- Open Access
Comparing the perception of emergency remote teaching experience between physics and nonphysics students
Phys. Rev. Phys. Educ. Res. 19, 020131 – Published 14 September, 2023
DOI: https://doi.org/10.1103/PhysRevPhysEducRes.19.020131
Abstract
A significant proportion of universities throughout the world switched from conventional face-to-face course delivery to emergency remote teaching (ERT) in response to the pervasive COVID-19 outbreak. A series of challenges are faced by both teachers and students as a result of the rapid and abrupt switch to ERT. Within the context of ERT, physics courses encounter certain challenges in contrast to certain liberal arts courses. In particular, this study sought to determine whether physics students and nonphysics students had diverse levels of flow experience and cognitive load when applying ERT during the global pandemic period. Furthermore, this study examined whether ERT for physics students varied depending on gender and educational level. Following the completion of their ERT courses at the end of both the Spring semester of 2020 and the Fall semester of 2022, a total of 1073 participants, including both physics majors and nonphysics majors, participated in our research. From the result, physics students had better performance in the flow experience encompassing its three constructs: enjoyment, engagement, and control. Physics students demonstrated a higher germane cognitive load and a lower extraneous cognitive load when compared to nonphysics students. Moreover, a considerably higher extraneous cognitive load was observed among male physics students than among their female counterparts during the ERT. Nonetheless, physics students at undergraduate and graduate levels did not significantly differ in their flow experiences or cognitive load. Overall, physics majors had a more positive perception of their ERT learning experience, and the impact of ERT on physics students was significantly less detrimental.
Physics Subject Headings (PhySH)
Article Text
References (119)
- United Nations Educational, Scientific and Cultural Organization (UNESCO). Global monitoring of school closures caused by COVID-19 (2021). Retrieved from https://en.unesco.org/covid19/educationresponse-school-closures.
- United Nations International Children’s Emergency Fund (UNICEF, COVID-19, and school closures (2021), https://data.unicef.org/resources/one-year-of-covid-19-and-school-closures/.
- C. Hodges, S. Moore, B. Lockee, T. Trust, and A. Bond, The difference between emergency remote teaching and online learning, EDUCAUSE Review (2020), https://er.educause.edu/articles/2020/3/the-difference-between-emergency-remote-teaching-and-online-learning.
- J. Xie and M. F. Rice, Instructional designers’ roles in emergency remote teaching during COVID-19, Distance Educ. 42, 70 (2021).
- J. Keengwe and T. T. Kidd, Towards best practices in online learning and teaching in higher education, J. Online Learn. Teach. 6, 533 (2010), http://jolt.merlot.org/vol6no2/keengwe_0610.htm.
- L. G. Manfuso, From emergency remote teaching to rigorous online learning, Ed. Tech. 7 (2020), https://edtechmagazine.com/higher/article/2020/05/emergency-remote-teaching-rigorousonlinelearning-perfcon.
- T. Anderson, The theory and practice of online learning (Athabasca University Press, Edmonton, 2008), 2nd ed.
- P. C. Herman, Online learning is not the future, The Chronicle of Higher Education (2020) https://data.unicef.org/resources/one-year-of-covid-19-and-school-closures/.
- L. Moorhouse and L. Kohnke, Thriving or surviving emergency remote teaching necessitated by COVID-19: University teachers’ perspectives, Asia-Pac. Educ. Res. 30, 279 (2021).
- R. J. Petillion and W. S. McNeil, Student experiences of emergency remote teaching: Impacts of instructor practice on student learning, engagement, and well-being, J. Chem. Educ. 97, 2486 (2020).
- J. Huang, Successes and challenges: Online teaching and learning of chemistry in higher education in China in the time of COVID-19, J. Chem. Educ. 97, 2810 (2020).
- K. A. Burke, N. M. Stephens, I. Bose, C. Bonaccorsi, A. M. Wade, and J. K. Awino, How the COVID-19 pandemic changed chemistry instruction at a large public university in the Midwest: Challenges met, (some) obstacles overcome, and lessons learned, J. Chem. Educ. 97, 2793 (2020).
- C. Rapanta, L. Botturi, P. Goodyear, L. Guàrdia, and M. Koole, Balancing technology, pedagogy and the new normal: Post-pandemic challenges for higher education, Postdigit. Sci. Educ. 3, 715 (2021).
