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Part VIII - Multimedia Learning with Media

Published online by Cambridge University Press:  19 November 2021

Richard E. Mayer
Affiliation:
University of California, Santa Barbara
Logan Fiorella
Affiliation:
University of Georgia
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Print publication year: 2021

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References

References

Aleven, V., & Koedinger, K. R. (2002). An effective metacognitive strategy: Learning by doing and explaining with a computer-based Cognitive Tutor. Cognitive Science, 26(2), 147179.CrossRefGoogle Scholar
Aleven, V., & Koedinger, K. R. (2013). Knowledge component approaches to learner modeling. In Sottilare, R., Graesser, A., Hu, X., & Holden, H. (eds.), Design Recommendations for Adaptive Intelligent Tutoring Systems (Learner Modeling, 1, pp. 165182). Orlando, FL: US Army Research Laboratory.Google Scholar
Aleven, V., McLaren, B. M., Roll, I., & Koedinger, K. R. (2016). Help helps, but only so much: Research on help seeking with intelligent tutoring systems. International Journal of Artificial Intelligence in Education, 26(1), 205223.CrossRefGoogle Scholar
Aleven, V., McLaren, B. M., Sewall, J., van Velsen, M., Popescu, O., Demi, S., Ringenberg, M., & Koedinger, K. R. (2016). Example-tracing tutors: Intelligent tutor development for non-programmers. International Journal of Artificial Intelligence in Education, 26(1), 224269.CrossRefGoogle Scholar
Aleven, V., McLaughlin, E. A., Glenn, R. A., & Koedinger, K. R. (2017). Instruction based on adaptive learning technologies. In Mayer, R. E., & Alexander, P. (eds.), Handbook of Research on Learning and Instruction (2nd ed., pp. 522560). New York: Routledge.Google Scholar
Anderson, J. R., Conrad, F. G., & Corbett, A. T. (1989). Skill acquisition and the LISP tutor. Cognitive Science, 13(4), 467505.CrossRefGoogle Scholar
Anderson, J. R., Corbett, A. T., Koedinger, K., & Pelletier, R. (1995). Cognitive tutors: Lessons learned. The Journal of Learning Sciences, 4, 167207.CrossRefGoogle Scholar
Baker, R. S. J. D., Corbett, A. T., & Koedinger, K. R. (2007). The difficulty factors approach to the design of lessons in intelligent tutor curricula. International Journal of Artificial Intelligence in Education, 17(4), 341369.Google Scholar
Butcher, K., & Aleven, V. (2013). Using student interactions to foster rule-diagram mapping during problem solving in an intelligent tutoring system. Journal of Educational Psychology, 105(4), 9881009.CrossRefGoogle Scholar
Carvalho, P. F., & Goldstone, R. L. (2014). Putting category learning in order: Category structure and temporal arrangement affect the benefit of interleaved over blocked study. Memory & Cognition, 42, 481495.CrossRefGoogle ScholarPubMed
Carvalho, P. F., & Goldstone, R. L. (2019). When does interleaving practice improve learning?. In Dunlosky, J., & Rawson, K. (eds.), The Cambridge Handbook of Cognition and Education (pp. 411436). Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Chi, M. T., & Wylie, R. (2014). The ICAP framework: Linking cognitive engagement to active learning outcomes. Educational Psychologist, 49(4), 219243.CrossRefGoogle Scholar
Clark, R. E., Feldon, D., van Merriënboer, J., Yates, K., & Early, S. (2007). Cognitive task analysis. In Spector, J. M., Merrill, M. D., van Merrie¨nboer, J. J. G., & Driscoll, M. P. (eds.), Handbook of Research on Educational Communications and Technology (3rd ed., pp. 577593). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
Corbett, A. T., & Anderson, J. R. (1995). Knowledge tracing: Modeling the acquisition of procedural knowledge. User Modeling and User-Adapted Interaction, 4, 253278.CrossRefGoogle Scholar
Corbett, A. T., & Anderson, J. R. (2001). Locus of feedback control in computer-based tutoring: Impact on learning rate, achievement and attitudes. In CHI ‘01: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 245252). New York: ACM Press.CrossRefGoogle Scholar
Corbett, A. T., McLaughlin, M., & Scarpinatto, K. C. (2000). Modeling student knowledge: Cognitive Tutors in high school and college. User Modeling and User-Adapted Interaction, 10, 81108.CrossRefGoogle Scholar
Deslauriers, L., McCarty, L. S., Miller, K., Callaghan, K., & Kestin, G. (2019). Measuring actual learning versus feeling of learning in response to being actively engaged in the classroom. Proceedings of the National Academy of Sciences, 116(39), 1925119257.CrossRefGoogle ScholarPubMed
Deslauriers, L., Schelew, E., & Wieman, C. (2011). Improved learning in a large-enrollment physics class. Science, 332(603), 862864.CrossRefGoogle Scholar
Doroudi, S., Holstein, K., Aleven, V., & Brunskill, E. (2015). Towards understanding how to leverage sense-making, induction/refinement and fluency to improve robust learning. In Santos, O. C., Boticario, J. G., Romero, C., Pechenizkiy, M., Merceron, A., Mitros, P., Luna, J. M., Mihaescu, C., Moreno, P., Hershkovitz, A., Ventura, S., & Desmarais, M. (eds.), Proceedings of the 8th International Conference on Educational Data Mining, EDM 2015 (pp. 376379). Worcester, MA: International Educational Data Mining Society.Google Scholar
Ericsson, K. A., Krampe, R. T., & Tesch-Römer, C. (1993). The role of deliberate practice in the acquisition of expert performance. Psychological Review, 100(3), 363406.CrossRefGoogle Scholar
Ericsson, K. A. & Simon, H. A. (1985). Protocol analysis. In van Dijk, T. A. (ed.), Handbook of Discourse Analysis (Vol. 2; pp. 259268). London: Academic Press.Google Scholar
Fries, L., Son, J. Y., Givvin, K. B. & Stigler, J. W. (2020). Practicing connections: A framework to guide instructional design for developing understanding in complex domains. Educational Psychology Review, 33, 739762.CrossRefGoogle Scholar
Hattie, J. (2008). Visible Learning: A Synthesis of over 800 Meta-Analyses Relating to Achievement. New York: Routledge.CrossRefGoogle Scholar
Holstein, K., Aleven, V., & Rummel, N. (2020). A conceptual framework for human–AI hybrid adaptivity in education. In Bittencourt, I., Cukurova, M., Muldner, K., Luckin, R., & Millán, E. (eds.), Proceedings, 21th International Conference on Artificial Intelligence in Education, AIED 2020 (pp. 240254). Cham: Springer.Google Scholar
Holstein, K., McLaren, B. M., & Aleven, V. (2018). Student learning benefits of a mixed-reality teacher awareness tool in AI-enhanced classrooms. In Rosé, C. P., Martínez-Maldonado, R., Hoppe, H. U., Luckin, R., Mavrikis, M., Porayska-Pomsta, K., McLaren, B., & du Boulay, B. (eds.), Proceedings, 19th International Conference on Artificial Intelligence in Education, AIED 2018 (Part 1, pp. 154168). Cham: Springer.Google Scholar
Holstein, K., McLaren, B. M., & Aleven, V. (2019). Co-designing a real-time classroom orchestration tool to support teacher–AI complementarity. Journal of Learning Analytics, 6(2), 2752.CrossRefGoogle Scholar
Huang, Y., Aleven, V., McLaughlin, E., & Koedinger, K. (2020). A general multi-method approach to design-loop adaptivity in intelligent tutoring systems. Artificial Intelligence in Education: 21st International Conference, AIED 2020, Ifrane, Morocco, July 6–10, 2020, Proceedings, Part II, 12164, 124–129.CrossRefGoogle Scholar
Kalyuga, S., Chandler, P., Tuovinen, J., & Sweller, J. (2001). When problem solving is superior to studying worked examples. Journal of Educational Psychology, 93, 579588.CrossRefGoogle Scholar
Kellogg, R. T., & Whiteford, A. P. (2009). Training advanced writing skills: The case for deliberate practice. Educational Psychologist, 44, 250266.CrossRefGoogle Scholar
Kellman, P. J., & Krasne, S. (2018). Accelerating expertise: Perceptual and adaptive learning technology in medical learning. Medical Teacher, 40(8), 797802.CrossRefGoogle ScholarPubMed
Koedinger, K. R. (2002). Toward evidence for instructional design principles: Examples from Cognitive Tutor Math 6. Invited paper. In Mewborn, D., Sztajn, P., White, D. Y., Wiegel, H. G., Bryant, R. L., & Nooney, K. (eds.), Proceedings of the 24th Annual Meeting of the North American Chapter of the International Group for the Psychology of Mathematics Education (pp. 2149). Columbus, OH: ERIC Clearinghouse for Science, Mathematics, and Environmental Education.Google Scholar
Koedinger, K. R. & Aleven, V. (2007). Exploring the assistance dilemma in experiments with Cognitive Tutors. Educational Psychology Review, 19(3), 239264.CrossRefGoogle Scholar
Koedinger, K. R., & Aleven, V. (2016). An interview reflection on “intelligent tutoring goes to school in the big city.” International Journal of Artificial Intelligence in Education, 26(1), 1324.CrossRefGoogle Scholar
Koedinger, K. R., Anderson, J. R., Hadley, W. H., & Mark, M. A. (1997). Intelligent tutoring goes to school in the big city. International Journal of Artificial Intelligence in Education, 8(1), 3043.Google Scholar
Koedinger, K. R., Booth, J. L., & Klahr, D. (2013). Instructional complexity and the science to constrain it. Science, 342, 935937.CrossRefGoogle Scholar
Koedinger, K. R., & Corbett, A. T. (2006). Cognitive Tutors: Technology bringing learning sciences to the classroom. In Sawyer, R. K. (ed.), The Cambridge Handbook of the Learning Sciences (pp. 6178). New York: Cambridge University Press.Google Scholar
Koedinger, K. R., Corbett, A. C., & Perfetti, C. (2012). The Knowledge-Learning-Instruction (KLI) framework: Bridging the science-practice chasm to enhance robust student learning. Cognitive Science, 36(5), 757798.CrossRefGoogle ScholarPubMed
Koedinger, K. R. & McLaughlin, E. A. (2010). Seeing language learning inside the math: Cognitive analysis yields transfer. In Ohlsson, S., & Catrambone, R. (eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society (pp. 471476). Austin, TX: Cognitive Science Society.Google Scholar
Koedinger, K. R., & McLaughlin, E. A. (2016). Closing the loop with quantitative cognitive task analysis. In Barnes, T., Chi, M., and Feng, M. (eds.), Proceedings of the 9th International Conference on Educational Data Mining (pp. 412417). Raleigh, NC: International Conference on Educational Data Mining (EDM).Google Scholar
Koedinger, K. R., McLaughlin, E. A., & Stamper, J. C. (2012). Automated student model improvement. In Yacef, K., Zaïane, O., Hershkovitz, H., Yudelson, M., & Stamper, J. (eds.), Proceedings of the 5th International Conference on Educational Data Mining (pp. 1724). Greece: Chania.Google Scholar
Li, N., Cohen, W. W., & Koedinger, K. R. (2013). Problem order implications for learning. International Journal of Artificial Intelligence in Education, 23(1–4), 7193.CrossRefGoogle Scholar
Li, N., Matsuda, N., Cohen, W. W., and Koedinger, K. R. (2015). Integrating representation learning and skill learning in a human-like intelligent agent. Artificial Intelligence, 219, 6791.CrossRefGoogle Scholar
Liu, R., & Koedinger, K. R. (2017). Closing the loop: Automated data-driven cognitive model discoveries lead to improved instruction and learning gains. Journal of Educational Data Mining, 9(1), 2541.Google Scholar
Liu, R., Koedinger, K. R., & McLaughlin, E. A. (2014). Interpreting model discovery and testing generalization to a new dataset. In Stamper, J., Pardos, Z., Mavrikis, M., & McLaren, B. M. (eds.), Proceedings of the 7th International Conference on Educational Data Mining (pp. 107113). Worcester, MA: International Conference on Educational Data Mining.Google Scholar
Lovett, M. C. (1998). Cognitive task analysis in service of intelligent tutoring system design: A case study in statistics. In International Conference on Intelligent Tutoring Systems (pp. 234243). Berlin: Springer.CrossRefGoogle Scholar
Lovett, M. C., Meyer, O., & Thille, C. (2008). JIME-The open learning initiative: Measuring the effectiveness of the OLI statistics course in accelerating student learning. Journal of Interactive Media in Education, 2008(1), Art. 13.CrossRefGoogle Scholar
MacLellan, C. J. (2017). Computational Models of Human Learning: Applications for Tutor Development, Behavior Prediction, and Theory Testing [Doctoral Dissertation]. Human-Computer Interaction Institute, Carnegie Mellon University, Pittsburgh, PA.Google Scholar
MacLellan, C. J., Harpstead, E., Patel, R., & Koedinger, K. (2016). The apprentice learner architecture: Closing the loop between learning theory and educational data. In Proceedings of the 9th International Conference in Educational Data Mining (pp. 151158). Worcester, MA: International Educational Data Mining Society.Google Scholar
Martin, B., Mitrovic, T., Mathan, S., & Koedinger, K.R. (2011). Evaluating and improving adaptive educational systems with learning curves. User Modeling and User-Adapted Interaction: The Journal of Personalization Research (UMUAI), 21(3), 249283.CrossRefGoogle Scholar
Mathan, S. A., & Koedinger, K. R. (2005). Fostering the intelligent novice: Learning from errors with metacognitive tutoring. Educational Psychologist, 40(4), 257265.CrossRefGoogle Scholar
Mayer, R. E. (2020). Multimedia Learning (3rd ed.), New York: Cambridge University Press.CrossRefGoogle Scholar
McDaniel, M. A., Agarwal, P. K., Huelser, B. J., McDermott, K. B., & Roediger, H. L. III (2011). Test-enhanced learning in a middle school science classroom: The effects of quiz frequency and placement. Journal of Educational Psychology, 103(2), 399.CrossRefGoogle Scholar
Mitrovic, A., Ohlsson, S., & Barrow, D. K. (2013). The effect of positive feedback in a constraint-based intelligent tutoring system. Computers & Education, 60(1), 264272.CrossRefGoogle Scholar
Moreno, R. (2004). Decreasing cognitive load for novice students: Effects of explanatory versus corrective feedback in discovery‐based multimedia. Instructional Science, 32, 99113.CrossRefGoogle Scholar
Moreno, R., & Mayer, R. E. (2005). Role of guidance, reflection, and interactivity in an agent‐based multimedia game. Journal of Educational Psychology, 97, 117128.CrossRefGoogle Scholar
Nagashima, T., Bartel, A. N., Silla, E., Vest, N., Alibali, M. W., & Aleven, V. (2020). Enhancing conceptual knowledge in early algebra through scaffolding diagrammatic self-explanation. In Proceedings of International Conference of the Learning Sciences, ICLS 2020 (Part 1, pp. 3542). Nashville, TN: International Society of the Learning Sciences.Google Scholar
Ohlsson, S. (1994). Constraint based student modeling. In Greer, J. E., & McCalla, G. (eds.), Student Modelling: The Key to Individualized Knowledge-Based Instruction. NATO ASI Series (Series F: Computer and Systems Sciences) (vol. 125, pp. 167189). Berlin: Springer.CrossRefGoogle Scholar
Paas, F. G. W. C., & 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(1), 122133.CrossRefGoogle Scholar
Pane, J. F., Griffin, B. A., McCaffrey, D. F., & Karam, R. (2014). Effectiveness of cognitive tutor algebra I at scale. Educational Evaluation and Policy Analysis, 36(2), 127144.CrossRefGoogle Scholar
Patel, R. (2017). Addressing Interference in Fraction Learning: What Difficulties are Desirable? [Doctoral Dissertation]. Human-Computer Interaction Institute, Carnegie Mellon University, Pittsburgh, PA.Google Scholar
Patel, R., Liu, R., & Koedinger, K. (2016). When to block versus interleave practice? Evidence against teaching fraction addition before fraction multiplication. In Papafragou, A., Grodner, D., Mirman, D., & Trueswell, J. C. (eds.), Proceedings of the 38th Annual Conference of the Cognitive Science Society (pp. 20692074). Austin, TX: Cognitive Science Society.Google Scholar
Rau, M. A. (2017). Conditions for the effectiveness of multiple visual representations in enhancing STEM learning. Educational Psychology Review, 29(4), 717761.CrossRefGoogle Scholar
Rau, M. A., Aleven, V., & Rummel, N. (2015). Successful learning with multiple graphical representations and self-explanation prompts. Journal of Educational Psychology, 107(1), 3046.CrossRefGoogle Scholar
Ritter, S., Anderson, J. R., Koedinger, K. R., & Corbett, A. (2007). Cognitive tutor: Applied research in mathematics education. Psychonomic Bulletin & Review, 14(2), 249255.CrossRefGoogle ScholarPubMed
Roediger, H. L., and Karpicke, J. D. (2006a). Test-enhanced learning: Taking memory tests improves long-term retention. Psychological Science, 17, 249255.CrossRefGoogle ScholarPubMed
Roediger, H. L., and Karpicke, J. D. (2006b). The power of testing memory: Basic research and implications for educational practice. Perspectives on Psychological Science, 1, 181210.CrossRefGoogle ScholarPubMed
Rohrer, D. (2012). Interleaving helps students distinguish among similar concepts. Educational Psychology Review, 24, 355367.CrossRefGoogle Scholar
Rohrer, D., & Taylor, K. (2007). The shuffling of mathematics practice problems boosts learning. Instructional Science, 35, 481498.CrossRefGoogle Scholar
Roll, I., Baker, R. S. J. D., Aleven, V., & Koedinger, K. R. (2014) On the benefits of seeking (and avoiding) help in online problem- solving environments. Journal of the Learning Sciences, 23(4), 537560.CrossRefGoogle Scholar
Schnackenberg, H. L., Sullivan, H. J., Leader, L. F., & Jones, E. E. K. (1998). Learner preferences and achievement under differing amounts of learner practice. Educational Technology Research and Development, 46, 516.CrossRefGoogle Scholar
Schofield, J. W. (1995). Computers and Classroom Culture. New York: Cambridge University Press.CrossRefGoogle Scholar
Schooler, L. J., & Anderson, J. R. (1990). The disruptive potential of immediate feedback. In Piattelli-Palmarini, M. (ed.), Proceedings of the Twelfth Annual Conference of the Cognitive Science Society (pp. 702708). Hillsdale, NJ: Lawrence Erlbaum Associates, Inc.Google Scholar
Shih, B., Koedinger, K. R., & Scheines, R. (2008). A response time model for bottom-out hints as worked examples. In Proceedings of the First International Conference on Educational Data Mining, 2008, Montreal, QC, pp. 117–126.Google Scholar
Tofel-Grehl, C., & Feldon, D. F. (2013). Cognitive task analysis-based training: A meta-analysis of studies. Journal of Cognitive Engineering and Decision Making, 7(2), 293304.CrossRefGoogle Scholar
van der Kleij, F. M., Feskens, C. W. R., & Eggen, T. J. H. M. (2015). Effects of feedback in a computer‐based learning environment on students’ learning outcomes: A meta‐analysis. Review of Educational Research, 85(4), 475511.CrossRefGoogle Scholar
VanLehn, K. (2011). The relative effectiveness of human tutoring, intelligent tutoring systems, and other tutoring systems. Educational Psychologist, 46(4), 197221.CrossRefGoogle Scholar
VanLehn, K. (2016). Regulative loops, step loops and task loops. International Journal of Artificial Intelligence in Education, 26(1), 107112.CrossRefGoogle Scholar
Weitekamp, D., Harpstead, E., & Koedinger, K. R. (2020). An interaction design for machine teaching to develop AI tutors. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, April 2020, Honolulu, HI, pp. 1–11.CrossRefGoogle Scholar
Wylie, R., Sheng, M., Mitamura, T., & Koedinger, K. R. (2011). Effects of adaptive prompted self-explanation on robust learning of second language grammar. In International Conference on Artificial Intelligence in Education (pp. 588590). Berlin: Springer.CrossRefGoogle Scholar
Yannier, N., Hudson, S. E., & Koedinger, K. R. (2020). Active learning is about more than hands-on: A mixed-reality AI system to support STEM education. International Journal of Artificial Intelligence in Education, 30(1), 7496.CrossRefGoogle Scholar

