Abstract
In this study, considering the effect of interactive learning environments on human cognition, we have examined extraneous processing effects of multimedia materials on cognitive load, metacognitive judgments and learning outcomes. This study examines Augmented Reality Learning Environments (ARLE) and Virtual Reality Learning Environments (VRLE) as interactive learning environments. Learners, assigned randomly to one of seven experimental conditions, participated in computer-assisted instructional presentations for Augmented Reality Learning Environments and mobile-assisted instructional presentations for Virtual Reality Learning Environments. Participants’ working memory capacity and prior knowledge levels were scrutinized as control variables. Findings revealed no significant differences in the learning outcomes and metacognitive judgments, although significant differences were reported in the objective cognitive load. Therefore, we faced some results that contradict our hypotheses. In addition, we found a significant difference in terms of interactive learning environments’ effect on metacognitive judgments. Conversely, we found that metacognitive judgments are affected directly by learning environments. Finally, we discussed theoretical and practical implications for further research, based on experimental studies and approaches in Cognitive Theory of Multimedia Learning and Cognitive Load Theory, in terms of interactive learning environments.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data Availability
Due to the nature of the experimental procedure, participants of the current research did not agree for their data to be shared publicly, so supporting data is not available.
References
Ainsworth, S. (2006). DeFT: A conceptual framework for considering learning with multiple representations. Learning and Instruction, 16(3), 183–198. https://doi.org/10.1016/j.learninstruc.2006.03.001
Aitamurto, T., Aymerich-Franch, L., Saldivar, J., Kircos, C., Sadeghi, Y., & Sakshuwong, S. (2020). Examining augmented reality in journalism: Presence, knowledge gain, and perceived visual authenticity. New Media & Society. https://doi.org/10.1177/1461444820951925
Albus, P., Vogt, A., & Seufert, T. (2021). Signaling in virtual reality influences learning outcome and cognitive load. Computers & Education, 166, 104154. https://doi.org/10.1016/j.compedu.2021.104154
Alter, A. L. (2013). The benefits of cognitive disfluency. Current Directions in Psychological Science, 22(6), 437–442. https://doi.org/10.1177/0963721413498894
Anmarkrud, Ø., Andresen, A., & Bråten, I. (2019). Cognitive load and working memory in multimedia learning: Conceptual and measurement issues. Educational Psychologist, 1–23. https://doi.org/10.1080/00461520.2018.1554484
Arbuckle, T. Y., & Cuddy, L. L. (1969). Discrimination of item strength at time of presentation. Journal of Experimental Psychology, 81, 126–131. https://doi.org/10.1037/h0027455
Azevedo, R. (2014). Multimedia learning of metacognitive strategies. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (pp. 647–672). Cambridge University Press. https://doi.org/10.1017/CBO9781139547369.032
Azevedo, R., Moos, D. C., Johnson, A. M., & Chauncey, A. D. (2010). Measuring cognitive and metacognitive regulatory processes during hypermedia learning: Issues and challenges. Educational Psychologist, 45(4), 210–223. https://doi.org/10.1080/00461520.2010.515934
Azuma, R. T. (1997). A survey of augmented reality. Presence-Teleoperators and Virtual Environments, 6(4), 355–385. https://doi.org/10.1162/pres.1997.6.4.355
Bacca, J., Baldiris, S., Fabregat, R., & Kinshuk. (2018). Insights into the factors influencing student motivation in augmented reality learning experiences in vocational education and training. Frontiers in Psychology, 9, 1486. https://doi.org/10.3389/fpsyg.2018.01486
Baddeley, A. D., & Hitch, G. (1974). Working memory. The Psychology of Learning and Motivation, 8, 47–89. https://doi.org/10.1016/S0079-7421(08)60452-1
Bailenson, J. N., Yee, N., Blascovich, J., Beall, A. C., Lundbald, N., & Jin, M. (2008). The use of immersive virtual reality in the learning sciences: Digital transformations of teachers, students, and social context. The Journal of the Learning Sciences, 17, 102–141. https://doi.org/10.1080/10508400701793141
Barrett, A., Pack, A., Guo, Y., & Wang, N. (2020). Technology acceptance model and multi-user virtual reality learning environments for Chinese language education. Interactive Learning Environments, 1-18. https://doi.org/10.1080/10494820.2020.1855209
Besken, M., & Mulligan, N. W. (2014). Perceptual fluency, auditory generation, and metamemory: analyzing the perceptual fluency hypothesis in the auditory modality. Journal of Experimental Psychology: Learning, Memory, and Cognition, 40(2), 429. https://doi.org/10.1037/a0034407
Billinghurst, M., Kato, H., & Poupyrev, I. (2001). The MagicBook: moving seamlessly between reality and virtuality. IEEE Computer Graphics & Applications, 21(3), 6–8. https://doi.org/10.1109/38.920621
Bjork, E. L., & Bjork, R. A. (2011). Making things hard on yourself, but in a good way: creating desirable difficulties to enhance learning. In M. A. Gernsbacher, R. W. Pew, L. M. Hough, & J. R. Pomerantz (Eds.), Psychology and the real world: Essays illustrating fundamental contributions to society (pp. 56-64). Worth Publishers.
Bodemer, D., Ploetzner, R., Feuerlein, I., & Spada, H. (2004). The active integration of information during learning with dynamic and interactive visualisations. Learning and Instruction, 14(3), 325–341. https://doi.org/10.1016/j.learninstruc.2004.06.006
Brünken, R., Plass, J. L., & Leutner, D. (2003). Direct measurement of cognitive load in multimedia learning. Educational Psychologist, 38(1), 53–61. https://doi.org/10.1207/S15326985EP3801_7
Brünken, R., Seufert, T., & Paas, F. (2011). Measuring cognitive load. In J. L. Plass, R. Moreno, & R. Brünken (Eds.), Cognitive load theory (pp. 181-202). Cambridge University Press.
Brünken, R., Steinbacher, S., Plass, J. L., & Leutner, D. (2002). Assessment of cognitive load in multimedia learning using dual-task methodology. Experimental Psychology, 49(2), 109–119. https://doi.org/10.1027//1618-3169.49.2.109
Bujak, K. R., Radu, I., Catrambone, R., MacIntyre, B., Zheng, R., & Golubski, G. (2013). A psychological perspective on augmented reality in the mathematics classroom. Computers & Education, 68, 536–544. https://doi.org/10.1016/j.compedu.2013.02.017
Bursali, H., & Yilmaz, R. M. (2019). Effect of augmented reality applications on secondary school students' reading comprehension and learning permanency. Computers in Human Behavior, 95, 126–135. https://doi.org/10.1016/j.chb.2019.01.035
Butcher, K. R. (2014). The multimedia principle. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (2nd ed., pp. 174–206). Cambridge University Press. https://doi.org/10.1017/CBO9781139547369.010
Callaghan, M. N., Long, J. J., van Es, E. A., Reich, S. M., & Rutherford, T. (2018). How teachers integrate a math computer game: Professional development use, teaching practices, and student achievement. Journal of Computer Assisted Learning, 34, 10–19. https://doi.org/10.1111/jcal.12209
Caudell, T. P., & Mizell, D. W. (1992). Augmented reality: An application of heads-up display technology to manual manufacturing processes. In Proceedings of the twenty-fifth Hawaii international conference on system sciences. https://doi.org/10.1109/HICSS.1992.183317
Chandler, P., & Sweller, J. (1991). Cognitive load theory and the format of instruction. Cognition and Instruction, 8(4), 293–332. https://doi.org/10.1207/s1532690xci0804_2
Chandler, P., & Sweller, J. (1992). The split-attention effect as a factor in the design of instruction. British Journal of Educational Psychology, 62(2), 233–246. https://doi.org/10.1111/j.2044-8279.1992.tb01017.x
Chang, G., Morreale, P., & Medicherla, P. (2010). Applications of augmented reality systems in education. Proceedings of Society for Information Technology and Teacher Education International Conference, 2010 (1), 1380–1385.