- F. Gallè, E. A. Sabella, G. D. Molin, O. D. Giglio, and C. Napoli, Understanding knowledge and behaviors related to COVID-19 epidemic in Italian undergraduate students: The EPICO study, Int. J. Environ. Res. Public Health 17, 3481 (2020).
- T. Elmer, K. Mepham, and C. Stadtfeld, Students under lockdown: Comparisons of students’ social networks and mental health before and during the Covid-19 crisis in Switzerland, PLoS One 15, e0236337 (2020).
- L. Giusti, S. Mammarella, A. Salza, S. D. Vecchio, D. Ussorio, M. Casacchia, and R. Roncone, Predictors of academic performance during the covid-19 outbreak: Impact of distance education on mental health, social cognition and memory abilities in an Italian university student sample, BMC Psychol. 9, 142 (2021).
- S. Rudenstine, K. Mcneal, T. Schulder, C. K. Ettman, M. Hernandez, K. Gvozdieva, and S. Garea, Depression and anxiety during the COVID-19 pandemic in an urban, low-income public university sample, J. Trauma. Stress 34, 12 (2020).
- K. Resch, G. Alnahdi, and S. Schwab, Exploring the effects of the COVID-19 emergency remote education on students’ social and academic integration in higher education in Austria, Higher Educ. Res. Dev. 42, 215 (2023).
- C. Y. Su and Y. Guo, Factors impacting university students’ online learning experiences during the COVID-19 epidemic, J. Comput. Assist. Learn. 37, 1578 (2021).
- P. Klein, L. Ivanjek, M. N. Dahlkemper, K. Jeličić, M.-A. Geyer, S. Küchemann, and A. Susac, Studying physics during the COVID-19 pandemic: Student assessments of learning achievement, perceived effectiveness of online recitations, and online laboratories, Phys. Rev. Phys. Educ. Res. 17, 010117 (2021).
- M. Kuhfeld, J. Soland, B. Tarasawa, A. Johnson, and J. Liu, Projecting the potential impact of COVID-19 school closures on academic achievement, Educ. Res. 49, 549 (2020).
- I. P. Santiago, Hernández-Garcíangel, Chaparro-Peláez Julián, and José Luis Prieto, Emergency remote teaching and students’ academic performance in higher education during the COVID-19 pandemic: A case study, Comput. Hum. Behav. 119, 106713 (2021).
- V. Borish, A. Werth, N. Sulaiman, M. F. Fox, J. R. Hoehn, and H. Lewandowski, Undergraduate student experiences in remote lab courses during the COVID-19 pandemic, Phys. Rev. Phys. Educ. Res. 18, 020105 (2022).
- M. Fox, J. R. Hoehn, A. Werth, and H. J. Lewandowski, Lab instruction during the COVID-19 pandemic: Effects on student views about experimental physics in comparison with previous years, Phys. Rev. Phys. Educ. Res. 17, 010148 (2021).
- T. Hynninen, H. Pesonen, O. Lintu, and P. Paturi, Ongoing effects of pandemic-imposed learning environment disruption on student attitudes, Phys. Rev. Phys. Educ. Res. 19, 010101 (2022).
- C. Conrad and A. Newman, Measuring mind wandering during online lectures assessed with EEG, Front. Hum. Neurosci. 15, 697532 (2021).
- A. P. Aguilera-Hermida, College students’ use and acceptance of emergency online learning due to COVID-19, Int. J. Educ. Res. 1, 100011 (2020).
- G. Orlov, D. McKee, J. Berry, A. Boyle, T. DiCiccio, T. Ransom, A. Rees-Jones, and J. Stoye, Learning during the COVID-19 pandemic: It is not who you teach, but how you teach, Econ. Lett. 202, 109812 (2021).
- A. Besser, G. L. Flett, and V. Zeigler-Hill, Adaptability to a sudden transition to online learning during the COVID-19 pandemic: Understanding the challenges for students, Scholarsh. Teach. Learn. Psychol. 8, 85 (2020).
- W. E. Copeland, E. McGinnis, Y. Bai, Z. Adams, H. Nardone, V. Devadanam, J. Rettew, and J. J. Hudziak, Impact of COVID-19 pandemic on college student mental health and wellness, J. Am. Acad. Child Adolesc. Psychiatry 60, 134 (2021).