References

Atkinson, R. K. (2002). Optimizing learning from examples using animated pedagogical agents. Journal of Educational Psychology, 94(2), 416427.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(1), 117139.CrossRefGoogle Scholar
Azevedo, R., Landis, R. S., Feyzi-Behnagh, R., Duffy, M., Trevors, G., Harley, J., Bouchet, F., Burlison, J., Taub, M., & Pacampara, N., Yeasin, M., Rahman, A. K. M. M., Tanveer, M. I., & Hossain, G. (2012). The effectiveness of pedagogical agents’ prompting and feedback in facilitating co-adapted learning with MetaTutor. In Cerri, S. A., Clancey, W. J., Papadourakis, G., & Panourgia, K. (eds.), Proceedings of the 11th International Conference on Intelligent Tutoring Systems (pp. 212221). Amsterdam: Springer.CrossRefGoogle Scholar
Bandura, A. (2001). Social cognitive theory: An agentic perspective. Annual Review of Psychology, 52, 126.CrossRefGoogle Scholar
Baylor, A. (2002). Expanding preservice teachers’ metacognitive awareness of instructional planning through pedagogical agents. Educational Technology Research and Development, 50, 522.CrossRefGoogle Scholar
Baylor, A. L., & Kim, S. (2009). Designing nonverbal communication for pedagogical agents: When less is more. Computers in Human Behavior, 25(2), 450457.CrossRefGoogle Scholar
Beege, M., Schneider, S., Nebel, S., & Rey, G. D. (2020). Does the effect of enthusiasm in a pedagogical agent’s voice depend on mental load in the learner’s working memory? Computers in Human Behavior, 112, 106483.CrossRefGoogle Scholar
Brucker, B., Ehlis, A. C., Häußinger, F., Fallgatter, A., & Gerjets, P. (2015). Watching corresponding gestures facilitates learning with animations by activating human mirror-neurons: An fNIRS study. Learning and Instruction, 36, 2737.CrossRefGoogle Scholar
Carlotto, T., & Jaques, P. A. (2016). The effects of animated pedagogical agents in an English-as-a-foreign-language learning environment. International Journal of Human–Computer Studies, 95, 1526.CrossRefGoogle Scholar
Choi, S., & Clark, R. E. (2006). Cognitive and affective benefits of an animated pedagogical agent for learning English as a second language. Journal of Educational Computing Research, 34(4), 441466.CrossRefGoogle Scholar
Cohen, J. A. (1992). A Power primer. Psychological Bulletin, 112, 155159.CrossRefGoogle Scholar
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), 428434.CrossRefGoogle 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), 314.CrossRefGoogle Scholar
Davis, R. O. (2018). The impact of pedagogical agent gesturing in multimedia learning environments: A meta-analysis. Educational Research Review, 24, 193209.CrossRefGoogle Scholar
Dehn, D., & van Mulken, S. (2000). The impact of animated interface agents: A review of empirical research. International Journal of Human–Computer Studies, 52, 122.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: Theories, Methods, and Applications, 22(2), 8497.CrossRefGoogle Scholar
Dunsworth, Q., & Atkinson, R. K. (2007). Fostering multimedia learning of science: Exploring the role of an animated agent’s image. Computers & Education, 49(3), 677690.CrossRefGoogle Scholar
Duval, S., & Tweedie, R. (2000). Trim and fill: A simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics, 56(2), 455463.CrossRefGoogle ScholarPubMed
Egger, M., Smith, G. D., Schneider, M., & Minder, C. (1997). Bias in meta-analysis detected by a simple, graphical test. BMJ Clinical Research, 315, 629634.CrossRefGoogle ScholarPubMed
Fiorella, L., & Mayer, R. E. (2016). Effects of observing the instructor draw diagrams on learning from multimedia messages. Journal of Educational Psychology, 108(4), 528546.CrossRefGoogle Scholar
Fiorella, L., & Mayer, R. E. (2018). What works and doesn’t work with instructional video. Computers in Human Behavior, 89, 465470.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), 11621171.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(5), 653665.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: Theories, Methods, and Applications, 22, 6172.CrossRefGoogle Scholar
Graesser, A., Jackson, G. T., Ventura, M., Mueller, J., & Hu, X. (2003). The impact of conversational navigational guides on the learning, use, and perceptions of users of a web site. Paper presented at the meeting of the AAAI Spring Symposium on Agent-Mediated Knowledge Management, March 2003, Stanford, CA.Google Scholar
Hedges, L. V., & Olkin, I. (1985). Statistical Methods for Meta-Analysis. New York: Academic Press.Google Scholar
Hedges, L. V., & Vevea, J. L. (1998). Fixed- and random-effects models in meta-analysis. Psychological Methods, 3, 486504.CrossRefGoogle Scholar
Heidig, S., & Clarebout, G. (2011). Do pedagogical agents make a difference to student motivation and learning? Educational Research Review, 6(1), 2754.CrossRefGoogle Scholar
Hong, Z. W., Chen, Y. L., & Lan, C. H. (2014). A courseware to script animated pedagogical agents in instructional material for elementary students in English education. Computer Assisted Language Learning, 27(5), 379394.CrossRefGoogle Scholar
Johnson, A. M., Ozogul, G., Moreno, R., & Reisslein, M. (2013). Pedagogical agent signaling of multiple visual engineering representations: The case of the young female agent. Journal of Engineering Education, 102(2), 319337.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), 97115.CrossRefGoogle Scholar
Kalyuga, S. (2007). Expertise reversal effect and its implications for learner-tailored instruction. Educational Psychology Review, 19(4), 509539.CrossRefGoogle Scholar
Kalyuga, S., Ayres, P., Chandler, P., & Sweller, J. (2003). The expertise reversal effect. Educational Psychologist, 38(1), 2331.CrossRefGoogle Scholar
Kang, S. (2014). The Effect of Animated Pedagogical Agent in Multimedia: The Role of Learner Characteristic and Learning Material [Master’s thesis]. Central China Normal University.Google Scholar
Kim, Y., Baylor, A. L., & Shen, E. (2007). Pedagogical agents as learning companions: The impact of agent emotion and gender. Journal of Computer Assisted Learning, 23(3), 220234.CrossRefGoogle Scholar
Kizilkaya, G., & Askar, P. (2008). The effect of an embedded pedagogical agent on the students’ science achievement. Interactive Technology and Smart Education, 5(4), 208216.CrossRefGoogle Scholar
Li, W., Tong, Y., Wang, F., Kang, S., Liu, H., & Yang, C. (2016). Effect of animation pedagogical agent in multimedia learning: The role of learner’s experience and agent preference. Psychological Development and Education, 32(4), 453462.Google 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), 13821395.CrossRefGoogle Scholar
Lin, L., Atkinson, R. K., Christopherson, R. M., Joseph, S. S., & Harrison, C. J. (2013). Animated agents and learning: Does the type of verbal feedback they provide matter? Computers & Education, 67, 239249.CrossRefGoogle Scholar
Lin, L., Ginns, P., Wang, T., & Zhang, P. (2020). Using a pedagogical agent to deliver conversational style instruction: What benefits can you obtain? Computers & Education, 143, 103658.CrossRefGoogle Scholar
Louwerse, M. M., Graesser, A. C., Lu, S., & Mitchell, H. H. (2005). Social cues in animated conversational agents. Applied Cognitive Psychology, 19(6), 693704.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(6), 747764.CrossRefGoogle Scholar
Mayer, R. E. (2005). The Cambridge Handbook of Multimedia Learning. New York: Cambridge University Press.CrossRefGoogle Scholar
Mayer, R. E. (2014a). Principles based on social cues in multimedia learning: Personalization, voice, image, and embodiment. In Mayer, R. E. (ed.), The Cambridge Handbook of Multimedia Learning (2nd ed., pp. 345370). New York: Cambridge University Press.CrossRefGoogle Scholar
Mayer, R. E. (2014b). Cognitive theory of multimedia learning. In Mayer, R. E. (ed.), The Cambridge Handbook of Multimedia Learning (2nd ed., pp. 4371). New York: Cambridge University Press.CrossRefGoogle Scholar
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), 239252.Google ScholarPubMed
Mayer, R. E., Dow, G. T., & Mayer, S. (2003). Multimedia learning in an interactive self-explaining environment: What works in the design of agent-based microworlds? Journal of Educational Psychology, 95(4), 806812.CrossRefGoogle Scholar
Mayer, R. E., & Fiorella, L. (2014). Principle for reducing extraneous processing in multimedia learning: Coherence, signaling, redundancy, spatial contiguity, and temporal contiguity principles. In Mayer, R. E. (ed.), The Cambridge Handbook of Multimedia Learning (2nd ed., pp. 279315). New York: Cambridge University Press.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(2), 419425.CrossRefGoogle Scholar
Moreno, R., & Flowerday, T. (2006). Students’ choice of animated pedagogical agents in science learning: A test of the similarity–attraction hypothesis on gender and ethnicity. Contemporary Educational Psychology, 31(2), 186207.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(2), 177213.CrossRefGoogle Scholar
Moreno, R., Reislein, M., & Ozogul, G. (2010). Using virtual peers to guide visual attention during learning. Journal of Media Psychology: Theories, Methods, and Applications, 22, 5260.CrossRefGoogle Scholar
Moundridou, M., & Virvou, M. (2002). Evaluating the persona effect of an interface agent in a tutoring system. Journal of Computer Assisted Learning, 18(3), 253261.CrossRefGoogle Scholar
Nye, B. D., Graesser, A. C., & Hu, X. (2014). Multimedia learning with intelligent tutoring systems. In Mayer, R. E. (ed.), The Cambridge Handbook of Multimedia Learning (2nd ed., pp. 705728). New York: Cambridge University Press.CrossRefGoogle Scholar
Ozogul, G., Johnson, A. M., Atkinson, R. K., & Reisslein, M. (2013). Investigating the impact of pedagogical agent gender matching and learner choice on learning outcomes and perceptions. Computers & Education, 67, 3650.CrossRefGoogle Scholar
Park, S. (2015). The effects of social cue principles on cognitive load, situational interest, motivation, and achievement in pedagogical agent multimedia learning. Educational Technology & Society, 18(4), 211229.Google Scholar
Plant, E. A., Baylor, A. L., Doerr, C. E., & Rosenberg-Kima, R. B. (2009). Changing middle-school students’ attitudes and performance regarding engineering with computer based social models. Computers & Education, 53(2), 209215.CrossRefGoogle Scholar
Rodicio, H. G., & Sánchez, E. (2012). Aids to computer-based multimedia learning: A comparison of human tutoring and computer support. Interactive Learning Environments, 20(5), 423439.CrossRefGoogle Scholar
Schroeder, N. L. (2017). The influence of a pedagogical agent on learners’ cognitive load. Educational Technology & Society, 20(4), 138147.Google Scholar
Schroeder, N. L., & Adesope, O. O. (2014). A systematic review of pedagogical agents’ persona, motivation, and cognitive load implications for learners. Journal of Research on Technology in Education, 46(3), 229251.CrossRefGoogle Scholar
Schroeder, N. L., Adesope, O. O., & Gilbert, R. B. (2013). How effective are pedagogical agents for learning? A meta-analytic review. Journal of Educational Computing Research, 49(1), 139.CrossRefGoogle Scholar
Singer, M., & Goldin-Meadow, S. (2005). Children learn when their teacher’s gestures and speech differ. Psychological Science, 16, 8589.CrossRefGoogle ScholarPubMed
van der Meij, H., van der Meij, J., & Harmsen, R. (2015). Animated pedagogical agents effects on enhancing student motivation and learning in a science inquiry learning environment. Educational Technology Research and Development, 63(3), 381403.CrossRefGoogle Scholar
van Gog, T. (2014). The signaling (or cueing) principle in multimedia learning. In Mayer, R. E. (ed.), The Cambridge Handbook of Multimedia Learning (2nd ed., pp. 263278). Cambridge: Cambridge University Press.CrossRefGoogle Scholar
van Vugt, H. C., Konijn, E. A., Hoorn, J. F., Keur, I., & Eliëns, A. (2007). Realism is not all! User engagement with task-related. Interacting with Computers, 19, 267280.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), 250268.CrossRefGoogle Scholar
Wang, F., Li, W., Xie, H., & Liu, H. (2017). Is pedagogical agent in multimedia learning good for learning? A meta-analysis. Advances in Psychological Science, 25, 1228.CrossRefGoogle Scholar
Ward, W., Cole, R., & Bolaños, D. (2013). My science tutor: A conversational multimedia virtual tutor. Journal of Educational Psychology, 105(4), 11151125.CrossRefGoogle Scholar
Wilson, M. (2002). Six views of embodied cognition. Psychonomic Bulletin & Review, 9(4), 625636.CrossRefGoogle ScholarPubMed
Xie, H., Mayer, R. E., Wang, F., & Zhou, Z. (2019). Coordinating visual and auditory cueing in multimedia learning. Journal of Educational Psychology, 111(2), 235255.CrossRefGoogle Scholar
Yilmaz, R., & Kılıç-Çakmak, E. (2012). Educational interface agents as social models to influence learner achievement, attitude and retention of learning. Computers & Education, 59(2), 828838.CrossRefGoogle Scholar
Yung, H. I. (2009). Effects of an animated pedagogical agent with instructional strategies in multimedia learning. Journal of Educational Multimedia and Hypermedia, 18(1), 113126.Google Scholar
Yung, H. I., & Paas, F. (2015). Effects of cueing by a pedagogical agent in an instructional animation: A cognitive load approach. Educational Technology and Society, 18, 153160.Google Scholar

