009a). A cognitive-load approach to collaborative learning: United brains for complex tasks. Educational Psychology Review, 21, 31–42.CrossRefGoogle Scholar
Kirschner, F., Paas, F., & Kirschner, P. A. (2009b). Individual and group-based learning from complex cognitive tasks: Effects on retention and transfer efficiency. Computers in Human Behavior, 25(2), 306–314.CrossRefGoogle Scholar
Kirschner, F., Paas, F., & Kirschner, P. A. (2011). Task complexity as a driver for collaborative learning efficiency: The collective working-memory effect. Applied Cognitive Psychology, 25, 615–624.CrossRefGoogle Scholar
Kirschner, F., Paas, F., Kirschner, P. A., & Janssen, J. (2011). Differential effects of problem-solving demands on individual and collaborative learning outcomes. Learning and Instruction, 21(4), 587–599.CrossRefGoogle Scholar
Kirschner, P. A., & Erkens, G. (2013). Toward a framework for CSCL research. Educational Psychologist, 48(1), 1–8.CrossRefGoogle Scholar
Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educational Psychologist, 41(2), 75–86.CrossRefGoogle Scholar
Kirschner, P. A., Sweller, J., Kirschner, F., & Zambrano, R. J. (2018). From cognitive load theory to collaborative cognitive load theory. International Journal of Computer-Supported Collaborative Learning, 13, 213–233.CrossRefGoogle ScholarPubMed
Le, H., Janssen, J., & Wubbels, T. (2018). Collaborative learning practices: Teacher and student perceived obstacles to effective student collaboration. Cambridge Journal of Education, 48, 103–122.CrossRefGoogle Scholar
Lou, Y., Abrami, P., Spence, J., Poulsen, C., Chambers, B., & d’Apollonia, S. (1996). Within-class grouping: A meta-analysis. Review of Educational Research, 66, 423–458.CrossRefGoogle Scholar
Malone, T. W., & Crowston, K. (1992). What is coordination theory and how can it help design cooperative work systems? In Marca, D., & Bock, G. (eds.), Groupware: Software for Computer-Supported Cooperative Work (pp. 100–113). Los Alamitos, CA: IEEE Computer Society Press.Google Scholar
Mayer, R. E. (2004). Should there be a three-strikes rule against pure discovery learning? American Psychologist, 59(1), 14–19.CrossRefGoogle ScholarPubMed
Mayer, R. E. (2008). Applying the science of learning: Evidence-based principles for the design of multimedia instruction. American Psychologist, 63(8), 760–769.CrossRefGoogle ScholarPubMed
Mayer, R. E. (2017). Using multimedia for e-learning. Journal of Computer Assisted Learning, 33(5), 403–423.CrossRefGoogle Scholar
Nokes-Malach, T. J., Zepeda, C. D., Richey, E., & Gadgil, S. (2019). Collaborative learning: The benefits and costs. In Dunlosky, J., & Rawson, K. A. (eds.), The Cambridge Handbook of Cognition and Learning (pp. 500–527). Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Noroozi, O., Teasley, S. D., Biemans, H. J. A., Weinberger, A., & Mulder, M. (2013). Facilitating learning in multidisciplinary groups with transactive CSCL scripts. International Journal of Computer-Supported Collaborative Learning, 8, 189–223.CrossRefGoogle Scholar
Peterson, A. T., & Roseth, C. J. (2016). Effects of four CSCL strategies for enhancing online discussion forums: Social interdependence, summarizing, scripts, and synchronicity. International Journal of Educational Research, 76, 147–161.CrossRefGoogle Scholar
Popov, V., van Leeuwen, A., & Buijs, S. C. A. (2017). Are you with me or not? Temporal synchronicity and transactivity during CSCL. Journal of Computer Assisted Learning, 33(5), 424–442.CrossRefGoogle Scholar
Retnowati, E., Ayres, P., & Sweller, J. (2017). Can collaborative learning improve the effectiveness of worked examples in learning mathematics? Journal of Educational Psychology, 109(5), 666–679.CrossRefGoogle Scholar
Roseth, C. J., Johnson, D. W., & Johnson, R. T. (2008). Promoting early adolescents’ achievement and peer relationships: The effects of cooperative, competitive, and individualistic goal structures. Psychological Bulletin, 134, 223–246.CrossRefGoogle ScholarPubMed
Roseth, C. J., Lee, Y. K., & Saltarelli, W. A. (2019). Reconsidering Jigsaw social psychology: Longitudinal effects on social interdependence, sociocognitive conflict regulation, motivation, and achievement. Journal of Educational Psychology, 111(1), 149–169.CrossRefGoogle Scholar
Slof, B., van Leeuwen, A., Janssen, J., & Kirschner, P. A. (2021). Mine, ours, and yours: Whose engagement and prior knowledge affects individual achievement from online collaborative learning? Journal of Computer Assisted Learning, 37, 39–50.CrossRefGoogle Scholar