- J. Engelbrecht, M. C. Borba, and G. Kaiser, Will we ever teach mathematics again in the way we used to before the pandemic, ZDM - Math. Educ. 55, 1 (2023).
- M. Csikszentmihalyi, Beyond boredom and anxiety (Jossey-Bass, San Francisco, CA 1975).
- M. Csikszentmihalyi and I. Csikszentmihalyi, The measurement of flow in everyday life, in Optimal Experience: Psychological Studies of Flow in Consciousness, edited by M. Csikszentmihalyi and I. Csikszentmihalyi (Cambridge University, Cambridge, England, 1988), p. 251.
- M. Csikszentmihalyi, Flow: The Psychology of Optimal Experience (Harper Perennial, New York, 1991).
- M. Csikszentmihalyi, Creativity: Flow and the Psychology of Discovery and Invention (Harper Collins, New York, 1996).
- L. Hoffman and T. P. Novak, Flow online: Lessons learned and future prospects, J. Interact. Mark. 23, 23 (2009).
- S. Freitas, S. Arnab, and T. Lainema, The design principles for flow experience in educational games, Procedia Comput. Sci. 15, 78 (2012).
- J. Webster, L. K. Trevino, and L. Ryan, The dimensionality and correlates of flow in human-computer interactions, Comput. Hum. Behav. 9, 411 (1993).
- M. Koufaris, Applying the technology acceptance model and flow theory to online consumer behavior, Inf. Syst. Res. 13, 205 (2002).
- J. M. Pearce, M. Ainley, and S. Howard, The ebb and flow of online learning, Comput. Hum. Behav. 21, 745 (2005).
- W. C. Yen and H. H. Lin, Investigating the effect of flow experience on learning performance and entrepreneurial self-efficacy in a business simulation systems context, Interact. Learn. Environ. 30, 1593 (2022).
- N. Hofferber, M. Basten, N. Großmann, and M. Wilde, The effects of autonomy-supportive and controlling teaching behaviour in biology lessons with primary and secondary experiences on students’ intrinsic motivation and flow-experience, Int. J. Sci. Educ. 38, 2114 (2016).
- N. O. Canarslan and G. Baris, Flow experience and consumer willingness to pay in online mass customization processes, Int. J. Online Mark. 12, 1 (2022).
- R. E. Kunz, C. Zabel, and V. Telkmann, Content-, system-, and hardware-related effects on the experience of flow in VR gaming, J. Media Econ. 34, 213 (2022).
- S. C. Lo and H. H. Tsai, Design of 3D virtual reality in the metaverse for environmental conservation education based on cognitive theory, Sensors 22, 8329 (2022).
- X. S. Cheng, X. W. Su, B. Yang, A. Zarifis, and J. Mou, Understanding users’ negative emotions and continuous usage intention in short video platforms, Electron. Commer. Res. Appl. 58, 101244 (2023).
- T. Zhou, The effect of flow experience on users’ social commerce intention, Kybernetes 49, 2349 (2020).
- I. U. Khan, Z. Hameed, Y. G. Yu, and S. U. Khan, Assessing the determinants of flow experience in the adoption of learning management systems: The moderating role of perceived institutional support, Behav. Inf. Tech. 36, 1162 (2017).
- A. Bodzin, R. A. Junior, T. Hammond, and D. Anastasio, An immersive virtual reality game designed to promote learning engagement and flow, in Proceedings of 2020 6th International Conference of the Immersive Learning Research Network (iLRN) (2020).
- C.C Chang, C. Y. Liang, P. N. Chou, and G. Y. Lin, Is game-based learning better in flow experience and various types of cognitive load than non-game-based learning? Perspective from multimedia and media richness, Comput. Hum. Behav. 71, 218 (2017).
- S. Kaya and E. Ercag, The impact of applying challenge-based gamification program on students’ learning outcomes: Academic achievement, motivation and flow, Educ. Inf. Technol. 28, 10053 (2023).
- A. C. Wang and M. C. Hsu, An exploratory study using inexpensive electroencephalography (EEG) to understand flow experience in computer-based instruction, Inf. Manag. 51, 912 (2014).
- M. B. Ibanez, A. D. Serio, D. Villaran, and C. D. Kloos, Experimenting with electromagnetism using augmented reality: Impact on flow student experience and educational effectiveness, Comput. Educ. 71, 1 (2014).