References

Ainsworth, S. (2006). DeFT: A conceptual framework for considering learning with multiple representations. Learning and Instruction, 16, 183198.CrossRefGoogle Scholar
AlZhrani, G., Alotaibi, F., Azarnoush, H. M., Winkler-Schwartz, A., Sabbagh, A., Lajoie, S. P., & Del Maestro, R. F. (2015). Proficiency performance benchmarks for removal of simulated brain tumors using “NeuroTouch” a virtual reality simulator. Journal of Surgical Education, 72(4), 685696.CrossRefGoogle ScholarPubMed
Azevedo, R., & Cromley, J. G. (2004). Does training on self-regulated learning facilitate students’ learning with hypermedia? Journal of Educational Psychology, 96, 523535.CrossRefGoogle Scholar
Azevedo, R., & Feyzi-Behnagh, R. (2011). Dysregulated learning with advanced learning technologies. Journal of e-Learning and Knowledge Society, 7(2), 918.Google Scholar
Azevedo, R., Mudrick, N. V., Taub, M., & Bradbury, A. E. (2019). Self-regulation in computer-assisted learning systems. In Dunlosky, J., & Rawson, K. A. (eds.), The Cambridge Handbook of Cognition and Education (pp. 587618). Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Bannert, M., & Reimann, P. (2012). Supporting self-regulated hypermedia learning through prompts. Instructional Science, 40, 193211.CrossRefGoogle Scholar
Birchfield, D., Thornburg, H., Megowan-Romanowicz, M. C., Hatton, S., Mechtley, B., Dolgov, I., & Burleson, W. (2008). Embodiment, multimodality, and composition: Convergent themes across HCI and education for mixed-reality learning environments. Advances in Human–Computer Interaction, 2008, 874563.CrossRefGoogle Scholar
Bransford, J., Brown, A. L., & Cocking, R. R. (2000). How People Learn: Brain, Mind, Experience, and School (expanded ed.). Commission on Behavioral and Social Sciences and Education, National Research Council. Washington, DC: The National Academies Press.Google Scholar
Burbules, N. C. (2006). Rethinking the virtual. In Weiss, J., Nolan, J., Hunsinger, J., & Trifonas, P. (eds.), The International Handbook of Virtual Learning Environments (pp. 3758). Dordrecht: Springer.CrossRefGoogle Scholar
Clark, J. M., & Paivio, A. (1991). Dual coding theory and education. Educational Psychology, 3(3), 149210.Google Scholar
Delorme, S., Laroche, D., DiRaddo, R., & Del Maestro, R. F. (2012). NeuroTouch: A physics-based virtual simulator for cranial microneurosurgery training. Neurosurgery, 71(1 Suppl Operative), 3242.Google ScholarPubMed
Duffy, M. C., Azevedo, R., Sun, N., Griscom, S., Stead, V., Crelinsten, L., Wiseman, J., Maniatis, T., & Lachapelle, K. (2015). Team regulation in a simulated medical emergency: An in-depth analysis of cognitive, metacognitive, and affective processes. Instructional Science, 43, 401426.CrossRefGoogle Scholar
Duffy, M. C., Lajoie, S. P., Pekrun, R., & Lachapelle, K. (2020). Emotions in medical education: Examining the validity of the Medical Emotion Scale (MES) across authentic medical learning environments. Journal of Learning and Instruction, 70, 101150.CrossRefGoogle Scholar
Ericsson, K. A., Krampe, R. T., & Tesch-Romer, C. (1993). The role of deliberate practice in the acquisition of expert performance. Psychological Review, 100(3), 363406.CrossRefGoogle Scholar
Goldman, S. R. (2003). Learning in complex domains: When and why do multiple representations help? Learning and Instruction, 13(2), 239244.CrossRefGoogle Scholar
Graesser, A. (2020). Emotions are the experiential glue of learning environments in the 21st century. Learning and Instruction, 70, 101212.CrossRefGoogle Scholar
Greeno, J. G. (1998). The situativity of knowing, learning, and research. American Psychologist, 53(1), 526 .CrossRefGoogle Scholar
Hadwin, A. F., Järvelä., S., & Miller, M. (2018). Self-regulation, co-regulation, and shared regulation in collaborative learning environments. In Schunk, D. H., & Greene, J. A. (eds.), Handbook of Self-regulation of Learning and Performance (2nd ed., pp. 83106). Abingdon: Routledge.Google Scholar
Issa, N., Mayer, R. E., Schuller, M., Wang, E., Shapiro, M. B., & Darosa, D. A. (2013). Teaching for understanding in medical classrooms using multimedia design principles. Medical Education, 47(4), 388396.CrossRefGoogle ScholarPubMed
Järvelä, S., Järvenoja, H., Malmberg, J., Isohätälä, J., & Sobocinski, M.(2016). How do types of interaction and phases of self-regulated learning set a stage for collaborative engagement? Learning and Instruction, 43, 3951.CrossRefGoogle Scholar
Järvenoja, H., Järvelä, S., & Malmberg, J. (2020). Supporting groups’ emotion and motivation regulation during collaborative learning. Learning and Instruction, 70, 101090.CrossRefGoogle Scholar
Kuang, X., Eysink, T. H., & de Jong, T. (2020). Effects of providing partial hypotheses as a support for simulation‐based inquiry learning. Journal of Computer Assisted Learning, 36(4), 487501.CrossRefGoogle Scholar
Lajoie, S. P. (2014). Multimedia learning of cognitive processes. In Mayer, R. E. (ed.) The Cambridge Handbook of Multimedia Learning (2nd ed., pp. 623646). Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Lajoie, S. P., Cruz-Panesso, I., & Lachapelle, K. (2015). Learning in the health sector with simulated systems. In Spector, M. (ed.), Encyclopedia of Educational Technology (pp. 470472). Thousand Oaks, CA: Sage.Google Scholar
Lajoie, S. P. & Li, S. (submitted). Interface designs applied to AIED learning and teaching environments. In. du Boulay, B., Mitrovic, A., & Yacef, K. (eds.), Handbook of Artificial Intelligence in Education. Cheltenham: Edward Elgar Press.Google Scholar
Lajoie, S. P., & Nakamura, C. (2005). Multimedia learning of cognitive skills. In Mayer, R. (ed.), Cambridge Handbook of Multimedia Learning (pp. 489504). Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Lajoie, S. P., Pekrun, R., Azevedo, R., & Leighton, J. P. (2020). Understanding and measuring emotions in technology-rich learning environments. Journal of Learning and Instruction, 70, 101272.CrossRefGoogle Scholar
Lajoie, S. P., & Poitras, E. (2017). Crossing disciplinary boundaries to improve technology rich learning. Teachers College Record, 119(3), 130.Google 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
Liu, C., Calvo, R., & Lim, R. (2016b). Improving medical students’ awareness of their nonverbal communication through automated nonverbal behavior feedback. Frontiers in ICT, 3(11).CrossRefGoogle Scholar
Liu, C., Lim, R., McCabe, K., Taylor, S., & Calvo, R. (2016a). A web-based telehealth training platform incorporating automated non-verbal behavior feedback for teaching communication skills to medical students: A randomized crossover study. Journal of Medical Internet Research, 18(9), e246.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), 691707.CrossRefGoogle Scholar
Mavin, T. J., & Murray, P. S. (2010). The development of airline pilot skills through simulated practice. In Billett, S. (ed.), Learning through Practice. Professional and Practice-based Learning (Vol 1, pp. 268286). Heidelberg: Springer.Google Scholar
Mayer, R. E. (2003). The promise of multimedia learning: Using the same instructional design methods across different media. Learning and Instruction, 13(2), 125139.CrossRefGoogle Scholar
Mayer, R. E. (2014). Computer Games for Learning: An Evidence-based Approach. Cambridge, MA: MIT 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., & Moreno, R. (1998). A split-attention effect in multimedia learning: Evidence for dual-processing systems in working memory. Journal of Educational Psychology, 90(2), 312320.CrossRefGoogle Scholar
McLean, G. M., Lambeth, S., & Mavin, T. (2016). The use of simulation in ab initio pilot training. The International Journal of Aviation Psychology, 26(1–2), 3645.CrossRefGoogle Scholar
Merchant, Z., Goetz, E. T., Cifuentes, L., Keeney-Kennicutt, W., & Davis, T. J. (2014). Effectiveness of virtual reality-based instruction on students’ learning outcomes in K-12 and higher education: A meta-analysis. Computers and Education, 70, 2940.CrossRefGoogle Scholar
Merriam-Webster. (n.d.). Simulation. In Merriam-Webster.com dictionary. Available from www.merriam-webster.com/dictionary/simulation (last accessed September 22, 2020).Google Scholar
Mirchi, N., Bissonnette, V., Yilmaz, R., Ledwos, N., Winkler-Schwartz, A., & Del Maestro, R. F. (2020). The virtual operative assistant: An explainable artificial intelligence tool for simulation based training in surgery and medicine. PLoS ONE, 15(2), e0229596.CrossRefGoogle Scholar
Olympiou, G., Zacharias, Z., & Dejong, T. (2013). Making the invisible visible: Enhancing students’ conceptual understanding by introducing representations of abstract objects in a simulation. Instructional Science, 41(3), 575596.CrossRefGoogle Scholar
Papert, S. (1987), Microworlds: Transforming education. In Lawler, R., & Yazsani, M. (eds.), Artificial Intelligence and Education Learning Environments and Tutoring Systems (pp. 7994). New York: Ablex Publishers.Google Scholar
Parong, J., & Mayer, R. E. (2021). Cognitive and affective processes for learning science in immersive virtual reality. Journal of Computer Assisted Learning, 37, 226241.CrossRefGoogle Scholar
Pekrun, R., & Perry, R. P. (2014). Control value theory of achievement emotions. In Pekrun, R., & Linnenbrink-Garcia, L. (eds.), International Handbook of Emotions in Education (pp. 120141). New York: Routledge.CrossRefGoogle Scholar
Platts, D., Anderson, B., Forshaw, T., & Burstow, D. (2011). Use of an echocardiographic mannequin simulator for early-sonographer training. Heart, Lung and Circulation, 20, S199S200.CrossRefGoogle Scholar
Reed, S. K. ( 2010). Cognitive architectures for multimedia learning. Educational Psychologist, 41(2), 8798.CrossRefGoogle Scholar
Rowe, J. P., Shores, L. R., Mott, B. W., & Lester, J. C. (2011). Integrating learning, problem solving, and engagement in narrative-centered learning environments. International Journal of Artificial Intelligence in Education, 21(1–2), 115133.Google Scholar
Sabourin, J. L., Rowe, J. P., Mott, B. W., & Lester, J. C. (2013). Considering alternate futures to classify off-task behavior as emotion self-regulation: A supervised learning approach. Journal of Educational Data Mining, 5(1), 938.Google Scholar
Salas, E., Bowers, C. A., & Rhodenizer, L. (1998). It is not how much you have but how you use it: Toward a rational use of simulation to support aviation training. The International Journal of Aviation Psychology, 8(3), 197208.CrossRefGoogle ScholarPubMed
Shute, V., Rahimi, S., Smith, G., Ke, F., Almond, R., Dai, C., Kuba, R., Liu, Z., Yang, X., & Sun, C. (2021). Maximizing learning without sacrificing the fun: Stealth assessment, adaptivity and learning supports in educational games. Journal of Computer Assisted Learning, 37, 127141.CrossRefGoogle Scholar
Shute, V., & Ventura, M. (2013). Measuring and Supporting Learning in Games: Stealth Assessment. Cambridge, MA: The MIT Press.CrossRefGoogle Scholar
Sroka, G., Feldman, L. S., Vassiliou, M. C., Kaneva, P. A., Fayez, R., & Fried, G. M. (2010). Fundamentals of laparoscopic surgery simulator training to proficiency improves laparoscopic performance in the operating room – A randomized controlled trial. American Journal of Surgery, 199(1), 115120.CrossRefGoogle ScholarPubMed
Sweller, J. (1994). Cognitive load theory, learning difficulty, and instructional design. Learning and Instruction, 4(4), 295312.CrossRefGoogle Scholar
Taub, M., Sawyer, R., Smith, A., Rowe, J., Azevedo, R., & Lester, J. (2020). The agency effect: The impact of student agency on learning, emotions, and problem-solving behaviors in a game-based learning environment. Computers & Education, 147, 103781.CrossRefGoogle Scholar
Vassiliou, M. C., Feldman, L. S., Andrew, C. G., Bergman, S., Leffondré, K., Stanbridge, D., & Fried, G. M. (2005). A global assessment tool for evaluation of intraoperative laparoscopic skills. American Journal of Surgery, 190, 107113.CrossRefGoogle ScholarPubMed
Wiseman, J., Blanchard, E. G., & Lajoie, S. P. (2016). The deteriorating patient smartphone app: Towards serious game design. In Bridges, S., Chan, L. K., & Hmelo-Silver, C. (eds.), Educational Technologies in Medical and Health Sciences Education (pp. 215-234). New York: Springer.CrossRefGoogle Scholar
Wiseman, J., & Snell, L. (2008). The deteriorating patient: A realistic but “low‐tech” simulation of emergency decision‐making. Clinical Teacher, 5(2), 9397.CrossRefGoogle Scholar