Stodolsky, S. S. (1984). Frameworks for studying instructional processes in peer work-groups. In Peterson, P. L., Wilkinson, L. C., & Hallinan, M. (eds.), The Social Context of Instruction: Group Organization and Group Processes (pp. 107–124). Orlando, FL: Academic Press.Google Scholar
Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12, 257–285.CrossRefGoogle Scholar
Sweller, J. (2010). Element interactivity and intrinsic, extraneous and germane cognitive load. Educational Psychology Review, 22, 123–138.CrossRefGoogle Scholar
Teasley, S. D., & Roschelle, J. (1993). Constructing a joint problem space: The computer as a tool for sharing knowledge. In Lajoie, S. P. (ed.), Computers as Cognitive Tools: Technology in Education (pp. 229–258). Hillsdale, NJ: Lawrence Erlbaum Associates Inc.Google Scholar
Tindale, R. S., & Kameda, T. (2000). Social sharedness as a unifying theme for information processing in groups. Group Processes & Intergroup Relations, 3, 123–140.CrossRefGoogle Scholar
van den Bossche, P., Gijselaers, W., Segers, M., Woltjer, G., & Kirschner, P. (2011). Team learning: Building shared mental models. Instructional Science, 39, 283–301.CrossRefGoogle Scholar
Webb, N. M. (2013). Information processing approaches to collaborative learning. In Hmelo-Silver, C. E., Chinn, C. A., Chan, C. K. K., & O’Donnell, A. M. (eds.), The International Handbook of Collaborative Learning (pp. 19–40). New York: Routledge.Google Scholar
Webb, N. M., & Farivar, S. (1994). Promoting helping-behavior in cooperative small-groups in middle school mathematics. American Educational Research Journal, 31(2), 369–395.CrossRefGoogle Scholar
Webb, N. M., & Farivar, S. (1999). Developing productive group interaction in middle school mathematics. In O’Donnell, A., & King, A. (eds.), Cognitive Perspectives on Peer Learning (pp. 117–149). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
Webb, N. M., & Mastergeorge, A. (2003). Promoting effective helping behavior in peer-directed groups. International Journal of Educational Research, 39, 73–97.CrossRefGoogle Scholar
Webb, N. M., Troper, J., & Fall, R. (1995). Constructive activity and learning in collaborative small-groups. Journal of Educational Psychology, 87(3), 406–423.CrossRefGoogle Scholar
Wegner, D. M. (1987). Transactive memory: A contemporary analysis of the group mind. In Mullen, B., & Goethals, G. R. (eds.), Theories of Group Behavior (pp. 185–208). Berlin: Springer-Verlag.CrossRefGoogle Scholar
Wegner, D. M. (1995). A computer network model of human transactive memory. Social Cognition, 13(3), 319–339.CrossRefGoogle Scholar
Wittrock, M. C. (1989). Generative processes of comprehension. Educational Psychologist, 24(4), 345–376.CrossRefGoogle Scholar
Yamane, D. (1996). Collaboration and its discontents: Steps toward overcoming barriers to successful group projects. Teaching Sociology, 24(4), 378–383.CrossRefGoogle Scholar
Zambrano, J. R., Kirschner, F., Sweller, J., & Kirschner, P. A. (2019a). Effects of group experience and information distribution on collaborative learning. Instructional Science, 47(5), 531–550.CrossRefGoogle Scholar
Zambrano, J. R., Kirschner, F., Sweller, J., & Kirschner, P. A. (2019b). Effects of prior knowledge on collaborative and individual learning. Learning and Instruction, 63, 101214.CrossRefGoogle Scholar
Zhang, L., Kalyuga, S., Lee, C., Lei, C., & Jiao, J. (2015). Effectiveness of collaborative learning with complex tasks under different learning group formations: A cognitive load perspective. In Cheung, S., Kwok, L., Yang, H., Fong, J., & Kwan, R. (eds.), Hybrid Learning: Innovation in Educational Practices (pp. 149–159). Berlin: Springer.CrossRefGoogle Scholar

References

Alpizar, D., Adesope, O. O., & Wong, R.M. (2020). A meta-analysis of signaling principle in multimedia learning environments. Education Technology Research and Development, 68, 2095–2119.CrossRefGoogle Scholar
Berney, S., & Bétrancourt, M. (2016). Does animation enhance learning? A meta-analysis. Computers & Education, 101, 150-167.CrossRefGoogle Scholar
Biard, N., Cojean, S., & Jamet, E. (2018). Effects of segmentation and pacing on procedural learning by video. Computers in Human Behavior, 89, 411–417.CrossRefGoogle 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, 123–135.CrossRefGoogle 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