- Z. Guo, L. Xiao, C. V. Toorn, Y. Lai, and C. Seo, Promoting online learners’ continuance intention: An integrated flow framework, Inf. Manag. 53, 279 (2016).
- P. Y. Wang, M. C. Chiu, and Y. T. Lee, Effects of video lecture presentation style and questioning strategy on learner flow experience, Innov. Educ. Teach. Int. 58, 473 (2021).
- H. Zhao and A. Khan, The Students’ Flow Experience with the Continuous Intention of Using online English platforms, Front. Psychol. 12, 807084 (2022).
- Y. H. Lee, H. Chan, and C. H. Ho, The effects of various multimedia instructional materials on students’ learning responses and outcomes: A comparative experimental study, Comput. Hum. Behav. 40, 119 (2014).
- T. Y. Liu, Using educational games and simulation software in a computer science course: Learning achievements and student flow experiences, Interact. Learn. Environ. 24, 1 (2016).
- Y. C. Liu, T. H. Huang, and H. I. Lin, Hands-on operation with a Rolling Alphabet-AR System improves English learning achievement, Innov. Lang. Learn. Teach. 17, 812 (2023).
- Y. J. Joo, E. Oh, and S. M. Kim, Motivation, instructional design, flow, and academic achievement at a Korean online university: A structural equation modelling study, J. Comput. High Educ. 27, 28 (2015).
- W. C. Yen and H. H. Lin, Investigating the effect of flow experience on learning performance and entrepreneurial self-efficacy in a business simulation systems context, Interact. Learn. Environ. 30, 1593 (2022).
- R. Ellwood and E. Abrams, Student’s social interaction in inquiry-based science education: How experiences of flow can increase motivation and achievement, Cult. Stud. Sci. Educ. 13, 395 (2018).
- Berenguel, F. Gil, A. B. Montoro, and M. F. Moreno, Influence of self-confidence and motivational profile in “flow” in mathematics, in Proceedings of 19th Symposium on Research in Mathematics Education (2015), p. 173, https://core.ac.uk/works/19529843.
- Y. M. Guo, B. D. Klein, and Y. K. Ro, On the effects of student interest, self-efficacy, and perceptions of the instructor on flow, satisfaction, and learning outcomes, Stud. Higher Educ. 45, 1 (2020).
- Belén Mesurado, María Cristina Richaud, and Niño José Mateo, Engagement, flow, self-efficacy, and Eustress of University students: A cross-national comparison between the Philippines, and Argentina, J. Psychol. 150, 281 (2016).
- S. Yao, L. Xie, and Y. Chen, Effect of active social media use on flow experience: Mediating role of academic self-efficacy, Educ. Inf. Technol. 28, 5833 (2023).
- J. C. Hong, C. R. Tsai, H. S. Hsiao, P. H. Chen, K. C. Chu, and J. Gu, The effect of the “Prediction-observation-quiz-explanation” inquiry-based e-learning model on flow experience in green energy learning, Comput. Educ. 133, 127 (2019).
- J. Sweller, Cognitive load during problem solving: Effects on learning, Cogn. Sci. 12, 257 (1988).
- J. Sweller, J. J. van Merrienboer, and F. G. Paas, Cognitive architecture and instructional design, Educ. Psychol. Rev. 10, 251 (1998).
- Q. Liu, S. F. Yu, W. L. Chen, Q. Y. Wang, and S. X. Xu, The effects of an augmented reality based magnetic experimental tool on students’ knowledge improvement and cognitive load, J. Comput. Assist. Learn. 37, 645 (2020).
- J. Sweller, P. Ayres, and S. Kalyuga, Cognitive Load Theory (Springer, London, 2011).
- E. İbili, Effect of augmented reality environments on cognitive load: Pedagogical effect, instructional design, motivation, and interaction interfaces, Int. J. Prog. Educ. 15, 42 (2019).
- A. F. Lai, C. H. Chen, and G. Y. Lee, An augmented reality-based learning approach to enhancing students’ science reading performances from the perspective of the cognitive load theory, Br. J. Educ. Technol. 50, 232 (2019).
- O. Chen, G. Woolcott, and J. Sweller, Using cognitive load theory to structure computer-based learning including MOOCs, J. Comput. Assist. Learn. 33, 293 (2017).
- A. Eitel, T. Endres, and A. Renkl, Self-management as a bridge between cognitive load and self-regulated learning: The illustrative case of seductive details, Educ. Psychol. Rev. 32, 1073 (2020).