Chang, S. C., & Hwang, G. J. (2018). Impacts of an augmented reality-based flipped learning guiding approach on students’ scientific project performance and perceptions. Computers & Education, 125, 226–239. https://doi.org/10.1016/j.compedu.2018.06.007
Chang, S. C., Hsu, T. C., Chen, Y. N., & Jong, M. S. Y. (2020). The effects of spherical video-based virtual reality implementation on students’ natural science learning effectiveness. Interactive Learning Environments, 28(7), 915–929. https://doi.org/10.1080/10494820.2018.1548490
Chavan, C. F., Mouthon, M., Draganski, B., van der Zwaag, W., & Spierer, L. (2015). Differential patterns of functional and structural plasticity within and between inferior frontal gyri support training-induced improvements in inhibitory control proficiency. Human Brain Mapping, 36(7), 2527–2543. https://doi.org/10.1002/hbm.22789
Chen, C., Toh, S., & Ismail, W. (2005). Are learning styles relevant to virtual reality? Journal of Research on Technology in Education, 38(2), 120–128. https://doi.org/10.1080/15391523.2005.10782453
Chen, L. T., & Liu, L. (2019). Content Analysis of Statistical Power in Educational Technology Research: Sample Size Matters. International Journal of Technology in Teaching & Learning, 15(1), 49–75.
Chen, R., & Wang, X. (2008). An empirical study on tangible augmented reality learning space for design skill transfer. Tsinghua Science and Technology, 13(S1), 13–18. https://doi.org/10.1016/S1007-0214(08)70120-2
Cheng, K.-H., & Tsai, C.-C. (2013). Affordances of augmented reality in science learning: Suggestions for future research. Journal of Science Education and Technology, 22(4), 449–462. https://doi.org/10.1007/s10956-012-9405-9
Chin, K. Y., Wang, C. S., & Chen, Y. L. (2019). Effects of an augmented reality-based mobile system on students’ learning achievements and motivation for a liberal arts course. Interactive Learning Environments, 27(7), 927–941. https://doi.org/10.1080/10494820.2018.1504308
Chittaro, L., & Ranon, R. (2007). Web3D technologies in learning, education and training: motivations, issues, opportunities. Computers & Education, 49, 3–18. https://doi.org/10.1016/j.compedu.2005.06.002
Choi, H. H., van Merriënboer, J. J., & Paas, F. (2014). Effects of the physical environment on cognitive load and learning: towards a new model of cognitive load. Educational Psychology Review, 26(2), 225–244. https://doi.org/10.1007/s10648-014-9262-6
Chou, P. N., Chang, C. C., & Lin, C. H. (2017). BYOD or not: A comparison of two assessment strategies for student learning. Computers in Human Behavior, 74, 63–71. https://doi.org/10.1016/j.chb.2017.04.024
Cierniak, G., Scheiter, K., & Gerjets, P. (2009). Explaining the split-attention effect: Is the reduction of extraneous cognitive load accompanied by an increase in germane cognitive load? Computers in Human Behavior, 25(2), 315–324. https://doi.org/10.1016/j.chb.2008.12.020
Clore, G. L., & Parrott, W. G. (1994). Cognitive feelings and metacognitive judgments. European Journal of Social Psychology, 24(1), 101–115. https://doi.org/10.1002/ejsp.2420240108
Cowan, N. (2001). The magical number 4 in short-term memory: A reconsideration of mental storage capacity. Behavioral and Brain Sciences, 24(1), 87–114. https://doi.org/10.1017/s0140525x01003922
de Vasconcelos, D. F. P., Júnior, E. A. L., de Oliveira Malaquias, F. F., Oliveira, L. A., & Cardoso, A. (2020). A virtual reality based serious game to aid in the literacy of students with intellectual disability: Design principles and evaluation. Technology and Disability, 32(3), 149–157. https://doi.org/10.3233/TAD-200272
Dede, C. (2000). Emerging influences of information technology on school curriculum. Journal of Curriculum Studies, 32(2), 282–303. https://doi.org/10.1080/002202700182763
Dede, C. (2009). Immersive interfaces for engagement and learning. Science, 323(5910), 66–69. https://doi.org/10.1126/science.1167311
Dehghani, M., Mohammadhasani, N., Hoseinzade Ghalevandi, M., & Azimi, E. (2020). Applying AR-based infographics to enhance learning of the heart and cardiac cycle in biology class. Interactive Learning Environments, 1-16. https://doi.org/10.1080/10494820.2020.1765394
Di Serio, Á., Ibáñez, M. B., & Kloos, C. D. (2013). Impact of an augmented reality system on students' motivation for a visual art course. Computers & Education, 68, 586–596. https://doi.org/10.1016/j.compedu.2012.03.002
Dindar, M., & Akbulut, Y. (2016). Effects of multitasking on retention and topic interest. Learning and Instruction, 41, 94–105. https://doi.org/10.1016/j.learninstruc.2015.10.005
Double, K. S., Birney, D. P., & Walker, S. A. (2018). A meta-analysis and systematic review of reactivity to judgements of learning. Memory, 26(6), 741–750. https://doi.org/10.1080/09658211.2017.1404111
Dunleavy, M., Dede, C., & Mitchell, R. (2009). Affordances and limitations of immersive participatory augmented reality simulations for teaching and learning. Journal of Science Education and Technology, 18, 7–22. https://doi.org/10.1007/s10956-008-9119-1
Dunlosky, J., & Lipko, A. (2007). Metacomprehension: A brief history and how to improve its accuracy. Current Directions in Psychological Science, 16, 228–232. https://doi.org/10.1111/j.1467-8721.2007.00509.x
Dunlosky, J., & Metcalfe, J. (2008). Metacognition. Sage Publications.