Castro-Alonzo, J. C., Wong, M., Adesope, O. O., & Ayres, P. (2019). Gender imbalance in instructional dynamic versus static visualizations: A meta-analysis. Educational Psychology Review, 31, 361–387.CrossRefGoogle Scholar
de Koning, B. B., & Tabbers, H. K. (2013). Gestures in instructional animations: A helping hand to understanding non-human movements? Applied Cognitive Psychology, 1(27), 683–689.Google Scholar
de Koning, B. B., Tabbers, H. K., Rijkers, R. M. P. J., & Paas, F. (2010a). Attention cueing in an instructional animation: The role of presentation speed. Computers in Human Behavior, 27, 41–45.CrossRefGoogle Scholar
de Koning, B. B., Tabbers, H. K., Rijkers, R. M. J. P., & Paas, F. (2010b). Attention guidance in learning from a complex animation: Seeing is understanding? Learning and Instruction, 20, 111–122.CrossRefGoogle Scholar
de Koning, B. B., Tabbers, H. K., Rijkers, R. M. J. P., & Paas, F. (2011). Improved effectiveness of cueing by self‐explanations when learning from a complex animation. Applied Cognitive Psychology, 25, 183–194.CrossRefGoogle Scholar
Fischer, S., Lowe, R. K., & Schwan, S. (2008). Effects of presentation speed of a dynamic visualization on the understanding of a mechanical system. Applied Cognitive Psychology, 22, 1126–1141.CrossRefGoogle Scholar
Höffler, T. N., & Leutner, D. (2007). Instructional animation versus static pictures: A meta-analysis. Learning and Instruction, 17, 722–738.CrossRefGoogle Scholar
Lowe, R. K., & Boucheix, J.-M. (2008). Learning from animated diagrams: How are mental models built? In Stapleton, G., Howse, J., & Lee, J. (eds.), Diagrammatic Representation and Inference (pp. 266–281). Berlin: Springer.CrossRefGoogle Scholar
Lowe, R. K., & Boucheix, J.-M. (2010). Manipulatable models for investigating processing of dynamic diagrams. In Goel, A. K., Jamnik, M., & Narayanan, N. H. (eds.), Diagrammatic Representation and Inference (pp. 319–321). Berlin: Springer.CrossRefGoogle Scholar
Lowe, R. K., & Boucheix, J.-M. (2011). Cueing complex animation: Does direction of attention foster learning processes? Learning and Instruction, 21, 650–663.CrossRefGoogle Scholar
Lowe, R. K., & Boucheix, J.-M. (2012a). Dynamic diagrams: A composition alternative. In Cox, P., Plimmer, B., & Rogers, P. (eds.), Diagrammatic Representation and Inference (pp. 233–240). Berlin: Springer.CrossRefGoogle Scholar
Lowe, R. K., & Boucheix, J-M. (2012b). Addressing challenges of biological animations. In de Vries, E., & Scheiter, K. (eds.), Proceedings of the Meeting of the EARLI Special Interest Group on Comprehension of Text and Graphics (pp. 217–129). Grenoble: University of Grenoble.Google Scholar
Lowe, R. K., & Boucheix, J. M. (2016). Principled animation design improves comprehension of complex dynamics. Learning and Instruction, 45, 72–84.CrossRefGoogle Scholar
Lowe, R.K., & Boucheix, J-M. (2020). Improving animations: Compositional anti-cueing makes conventional designs more effective. Paper presented at EARLI SIG2, Comprehension of Text and Graphics. Charles University, Prague, Czech Republic. Online Conference, August 31–September 2.Google Scholar
Lowe, R. K., Boucheix, J. M., & Menant, M. (2018). Perceptual processing and the comprehension of relational information in dynamic diagrams. In Chapman, P., Stapleton, G., Moktefi, A., Perez-Kriz, S., & Bellucci, F. (eds.), Diagrammatic Representation and Inference, LNAI, Lecture Notes in Artificial Intelligence, 10871 (pp. 470–483). Cham: Springer.Google Scholar
Meyer, K., Rasch, T., & Schnotz, W. (2010). Effects of animation’s speed of presentation on perceptual processing and learning. Learning and Instruction, 20, 136–145.CrossRefGoogle Scholar
Mierowsky, R., Marcus, N., & Ayres, P. (2019). Using mimicking gestures to improve observational learning from instructional videos. Educational Psychology, 40, 1–20.Google Scholar
Neisser, U. (1976). Cognition and Reality. San Francisco, CA: Freeman.Google Scholar
Ploetzner, R., Berney, S., & Bétrancourt, M. (2020). A review of learning demands in instructional animations: The educational effectiveness of animations unfolds if the features of change need to be learned. Journal of Computer Assisted Learning, 36(6), 838–860.CrossRefGoogle Scholar
Ploetzner, R., & Fillisch, B. (2017). Not the silver bullet: Learner-generated drawings make it difficult to understand broader spatiotemporal structures in complex animations. Learning and Instruction, 47, 13–24.CrossRefGoogle Scholar