References

Abt, C. C. (1970). Serious Games. New York: Viking.Google Scholar
Adams, D. M., Mayer, R. E., MacNamara, A., Koening, A., & Wainess, R. (2012). Narrative games for learning: Testing the discovery and narrative hypothesis. Journal of Educational Psychology, 104, 235249.CrossRefGoogle Scholar
Adams, D. M., Pilegard, C., & Mayer, R. E. (2016). Evaluating the cognitive consequences of playing Portal for a short duration. Journal of Educational Computing Research, 54, 173195.CrossRefGoogle Scholar
Anguera, J. A., Boccanfuso, J., Rintoul, J. L., Al-Hashimi, O., Faraji, F., Janowich, J., Kong, E., Larraburo, Y., Rolle, C., Johnston, E., and Gazzaley, A. (2013). Video game training enhances cognitive control in older adults. Nature, 501(7465), 97101.CrossRefGoogle ScholarPubMed
Bainbridge, K., & Mayer, R. E. (2018). Shining the light of research on lumosity. Journal of Cognitive Enhancement, 2, 4362.CrossRefGoogle Scholar
Bediou, B., Adams, D. M., Mayer, R. E., Tipton, E., Green, C. S., & Bavelier, D. (2018). Meta-analysis of action video game impact on perceptual, attentional, and cognitive skills. Psychological Bulletin, 144(1), 77110.CrossRefGoogle ScholarPubMed
Cameron, B., & Dwyer, F. (2005). The effect of online gaming, cognition and feedback type in facilitating delayed achievement of different learning objectives. Journal of Interactive Learning Research, 16, 243258.Google Scholar
Clark, D. B., Tanner-Smith, E. E., & Killingsworth, S. S. (2016). Digital games, design, and learning: A systematic review and meta-analysis. Review of Educational Research, 86, 79122.CrossRefGoogle ScholarPubMed
Clark, R. E. (2001). Learning from Media. Greenwich, CT: Information Age Publishing.Google Scholar
Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Hillsdale, NJ: Erlbaum.Google Scholar
Connolly, T. M., Boyle, E. A., MacArthur, E., Hainey, T., & Boyle, J. M. (2012). A systematic review of empirical evidence on computer games and serious games. Computers & Education, 59, 661686.CrossRefGoogle Scholar
DeLeeuw, K., & Mayer, R. E. (2011). Cognitive consequences of making computer-based learning activities more game-like. Computers in Human Behavior, 27, 20112016.CrossRefGoogle Scholar
Fiorella, L., & Mayer, R. E. (2012). Paper-based aids for learning with a computer-based game. Journal of Educational Psychology, 104, 10741082.CrossRefGoogle Scholar
Fiorella, L., & Mayer, R. E. (2015). Learning As a Generative Activity. New York: Cambridge University Press.CrossRefGoogle Scholar
Hardy, J. L., Nelson, R. A., Thomason, M. E., Sternberg, D. A., Katovich, K., Farzin, , & Scanlon, M. (2015). Enhancing cognitive abilities with comprehensive training: A large, online, randomized, active-controlled trial. PLoS ONE, 10(9), e0134467.CrossRefGoogle ScholarPubMed
Honey, M., & Hilton, M. (eds.). (2011). Learning Science through Computer Games and Simulations. Washington, DC: National Academy Press.Google Scholar
James, K., & Mayer, R. E. (2019). Learning a second language by playing a game. Applied Cognitive Psychology, 33, 669674.CrossRefGoogle Scholar
Johnson, C. I., & Mayer, R. E. (2010). Adding the self-explanation principle to multimedia learning in a computer-based game-like environment. Computers in Human Behavior, 26, 12461252.CrossRefGoogle Scholar
Kable, J. W., Caufield, M. K., Falcone, M., McConnell, M., Bernardo, L., Parthasarathi, T., ... & Lerman, C. (2017). No effect of commercial cognitive training on brain activity, choice behavior, or cognitive performance. Journal of Neuroscience, 37(31), 73907402.CrossRefGoogle ScholarPubMed
Leutner, D. (1993). Guided discovery learning with computer-based simulation games: Effects of adaptive and non-adaptive instructional support. Learning and Instruction, 3, 113132.CrossRefGoogle Scholar
Loftus, G. R., & Loftus, E. F. (1983). Mind at Play: The Psychology of Video Games. New York: Basic Books.Google Scholar
Lorant-Royer, S., Munch, C., Mescle, H., & Lieury, A. (2010). Kawashima vs “Super Mario”! Should a game be serious in order to stimulate cognitive aptitudes? European Review of Applied Psychology, 60 (4), 221232.CrossRefGoogle Scholar
Mayer, R. E. (2011). Applying the Science of Learning. Boston: Pearson.Google Scholar
Mayer, R. E. (2014). Games for Learning: An Evidence-based Approach. Cambridge, MA: MIT Press.CrossRefGoogle Scholar
Mayer, R. E. (2016). What should be the role of computer games in education? Policy Insights from Behavioral and Brain Sciences, 3(1), 2026.CrossRefGoogle Scholar
Mayer, R. E. (2019a). Computer games in education. Annual Review of Psychology, 70, 531549.CrossRefGoogle Scholar
Mayer, R. E. (2019b). Cognitive foundations of game-based learning. In Plass, J., Homer, B., & Mayer, R. E. (eds.), Handbook of Game-based Learning (pp. 83110). Cambridge, MA: MIT Press.Google Scholar
Mayer, R. E., & Johnson, C. I. (2010). Adding instructional features that promote learning in a game-like environment. Journal of Educational Computing Research, 42, 241265.CrossRefGoogle Scholar
Mayer, R. E., Mautone, P. D., & Prothero, W. (2002). Pictorial aids for learning by doing in a multimedia geology simulation game. Journal of Educational Psychology, 94, 171185.CrossRefGoogle Scholar
Mayer, R. E., Parong, J., & Bainbridge, K. (2019). Young adults learning executive function skills by playing focused video games. Cognitive Development, 49, 4350.CrossRefGoogle Scholar
McGonigal, J. (2011). Reality Is Broken: Why Games Make Us Better and How They Can Change the World. New York: Penguin Press.Google Scholar
McLaren, B. M., Adams, D., Mayer, R., & Forlizzi, J. (2017). Decimal point: An educational game that benefits mathematics learning more than a conventional approach. International Journal of Game-Based Learning, 7(1), 3656.CrossRefGoogle Scholar
Moreno, R., & Mayer, R. E. (2000). Engaging students in active learning: The case for personalized multimedia messages. Journal of Educational Psychology, 93, 724733.CrossRefGoogle Scholar
Moreno, R., & Mayer, R. E. (2002a). Verbal redundancy in multimedia learning: When reading helps listening. Journal of Educational Psychology, 94, 156163.CrossRefGoogle Scholar
Moreno, R., & Mayer, R. E. (2002b). Learning science in virtual reality environments: Role of methods and media. Journal of Educational Psychology, 94, 598610.CrossRefGoogle Scholar
Moreno, R., & Mayer, R. E. (2004). Personalized messages that promote science learning in virtual environments. Journal of Educational Psychology, 96, 165173.CrossRefGoogle Scholar
Moreno, R., & Mayer, R. E. (2005). Role of guidance, reflection, and interactivity in an agent-based multimedia game. Journal of Educational Psychology, 97, 117128.CrossRefGoogle Scholar
Moreno, R., Mayer, R. E., Spires, H., & Lester, J. (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, 177214.CrossRefGoogle Scholar
Nouchi, R., Yasuyuki, T., Takeuchi, H., Hashizume, H., Akitsuki, Y., Shigemune, Y., Sekiguchi, A., Kotozaki, Y., Tsukiura, T., Yomogida, Y., & Kawashima, R. (2012). Brain training game improves executive functions and processing speed in the elderly: A randomized controlled trial. PLoS ONE, 7(1), e29676.CrossRefGoogle ScholarPubMed
O’Neil, H. F., Chung, G., Kerr, D., Vendlinski, T., Bushchang, R., & Mayer, R. E. (2014). Adding self-explanation prompts to an educational game. Computers in Human Behavior, 30, 2328.CrossRefGoogle Scholar
O’Neil, H. F., & Perez, R. S. (eds.) (2008). Computer Games and Team and Individual Learning. Amsterdam: Elsevier.Google Scholar
Owen, A. M., Hampshire, A., Grahn, J. A., Stenton, R., Dajani, S., Burns, A. S., Howard, R. J., & Ballard, C. G. (2010). Putting brain training to the test. Nature, 465(7299), 775778.CrossRefGoogle ScholarPubMed
Parong, J., & Mayer, R. E. (2020). Cognitive consequences of playing brain training games in virtual reality. Applied Cognitive Psychology, 34, 2938.CrossRefGoogle Scholar
Parong, J., Mayer, R. E., Fiorella, L., MacNamara, A., Plass, J., & Homer, B. (2017). Learning executive function skills by playing focused video games. Contemporary Educational Psychology, 51, 141151.CrossRefGoogle Scholar
Parong, J., Wells, A., & Mayer, R. E. (2020). Replicated evidence towards a cognitive theory of game-based training. Journal of Educational Psychology, 112, 922937.CrossRefGoogle Scholar
Pilegard, C., & Mayer, R. E. (2016). Improving academic learning from computer-based narrative games. Contemporary Educational Psychology, 44, 1220.CrossRefGoogle Scholar
Pilegard, C., & Mayer, R. E. (2018). Game over for Tetris as a platform for cognitive skill training. Contemporary Educational Psychology, 54, 2941.CrossRefGoogle Scholar
Plass, J., Mayer, R. E., & Homer, B. (eds.) (2019). Handbook of Game-based Learning. Cambridge, MA: MIT Press.Google Scholar
Shavelson, R. J., & Towne, L. (eds.) (2002). Scientific Research in Education. Washington, DC: National Academy Press.Google Scholar
Simons, D. J., Boot, W. R., Charbness, N., Gathercole, S. E., Chabris, C. F., Hambrick, D. Z., & Stine-Morrow, E. A. L. (2016). Do brain training programs work? Psychological Science in the Public Interest, 17(3), 103186.CrossRefGoogle ScholarPubMed
Sims, V. K., & Mayer, R. E. (2002). Domain specificity of spatial expertise: The case of video game players. Applied Cognitive Psychology, 16, 97115.CrossRefGoogle Scholar
Sitzmann, T. (2011). A meta-analytic examination of the instructional effectiveness of computer-based simulation games. Personnel Psychology, 64, 489528.CrossRefGoogle Scholar
Tobias, S., & Fletcher, J. D. (eds.) (2011). Computer Games and Instruction. Charlotte, NC: Information Age Publishing.Google Scholar
Tobias, S., Fletcher, J. D., Dai, D. Y., & Wind, A. P. (2011). Review of research on computer games. In Tobias, S., & Fletcher, J. D. (eds.), Computer Games and Instruction (pp. 525545). Charlotte, NC: Information Age Publishing.Google Scholar
van Eck, R., & Dempsey, J. (2002). The effect of competition and contextualized advisement on the transfer of mathematics skills in a computer-based instructional simulation game. Educational Technology Research and Development, 50, 2341.CrossRefGoogle Scholar
Vogel, J. J., Vogel, D. S., Cannon-Bowers, J., Bowers, C. A., Muse, K., & Wright, M. (2006). Computer gaming and interactive simulations for learning: A meta-analysis. Journal of Educational Computing Research, 34, 229243.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, 96112.CrossRefGoogle Scholar
Wells, A., Parong, J., & Mayer, R. E. (2021). Limits on training inhibitory control with a focused video game. Journal of Cognitive Enhancement, 5, 8398.CrossRefGoogle Scholar
Wouters, P., van Nimwegen, C., van Oostendorp, H., & van der Spek, E. D. (2013). A meta-analysis of the cognitive and motivational effects of serious games. Journal of Educational Psychology, 105, 249265.CrossRefGoogle Scholar
Wouters, P., & van Oostendorp, H. (eds.) (2017). Instructional Techniques to Facilitate Learning and Motivation of Serious Games. New York: Springer.CrossRefGoogle Scholar
Young, M. F., Slota, S., Cutter, A. B., Jalette, G., Mullin, G., Lai, B., Simeoni, Z., Tran, M., & Yukhymenko, M. (2012). Our princess is in another castle: A review of trends in serious gaming for education. Review of Educational Research, 82, 6189.CrossRefGoogle Scholar