Dunlosky, J., & Mueller, M. L. (2016). Recommendations for exploring the disfluency hypothesis for establishing whether perceptually degrading materials impacts performance. Metacognition and Learning, 11(1), 123–131. https://doi.org/10.1007/s11409-016-9155-9
Dunlosky, J., & Nelson, T. O. (1992). Importance of the kind of cue for judgements of learning (JOLs) and the delayed-JOL effect. Memory & Cognition, 20, 374–380. https://doi.org/10.3758/bf03210921
Dunlosky, J., & Nelson, T. O. (1997). Similarity between the cue for judgements of learning (JOL) and the cue for test is not the primary determinant of JOL accuracy. Journal of Memory and Language, 36, 34–49. https://doi.org/10.1006/jmla.1996.2476
Dunlosky, J., Serra, M. J., Matvey, G., & Rawson, K. A. (2005). Second-order judgments about judgments of learning. The Journal of General Psychology, 132(4), 335–346. https://doi.org/10.3200/GENP.132.4.335-346
Dunning, D., Johnson, K., Ehrlinger, J., & Kruger, J. (2003). Why people fail to recognize their own incompetence. Current Directions in Psychological Science, 12(3), 83–87. https://doi.org/10.1111/1467-8721.01235
Eitel, A., & Kühl, T. (2016). Effects of disfluency and test expectancy on learning with text. Metacognition and Learning, 11, 107–121. https://doi.org/10.1007/s11409-015-9145-3
Eitel, A., Kühl, T., Scheiter, K., & Gerjets, P. (2014). Disfluency Meets Cognitive Load in Multimedia Learning: Does Harder-to-Read Mean Better-to-Understand? Applied Cognitive Psychology, 28(4), 488–501. https://doi.org/10.1002/acp.3004
Erez, A., & Isen, A. M. (2002). The influence of positive affect on the components of expectancy motivation. Journal of Applied psychology, 87(6), 1055–1067. https://doi.org/10.1037/0021-9010.87.6.1055
Fonseca, D., Martí, N., Redondo, E., Navarro, I., & Sánchez, A. (2014). Relationship between student profile, tool use, participation, and academic performance with the use of Augmented Reality technology for visualized architecture models. Computers in Human Behavior, 31, 434–445. https://doi.org/10.1016/j.chb.2013.03.006
Francis, P., Broughan, C., Foster, C., & Wilson, C. (2020). Thinking critically about learning analytics, student outcomes, and equity of attainment. Assessment & Evaluation in Higher Education, 45(S1), 811–821. https://doi.org/10.1080/02602938.2019.1691975
French, M. M. J., Blood, A., Bright, N. D., Futak, D., Grohmann, M. J., Hasthorpe, A., Heritage, J., Poland, R., Reece, S., & Tabor, J. (2013). Changing fonts in education: how the benefits vary with ability and dyslexia. The Journal of Educational Research, 106(4), 301–304. https://doi.org/10.1080/00220671.2012.736430
Garzón, J. (2021). An Overview of Twenty-Five Years of Augmented Reality in Education. Multimodal Technologies and Interaction, 5(7), 37. https://doi.org/10.3390/mti5070037
Garzón, J., & Acevedo, J. (2019). A Meta-analysis of the impact of Augmented Reality on students’ learning effectiveness. Educational Research Review., 27, 244–260. https://doi.org/10.1016/j.edurev.2019.04.001
Garzón, J., Baldiris, S., Gutiérrez, J., & Pavón, J. (2020). How do pedagogical approaches affect the impact of augmented reality on education? A meta-analysis and research synthesis. Educational Research Review, 31, 100334. https://doi.org/10.1016/j.edurev.2020.100334
Garzón, J., Pavón, J., & Baldiris, S. (2019). Systematic review and meta-analysis of augmented reality in educational settings. Virtual Reality, 23(4), 447–459. https://doi.org/10.1007/s10055-019-00379-9
Godden, D., & Baddeley, A. D. (1980). When does context influence recognition memory? British Journal of Psychology, 71(1), 99–104. https://doi.org/10.1016/j.learninstruc.2005.07.001
Greene, J. A., & Azevedo, R. (2009). A macro-level analysis of SRL processes and their relations to the acquisition of a sophisticated mental model of a complex system. Contemporary Educational Psychology, 34(1), 18–29. https://doi.org/10.1016/j.cedpsych.2008.05.006
Harp, S. F., & Mayer, R. E. (1997). The role of interest in learning from scientific text and illustrations: On the distinction between emotional interest and cognitive interest. Journal of Educational Psychology, 89(1), 92–102. https://doi.org/10.1037/0022-0663.89.1.92
Harp, S. F., & Mayer, R. E. (1998). How seductive details do their damage: A theory of cognitive interest in science learning. Journal of Educational Psychology, 90(3), 414–434. https://doi.org/10.1037//0022-0663.90.3.414
Higgins, S., Hall, E., Wall, K., Woolner, P., & McCaughey, C. (2005). The impact of school environments: A literature review. Design Council.
Holden, C. L., & Sykes, J. M. (2011). Leveraging mobile games for place-based language learning. International Journal of Game-Based Learning, 1(2), 1–18. https://doi.org/10.4018/978-1-4666-1864-0.ch003
Horvath, L. (2014). Influence of Personality Factors on Working Memory Training and Transfer Gains. (Master thesis) University of Zurich, Zurich, Switzerland. 10.3758/s13428-012-0e224-y
Huang, H. M., Rauch, U., & Liaw, S. S. (2010). Investigating learners’ attitudes toward virtual reality learning environments: Based on a constructivist approach. Computers & Education, 55(3), 1171–1182. https://doi.org/10.1016/j.compedu.2010.05.014
Huck, S. W. (2008). Reading statistics and research (5th ed.). Pearson Education/Allyn & Bacon.
Huck, S. W. (2012). Reading statistics and research (6th ed.). Pearson.
Ilic, U., & Akbulut, Y. (2019). Effect of disfluency on learning outcomes, metacognitive judgments and cognitive load in computer assisted learning environments. Computers in Human Behavior, 99, 310–321. https://doi.org/10.1016/j.chb.2019.06.001
Izard, S. G., Méndez, J. A. J., Palomera, P. R., & García-Peñalvo, F. J. (2019). Applications of virtual and augmented reality in biomedical imaging. Journal of Medical Systems, 43(4), 1–5. https://doi.org/10.1007/s10916-019-1239-z
Jia, L., Hirt, E. R., & Karpen, S. C. (2009). Lessons from a faraway land: The effect of spatial distance on creative cognition. Journal of Experimental Social Psychology, 45(5), 1127–1131. https://doi.org/10.1016/j.jesp.2009.05.015
Kalyuga, S., Chandler, P., & Sweller, J. (1998). Levels of expertise and instructional design. Human Factors, 40(1), 1–17. https://doi.org/10.1518/001872098779480587
Kalyuga, S., Chandler, P., & Sweller, J. (1999). Managing split-attention and redundancy in multimedia instruction. Applied Cognitive Psychology, 13(4), 351–371.