Post, L. S., van Gog, T., Paas, F., & Zwaan, R. A. (2013). Effects of simultaneously observing and making gestures while studying grammar animations on cognitive load and learning. Computers in Human Behavior, 29, 1450–1455.CrossRefGoogle Scholar
Rey, G. D., Beege, M., Nebel, S., Wirzberger, M., Schmitt, T. H., & Schneider, S. (2019). A meta-analysis of the segmenting effect. Educational Psychology Review, 31, 389–419.CrossRefGoogle 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.CrossRefGoogle Scholar
Scheiter, K. (2014). The learner control principle in multimedia learning. In Mayer, R. E. (ed.), The Cambridge Handbook of Multimedia Learning (2nd ed., pp. 487–512). New York: Cambridge University Press.CrossRefGoogle 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.CrossRefGoogle Scholar
Schwan, S., & Riempp, R. (2004). The cognitive benefits of interactive videos: Learning to tie nautical knots. Learning and Instruction, 14, 293–305.CrossRefGoogle Scholar
Sepp, S., Agostinho, S., Tindall-Ford, S., & Paas, F (in press). To trace or not to trace? Meaningful gesture for learning geometry using touch-based multimedia learning materials.Google Scholar
Spanjers, I. A. E., van Gog, T., & van Merrienboer, J. J. G. (2010). A theoretical analysis of how segmentation of dynamic visualizations optimizes students’ learning. Educational Psychology Review, 22, 411–423.CrossRefGoogle Scholar
Spanjers, I. A. E., Wouters, P., van Gog, T., & van Merriënboer, J. J. G. (2011). An expertise reversal effect of segmentation in learning from animated worked-out examples, Computers in Human Behavior, 27(1), 46–52.CrossRefGoogle Scholar
Stull, A. T., Gainer, M. J., & Hegarty, M. (2018). Learning by enacting: The role of embodiment in chemistry education. Learning and Instruction, 55, 80–92.CrossRefGoogle Scholar
Ullman, S. (1984). Visual routines. Cognition, 18, 97–159.CrossRefGoogle ScholarPubMed
van Gog, T., Paas, F., Marcus, N., Ayres, P., & Sweller, J. (2009). The mirror neuron system and observational learning: Implications for the effectiveness of dynamic visualizations. Educational Psychology Review, 21, 21–30.CrossRefGoogle Scholar
van Meter, P., & Garner, J. (2005). The promise and practice of learner-generated drawing: Literature review and synthesis. Educational Psychology Review, 17, 285–325.CrossRefGoogle Scholar
Wong, A., Leahy, W., Marcus, N., & Sweller, J. (2012). Cognitive load theory, the transient information effect and e-learning. Learning and Instruction, 22, 449–457.CrossRefGoogle Scholar
Zacks, J. M., & Tversky, B. (2001). Event structure in perception and conception. Psychological Bulletin, 127, 3–21.CrossRefGoogle ScholarPubMed

References

Ainley, M., Hidi, S., & Berndorff, D. (2002). Interest, learning, and the psychological processes that mediate their relationship. Journal of Educational Psychology, 94(3), 545–561.CrossRefGoogle Scholar
Astleitner, H., & Leutner, D. (2014). Designing instructional technology from an emotional perspective. Journal of Research on Computing in Education, 32, 497–510.CrossRefGoogle Scholar
Baker, R. S., D’Mello, S. K., Rodrigo, M. M. T., & Graesser, A. C. (2010). Better to be frustrated than bored: The incidence, persistence, and impact of learners’ cognitive–affective states during interactions with three different computer-based learning environments. International Journal of Human–Computer Studies, 68(4), 223–241.CrossRefGoogle Scholar
Beilock, S. L., Kulp, C. A., Holt, L. E., & Carr, T. H. (2004). More on the fragility of performance: Choking under pressure in mathematical problem solving. Journal of Experimental Psychology: General, 133(4), 584–600.CrossRefGoogle ScholarPubMed
Bianchi-Berthouze, N., Kim, W. W., & Patel, D. (2007). Does body movement engage you more in digital game play? and why? In International Conference on Affective Computing and Intelligent Interaction (pp. 102–113). Berlin: Springer.CrossRefGoogle Scholar
Biles, M. L., Plass, J., & Homer, B. D. (2018). Designing digital badges for educational games: The impact of badge type on student motivation and learning. International Journal of Gaming and Computer-Mediated Simulations, 10(4), 1–19.CrossRefGoogle Scholar
Bradley, M. M., & Lang, P. J. (1994). Measuring emotion: The self-assessment manikin and the semantic differential. Journal of Behavior Therapy and Experimental Psychiatry, 25(1), 49–59.CrossRefGoogle ScholarPubMed
Bradley, M. M., & Lang, P. J. (2000). Affective reactions to acoustic stimuli. Psychophysiology, 37(2), 204–215.CrossRefGoogle ScholarPubMed