References

Ainsworth, S., & Loizou, A. (2003). The effects of self‐explaining when learning with text or diagrams. Cognitive Science27(4), 669681.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, 117139.CrossRefGoogle Scholar
Beege, M., Schneider, S., Nebel, S., & Rey, G. D. (2017). Look into my eyes! Exploring the effect of addressing in educational videos. Learning and Instruction49, 113120.CrossRefGoogle Scholar
Betrancourt, M., & Benetos, K. (2018). Why and when does instructional video facilitate learning? A commentary to the special issue “Developments and trends in learning with instructional video.” Computers in Human Behavior, 89, 471475.CrossRefGoogle Scholar
Biard, N., Cojean, S., & Jamet, E. (2018). Effects of segmentation and pacing on procedural learning by video. Computers in Human Behavior89, 411417.CrossRefGoogle Scholar
Bjork, E. L., & Bjork, R. A. (2011). Making things hard on yourself, but in a good way: Creating desirable difficulties to enhance learning. In Gernsbacher, M. A., Pew, R. W., Hough, L. M., & Pomerantz, J. R. (eds.) & FABBS Foundation, Psychology and the Real World: Essays Illustrating Fundamental Contributions to Society (pp. 5664). New York: Worth Publishers.Google Scholar
Bonk, C. J., Lee, M. M., Reeves, T. C., & Reynolds, T. H. (2015). MOOCs and Open Education around the World. New York: Routledge.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 Behavior89, 418429.CrossRefGoogle Scholar
Breslow, L., Pritchard, D. E., DeBoer, J., Stump, G. S., Ho, A. D., & Seaton, D. T. (2013). Studying learning in the worldwide classroom: Research into EdX’s first MOOC. Research and Practice in Assessment, 8, 1325.Google Scholar
Carpenter, S. K., & Toftness, A. R. (2017). The effect of prequestions on learning from video presentations. Journal of Applied Research in Memory and Cognition6(1), 104109.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 Development66(6), 14151433.CrossRefGoogle Scholar
Cuban, L. (1986). Teachers and Machines: The Classroom Use of Technology since 1920. New York: Teachers College Press.Google Scholar
de Koning, B. B., Hoogerheide, V., & Boucheix, J.-M. (2018). Developments and trends in learning with instructional videos. Computers in Human Behavior, 89, 395398.CrossRefGoogle Scholar
DeLozier, S. J., & Rhodes, M. G. (2017). Flipped classrooms: A review of key ideas and recommendations for practice. Educational Psychology Review, 29(1), 141151.CrossRefGoogle Scholar
Fiorella, L. (2020). The science of habit and its implications for student learning and well-being. Educational Psychology Review, 32, 603625.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 Review28(4), 717741.CrossRefGoogle Scholar
Fiorella, L., & Mayer, R. E. (2016b). Effects of observing the instructor draw diagrams on learning from multimedia messages. Journal of Educational Psychology108(4), 528546.CrossRefGoogle Scholar
Fiorella, L., & Mayer, R. E. (2017). Spontaneous spatial strategy use in learning from scientific text. Contemporary Educational Psychology49, 6679.CrossRefGoogle Scholar
Fiorella, L., & Mayer, R. E. (2018). What works and doesn’t work with instructional video. Computers in Human Behavior, 89, 465470.CrossRefGoogle Scholar
Fiorella, L., & Zhang, Q. (2018). Drawing boundary conditions for learning by drawing. Educational Psychology Review, 30, 11151137.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 Psychology111(7), 11621171.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 Psychology112(5), 895906.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, 653665.CrossRefGoogle Scholar
Fries, L., DeCaro, M. S., & Ramirez, G. (2019). The lure of seductive details during lecture learning. Journal of Educational Psychology, 111(4), 736749.CrossRefGoogle Scholar
Garland, T. B., & Sanchez, C. A. (2013). Rotational perspective and learning procedural tasks from dynamic media. Computers & Education69, 3137.CrossRefGoogle Scholar
Gorissen, P., van Bruggen, J., & Jochems, W. (2012). Students and recorded lectures: Survey on current use and demands for higher education. Research in Learning Technology, 20, 297311.CrossRefGoogle Scholar
Hasler, B. S., Kersten, B., & Sweller, J. (2007). Learner control, cognitive load and instructional animation. Applied Cognitive Psychology, 21(6), 713729.CrossRefGoogle Scholar
Homer, B. D., Plass, J. L., & Blake, L. (2008). The effects of video on cognitive load and social presence in multimedia-learning. Computers in Human Behavior24(3), 786797.CrossRefGoogle Scholar
Hoogerheide, V., Loyens, S. M., & van Gog, T. (2016). Learning from video modeling examples: Does gender matter? Instructional Science44(1), 6986.CrossRefGoogle Scholar
Hoogerheide, V., van Wermeskerken, M., Loyens, S. M., & van Gog, T. (2016). Learning from video modeling examples: Content kept equal, adults are more effective models than peers. Learning and Instruction44, 2230.CrossRefGoogle Scholar
Hoogerheide, V., van Wermeskerken, M., van Nassau, H., & van Gog, T. (2018). Model-observer similarity and task-appropriateness in learning from video modeling examples: Do model and student gender affect test performance, self-efficacy, and perceived competence? Computers in Human Behavior89, 457464.CrossRefGoogle Scholar
Jing, H. G., Szpunar, K. K., & Schacter, D. L. (2016). Interpolated testing influences focused attention and improves integration of information during a video-recorded lecture. Journal of Experimental Psychology: Applied22(3), 305.Google ScholarPubMed
Kane, M. J., Smeekens, B. A., von Bastian, C. C., Lurquin, J. H., Carruth, N. P., & Miyake, A. (2017). A combined experimental and individual-differences investigation into mind wandering during a video lecture. Journal of Experimental Psychology: General146(11), 16491674.CrossRefGoogle ScholarPubMed
Kapur, M. (2016). Examining productive failure, productive success, unproductive failure, and unproductive success in learning. Educational Psychologist51(2), 289299.CrossRefGoogle Scholar
Karpicke, J. D. (2012). Retrieval-based learning: Active retrieval promotes meaningful learning. Current Directions in Psychological Science, 21(3), 157163.CrossRefGoogle Scholar
Karpicke, J. D., Butler, A. C., & Roediger, H. L. III (2009). Metacognitive strategies in student learning: Do students practise retrieval when they study on their own? Memory17(4), 471479.CrossRefGoogle Scholar
Kay, R. H. (2012). Exploring the use of video podcasts in education: A comprehensive review of the literature. Computers in Human Behavior, 28, 820831.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 Psychology107(3), 724739.CrossRefGoogle Scholar
Lee, H., & Mayer, R. E. (2018). Fostering learning from instructional video in a second language. Applied Cognitive Psychology, 32, 648654.CrossRefGoogle Scholar
Lindgren, R. (2012). Generating a learning stance through perspective-taking in a virtual environment. Computers in Human Behavior28(4), 11301139.CrossRefGoogle Scholar
Loh, K. K., Tan, B. Z. H., & Lim, S. W. H. (2016). Media multitasking predicts video-recorded lecture learning performance through mind wandering tendencies. Computers in Human Behavior63, 943947.CrossRefGoogle Scholar
Mayer, R. E., & Chandler, P. (2001). When learning is just a click away: Does simple user interaction foster deeper understanding of multimedia messages? Journal of Educational Psychology, 93(2), 390397.CrossRefGoogle Scholar
Mayer, R. E., Fiorella, L., & Stull, A. (2020). Five ways to increase the effectiveness of instructional video. Educational Technology Research & Development68(3), 837852.CrossRefGoogle Scholar
Mayer, R. E., Heiser, J., & Lonn, S. (2001). Cognitive constraints on multimedia learning: When presenting more material results in less understanding. Journal of Educational Psychology, 93(1), 187198.CrossRefGoogle Scholar
Merkt, M., Weigand, S., Heier, A., & Schwan, S. (2011). Learning with videos vs. learning with print: The role of interactive features. Learning and Instruction, 21(6), 687704.Google Scholar
Moreno, R. (2007). Optimising learning from animations by minimizing cognitive load: Cognitive and affective consequences of signaling and segmentation methods. Applied Cognitive Psychology, 21(6), 765781.CrossRefGoogle Scholar
O’Callagan, F. V., Neumann, D. L., Jones, L., & Creed, P. A. (2017). The use of lecture recordings in higher education: A review of institutional, student, and lecturer issues. Education and Information Technologies, 22, 399415.CrossRefGoogle Scholar
Ouwehand, K., van Gog, T., & Paas, F. (2015a). Designing effective video-based modeling examples using gaze and gesture cues. Educational Technology & Society (online)18, 7888.Google Scholar
Ouwehand, K., van Gog, T., & Paas, F. (2015b). Effects of gestures on older adults’ learning from video‐based models. Applied Cognitive Psychology29(1), 115128.CrossRefGoogle Scholar
Ozogul, G., Johnson, A., Atkinson, R. K., & Reisslein, M. (2013). Investigating the impact of pedagogical agent gender matching and learner choice on learning outcomes and perceptions. Computers & Education, 67, 3650.CrossRefGoogle Scholar
Pi, Z., Hong, J., & Yang, J. (2017). Effects of the instructor’s pointing gestures on learning performance in video lectures. British Journal of Educational Technology48(4), 10201029.CrossRefGoogle Scholar
Pi, Z., Zhang, Y., Zhu, F., Xu, K., Yang, J., & Hu, W. (2019). Instructors’ pointing gestures improve learning regardless of their use of directed gaze in video lectures. Computers & Education128, 345352.CrossRefGoogle Scholar
Renkl, A. (1997). Learning from worked-out examples: A study on individual differences. Cognitive Science21(1), 129.CrossRefGoogle Scholar
Rey, G. D. (2012). A review of research and a meta-analysis of the seductive detail effect. Educational Research Review7(3), 216237.CrossRefGoogle Scholar
Roediger, H. L. III, & Karpicke, J. D. (2006). Test-enhanced learning: Taking memory tests improves long-term retention. Psychological Science17(3), 249255.CrossRefGoogle ScholarPubMed
Schroeder, N. L., & Traxler, A. L. (2017). Humanizing instructional videos in physics: When less is more. Journal of Science Education and Technology26(3), 269278.CrossRefGoogle Scholar
Schunk, D. H., & Hanson, A. R. (1985). Peer models: Influence on children’s self-efficacy and achievement. Journal of Educational Psychology, 77, 313322.CrossRefGoogle Scholar
Schwartz, D. L., Chase, C. C., Oppezzo, M. A., & Chin, D. B. (2011). Practicing versus inventing with contrasting cases: The effects of telling first on learning and transfer. Journal of Educational Psychology103(4), 759775.CrossRefGoogle Scholar
Shen, B., McCaughtry, N., Martin, J., & Dillion, S. (2006). Does “sneaky fox” facilitate learning? Examining the effects of seductive details in physical education. Research Quarterly for Exercise and Sport, 77(4), 498506.Google ScholarPubMed
Spanjers, I. E. A., van Gog, T., Wouters, P., & van Merrienboer, J. J. G. (2012). Explaining the segmentation effect in learning form animations: The role of pausing and temporal cueing. Computers & Education, 59(2), 274280.CrossRefGoogle Scholar
Spanjers, I. E. A., Wouters, P., van Gog, T., & van Merrienboer, J. J. G. (2011). An expertise reversal effect for segmentation in learning from animated worked-out examples. Computers in Human Behavior, 27(1), 4652.CrossRefGoogle Scholar
Stull, A. T., Fiorella, L., Gainer, M. J., & Mayer, R. E. (2018). Using transparent whiteboards to boost learning from online STEM lectures. Computers & Education120, 146159.CrossRefGoogle Scholar
Stull, A. T., Fiorella, L., & Mayer, R. E. (2018). An eye-tracking analysis of instructor presence in video lectures. Computers in Human Behavior88, 263272.CrossRefGoogle Scholar
Sundararajan, N., & Adesope, O. (2020). Keep it coherent: A meta-analysis of the seductive details effect. Educational Psychology Review, 32, 707734.CrossRefGoogle Scholar
Szpunar, K. K., Jing, H. G., & Schacter, D. L. (2014). Overcoming overconfidence in learning from video-recorded lectures: Implications of interpolated testing for online education. Journal of Applied Research in Memory and Cognition3(3), 161164.CrossRefGoogle Scholar
Szpunar, K. K., Khan, N. Y., & Schacter, D. L. (2013). Interpolated memory tests reduce mind wandering and improve learning of online lectures. Proceedings of the National Academy of Sciences110(16), 63136317.CrossRefGoogle ScholarPubMed
Toftness, A. R., Carpenter, S. K., Lauber, S., & Mickes, L. (2018). The limited effects of prequestions on learning from authentic lecture videos. Journal of Applied Research in Memory and Cognition7(3), 370378.CrossRefGoogle Scholar
Türkay, S. (2016). The effects of whiteboard animations on retention and subjective experiences when learning advanced physics topics. Computers & Education98, 102114.CrossRefGoogle Scholar
van Gog, T., Verveer, I., & Verveer, L. (2014). Learning from video modeling examples: Effects of seeing the human model’s face. Computers & Education72, 323327.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 Learning34(1), 3241.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 Behavior89, 430438.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 & Education113, 98107.CrossRefGoogle Scholar
Wammes, J. D., & Smilek, D. (2017). Examining the influence of lecture format on degree of mind wandering. Journal of Applied Research in Memory and Cognition6(2), 174184.CrossRefGoogle Scholar
Wang, H., Pi, Z., & Hu, W. (2019). The instructor’s gaze guidance in video lectures improves learning. Journal of Computer Assisted Learning35(1), 4250.CrossRefGoogle Scholar
Wang, J., & Antonenko, P. D. (2017). Instructor presence in instructional video: Effects on visual attention, recall, and perceived learning. Computers in Human Behavior71, 7989.CrossRefGoogle Scholar
Wittrock, M. C. (1989). Generative processes of comprehension. Educational Psychologist24(4), 345376.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(6), 449457.CrossRefGoogle Scholar
Yong, P. Z., & Lim, S. W. H. (2016). Observing the testing effect using Coursera video-recorded lectures: A preliminary study. Frontiers in Psychology6, 2064.CrossRefGoogle ScholarPubMed
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), 266277.CrossRefGoogle Scholar