Kaplan, A. D., Cruit, J., Endsley, M., Beers, S. M., Sawyer, B. D., & Hancock, P. A. (2021). The effects of virtual reality, augmented reality, and mixed reality as training enhancement methods: A meta-analysis. Human Factors, 63(4), 706–726. https://doi.org/10.1177/0018720820904229
Katell, M., Dechesne, F., Koops, B. J., & Meessen, P. (2019). Seeing the whole picture: visualising socio-spatial power through augmented reality. Law, Innovation and Technology, 11(2), 279–310. https://doi.org/10.1080/17579961.2019.1665800
Kelemen, W. L., & Weaver III, C. A. (1997). Enhanced memory at delays: Why do judgments of learning improve over time? Journal of Experimental Psychology: Learning, Memory, and Cognition, 23(6), 1394–1409. https://doi.org/10.1037/0278-7393.23.6.1394
Kester, L., Kirschner, P. A., & Van Merriënboer, J. J. (2005). The management of cognitive load during complex cognitive skill acquisition by means of computer-simulated problem solving. British Journal of Educational Psychology, 75(1), 71–85. https://doi.org/10.1348/000709904X19254
Kılıç, E., & Karadeniz, Ş. (2004). Hiper ortamlarda öğrencilerin bilişsel yüklenme ve kaybolma düzeylerinin belirlenmesi [Specifying students’ cognitive load and disorientation level in hypermedia]. Educational Administration-Theory and Practice, 40(40), 562–579.
Kipper, G., & Rampolla, J. (2013). Augmented reality: An emerging technologies guide to AR. Elsevier.
Klopfer, E. (2008). Augmented learning: Research and design of mobile educational games. MIT Press.
Klopfer, E., & Squire, K. (2008). Environmental Detectives—the development of an augmented reality platform for environmental simulations. Educational Technology Research and Development, 56(2), 203–228. https://doi.org/10.1007/s11423-007-9037-6
Knez, I., & Hygge, S. (2002). Irrelevant speech and indoor lighting: effects on cognitive performance and self-reported affect. Applied Cognitive Psychology, 16(6), 709–718. https://doi.org/10.1002/acp.829
Koller, C. I., Wetter, O. E., & Hofer, F. (2015). What is suspicious when trying to be inconspicuous? Criminal intentions inferred from nonverbal behavioral cues. Perception, 44(6), 679–708. https://doi.org/10.1177/0301006615594271
Koriat, A., & Goldsmith, M. (1996). Monitoring and control processes in the strategic regulation of memory accuracy. Psychological Review, 103(3), 490–517. https://doi.org/10.1037/0033-295x.103.3.490
Krajčovič, M., Gabajová, G., Matys, M., Grznár, P., Dulina, Ľ., & Kohár, R. (2021). 3D interactive learning environment as a tool for knowledge, transfer and retention. Sustainability, 13(14), 7916. https://doi.org/10.3390/su13147916
Küçük, S., Yılmaz, R. M., Baydaş, Ö., & Göktaş, Y. (2014). Augmented reality applications attitude scale in secondary schools: Validity and reliability study. Education and Science, 39(176), 383–392. https://doi.org/10.15390/EB.2014.3590
Kühl, T., Eitel, A., Damnik, G., & Körndle, H. (2014). The impact of disfluency, pacing, and students’ need for cognition on learning with multimedia. Computers in Human Behavior, 35, 189–198. https://doi.org/10.1016/j.chb.2014.03.004
Kye, B., & Kim, Y. (2008). Investigation of the relationships between media characteristics, presence, flow, and learning effects in augmented reality based learning augmented reality. International Journal, 2(1), 4–14. https://doi.org/10.1007/978-3-8348-9313-0_3
Lai, A.-F., Chen, C.-H., & Lee, G.-Y. (2019). An augmented reality-based learning approach to enhancing students’ science reading performances from the perspective of the cognitive load theory. British Journal of Educational Technology, 50(1), 232–247. https://doi.org/10.1111/bjet.12716
Lan, L., Wargocki, P., Wyon, D. P., & Lian, Z. (2011). Effects of thermal discomfort in an office on perceived air quality, SBS symptoms, physiological responses, and human performance. Indoor Air, 21(5), 376–390. https://doi.org/10.1111/j.1600-0668.2011.00714.x
Langer, N., von Bastian, C. C., Wirz, H., Oberauer, K., & Jäncke, L. (2013). The effects of working memory training on functional brain network efficiency. Cortex, 49(9), 2424–2438. https://doi.org/10.1016/j.cortex.2013.01.008
Larmuseau, C., Evens, M., Elen, J., Van Den Noortgate, W., Desmet, P., & Depaepe, F. (2018). The relationship between acceptance, actual Use of a virtual learning environment and performance: An ecological approach. Journal of Computers in Education, 5(1), 95–111. https://doi.org/10.1007/s40692-018-0098-9
Lau, C., Sinclair, J., Taub, M., Azevedo, R., & Jang, E. E. (2017). Transitioning self-regulated learning profiles in hypermedia-learning environments. In Proceedings of the annual meeting of the international conference on Learning Analytics and Knowledge (LAK)(pp. 198–202). Vancouver, British Columbia, Canada: ACM. https://doi.org/10.1145/3027385.3027443
Lee, E. A.-L., & Wong, K. W. (2008). A review of using virtual reality for learning. In Z. Pan, A. D. Cheok, W. Müller, & A. El Rhalibi (Eds.), Transactions on edutainment I: Vol. 5080 Lecture notes in computer science (pp. 231-241). Berlin: Springer. https://doi.org/10.1007/978-3-540-69744-2_18
Lee, H. (2014). Measuring cognitive load with electroencephalography and self-report: focus on the effect of English-medium learning for Korean students. Educational Psychology, 34(7), 838–848. https://doi.org/10.1080/01443410.2013.860217
Lehmann, J., Goussios, C., & Seufert, T. (2015). Working memory capacity and disfluency effect: An aptitude-treatment-interaction study. Metacognition and Learning, 11(1), 89–105. https://doi.org/10.1007/s11409-015-9149-z
Lin, T. J., & Lan, Y. J. (2015). Language learning in Virtual Reality environments: Past, present, and future. Educational Technology & Society, 18(4), 486–497 https://www.jstor.org/stable/jeductechsoci.18.4.486
Lindner, M. A., Eitel, A., Barenthien, J., & Köller, O. (2018a). An integrative study on learning and testing with multimedia: Effects on students’ performance and metacognition. Learning and Instruction. https://doi.org/10.1016/j.learninstruc.2018.01.002
Lindner, M. A., Ihme, J. M., Saß, S., & Köller, O. (2018b). How representational pictures enhance students’ performance and test-taking pleasure in low-stakes assessment. European Journal of Psychological Assessment, 34(6), 376–385. https://doi.org/10.1027/1015-5759/a000351
Lu, Z. J. (2012). Learning with mobile technologies handheld devices, and smart phones: Innovative methods. (pp. 1-272). IGI-Global. https://doi.org/10.4018/978-1-4666-0936-5.