Brom, C., Děchtěrenko, F., Frollová, N., Stárková, T., Bromová, E., & D’Mello, S. K. (2017). Enjoyment or involvement? Affective-motivational mediation during learning from a complex computerized simulation. Computers & Education, 114, 236–254.CrossRefGoogle Scholar
Brom, C., Starkova, T., & D’Mello, S. K. (2018). How effective is emotional design? A meta-analysis on facial anthropomorphisms and pleasant colors during multimedia learning. Educational Research Review, 25, 100–119.CrossRefGoogle Scholar
Chung, S., & Cheon, J. (2020). Emotional design of multimedia learning using background images with motivational cues. Journal of Computer Assisted Learning, 36(6), 922–932.CrossRefGoogle Scholar
Chung, S., Cheon, J., & Lee, K. W. (2015). Emotion and multimedia learning: An investigation of the effects of valence and arousal on different modalities in an instructional animation. Instructional Science, 43(5), 545–559.CrossRefGoogle Scholar
Derryberry, D., & Tucker, D. M. (1994). Motivating the focus of attention. In Niedenthal, P. M., & Kitayama, S. (eds.), The Heart’s Eye: Emotional Influences in Perception and Attention (pp. 167–196). San Diego, CA: Academic Press.CrossRefGoogle Scholar
D’Mello, S., & Graesser, A. (2011). The half-life of cognitive-affective states during complex learning. Cognition & Emotion, 25(7), 1299–1308.CrossRefGoogle ScholarPubMed
D’Mello, S., & Graesser, A. (2012). Dynamics of affective states during complex learning. Learning and Instruction, 22(2), 145–157.CrossRefGoogle Scholar
D’Mello, S., & Graesser, A. (2013). AutoTutor and affective AutoTutor: Learning by talking with cognitively and emotionally intelligent computers that talk back. ACM Transactions on Interactive Intelligent Systems (TiiS), 2(4), 1–39.Google Scholar
D’Mello, S., Lehman, B., Pekrun, R., & Graesser, A. (2014). Confusion can be beneficial for learning. Learning and Instruction, 29, 153–170.CrossRefGoogle Scholar
Eerola, T., Friberg, A., & Bresin, R. (2013). Emotional expression in music: Contribution, linearity, and additivity of primary musical cues. Frontiers in Psychology, 4, 487.CrossRefGoogle ScholarPubMed
Endres, T., Weyreter, S., Renkl, A., & Eitel, A. (2020). When and why does emotional design foster learning? Evidence for situational interest as a mediator of increased persistence. Journal of Computer Assisted Learning, 36(4), 514–525.CrossRefGoogle Scholar
Fraser, K., Ma, I., Teteris, E., Baxter, H., Wright, B., & McLaughlin, K. (2012). Emotion, cognitive load and learning outcomes during simulation training. Medical Education, 46(11), 1055–1062.CrossRefGoogle ScholarPubMed
Gatti, E., Calzolari, E., Maggioni, E., & Obrist, M. (2018). Emotional ratings and skin conductance response to visual, auditory and haptic stimuli. Scientific Data, 5, 180120.CrossRefGoogle ScholarPubMed
Graesser, A. C. (2019). Emotions are the experiential glue of learning environments in the 21st century. Learning and Instruction, 70, 101212.CrossRefGoogle Scholar
Graesser, A. C., & D’Mello, S. (2012). Emotions during the learning of difficult material. In Ross, B. H. (ed.), Psychology of Learning and Motivation (Vol. 57, pp. 183–225). Cambridge, MA: Academic Press.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.CrossRefGoogle Scholar
Hasler, B. S., Kersten, B., & Sweller, J. (2007). Learner control, cognitive load and instructional animation. Applied Cognitive Psychology, 21(6), 713–729.CrossRefGoogle Scholar
Heidig, S., Müller, J., & Reichelt, M. (2015). Emotional design in multimedia learning: Differentiation on relevant design features and their effects on emotions and learning. Computers in Human Behavior, 44, 81–95.CrossRefGoogle Scholar
Homer, B. D., Plass, J. L., Rose, M. C., MacNamara, A., Pawar, S., & Ober, T. M. (2019). Activating adolescents’ “hot” executive functions in a digital game to train cognitive skills: The effects of age and prior abilities. Cognitive Development, 49, 20–32.CrossRefGoogle Scholar
Isbister, K. (2016). How Games Move Us: Emotion by Design. Cambridge, MA: MIT Press.CrossRefGoogle Scholar
Isen, A. M., Daubman, K. A., & Nowicki, G. P. (1987). Positive affect facilitates creative problem solving. Journal of Personality and Social Psychology, 52(6), 1122.CrossRefGoogle ScholarPubMed
Isen, A. M., Shalker, T. E., Clark, M., & Karp, L. (1978). Affect, accessibility of material in memory, and behavior: A cognitive loop? Journal of Personality and Social Psychology, 36(1), 1–12.CrossRefGoogle ScholarPubMed