References

Anthes, C., García-Hernández, R. J., Wiedemann, M., & Kranzlmüller, D. (2016). State of the art of virtual reality technology. IEEE Aerospace Conference Proceedings, 2016, 1–19.CrossRefGoogle Scholar
Avcı, Ş. K., Çoklar, A. N., & İstanbullu, A. (2019). The effect of three dimensional virtual environments and augmented reality applications on the learning achievement: A meta-analysis study. Education and Science, 44(198), 149182.Google Scholar
Azuma, R. T. (1997). A survey of augmented reality. Presence, 6(4), 355385.CrossRefGoogle Scholar
Birchfield, D., & Megowan-Romanowicz, C. (2009). Earth science learning in SMALLab: A design experiment for mixed-reality. Journal of Computer Supported Collaborative Learning, 4, 403421.CrossRefGoogle Scholar
Carrera, J. F., Wang, C. C., Clark, W., & Southerland, A. M. (2019). A systematic review of the use of google glass in graduate medial education. Journal of Graduate Medical Education, 11(6), 637648.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, 55015527.CrossRefGoogle Scholar
Chen, C. Zhang, L., Luczak, T., Smith, E., & Burch, R. F. (2019). Using Microsoft HoloLens to improve memory recall in anatomy and physiology: A pilot study to examine the efficacy of using augmented reality in education. Journal of Educational Technology Development and Exchange, 12(1), 1731.CrossRefGoogle Scholar
Clark, R. E. (1983). Reconsidering research on learning from media. Review of Educational Research, 53(4), 445459.CrossRefGoogle Scholar
Clark, R. E. (1994). Media will never influence learning. Educational Technology Research and Development, 42(1), 2129.CrossRefGoogle Scholar
Concannon, B. J., Esmail, S., & Roberts, M. R. (2019). Head-mounted display virtual reality in post-secondary education and skill training. Frontiers in Education, 4(80), 123.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), 272309.CrossRefGoogle Scholar
Dede, C. (2009). Immersive interfaces for engagement and learning. Science, 323, 6669.CrossRefGoogle Scholar
Dolgunsöz, E., Yildirim, G., & Yildirim, S. (2018). The effect of virtual reality on EFL writing performance. Journal of Language and Linguistic Studies, 14(1), 278292.Google Scholar
Ekstrand, C., Jamal, A., Nguyen, R., Kudryk, A., Mann, J., & Mendez, I. (2018). Immersive and interactive virtual reality to improve learning and retention of neuroanatomy in medical students: A randomized controlled study. CMAJ Open, 6(1), E103E109.CrossRefGoogle ScholarPubMed
Freina, L., & Ott, M. (2015). A literature review on immersive virtual reality in education: State of the art and perspectives. Proceedings of eLearning and Software for Education (eLSE), 1, 133141.Google Scholar
Garzón, J., & Acevedo, J. (2019). Meta-analysis of the impact of augmented reality on students’ learning gains. Educational Research Review, 27, 244260.CrossRefGoogle Scholar
Halabi, O. (2020). Immersive virtual reality to enforce teaching in engineering education. Multimedia Tools and Applications, 79, 29873004.CrossRefGoogle Scholar
Innocenti, E. D., Geronazzo, M., Vescovi, D., Nordahl, R., Serafin, S., Ludovico, A., & Avanzini, F. (2019). Mobile virtual reality for musical genre learning in primary education. Computers & Education, 139, 102117.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, 15151529.CrossRefGoogle Scholar
Johnson-Glenberg, M. C., Birchfield, D., Tolentino, L., & Koziupa, T. (2014). Collaborative embodied learning in mixed reality motion-capture environments: Two science studies. Journal of Educational Psychology, 106(1), 86104.CrossRefGoogle Scholar
Kaplan, A. D., Cruit, J., Endsley, M., Beers, S. M., Sawyer, B. D., & Hancock, P. A. (2020). The effects of virtual reality, augmented reality, and mixed reality as training enhancements: A meta-analysis. Human Factors. Advance online publication. https://doi.org/10.1177/0018720820904229CrossRefGoogle Scholar
Kavanagh, S., Luxton-Reilly, A., Wuensche, B., & Plimmer, B. (2017). A systematic review of virtual reality in education. Themes in Science and Technology Education, 10(2), 85119.Google Scholar
Kim, Y. M., Rhiu, I., & Yun, M. H. (2019). A systematic review of virtual reality system from the perspective of user experience. International Journal of Human–Computer Interaction, 36, 893910.CrossRefGoogle Scholar
Kozhevnikov, M., Gurlitt, J., & Kozhevnikov, . (2013). Learning relative motion concepts in immersive and non-immersive virtual environments. Journal of Science Education and Technology, 22(6), 952962.CrossRefGoogle Scholar
Kozma, R. B. (1991). Learning with media. Review of Educational Research, 61(2), 179211.CrossRefGoogle Scholar
Kozma, R. B. (1994). Will media influence learning? Reframing the debate. Educational Technology Research & Development, 42(2), 719.CrossRefGoogle Scholar
Kuhn, J., Lukowicz, P., Hirth, M., Poxrucker, A., Weppner, J., & Younas, J. (2016). gPhysics – Using smart glasses for head-centered, context-aware learning in physics experiments. IEEE Transactions on Learning Technologies, 9(4), 304317.CrossRefGoogle Scholar
Limniou, M., Roberts, D., & Papadopoulos, N. (2008). Full immersive virtual environment CAVETM in chemistry education. Computers & Education, 51, 584593.CrossRefGoogle Scholar
Lindgren, R., Tscholl, M., Wang, S., & Johnson, E. (2016). Enhancing learning and engagement through embodied interaction within a mixed reality simulation. Computers & Education, 95, 174187.CrossRefGoogle Scholar
Maas, M. J., & Hughes, M. (2020). Virtual, augmented, and mixed-reality in K-12 education: A review of the literature. Technology, Pedagogy, and Education, 29(2), 231249.CrossRefGoogle Scholar
Makransky, G., Andreasen, N. K., Baceviciute, S., & Mayer, R. E. (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. Advance online publication. https://doi.org/10.1037/edu0000473CrossRefGoogle 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), 691707.CrossRefGoogle Scholar
Makransky, D., Terkildsen, T. S., & Mayer, R. E. (2017). Adding immersive virtual reality to a science lab simulation causes more presence but less learning. Learning and Instruction, 60, 225236.CrossRefGoogle Scholar
Mann, S., Havens, J. C., Iorio, J., Yuan, Y., & Furness, T. (2018). All reality: Virtual, augmented, mixed (X), mediated (X, Y), and multimediated reality. In 2018 Augmented World Expo, May 30–June 1, 2018. Santa Clara, CA.Google Scholar
Maresky, H. S., Oikonomou, A., Ali, I., Ditkofsky, N., Pakkal, M., & Ballyk, B. (2018). Virtual reality and cardiac anatomy: Exploring immersive three-dimensional cardiac imaging, a pilot study in undergraduate medical anatomy education. Clinical Anatomy, 32, 238243.CrossRefGoogle ScholarPubMed
Mayer, R. E. (2014). Media comparison approach: Are games more effective than conventional media? In Mayer, R. E. (ed.), Computer Games for Learning: An Evidence-Based Approach (pp. 225249). Cambridge, MA: The MIT Press.CrossRefGoogle Scholar
Merchant, Z., Goetz, E. T., Cifuentes, L., Keeney-Kennicutt, W., & Davis, T. J. (2014). Effectiveness of virtual reality-based instruction on students’ learning outcomes in K-12 and higher education: A meta-analysis. Computers & Education, 70, 2940.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, 117.CrossRefGoogle Scholar
Milgram, P., & Kishino, F. (1994). A taxonomy of mixed reality visual displays. IEEE Transactions on Information Systems, 77(12), 13211329.Google Scholar
Moreno, R., & Mayer, R. E. (2002). Learning science in virtual reality multimedia environments: Role of methods and media. Journal of Educational Psychology, 94(2), 598610.CrossRefGoogle Scholar
Moreno, R., & Mayer, R. E. (2004). Personalized messages that promote science Learning in virtual environments. Journal of Educational Psychology, 96(1), 165173.CrossRefGoogle Scholar
Muhanna, M. A. (2015). Virtual reality and the CAVE: Taxonomy, interaction challenges and research directions. Journal of King Saud University – Computer and Information Sciences, 27, 344361.CrossRefGoogle Scholar
Nilsson, N. C., Nordhal, R., & Serafin, S. (2016). Immersion revisited: A review of existing definitions of immersion and their relation to different theories of presence. Human Technology, 12(2), 108134.CrossRefGoogle Scholar
Ozdemir, M., Sahin, C., Arcagok, S., & Demir, M. K. (2018). The effect of augmented reality applications in the learning process: A meta-analysis study. Eurasian Journal of Educational Research, 74, 165186.Google Scholar
Parong, J., & Mayer, R. E. (2018). Learning science in immersive virtual reality. Journal of Educational Psychology, 110(6), 785797.CrossRefGoogle Scholar
Parong, J., & Mayer, R. E. (2020). Cognitive and affective processes for learning science in immersive virtual reality. Journal of Computer Assisted Learning, 37, 226241.CrossRefGoogle Scholar
Pennefather, P., Krebs, C. (2019). Exploring the role of xR in visualisations for use in medical education. In Rea, P. (ed.), Biomedical Visualisation. Advances in Experimental Medicine and Biology (Vol. 1171, pp. 1524). Cham: Springer.CrossRefGoogle Scholar
Radianti, J., Majchrzak, T. A., Fromm, J., & Wohlgenannt, I. (2020). A systematic review of immersive virtual reality applications for higher education: Design elements, lessons learned, and research agenda. Computers & Education, 147, 103778.CrossRefGoogle Scholar
Ren, S., McKenzie, F. D., Chaturvedi, S. K., Prabhakaran, R., Yoon, J., Katisioloudis, P. J., & Garcia, H. (2015). Design and comparison of immersive interactive learning and instructional techniques of 3D virtual laboratories. Presence, 24(2), 93112.CrossRefGoogle Scholar
Selzer, M. N., Gazcon, N. F., & Larrea, M. L. (2019). Effects of virtual presence and learning outcome using low-end virtual reality systems. Displays, 59, 915.CrossRefGoogle Scholar
Shi, A., Wang, Y., & Ding, N. (2019). The effect of game-based immersive virtual reality learning environment on learning outcomes: Designing an intrinsic integrated educational game for pre-class learning. Interactive Learning Environments. Advance online publication. https://doi.org/10.1080/10494820.2019.1681467CrossRefGoogle Scholar
Sitzmann, T. (2011). A meta-analytic examination of the instructional effectiveness of computer-based simulation games. Personnel Psychology, 64, 489528.CrossRefGoogle Scholar
Slater, M. (2009). Place illusion and plausibility can lead to realistic behaviour in immersive virtual environments. Philosophical transactions of the Royal Society of London. Series B, Biological Sciences, 364(1535), 35493557.CrossRefGoogle ScholarPubMed
Slater, M., & Sanchez-Vives, M. V. (2016). Enhancing out lives with immersive virtual reality. Frontiers in Robotics and AI, 3(74), 147.CrossRefGoogle Scholar
Smith, S. J., Farra, S. L., Ulrich, D. L., Hodgson, E., Nicely, S., & Mickle, A. (2018). Effectiveness of two varying levels of virtual reality simulation. Nursing Education Perspectives, 39, E10E15.CrossRefGoogle ScholarPubMed
Starkey, E. M., Spencer, C., Lesniak, K., Tucker, C., & Miller, S. R. (2017). Do technological advancements lead to learning enhancements? An exploration in virtual product dissection. Paper Presented at the ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Cleveland, OH.CrossRefGoogle Scholar