Lv, Z. (2020). Virtual reality in the context of Internet of Things. Neural Computing and Applications, 32(13), 9593–9602. https://doi.org/10.1007/s00521-019-04472-7
Magreehan, D. A., Serra, M. J., Schwartz, N. H., & Narciss, S. (2015). Further boundary conditions for the effects of perceptual disfluency on judgments of learning. Metacognition and Learning, 11(1), 35–56. https://doi.org/10.1007/s11409-015-9147-1
Makhataeva, Z., & Varol, H. A. (2020). Augmented reality for robotics: a review. Robotics, 9(2), 21. https://doi.org/10.3390/robotics9020021
Makransky, G., 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, 225–236. https://doi.org/10.1016/j.learninstruc.2017.12.007
Martens, R., Bastiaens, T., & Kirschner, P. A. (2007). New learning design in distance education: The impact on student perception and motivation. Distance Education, 28(1), 81–93. https://doi.org/10.1080/01587910701305327
Martín-Gutiérrez, J. M., Añorbe-Díaz, C. E., & Beatriz González-Marrero, A. (2017). Virtual technologies trends in education. Eurasia Journal of Mathematics Science & Technology Education, 13(2), 469–486. https://doi.org/10.12973/eurasia.2017.00626a
Martín-Gutiérrez, J., Saorín, J. L., Contero, M., Alcañiz, M., Pérez-López, D. C., & Ortega, M. (2010). Design and validation of an augmented book for spatial abilities development in engineering students. Computers & Graphics, 34(1), 77–91. https://doi.org/10.1016/j.cag.2009.11.003
Matcha, W., & Rambli, D. R. A. (2013). Exploratory study on collaborative interaction through the use of augmented reality in science learning. Procedia Computer Science, 25, 144–153. https://doi.org/10.1016/j.procs.2013.11.018
Matvey, G., Dunlosky, J., & Guttentag, R. (2001). Fluency of retrieval at study affects judgments of learning (JOLs): An analytic or nonanalytic basis for JOLs? Memory & Cognition, 29(2), 222–233. https://doi.org/10.3758/bf03194916
Matvey, G., Dunlosky, J., & Schwartz, B. (2006). The effects of categorical relatedness on judgements of learning (JOLs). Memory, 14(2), 253–261. https://doi.org/10.1080/09658210500216844
Mautone, P. D., & Mayer, R. E. (2001). Signaling as a cognitive guide in multimedia learning. Journal of Educational Psychology, 93(2), 377–389. https://doi.org/10.1037/0022-0663.93.2.377
Mayer, R. E. & Fiorella, L. (2014). Principles for reducing extraneous processing in multimedia learning: Coherence, signaling, redundancy, spatial contiguity, and temporal contiguity. In: Mayer R (ed.) The Cambridge Handbook of Multimedia Learning (2nd ed.). New York: Cambridge University Press, pp. 345–368. https://doi.org/10.1017/CBO9781139547369.015
Mayer, R. E. (2001). Multimedia learning. Cambridge University Press. https://doi.org/10.1017/CBO9781139164603
Mayer, R. E. (2009). Multimedia learning (2nd ed.). Cambridge University Press. https://doi.org/10.1017/CBO9780511811678
Mayer, R. E. (2014). Cognitive theory of multimedia learning. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (2nd ed., pp. 43–71). Cambridge University Press. https://doi.org/10.1017/CBO9781139547369.005
Mayer, R. E. (Ed.). (2005). The Cambridge handbook of multimedia learning. Cambridge University Press. https://doi.org/10.1017/CBO9781139547369
Mayer, R. E., & Moreno, R. (2002). Animation as an aid to multimedia learning. Educational Psychology Review, 14(1), 87–99. https://doi.org/10.1023/A:1013184611077
Mayer, R. E., Steinhoff, K., Bower, G., & Mars, R. (1995). A generative theory of textbook design: Using annotated illustrations to foster meaningful learning of science text. Educational Technology Research and Development, 43(1), 31–41. https://doi.org/10.1007/BF02300480
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, 29–40. https://doi.org/10.1016/j.compedu.2013.07.033
Metcalfe, J. (2009). Metacognitive judgments and control of study. Current Directions in Psychological Science, 18(3), 159–163. https://doi.org/10.1111/j.1467-8721.2009.01628.x
Metcalfe, J., & Finn, B. (2008). Familiarity and retrieval processes in delayed judgments of learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 34, 1084–1097. https://doi.org/10.1037/a0012580
Mikropoulos, T. A., & Natsis, A. (2011). Educational virtual environments: A ten-year review of empirical research (1999–2009). Computers & Education, 56(3), 769–780. https://doi.org/10.1016/j.compedu.2010.10.020
Monahan, T., McArdle, G., & Bertolotto, M. (2008). Virtual reality for collaborative e-learning. Computers & Education, 50(4), 1339–1353. https://doi.org/10.1016/j.compedu.2006.12.008
Moreno, R., & Mayer, R. E. (1999). Cognitive principles of multimedia learning: The role of modality and contiguity. Journal of Educational Psychology, 91(2), 358–368. https://doi.org/10.1037/0022-0663.91.2.358
Moreno, R., & Mayer, R. E. (2000). A coherence effect in multimedia learning: The case for minimizing irrelevant sounds in the design of multimedia messages. Journal of Educational Psychology, 92, 117–125. https://doi.org/10.1037/0022-0663.92.1.117
Moreno, R., & Mayer, R. E. (2002a). Verbal redundancy in multimedia learning: When reading helps listening. Journal of Educational Psychology, 94(1), 156–163. https://doi.org/10.1037/0022-0663.94.1.156
Moreno, R., & Mayer, R. E. (2002b). Learning science in virtual reality multimedia environments: Role of methods and media. Journal of Educational Psychology, 94(3), 598–610. https://doi.org/10.1037/0022-0663.94.3.598
Mousavi, S. Y., Low, R., & Sweller, J. (1995). Reducing cognitive load by mixing auditory and visual presentation modes. Journal of Educational Psychology, 87(2), 319–334. https://doi.org/10.1037/0022-0663.87.2.319
Mudrick, N. V., Azevedo, R., & Taub, M. (2019). Integrating metacognitive judgments and eye movements using sequential pattern mining to understand processes underlying multimedia learning. Computers in Human Behavior, 96, 223–234. https://doi.org/10.1016/j.chb.2018.06.028
Mutlu-Bayraktar, D., Cosgun, V., & Altan, T. (2019). Cognitive load in multimedia learning environments: A systematic review. Computers & Education, 141, 103618. https://doi.org/10.1016/j.compedu.2019.103618
Nedim, S. (2013). The effect of augmented reality treatment on learning, cognitive load, and spatial visualization abilities. Unpublished doctoral dissertation, University of Kentucky, Lexington, USA.