Izard, C. E. (2007). Basic emotions, natural kinds, emotion schemas, and a new paradigm. Perspectives on Psychological Science, 2, 260–280.CrossRefGoogle Scholar
Izard, C. E. (2009). Emotion theory and research: Highlights, unanswered questions, and emerging issues. Annual Review of Psychology, 60, 1–25.CrossRefGoogle ScholarPubMed
Kalyuga, S. (2014). The expertise reversal principle in multimedia learning. In Mayer, R. E. (ed.), The Cambridge Handbook of Multimedia Learning (pp. 576–597). New York: Cambridge University Press.CrossRefGoogle Scholar
Knörzer, L., Brünken, R., & Park, B. (2016a). Facilitators or suppressors: Effects of experimentally induced emotions on multimedia learning. Learning and Instruction, 44, 97–107.CrossRefGoogle Scholar
Knörzer, L., Brünken, R., & Park, B. (2016b). Emotions and multimedia learning: The moderating role of learner characteristics. Journal of Computer Assisted Learning, 32(6), 618–631.CrossRefGoogle Scholar
Kühl, T., Moersdorf, F., Römer, M., & Münzer, S. (2019). Adding emotionality to seductive details – Consequences for learning? Applied Cognitive Psychology, 33(1), 48–61.CrossRefGoogle Scholar
Laird, J. D., Wagener, J. J., Halal, M., & Szegda, M. (1982). Remembering what you feel: Effects of emotion on memory. Journal of Personality and Social Psychology, 42(4), 646.CrossRefGoogle Scholar
Lang, P. J., Bradley, M. M., & Cuthbert, B. N. (1990). Emotion, attention, and the startle reflex. Psychological Review, 97(3), 377.CrossRefGoogle ScholarPubMed
Le, Y., Liu, J., Deng, C., & Dai, D. Y. (2018). Heart rate variability reflects the effects of emotional design principle on mental effort in multimedia learning. Computers in Human Behavior, 89, 40–47.CrossRefGoogle Scholar
Lewis, M. D. (1995). Cognition-emotion feedback and the self-organization of developmental paths. Human Development, 38, 71–102.CrossRefGoogle Scholar
Li, J., Luo, C., Zhang, Q., & Shadiev, R. (2020). Can emotional design really evoke emotion in multimedia learning? International Journal of Educational Technology in Higher Education, 17, 1–18.CrossRefGoogle Scholar
Loderer, K., Pekrun, R., & Lester, J. C. (2020). Beyond cold technology: A systematic review and meta-analysis on emotions in technology-based learning environments. Learning and instruction, 70, 101162.CrossRefGoogle Scholar
Loderer, K., Pekrun, R., & Plass, J.L. (2020). Emotional foundations of game-based learning. In Plass, J. L., Mayer, R. E., & Homer, B. D. (eds.), Handbook of Game-based Learning (pp. 111–151). Cambridge, MA: MIT Press.Google Scholar
Lorenz, K. (1950). Ganzheit und Teil in der tierischen und menschlichen Gemeinschaft [Part and Parcel in Animal and Human Societies]. Studium Generale, 3(9), 455–499.CrossRefGoogle Scholar
Magner, U. I., Schwonke, R., Aleven, V., Popescu, O., & Renkl, A. (2014). Triggering situational interest by decorative illustrations both fosters and hinders learning in computer-based learning environments. Learning and instruction, 29, 141–152.CrossRefGoogle Scholar
Mayer, R. E. (2005). Cognitive theory of multimedia learning. In Mayer, R. E. (ed.), The Cambridge Handbook of Multimedia Learning (p. 31–48). New York: Cambridge University Press.CrossRefGoogle Scholar
Mayer, R. E. (2020a). Multimedia Learning (3rd ed.). New York: Cambridge University Press.CrossRefGoogle Scholar
Mayer, R. E. (2020b). Searching for the role of emotions in e-learning. Learning and Instruction, 70, 101213.CrossRefGoogle Scholar
Mayer, R. E., & Estrella, G. (2014). Benefits of emotional design in multimedia instruction. Learning and Instruction, 33, 12–18.CrossRefGoogle Scholar
Moreno, R., & Mayer, R. (2007). Interactive multimodal learning environments. Educational Psychology Review, 19(3), 309–326.CrossRefGoogle Scholar
Münchow, H., & Bannert, M. (2019). Feeling good, learning better? Effectivity of an emotional design procedure in multimedia learning. Educational Psychology, 39(4), 530–549.CrossRefGoogle Scholar
Münchow, H., Mengelkamp, C., & Bannert, M. (2017). The better you feel the better you learn: Do warm colours and rounded shapes enhance learning outcome in multimedia learning? Education Research International, 2017(2), 1–15.CrossRefGoogle Scholar
Navratil, S. D., Kühl, T., & Heidig, S. (2018). Why the cells look like that – the influence of learning with emotional design and elaborative interrogations. Frontiers in Psychology, 9, 1653.CrossRefGoogle ScholarPubMed