- H. Altinpulluk, H. Kilinc, M. Firat, and O. Yumurtaci, The influence of segmented and complete educational videos on the cognitive load, satisfaction, engagement, and academic achievement levels of learners, J. Comput. Educ. 7, 155 (2020).
- A. Younas et al., Role of design attributes to determine the intention to use online learning via cognitive beliefs, IEEE Access 9, 94181 (2021).
- C. Conrad, Q. Deng, I. Caron, O. Shkurska, P. Skerrett, and B. Sundararajan, How student perceptions about online learning difficulty influenced their satisfaction during Canada’s COVID-19 response, Br. J. Educ. Technol. 53, 534 (2022).
- D. Yang, Instructional strategies, and course design for teaching statistics online: Perspectives from online students, Int. J. Stem Educ. 4, 34 (2017).
- D. Moszkowicz, H. Duboc, C. Dubertret, D. Roux, and F. Bretagnol, Daily medical education for confined students during coronavirus disease 2019 pandemic: A simple videoconference solution, Clin. Anat. 33, 927 (2020).
- N. Alsuwaida, Online courses in art and design during the coronavirus (COVID-19) pandemic: Teaching reflections from a first-time online instructor, SAGE Open 12, 59 (2022).
- Jung-in. Park, A case study on the operation of University Liberal Arts Classes in the context of COVID-19: Based on the experiences of the professors in charge, J. Learn. Cent. Curric. Instr. 21, 389 (2021).
- E. G. Campari, M. Barbetta, S. Braibant, N. Cuzzuol, A. Gesuato, L. Maggiore, F. Marulli, G. Venturoli, and C. Vignali, Physics laboratory at home during the COVID-19 pandemic, Phys. Teach. 59, 68 (2021).
- M. Carli, M. R. Fontolan, and O. Pantano, Teaching optics as inquiry under lockdown: How we transformed a teaching-learning sequence from face-to-face to distance teaching, Phys. Educ. 56, 025010 (2021).
- E. Wieman, W. K. Adams, and K. K. Perkins, PhET: Simulations that enhance learning, Science 322, 682 (2008).
- E. Wieman, W. K. Adams, P. Loeblein, and K. K. Perkins, Teaching physics using PhET simulations, Phys. Teach. 48, 225 (2010).
- T. Walsh, Creating interactive physics simulations using the power of GeoGebra, Phys. Teach. 55, 316 (2017).
- J. Lincoln, Virtual labs and simulations: Where to find them and tips to make them work, Phys. Teach. 58, 444 (2020).
- Howard M. Meier, Meeting laboratory course learning goals remotely via custom home experiment kits, arXiv.2007.05390.
- J. Malec et al., On teaching experimental reactor physics in times of pandemic, EPJ Web Conf. 253, 10001 (2021).
- M. Pawlak, A. Derakhshan, M. Mehdizadeh, and M. Kruk, Boredom in online English language classes: Mediating variables and coping strategies, Lang. Teach. Res. 1 (2022).
- E. Dorn, B. Hancock, J. Sarakatsannis, and E. Viruleg, COVID-19 and Student Learning in the United States: The Hurt Could Last a Lifetime (McKinsey & Company, New York, NY, 2020), https://www.mckinsey.com/industries/education/our-insights/covid-19-and-student-learning-in-the-united-states-the-hurt-could-last-a-lifetime.
- B. R. Wilcox and M. Vignal, Understanding the student experience with emergency remote teaching, presented at PER Conf. 2020, virtual conference, 10.1119/perc.2020.pr.Wilcox.
- J. Wilhelm, S. Mattingly, and V. H. Gonzalez, Perceptions, satisfactions, and performance of undergraduate students during COVID-19 emergency remote teaching, Anat. Sci. Educ. 15, 42 (2021).
- C. S. Chang, Z. F. Liu, H. Y. Sung, C. H. Lin, N. S. Chen, and S. S. Cheng, Effects of online college student’s internet self-efficacy on learning motivation and performance, Innov. Educ. Teach. Int. 51, 366 (2014).
- J. C. Hong, Y. Liu, Y. S. Liu, and L. Zhao, High school students’ online learning ineffectiveness in experimental courses during the COVID-19 pandemic, Front. Psychol. 12, 1 (2021).