Stepan, K., Zeiger, J., Hanchuk, S., Del Signore, A., Shrivastava, R., Govindaraj, S., & Iloreta, A. (2017). Immersive virtual reality as a teaching tool for neuroanatomy. International Forum of Allergy & Rhinology, 7(10), 10061013.CrossRefGoogle ScholarPubMed
Strzys, M. P., 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 condution. European Journal of Physics, 39, 112.CrossRefGoogle Scholar
Tai, T.-Y., Chen, H. H.-J., & Todd, G. (2020). The impact of a virtual reality app on adolescent efl learners’ vocabulary learning. Computer Assisted Language Learning. Advance online publication. https://doi/org/10.1080/09588221.2020.1752735CrossRefGoogle Scholar
Tang, Y. M., Au, K. M., Lau, H. C. W., Ho, G. T. S., & Wu, C. H. (2020). Evaluating the effectiveness of learning design with mixed reality (MR) in higher education. Virtual Reality, 24, 797807.CrossRefGoogle Scholar
Tekedere, H., & Göke, H. (2016). Examining the effectiveness of augmented reality applications in education: A meta-analysis. International Journal of Environmental and Science Education, 11(16), 94699481.Google Scholar
The Body VR. (2016). The Body VR: Journey into the Cell [Computer software]. The Body VR.Google Scholar
Thees, M., Kapp, S., Strzys, M. P., Beil, F., & Lukowicz, P. (2020). Effects of augmented reality on learning and cognitive load in university laboratory courses. Computers in Human Behavior, 108, 106316.CrossRefGoogle Scholar
Tolentino, L., Birchfield, D., Megowan-Romanowicz, C., Johnson- Glenberg, M. C., Kelliher, A., & Martinez, C. (2009). Teaching and learning in the mixed-reality science classroom. Journal of Science Education and Technology, 18, 501517.CrossRefGoogle Scholar
Visible Body. (2017). Human Anatomy Atlas [Mobile application]. Visible Body.Google Scholar
Webster, R. (2016). Declarative knowledge acquisition in immersive virtual learning environments. Interactive Learning Environments, 24(6), 13191333.CrossRefGoogle Scholar
Winn, W., Windschitl, M., Fruland, R., & Lee, Y. (2002). When does immersion in a virtual environment help students construct understanding? In Proceedings of the International Conference of Learning Societies, October 23–26, 2002. Seattle, WA. pp. 497503.Google Scholar
Yu, S.-J., Sun, J. C.-Y., & Chen, O. T.-C. (2019). Effect of AR-based online wearable guides on university students’ situational interest and learning performance. Universal Access in the Information Society, 18, 287299.CrossRefGoogle Scholar
Zhu, B., Feng, M., Lowe, H., Kesselman, J., Harrison, L., & Dempski, R. E. (2018). Increasing enthusiasm and enhancing learning for biochemistry-laboratory safety with an augmented reality program. Journal of Chemical Education, 95, 17471753.CrossRefGoogle Scholar
Zinchenko, Y. P., Khoroshikh, P. P., Sergievich, A. A., Smirnov, A. S., Tumyalis, A. V., Kovalev, A. I., Gutnikov, S. A., & Golokhvast, K. S. (2020). Virtual reality is more efficient in learning human heart anatomy especially for subjects with ow baseline knowledge. New Ideas in Psychology, 59, 100786.CrossRefGoogle Scholar

References

Ayres, P., & Sweller, J. (2005). The split-attention principle in multimedia learning. In Mayer, R. E. (ed.), The Cambridge Handbook of Multimedia Learning (pp. 135146). Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Baddeley, A. D. (1999). Cognitive Psychology: A Modular Course. Essentials of Human Memory. Hove: Psychology Press.Google Scholar
Butcher, K. R. (2006). Learning from text with diagrams: Promoting mental model development and inference generation. Journal of Educational Psychology, 98(1), 182.CrossRefGoogle Scholar
Chi, M., de Leeuw, N., Chiu, M., & LaVancher, C. (1994). Eliciting self-explanations improves understanding. Cognitive Science, 18, 439477.Google Scholar
Daher, T. A., & Kiewra, K. A. (2016). An investigation of SOAR study strategies for learning from multiple online resources. Contemporary Educational Psychology, 46, 1021.CrossRefGoogle Scholar
Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving students’ learning and comprehension by using effective learning techniques: Promising directions from cognitive and educational psychology. Psychological Science in the Public Interest, 14, 458.CrossRefGoogle ScholarPubMed
Eitel, A., Scheiter, K., & Schüler, A. (2013). How inspecting a picture affects processing of text in multimedia learning. Applied Cognitive Psychology, 27(4), 451461.CrossRefGoogle Scholar
Fiorella, L., & Mayer, R. E. (2015). Learning As a Generative Activity: Eight Learning Strategies That Promote Understanding. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Firetto, C. M., & Van Meter, P. N. (2018). Inspiring integration in college students reading multiple biology texts. Learning and Individual Differences, 65, 123134.CrossRefGoogle Scholar
Fletcher, J. D., & Tobias, S. (2005). The multimedia principle. In Mayer, R. E. (ed.), The Cambridge Handbook of Multimedia Learning (pp. 117133). Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Ginns, P. (2005). Meta-analysis of the modality effect. Learning and Instruction, 15, 313332.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), 414434.CrossRefGoogle Scholar
Igo, L. B., Bruning, R., & McCrudden, M. T. (2005). Exploring differences in students’ copy-and-paste decision making and processing: A mixed-methods study. Journal of Educational Psychology, 97(1), 103116.CrossRefGoogle Scholar
Jairam, D., & Kiewra, K. A. (2010). Helping students soar to success on computers: An investigation of the SOAR study method for computer-based learning. Journal of Educational Psychology, 102(3), 601614.CrossRefGoogle 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, 6270.CrossRefGoogle Scholar
Jonassen, D. H., Beissner, K., & Yacci, M. A. (1993). Structural Knowledge: Techniques for Representing, Assessing, and Acquiring Structural Knowledge. Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
Kendeou, P., van den Broek, P., Helder, A., & Karlsson, J. (2014). A cognitive view of reading comprehension: Implications for reading difficulties. Learning Disabilities Research & Practice, 29(1), 1016.CrossRefGoogle Scholar
Lehman, S., Schraw, G., McCrudden, M. T., & Hartley, K. (2007). Processing and recall of seductive details in scientific text. Contemporary Educational Psychology, 32(4), 569587.CrossRefGoogle Scholar
Mayer, R. E. (2009). Multimedia Learning (2nd ed). New York: Cambridge University Press.CrossRefGoogle Scholar
Mayer, R. E. (2014). Cognitive theory of multimedia learning. In Mayer, R. E. (ed.), The Cambridge Handbook of Multimedia Learning (2nd ed., pp. 4371). New York: Cambridge University Press.CrossRefGoogle Scholar
Mayer, R. E., & Fiorella, L. (2014). Principles for reducing extraneous processing in multimedia learning: Coherence, signaling, redundancy, spatial contiguity, and temporal contiguity principles. In Mayer, R. E. (ed.), The Cambridge Handbook of Multimedia Learning (2nd ed., pp. 279315). New York: Cambridge University Press.CrossRefGoogle Scholar
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), 256265.Google ScholarPubMed
Mayer, R. E., & Moreno, R. (1998). A split-attention effect in multimedia learning: Evidence for dual processing systems in working memory. Journal of Educational Psychology, 90(2), 312320.CrossRefGoogle Scholar
McCrudden, M. T., & Rapp, D. N. (2017). How visual displays affect cognitive processing. Educational Psychology Review, 29(3), 623639.CrossRefGoogle Scholar
McCrudden, M. T., Schraw, G., Lehman, S., & Poliquin, A. (2007). The effect of causal diagrams on text learning. Contemporary Educational Psychology, 32(3), 367388.CrossRefGoogle Scholar
Paivio, A. (1986). Mental Representations: A Dual-Coding Approach. Oxford: Oxford University Press.Google Scholar
Paivio, A. (2007). Mind and Its Evolution: A Dual-Coding Approach. Mahwah, NJ: Erlbaum.Google Scholar
Pressley, M., Yokoi, L., Van Meter, P., van Etten, S., & Freebern, G. (1997). Some of the reasons why preparing for exams is so hard: What can be done to make it easier? Educational Psychology Review, 9, 138.CrossRefGoogle Scholar
Renkl, A., & Scheiter, K. (2017). Studying visual displays: How to instructionally support learning. Educational Psychology Review, 29(3), 599621.CrossRefGoogle Scholar
Rey, G. D. (2012). A review of research and a meta‐analysis of the seductive detail effect. Educational Research Review, 7, 216237.CrossRefGoogle Scholar
Robinson, D. H., & Schraw, G. (1994). Computational efficiency through visual argument: Do graphic organizers communicate relations in text too effectively? Contemporary Educational Psychology, 19(4), 399415.CrossRefGoogle Scholar
Rosch, E., Mervis, C. B., Gray, W. D., Johnson, D. M., & Boyes-Braem, P. (1976). Basic objects in natural categories. Cognitive Psychology, 8(3), 382439.CrossRefGoogle Scholar
Schraw, G., McCrudden, M. T., & Robinson, D. (2013). Visual displays and learning: Theoretical and practical considerations. In Schraw, G., McCrudden, M. T., & Robinson, D. (eds.), Learning through Visual Displays (pp. 317). Charlotte, NC: Information Age Publishing.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, 124.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, 679701.CrossRefGoogle Scholar
Schweppe, J., & Rummer, R. (2016). Integrating written text and graphics as a desirable difficulty in long-term multimedia learning. Computers in Human Behavior, 60, 131137.CrossRefGoogle Scholar
Sundararajan, N., & Adesope, O. (2020). Keep it coherent: A meta-analysis of the seductive details effect. Educational Psychology Review, 32, 707734.CrossRefGoogle Scholar
Sweller, J. (1999). Instructional Design in Technical Areas. Camberwell, Australia: ACER Press.Google Scholar
Sweller, J. (2005). Implications of cognitive load theory for multimedia learning. In Mayer, R. E. (ed.), The Cambridge Handbook of Multimedia Learning (pp. 1930). Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Sweller, J., van Merrienboer, J. J. G., & Paas, F. G. W. C. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10, 251296.CrossRefGoogle Scholar
van Gog, T. (2014). The signaling (or cueing) principle in multimedia learning. In Mayer, R. E. (ed.), The Cambridge Handbook of Multimedia Learning (2nd ed., pp. 263278). New York: Cambridge University Press.CrossRefGoogle Scholar
Van Meter, P. N., Cameron, C., & Waters, J. R. (2017). Effects of response prompts and diagram comprehension ability on text and diagram learning in a college biology course. Learning and Instruction, 49, 188198.CrossRefGoogle Scholar
Van Meter, P. N., Firetto, C. M., Turns, S. R., Litzinger, T. A., Cameron, C. E., & Shaw, C. W. (2016). Improving students’ conceptual reasoning by prompting cognitive operations. Journal of Engineering Education, 105(2), 245277.CrossRefGoogle Scholar
Van Meter, P. N., & Stepanik, N. (2020). Interventions to support learning from multiple external representations. In Van Meter, P. N., List, A., Lombardi, D., & Kendeou, P. (eds.), Handbook of Learning from Multiple Representations and Perspectives (pp. 7691). New York: Routledge.CrossRefGoogle Scholar
Wittrock, M. C. (1989). Generative processes of comprehension. Educational Psychologist, 24(4), 345376.CrossRefGoogle Scholar