Paivio, A. (2007). Mind and Its Evolution: A Dual Coding Theoretical Approach. Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
Paivio, A. (2013). Dual coding theory, word abstractness, and emotion: A critical review of Kousta et al. (2011). Journal of Experimental Psychology: General, 142(1), 282–287.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.CrossRefGoogle Scholar
Park, B., Knörzer, L., Plass, J. L., & Brünken, R. (2015). Emotional design and positive emotions in multimedia learning: An eyetracking study on the use of anthropomorphisms. Computers & Education, 86, 30–42.CrossRefGoogle Scholar
Pawar, S., Tam, F., & Plass, J. L. (2020). Emerging design factors in game-Bbased learning: Emotional design, musical score, and game mechanics design. In Plass, J. L., Mayer, R. E., & Homer, B. D. (eds.), Handbook of Game-based Learning (pp. 347–365). Cambridge, MA: MIT Press.Google Scholar
Pekrun, R. (2006). The control-value theory of achievement emotions: Assumptions, corollaries, and implications for educational research and practice. Educational Psychology Review, 18, 315–341.CrossRefGoogle Scholar
Pekrun, R., & Linnenbrink-Garcia, L. (eds.) (2014). International Handbook of Emotions in Education. New York: Routledge.CrossRefGoogle Scholar
Pessoa, L. (2008). On the relationship between emotion and cognition. Nature Reviews Neuroscience, 9(2), 148–158.CrossRefGoogle ScholarPubMed
Phelps, E. A. (2004). Human emotion and memory: Interactions of the amygdala and hippocampal complex. Current Opinion in Neurobiology, 14(2), 198–202.CrossRefGoogle ScholarPubMed
Plass, J. L., Heidig, S., Hayward, E. O., Homer, B. D., & Um, E. (2014). Emotional design in multimedia learning: Effects of shape and color on affect and learning. Learning and Instruction, 29, 128–140.CrossRefGoogle Scholar
Plass, J. L., Homer, B. D., Hayward, E. O., Frye, J., Huang, T. T., Biles, M., Stein, M., & Perlin, K. (2012). The effect of learning mechanics design on learning outcomes in a computer-based geometry game. E-Learning and Games for Training, Education, Health and Sports. Lecture Notes in Computer Science, 7516, 65–71.CrossRefGoogle Scholar
Plass, J. L., Homer, B. D., & Kinzer, C. K. (2015). Foundations of game-based learning. Educational Psychologist, 50(4), 258–283.CrossRefGoogle Scholar
Plass, J. L., Homer, B. D., MacNamara, A., Ober, T., Rose, M. C., Hovey, C. M., Pawar, S., & Olsen, A. (2019). Emotional design for digital games for learning: The affective quality of expression, color, shape, and dimensionality of game characters. Learning and Instruction, 70, 101194.CrossRefGoogle Scholar
Plass, J. L., Homer, B. D., Pawar, S., & Tam, F. (2018). Connecting theory and design through research: Cognitive skills training games. In Göbel, S., Garcia-Agundez, A., Tregel, T., Ma, M., Hauge, J. B., Oliveira, M., Marsh, T., & Caserman, P. (eds.), Serious Games. JCSG 2018. Lecture Notes in Computer Science (vol 11243). Cham: Springer.Google Scholar
Plass, J. L., & Kalyuga, S. (2019). Four ways of considering emotion in cognitive load theory. Educational Psychology Review, 31, 339–359.CrossRefGoogle Scholar
Plass, J. L., & Kaplan, U. (2016). Emotional design in digital media for learning. In Tettegah, S., & Gartmeier, M. (eds.), Emotions, Technology, Design, and Learning (pp. 131–161). New York: Elsevier.CrossRefGoogle Scholar
Plass, J. L., Mayer, R. E., & Homer, B. D. (eds.) (2020). Handbook of Game-Based Learning. Cambridge, MA: MIT Press.Google Scholar
Plass, J. L., Moreno, R., & Brünken, R. (eds.) (2010). Cognitive Load Theory. New York: Cambridge University Press.CrossRefGoogle Scholar
Plass, J. L., O’Keefe, P., Homer, B. D., Hayward, E. O., Stein, M, & Perlin, K. (2013). Motivational and cognitive outcomes associated with individual, competitive, and collaborative game play. Journal of Educational Psychology, 4, 1050–1066.CrossRefGoogle Scholar
Riva, G., Mantovani, F., Capideville, C. S., Preziosa, A., Morganti, F., Villani, D., … Alcañiz, M. (2007). Affective interactions using virtual reality: The link between presence and emotions. CyberPsychology & Behavior, 10(1), 45–56.CrossRefGoogle ScholarPubMed
Rop, G., van Wermeskerken, M., de Nooijer, J. A., Verkoeijen, P. P., & van Gog, T. (2018). Task experience as a boundary condition for the negative effects of irrelevant information on learning. Educational Psychology Review, 30(1), 229–253.CrossRefGoogle Scholar