Nelson, T. O., & Narens, L. (1990). Metamemory: A theoretical framework and new findings. In G. Bower (Ed.), The psychology of learning and motivation: Advances in research and theory (pp. 125–173). Academic Press. https://doi.org/10.1016/S0079-7421(08)60053-5
Oberauer, K., Süß, H. M., Schulze, R., Wilhelm, O., & Wittmann, W. W. (2000). Working memory capacity—facets of a cognitive ability construct. Personality and Individual Differences, 29(6), 1017–1045. https://doi.org/10.1016/S0191-8869(99)00251-2
Oberauer, K., Süß, H.-M., Wilhelm, O., & Wittmann, W. W. (2003). The multiple faces of working memory: Storage, processing, supervision, and coordination. Intelligence, 31, 167–193. https://doi.org/10.1016/S0160-2896(02)00115-0
Oleksy, T., & Wnuk, A. (2017). Catch them all and increase your place attachment! The role of location-based augmented reality games in changing people-place relations. Computers in Human Behavior, 76, 3–8. https://doi.org/10.1016/j.chb.2017.06.008
Oppenheim, C. (1993). Virtual Reality and the Virtual Library. Information services and use, 13(3), 215–227.
Ostler, T. (1994). Revolution in reality: Virtual reality applications in geography. Geographical Magazine, 66(5), 12–13.
Örün, Ö., & Akbulut, Y. (2019). Effect of multitasking, physical environment and electroencephalography use on cognitive load and retention. Computers in Human Behavior, 92, 216–229. https://doi.org/10.1016/j.chb.2018.11.027
Ozcelik, E., Arslan-Ari, I., & Cagiltay, K. (2010). Why does signaling enhance multimedia learning? Evidence from eye movements. Computers in Human Behavior, 26(1), 110–117. https://doi.org/10.1016/j.chb.2009.09.001.
Paas, F. G. W. C. (1992). Training strategies for attaining transfer of problem-solving skill in statistics: A cognitive-load approach. Journal of Educational Psychology, 84(4), 429–434. https://doi.org/10.1037/0022-0663.84.4.429
Paas, F. G. W. C., & van Merriënboer, J. J. (1993). The efficiency of instructional conditions: An approach to combine mental effort and performance measures. Human Factors, 35, 737–743. https://doi.org/10.1177/001872089303500412
Paas, F. G. W. C., & van Merriënboer, J. J. (1994). Instructional control of cognitive load in the training of complex cognitive tasks. Educational Psychology Review, 6(4), 351–371. https://doi.org/10.1007/BF02213420
Paas, F., & Sweller, J. (2014). Implications of cognitive load theory. The cambridge handbook of multimedia learning (pp. 27–43) (2nd ed.). Cambridge University Press.
Paas, F., Renkl, A., & Sweller, J. (2003a). Cognitive load theory and instructional design: Recent developments. Educational Pychologist, 38(1), 1–4. https://doi.org/10.1207/S15326985EP3801_1
Paas, F., Tuovinen, J. E., Tabbers, H., & van Gerven, P. W. (2003b). Cognitive load measurement as a means to advance cognitive load theory. Educational Psychologist, 38(1), 63–71. https://doi.org/10.1207/S15326985EP3801_8
Paas, F., Renkl, A., & Sweller, J. (2004). Cognitive load theory: Instructional implications of the interaction between information structures and cognitive architecture. Instructional Science, 32(1), 1–8. https://doi.org/10.1023/B:TRUC.0000021806.17516.d0.
Pan, Z., Cheok, A. D., Yang, H., Zhu, J., & Shi, J. (2006). Virtual reality and mixed reality for virtual learning environments. Computers & Graphics, 30, 20–28. https://doi.org/10.1016/j.cag.2005.10.004
Park, S., & Lee, G. (2020). Full-immersion virtual reality: Adverse effects related to static balance. Neuroscience Letters, 733, 134974. https://doi.org/10.1016/j.neulet.2020.134974
Parsons, D. (2012). Refining current practices in mobile and blended learning: New applications. IGI-Global, 1–334. https://doi.org/10.4018/978-1-4666-0053-9.
Pérez-López, D., & Contero, M. (2013). Delivering educational multimedia contents through an augmented reality application: A case study on its impact on knowledge acquisition and retention. TOJET – Turkish Online Journal of Educational Technology, 12(4), 19–28.
Pieger, E., Mengelkamp, C., & Bannert, M. (2016). Metacognitive judgments and disfluency–Does disfluency lead to more accurate judgments, better control, and better performance? Learning and Instruction, 44, 31–40. https://doi.org/10.1016/j.learninstruc.2016.01.012
Pintrich, P. (2000). The role of goal orientation in self-regulated learning. In M. Boekaerts, P. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 451–502). Academic Press. https://doi.org/10.1016/B978-012109890-2/50043-3
Plass, J. L., Moreno, R., & Brünken, R. (2010). Cognitive load theory. Cambridge University Press. https://doi.org/10.1017/CBO9780511844744
Pribeanu, C., Balog, A., & Iordache, D. D. (2017). Measuring the perceived quality of an AR-based learning application: A multidimensional model. Interactive Learning Environments, 25, 482–495. https://doi.org/10.1080/10494820.2016.1143375
Prit Kaur, D., Mantri, A., & Horan, B. (2019). Design implications for adaptive augmented reality based interactive learning environment for improved concept comprehension in engineering paradigms. Interactive Learning Environments, 1-19. https://doi.org/10.1080/10494820.2019.1674885
Quintero, J., Baldiris, S., Rubira, R., Cerón, J., & Velez, G. (2019). Augmented reality in educational inclusion. A systematic review on the last decade. Frontiers in Psychology, 10, 1835. https://doi.org/10.3389/fpsyg.2019.01835
Rauch, U. (2007). Who owns this space anyway? The Arts 3D VL Metaverse as a network of imagination. In Proceedings of ED-MEDIA, 2007, Vancouver, Canada, (pp. 4249–4253).
Raupers, P. M. (2000). Effects of accommodating learning-style preferences on long-term retention of technology training content. National Forum of Applied Educational Research Journal, 13(2), 23–26.
Renkl, A., & Scheiter, K. (2017). Studying visual displays: how to instructionally support learning. Educational Psychology Review, 29(3), 599–621. https://doi.org/10.1007/s10648-015-9340-4
Rhodes, M. G., & Castel, A. D. (2008). Memory predictions are influenced by perceptual information: evidence for metacognitive illusions. Journal of Experimental Psychology: General, 137(4), 615–625. https://doi.org/10.1037/a0013684
Riva, G. (2003). Applications of virtual environments in medicine. Methods of Information in Medicine, 42(5), 524–534. https://doi.org/10.1055/s-0038-1634379
Rivers, D. J., Nakamura, M., & Vallance, M. (2021). Online Self-Regulated Learning and Achievement in the Era of Change. Journal of Educational Computing Research. https://doi.org/10.1177/07356331211025108
Rosner, T. M., Davis, H., & Milliken, B. (2015). Perceptual blurring and recognition memory: A desirable difficulty effect revealed. Acta Psychologica, 160, 11–22. https://doi.org/10.1016/j.actpsy.2015.06.006
Roussou, M., Oliver, M., & Slater, M. (2006). The virtual playground: An educational virtual reality environment for evaluating interactivity and conceptual learning. Virtual Reality, 10(3), 227–240. https://doi.org/10.1007/s10055-006-0035-5
Salar, R., Arici, F., Caliklar, S., & Yilmaz, R. M. (2020). A model for augmented reality immersion experiences of university students studying in science education. Journal of Science Education and Technology, 29(2), 257–271. https://doi.org/10.1007/s10956-019-09810-x
Sanchez, C. A., & Jaeger, A. J. (2015). If it’s hard to read, it changes how long you do it: Reading time as an explanation for perceptual fluency effects on judgment. Psychonomic Bulletin & Review, 22(1), 206–211. https://doi.org/10.3758/s13423-014-0658-6
Saß, S., Wittwer, J., Senkbeil, M., & Koller, O. (2012). Pictures in test items: Effects on response time and response correctness. Applied Cognitive Psychology, 26(1), 70–81. https://doi.org/10.1002/acp.1798
Schank, P., & Kozma, R. (2002). Learning chemistry through the use of a representation-based knowledge building environment. Journal of Computers in Mathematics and Science Teaching, 21(3), 253–279.