References

Albrecht, J. E., & O’Brien, E. J. (1993). Updating a mental model: Maintaining both local and global coherence. Journal of Experimental Psychology: Learning, Memory, and Cognition, 19(5), 10611070.Google Scholar
Anmarkrud, Ø., Bråten, I., & Strømsø, H. I. (2014). Multiple-documents literacy: Strategic processing, source awareness, and argumentation when reading multiple conflicting documents. Learning and Individual Differences, 30, 6476.CrossRefGoogle Scholar
Barzilai, S., Mor-Hagani, S., Zohar, A. R., Shlomi-Elooz, T., & Ben-Yishai, R. (2020). Making sources visible: Promoting multiple document literacy with digital epistemic scaffolds. Computers & Education, 157, 103980.CrossRefGoogle Scholar
Barzilai, S., Zohar, A. R., & Mor-Hagani, S. (2018). Promoting integration of multiple texts: A review of instructional approaches and practices. Educational Psychology Review, 30(3), 973999.CrossRefGoogle Scholar
Blaum, D., Griffin, T. D., Wiley, J., & Britt, M. A. (2017). Thinking about global warming: The effect of policy-related documents and prompts on learning about causes of climate change. Discourse Processes, 54, 303316.CrossRefGoogle Scholar
Braasch, J. L. G., & Bråten, I. (2017). The discrepancy-induced source comprehension (D-ISC) model: Basic assumptions and preliminary evidence. Educational Psychologist, 52(3), 167181.CrossRefGoogle Scholar
Braasch, J. L. G., Bråten, I., Strømsø, H. I., Anmarkrud, Ø., & Ferguson, L. E. (2013). Promoting secondary school students’ evaluation of source features of multiple documents. Contemporary Educational Psychology, 38(3), 180195.CrossRefGoogle Scholar
Braasch, J. L. G., Rouet, J.-F., Vibert, N., & Britt, M. A. (2012). Readers’ use of source information in text comprehension. Memory and Cognition, 40, 450465.CrossRefGoogle ScholarPubMed
Brante, E. W., & Strømsø, H. I. (2018). Sourcing in text comprehension: A review of interventions targeting sourcing skills. Educational Psychology Review, 30(3), 773799.CrossRefGoogle Scholar
Bråten, I., & Strømsø, H. I. (2010). When law students read multiple documents about global warming: Examining the role of topic-specific beliefs about the nature of knowledge and knowing. Instructional Science, 38, 655657.CrossRefGoogle Scholar
Bråten, I., Strømsø, H. I., & Britt, M. A. (2009). Trust matters: Examining the role of source evaluation in students’ construction of meaning within and across multiple texts. Reading Research Quarterly, 44, 628.CrossRefGoogle Scholar
Bråten, I., Strømsø, H. I., Britt, M. A., & Rouet, J.-F. (2011). The role of epistemic beliefs in the comprehension of multiple expository texts: Towards an integrated model. Educational Psychologist, 46, 4870.CrossRefGoogle Scholar
Bråten, I., Strømsø, H. I., & Salmerón, L. (2010). Trust and mistrust when students read multiple information sources about climate change. Learning and Instruction, 21, 180192.CrossRefGoogle Scholar
Breakstone, J., Smith, M., Wineburg, S., Rapaport, A., Carle, J., Garland, M., & Saavedra, A. (2019). Students’ Civic Online Reasoning: A National Portrait. Stanford, CA: Stanford History Education Group & Gibson Consulting.Google Scholar
Brem, S. K., Russell, J., & Weems, L. (2001). Science on the Web: Students’ evaluation of scientific arguments. Discourse Processes, 32, 191213.CrossRefGoogle Scholar
Britt, M. A., & Aglinskas, C. (2002). Improving students’ ability to identify and use source information. Cognition and Instruction, 20, 485522.CrossRefGoogle Scholar
Britt, M. A., Perfetti, C. A., Sandak, R., & Rouet, J. F. (1999). Content integration and source separation in learning from multiple texts. In Goldman, S. R., Graesser, A. C., & van den Broek, P. (eds.), Narrative Comprehension, Causality, and Coherence: Essays in Honor of Tom Trabasso (pp. 209233). Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
Britt, M. A., Perfetti, C. A., van Dyke, J., & Gabrys, G. (2000). The sourcer’s apprentice: A tool for document-supported history instruction. In Stearns, P., Seixas, P., & Wineburg, S. (eds.), Knowing, Teaching and Learning History: National and International Perspectives (pp. 437470). New York: New York University Press.Google Scholar
Britt, M. A., & Rouet, J.-F. (2012). Learning with multiple documents: Component skills and their acquisition. In Lawson, M. J. and Kirby, J. R. (eds.), The Quality of Learning (pp. 276314). New York: Cambridge University Press.Google Scholar
Britt, M. A. & Rouet, J.-F. (2020). Multiple document comprehension. In Zhang, L. (ed.) Oxford Research Encyclopedia of Education (pp. 123). Oxford: Oxford University Press.Google Scholar
Britt, M. A., Rouet, J.-F., Blaum, D., & Millis, K. (2019). A reasoned approach to dealing with fake news. Policy Insights from the Behavioral and Brain Sciences, 6(1), 94101.CrossRefGoogle Scholar
Britt, M. A., Rouet, J.-F., & Braasch, J. L. G. (2013). Documents as entities. In Britt, M. A., Goldman, S. R., & Rouet, J.-F. (eds.), Reading: From Words to Multiple Texts (pp. 160179). New York: Routledge.Google Scholar
Britt, M. A., Rouet, J.-F., & Durik, A. (2018). Literacy beyond Text Comprehension: A Theory of Purposeful Reading. New York: Taylor & Francis.Google Scholar
Britt, M. A., Wiemer-Hasting, P., Larson, A., & Perfetti, C. A. (2004). Automated feedback on source citation in essay writing. International Journal of Artificial Intelligence in Education, 14, 359374.Google Scholar
Butterfuss, R., Kim, J., & Kendeou, P. (2020). Reading Comprehension. In Zhang, L. (ed.) Oxford Research Encyclopedia of Education. (pp. 124). Oxford: Oxford University Press.Google Scholar
Clinton, V. (2019). Reading from paper compared to screens: A systematic review and meta‐analysis. Journal of Research in Reading, 42(2), 288325.CrossRefGoogle Scholar
de Pereyra, G., Britt, M. A., Braasch, J. L. G., & Rouet, J. F. (2014). Reader’s memory for information sources in simple news stories: Effects of text and task features. Journal of Cognitive Psychology, 24(2), 187204.CrossRefGoogle Scholar
Delgado, P., Vargas, C., Ackerman, R., & Salmerón, L. (2018). Don’t throw away your printed books: A meta-analysis on the effects of reading media on reading comprehension. Educational Research Review, 25, 2338.CrossRefGoogle Scholar
Goldman, S. R., Braasch, J. L. G., Wiley, J., Graesser, A. C., & Brodowinska, K. (2012). Comprehending and learning from internet sources: Processing patterns of better and poorer learners. Reading Research Quarterly, 47, 356381.Google Scholar
Goldman, S. R., & Brand-Gruwel, S. (2018). Learning from multiple sources in a digital society. In Fischer, F., Hmelo-Silver, C. E., Goldman, S. R., & Reimann, P. (eds.), International Handbook of the Learning Sciences (pp. 8695). New York: Routledge.CrossRefGoogle Scholar
Goldman, S. R., Greenleaf, C., Yukhymenko-Lescroart, M., Brown, W., Ko, M. L. M., Emig, J. M., George, M., Wallace, P., Blaum, D., & Britt, M. A. (2019). Explanatory modeling in science through text-based investigation: Testing the efficacy of the Project READI intervention approach. American Educational Research Journal, 56(4), 11481216.CrossRefGoogle Scholar
Graesser, A. C., Wiley, J., Goldman, S. R., O’Reilly, T., Jeon, M., & McDaniel, B. (2007). SEEK Web Tutor: Fostering a critical stance while exploring the causes of volcanic eruption. Metacognition and Learning, 2, 89105.CrossRefGoogle Scholar
Kammerer, Y., & Gerjets, P. (2012). Effects of search interface and Internet-specific epistemic beliefs on source evaluations during web search for medical information: An eye-tracking study. Behaviour & Information Technology, 31, 8397.CrossRefGoogle Scholar
Kammerer, Y., Kalbfell, E., & Gerjets, P. (2016). Is this information source commercially biased? How contradictions between web pages stimulate the consideration of source information. Discourse Processes, 53(5–6), 430456.CrossRefGoogle Scholar
Keck, D., Kammerer, Y., & Starauschek, E. (2015). Reading science texts online: Does source information influence the identification of contradictions within texts? Computers and Education, 82, 442449.CrossRefGoogle Scholar
Kienhues, D., Stadtler, M., & Bromme, R. (2011). Dealing with conflicting or consistent medical information on the web: When expert information breeds laypersons’ doubts about experts. Learning and Instruction, 21, 193204.CrossRefGoogle Scholar
Kim, H. J. & Millis, K. (2006). The influence of sourcing and relatedness on event integration. Discourse Processes, 41, 5165.CrossRefGoogle Scholar
Kintsch, W. (1998). Comprehension: A Paradigm for Cognition. Cambridge University Press.Google Scholar
Kintsch, W., & van Dijk, T. A. (1978). Toward a model of text comprehension and production. Psychological Review, 85, 363394.CrossRefGoogle Scholar
List, A., & Alexander,