Russell, J. A. (2003). Core affect and the psychological construction of emotion. Psychological Review, 110(1), 145.CrossRefGoogle ScholarPubMed
Sabourin, J., Mott, B., & Lester, J. C. (2011). Modeling learner affect with theoretically grounded dynamic Bayesian networks. In International Conference on Affective Computing and Intelligent Interaction (pp. 286–295). Berlin: Springer.CrossRefGoogle Scholar
Salminen, K., Rantala, J., Laitinen, P., Interactive, A., Surakka, V., Lylykangas, J., & Raisamo, R. (2009). Emotional responses to haptic stimuli in laboratory versus travelling by bus contexts. In 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops, Amsterdam (pp. 1–7). New York: IEEE.Google Scholar
Salminen, K., Surakka, V., Lylykangas, J., Raisamo, J., Saarinen, R., Raisamo, R., … & Evreinov, G. (2008). Emotional and behavioral responses to haptic stimulation. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Florence, Italy (pp. 1555–1562). New York: ACM.CrossRefGoogle Scholar
Schneider, S., Nebel, S., Beege, M., & Rey, G. D. (2018). Anthropomorphism in decorative pictures: Benefit or harm for learning? Journal of Educational Psychology, 110(2), 218.CrossRefGoogle Scholar
Schneider, S., Nebel, S., & Rey, G. D. (2016). Decorative pictures and emotional design in multimedia learning. Learning and Instruction, 44, 65–73.CrossRefGoogle Scholar
Stark, L., Brünken, R., & Park, B. (2018). Emotional text design in multimedia learning: A mixed-methods study using eye tracking. Computers & Education, 120, 185–196.CrossRefGoogle Scholar
Stark, L., Malkmus, E., Stark, R., Brünken, R., & Park, B. (2018). Learning-related emotions in multimedia learning: An application of control-value theory. Learning and Instruction, 58, 42–52.CrossRefGoogle Scholar
Stevenson, R. A., & James, T. W. (2008). Affective auditory stimuli: Characterization of the International Affective Digitized Sounds (IADS) by discrete emotional categories. Behavior Research Methods, 40(1), 315–321.CrossRefGoogle ScholarPubMed
Sweller, J., Ayres, P., & Kalyuga, S. (2011). Cognitive Load Theory. New York: Springer.CrossRefGoogle Scholar
Tajadura-Jiménez, A., Väljamäe, A., Asutay, E., & Västfjäll, D. (2010). Embodied auditory perception: The emotional impact of approaching and receding sound sources. Emotion, 10(2), 216.CrossRefGoogle ScholarPubMed
Taub, M., Azevedo, R., Rajendran, R., Cloude, E. B., Biswas, G., & Price, M. J. (2019). How are students’ emotions related to the accuracy of cognitive and metacognitive processes during learning with an intelligent tutoring system? Learning and Instruction, 72, 101200.CrossRefGoogle 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.CrossRefGoogle Scholar
Uzun, A. M., & Yıldırım, Z. (2018). Exploring the effect of using different levels of emotional design features in multimedia science learning. Computers & Education, 119, 112–128.CrossRefGoogle Scholar
Västfjäll, D. (2003). The subjective sense of presence, emotion recognition, and experienced emotions in auditory virtual environments. CyberPsychology & Behavior, 6(2), 181–188.CrossRefGoogle ScholarPubMed
Vuoskoski, J. K., Gatti, E., Spence, C., & Clarke, E. F. (2016). Do visual cues intensify the emotional responses evoked by musical performance? A psychophysiological investigation. Psychomusicology: Music, Mind, and Brain, 26(2), 179.CrossRefGoogle Scholar
Watson, D., & Clark, L. A. (1999). The PANAS-X: Manual for the Positive and Negative Affect Schedule-Expanded Form. Available from https://ir.uiowa.edu/cgi/viewcontent.cgi?article=1011&context=psychology_pubs (last accessed May 7, 2017).Google Scholar
Wolfson, S., & Case, G. (2000). The effects of sound and colour on responses to a computer game. Interacting with Computers, 13(2), 183–192.CrossRefGoogle Scholar
Wong, R. M., and Adesope, O. O. (2020). Meta-analysis of emotional designs in multimedia learning: A replication and extension study. Educational Psychology Review, 33, 357–385.CrossRefGoogle Scholar
Yoo, Y., Yoo, T., Kong, J., & Choi, S. (2015). Emotional responses of tactile icons: Effects of amplitude, frequency, duration, and envelope. In 2015 IEEE World Haptics Conference (WHC), Chicago, IL (pp. 235–240). New York: IEEE.Google Scholar
Zhong, B., Qin, Z., Yang, S., Chen, J., Mudrick, N., Taub, M., Azevedo, R., & Lobaton, E. (2017). Emotion recognition with facial expressions and physiological signals. In 2017 IEEE Symposium Series on Computational Intelligence (SSCI), McLean, VA (pp. 1–8). New York: IEEE.Google Scholar