Schmidt, N. (1996). Uses and abuses of coefficient alpha. Psychological Assessment, 8(4), 350–353. https://doi.org/10.1037/1040-3590.8.4.350
Schnotz, W., & Bannert, M. (2003). Construction and interference in learning from multiple representation. Learning and Instruction, 13(2), 141–156. https://doi.org/10.1016/S0959-4752(02)00017-8
Schraw, G. (2009). Measuring metacognitive judgments. In D. J. Hacker, J. Dunlosky, & A. C. Graesser (Eds.), Handbook of metacognition in education (pp. 415–428). Routledge.
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(3), 679–701. https://doi.org/10.1007/s10648-018-9435-9
Serra, M. J., & Dunlosky, J. (2010). Metacomprehension judgements reflect the belief that diagrams improve learning from text. Memory, 18(7), 698–711. https://doi.org/10.1080/09658211.2010.506441
Servotte, J. C., Goosse, M., Campbell, S. H., Dardenne, N., Pilote, B., Simoneau, I. L., et al. (2020). Virtual reality experience: immersion, sense of presence, and cybersickness. Clinical Simulation in Nursing, 38, 35–43. https://doi.org/10.1016/j.ecns.2019.09.006
Seufert, T., Wagner, F., & Westphal, J. (2017). The effects of different levels of disfluency on learning outcomes and cognitive load. Instructional Science, 45(2), 221–238. https://doi.org/10.1007/s11251-016-9387-8
Sidi, Y., Ophir, Y., & Ackerman, R. (2016). Generalizing screen inferiority-does the medium, screen versus paper, affect performance even with brief tasks? Metacognition and Learning, 11(1), 15–33. https://doi.org/10.1007/s11409-015-9150-6
Smink, A. R., van Reijmersdal, E. A., van Noort, G., & Neijens, P. C. (2020). Shopping in augmented reality: The effects of spatial presence, personalization and intrusiveness on app and brand responses. Journal of Business Research, 118, 474–485. https://doi.org/10.1016/j.jbusres.2020.07.018
Smith, S. M., & Vela, E. (2001). Environmental context-dependent memory: A review and meta-analysis. Psychonomic Bulletin & Review, 8(2), 203–220. https://doi.org/10.3758/BF03196157
Soltani, P., & Morice, A. H. (2020). Augmented reality tools for sports education and training. Computers & Education, 155, 103923. https://doi.org/10.1016/j.compedu.2020.103923
Song, H. S., Pusic, M., Nick, M. W., Sarpel, U., Plass, J. L., & Kalet, A. L. (2014). The cognitive impact of interactive design features for learning complex materials in medical education. Computers & Education, 71, 198–205. https://doi.org/10.1016/j.compedu.2013.09.017
Song, H., & Schwarz, N. (2008). If it's hard to read, it's hard to do processing fluency affects effort prediction and motivation. Psychological Science, 19(10), 986–988. https://doi.org/10.1111/j.1467-9280.2008.02189.x
Sotiriou, S., & Bogner, F. X. (2008). Visualizing the invisible: Augmented reality as an innovative science education scheme. Advanced Science Letters, 1(1), 114–122. https://doi.org/10.1166/asl.2008.012
Squire, K. D., & Jan, M. (2007). Mad city mystery: Developing scientific argumentation skills with a place-based augmented reality game on handheld computers. Journal of Science Education and Technology, 16(1), 5–29. https://doi.org/10.1007/s10956-006-9037-z
Stone, J. M., & Towse, J. (2015). A working memory test battery: Java-based collection of seven working memory tasks. Journal of Open Research Software, 3(1). https://doi.org/10.5334/jors.br
Stone, R. J. (1991). Virtual reality and cyberspace: from science fiction to science fact. Information Services & Use, 11(5-6), 283–300.
Strukelj, A., Scheiter, K., Nyström, M., & Holmqvist, K. (2016). Exploring the lack of a disfluency effect: Evidence from eye movements. Metacognition and Learning, 11(1), 71–88. https://doi.org/10.1007/s11409-015-9146-2
Stull, A. T., & Mayer, R. E. (2007). Learning by doing versus learning by viewing: Three experimental comparisons of learner-generated versus author-provided graphic organizers. Journal of Educational Psychology, 99(4), 808–820. https://doi.org/10.1037/0022-0663.99.4.808
Sun, R., Wu, Y. J., & Cai, Q. (2019). The effect of a virtual reality learning environment on learners’ spatial ability. Virtual Reality, 23(4), 385–398. https://doi.org/10.1007/s10055-018-0355-2
Susser, J. A., Jin, A., & Mulligan, N. W. (2016). Identity priming consistently affects perceptual fluency but only affects metamemory when primes are obvious. Journal of Experimental Psychology: Learning, Memory, and Cognition, 42(4), 657–662. https://doi.org/10.1037/xlm0000189
Susser, J. A., Mulligan, N. W., & Besken, M. (2013). The effects of list composition and perceptual fluency on judgments of learning (JOLs). Memory & Cognition, 41(7), 1000–1011. https://doi.org/10.3758/s13421-013-0323-8
Sweller, J. (2008). Human cognitive architecture. In J. M. Spector, M. D. Merrill, J. J. G. van Merriënboer, & M. P. Driscoll (Eds.). Handbook of research on educational communications and technology (pp. 369 - 381). (3rd ed.). New York: Routledge.