- J. T. Richardson and A. Woodley, Another look at the role of age, gender and subject as predictors of academic attainment in higher education, Stud. Higher Educ. 28, 475 (2003).
- Z. Yu, Gender differences in cognitive loads, attitudes, and academic achievements in mobile English learning, Int. J. Distance Educ. Technol. 17, 21 (2019).
- H. Gülru Yüksel, Remote learning during COVID-19: Cognitive appraisals, and perceptions of English medium of instruction (EMI) students, Educ. Inf. Technol. 27, 347 (2022).
- Y. M. Tang, P. C. Chen, K. M. Y. Law, C. H. Wu, and G. T. S. Ho, Comparative analysis of student’s live online learning readiness during the coronavirus (COVID-19) pandemic in the higher education sector, Comput. Educ. 168, 104211 (2021).
- K. Evans, An experimental investigation of videotaped lectures in online courses, Tech. Trends 58, 63 (2014).
- Z. Yu, The effects of gender, educational level, and personality on online learning outcomes during the COVID-19 pandemic, Int. J. Educ. Technol. Higher Educ. 18, 14 (2021).
- P. Gerjets, K. Scheiter, M. Opfermann, F. W. Hesse, and T. H. S. Eysink, Learning with hypermedia: The influence of representational formats and different levels of learner control on performance and learning behavior, Comput. Hum. Behav. 25, 360 (2009).
- J. Leppink, F. Paas, C. P. M. Van der Vleuten, T. Van Gog, and J. J. G. Van Merriënboer, Development of an instrument for measuring different types of cognitive load, Behav. Res. 45, 1058 (2013).
- J. Cohen, A power primer, Psychol. Bull. 112, 155 (1992).
- R. Schoenfeld-Tacher, S. McConnell, and M. Graham, Do no harm—A comparison of the effects of on-line vs. traditional delivery media on a science course, J. Sci. Educ. Technol. 10, 257 (2001).
- D. Johnson and C. C. Palmer, Comparing student assessments and perceptions of online and face-to-face versions of an introductory linguistics course, Online Learn. 19, 33 (2015).
- J. L. Helms, Comparing student performance in online and face-to-face delivery modalities, Asynchr. Learn. Netw. 18, 1 (2014).
- M. Hillier, The very idea of e-exams: Student (pre) conceptions, in Proceedings of ASCILITE 2014—Annual Conference of the Australian Society for Computers in Tertiary Education, edited by B. Hegarty, J. McDonald, and S.-K. Lok (Dunedin, New Zealand, 2014), p. 77.
- M. Moradi et al., Enhancing teaching learning effectiveness by creating online interactive instructional modules for fundamental concepts of physics and mathematics, Educ. Sci. 8, 109 (2018).
- E. Bergeler and M. F. Read, Comparing learning outcomes and satisfaction of an online algebra-based physics course with a face-to-face course, J. Sci. Educ. Technol. 30, 97 (2021).
- G. Blau and R. Drennan, Exploring difference in business undergraduate perceptions by preferred classroom delivery mode, Online Learn. 21, 222 (2017).
- J. Sweller, Element interactivity and intrinsic, extraneous, and germane cognitive load, Educ. Psychol. Rev. 22, 123 (2010).
- A. Alghamdi, A. C. Karpinski, A. Lepp, and J. Barkley, Online and face-to-face classroom multitasking and academic performance: Moderated mediation with self-efficacy for self-regulated learning and gender, Comput. Hum. Behav. 102, 214 (2020).
- N. Nistor, Stability of attitudes, and participation in online university courses: Gender, and location effects, Comput. Educ. 68, 284 (2013).
- L. Harvey, S. Parahoo, and M. Santally, Should gender differences be considered when assessing student satisfaction in the online learning environment for millennials? Higher Educ. Q. 71, 141 (2017).
- L. Harasim, Shift happens: Online education as a new paradigm in learning, Internet Higher Educ. 3, 41 (2000).
- A. Bozkurt and R. C. Sharma, Emergency remote teaching in a time of global crisis due to Corona Virus pandemic, Asian J. Distance Educ. 15, 1 (2020).
- K. Tzafilkou, M. Perifanou, and A. A. Economides, Negative emotions, cognitive load, acceptance, and self-perceived learning outcome in emergency remote education during COVID-19, Educ. Inf. Technol. 26, 7497 (2021).