Sweller, J., & Sweller, S. (2006). Natural information processing systems. Evolutionary Psychology, 4, 434–458. https://doi.org/10.1177/147470490600400135
Sweller, J., van Merriënboer, J. J., & Paas, F. (2019). Cognitive architecture and instructional design: 20 years later. Educational Psychology Review, 31(2), 261–292. https://doi.org/10.1007/s10648-019-09465-5
Sweller, J., van Merrienboer, J. J., & Paas, F. G. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10(3), 251–296. https://doi.org/10.1023/A:1022193728205
Terras, M. M., & Ramsay, J. (2014). Massive open online courses (MOOCs): Insights and challenges from a psychological perspective. British Journal of Educational Technology, 46, 472–487. https://doi.org/10.1111/bjet.12274
Thompson, D. V., & Ince, E. C. (2013). When disfluency signals competence: The effect of processing difficulty on perceptions of service agents. Journal of Marketing Research, 50(2), 228–240. https://doi.org/10.1509/jmr.11.0340
Tomi, A. B., & Rambli, D. R. A. (2013). An interactive mobile augmented reality magical playbook: Learning number with the thirsty crow. Procedia Computer Science, 25, 123–130. https://doi.org/10.1016/j.procs.2013.11.015
Trindade, J., Fiolhais, C., & Almeida, L. (2002). Science learning in virtual environments: A descriptive study. British Journal of Educational Technology, 33(4), 471–488. https://doi.org/10.1111/1467-8535.00283
Tsou, W., Wang, W., & Tzeng, Y. (2006). Applying a multimedia storytelling website in foreign language learning. Computers & Education, 47(1), 17–28. https://doi.org/10.1016/j.compedu.2004.08.013
Uline, C., & Tschannen-Moran, M. (2008). The walls speak: The interplay of quality facilities, school climate, and student achievement. Journal of Educational Administration, 46(1), 55–73. https://doi.org/10.1108/09578230810849817
van Merriënboer, J. J. G. (2002). Bleuprints for complex learning: The 4C/ID-model. Educational Technology Research and Development, 50, 39–61. https://doi.org/10.1007/BF02504993
vanMeerten, N., & Varma, K. (2017). Exploring student engagement in an augmented reality learning game. International Journal of Gaming and Computer-Mediated Simulations (IJGCMS), 9(4), 44–61. https://doi.org/10.4018/IJGCMS.2017100103
von Bastian, C. C., & Eschen, A. (2016). Does working memory training have to be adaptive? Psychological research, 80(2), 181–194. https://doi.org/10.1007/s00426-015-0655-z
von Bastian, C. C., & Oberauer, K. (2013). Distinct transfer effects of training different facets of working memory capacity. Journal of Memory and Language, 69(1), 36–58. https://doi.org/10.1016/j.jml.2013.02.002
von Bastian, C. C., Locher, A., & Ruflin, M. (2013). Tatool: A Java-based open-source programming framework for psychological studies. Behavior Research Methods, 45(1), 108–115.
von Bastian, C. C., Souza, A. S., & Gade, M. (2016). No evidence for bilingual cognitive advantages: A test of four hypotheses. Journal of Experimental Psychology: General, 145(2), 246. https://doi.org/10.1037/xge0000120
Wang, J., & Antonenko, P. D. (2017). Instructor presence in instructional video: Effects on visual attention, recall, and perceived learning. Computers in Human Behavior, 71, 79–89. https://doi.org/10.1016/j.chb.2017.01.049
Wang, S.-h. (2012). Applying a 3D situational virtual learning environment to the real world business-An extended research in marketing. British Journal of Educational Technology, 43(3), 411–427. https://doi.org/10.1111/j.1467-8535.2011.01194.x
Webster, R. (2016). Declarative knowledge acquisition in immersive virtual learning environments. Interactive Learning Environments, 24(6), 1319–1333. https://doi.org/10.1080/10494820.2014.994533
Weissgerber, S. C., & Reinhard, M. A. (2017). Is disfluency desirable for learning? Learning and Instruction, 49, 199–217. https://doi.org/10.1016/j.learninstruc.2017.02.004
Wong, B. L. W., Ng, B. P., & Clark, S. A. (2000). Assessing the effectiveness of animation and virtual reality in teaching operative dentistry. Journal of Dentistry: Educational Technology Section, 1(1).
Wu, H. K., Lee, S. W. Y., Chang, H. Y., & Liang, J. C. (2013). Current status, opportunities and challenges of augmented reality in education. Computers & Education, 62, 41–49. https://doi.org/10.1016/j.compedu.2012.10.024
Wu, J., Guo, R., Wang, Z., & Zeng, R. (2019). Integrating spherical video-based virtual reality into elementary school students’ scientific inquiry instruction: effects on their problem-solving performance. Interactive Learning Environments, 1-14. https://doi.org/10.1080/10494820.2019.1587469
Yen, J.-C., Tsai, C.-H., & Wu, M. (2013). Augmented reality in the higher education: students’ science concept learning and academic achievement in astronomy. Procedia-Social and Behavioral Sciences, 103, 165–173. https://doi.org/10.1016/j.sbspro.2013.10.322
Yue, C. L., Castel, A. D., & Bjork, R. A. (2013). When disfluency is—and is not—a desirable difficulty: The influence of typeface clarity on metacognitive judgments and memory. Memory & Cognition, 41(2), 229–241. https://doi.org/10.3758/s13421-012-0255-8
Zagoranski, S., & Divjak, S. (2003). Use of augmented reality in education. In The IEEE Region 8 EUROCON 2003. Computer as a Tool. (Vol. 2, pp. 339-342). https://doi.org/10.1109/EURCON.2003.1248213
Zareie, B., & Navimipour, N. J. (2016). The effect of electronic learning systems on the employee's commitment. The International Journal of Management Education, 14(2), 167–175. https://doi.org/10.1016/j.ijme.2016.04.003
Zhang, F. (2021). Human–Computer Interactive Gesture Feature Capture and Recognition in Virtual Reality. Ergonomics in Design, 29(2), 19–25. https://doi.org/10.1177/1064804620924133
Zhang, Z., Li, Z., Han, M., Su, Z., Li, W., & Pan, Z. (2021). An augmented reality-based multimedia environment for experimental education. Multimedia Tools and Applications, 80(1), 575–590. https://doi.org/10.1007/s11042-020-09684-x
Acknowledgements
The current study is the summary of the correspondence author’s PhD dissertation, which was supervised by the second author.
Code availability (software application or custom code)
Not applicable.
Funding
The current research was supported by the Scientific Research Projects [Grant No: 1705E112]; Anadolu University, Eskisehir, Turkey.
Author information
Authors and Affiliations
Contributions
Authors were both responsible for all sections of the manuscript, in general. The second author was responsible for funding acquisition, supervision, project administration, writing and original draft. The first author was responsible for conceptualization, writing, methodology and formal data analysis, and original draft. The authors checked and approved the final version of the manuscript.
Corresponding author
Ethics declarations
Conflict of Interest
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Ethics Approval
The research proposal was approved by the Institutional Review Board of Anadolu University.
Consent to participate
Written informed consent was obtained from all subjects before the study.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Tugtekin, U., Odabasi, H.F. Do Interactive Learning Environments Have an Effect on Learning Outcomes, Cognitive Load and Metacognitive Judgments?. Educ Inf Technol 27, 7019–7058 (2022). https://doi.org/10.1007/s10639-022-10912-0
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10639-022-10912-0