EĞİTSEL BAĞLAMDA TEKNOLOJİ VE DUYGU ÇALIŞMALARI ÜZERİNE BİR SİSTEMATİK HARİTALAMA ÇALIŞMASI: TANIMLAR, KURAMLAR VE GELECEKTEKİ YÖNELİMLER

Yıl 2021, , 20 - 47, 28.01.2021

Gülay Öztüre , Ayça Fidan , Eda Bakır , Nilüfer Atman Uslu , Yasemin Usluel

https://doi.org/10.17943/etku.745236

Cited By: 4

Öz

Bu çalışmada, sistematik haritalama yoluyla, alanyazında eğitim ve eğitim araştırmaları kategorisinde duygu ve teknolojiyi bir arada ele alan araştırma makalelerinin, ‘duygunun tanımı’, ‘temel alınan kuramsal çerçeve,’ ‘teknolojinin ele alındığı bağlamla’ ilgili olarak analiz edilmesi; böylece, bir yandan var olan durumun betimlenmesi, bir yandan da araştırmaların nereye doğru evrildiğinin ortaya konulması amaçlanmıştır. Çalışmada 2015 - 2019 yılları arasında SSCI indeksinde taranan dergilerde yayınlanmış olan ve belirlenmiş ölçütlere uyan 75 araştırma makalesi analiz edilmiştir. Analiz sonucunda araştırmaların demografik özellikleri ile ilgili olarak; en fazla yükseköğretim düzeyinde ve lisans ile lisansüstü öğrencilerle çalışıldığı; verilerin, öz bildirime dayalı ölçek ve anket ile toplandığı, bazı çalışmalarda birden fazla veri toplama yaklaşımının kullandığı belirlenmiştir. 75 makalenin 59’unda duygu ile ilgili tanımlara yer verilmediği, 55’inde duygu konusunda herhangi bir kuramsal çerçevenin temel alınmadığı, teknolojinin en çok çevrimiçi öğrenme bağlamında ele alındığı ortaya çıkmıştır. Analiz edilen araştırmalarda duygu ile ilgili operasyonel tanımların eksikliği, araştırmacının duyguya olan yaklaşımının ve araştırma sürecini yürütme perspektifinin anlaşılmasında sınırlılığı beraberinde getirmektedir. Oysa yapılan çalışmalarda kuramsal bir çerçeveden hareket edilmesinin, ilişkileri içeren mekanizmaların anlaşılması için bir zemin oluşturacağı ileri sürülebilir. Bu durum, eğitsel bağlamda duygu ve teknoloji konusunda yapılacak çalışmalar için önceliğin nerede olduğunu ortaya koymaktadır. Sonuç olarak eğitsel bağlamda duygu ve teknoloji üzerine yapılması planlanan araştırmalarda, araştırmacının perspektifini işlevsel tanımlamalar, modeller ve temel aldığı kuramsal çerçeve üzerinden ortaya koymasına gereksinim olduğu ifade edilebilir.

Anahtar Kelimeler

duygu, teknoloji, öğrenme, sistematik haritalama

Kaynakça

• Allcoat, D. & Mühlenen, A. V. (2018). Learning in virtual reality: effects on performance, emotion, and engagement. Research in Learning Technology, 26, 2-13.
• Arguel, A., Lockyer, L., Kennedy, G., Lodge, J. M., & Pachman, M. (2019). Seeking optimal confusion: a review on epistemic emotion management in interactive digital learning environments. Interactive Learning Environments, 27(2), 200-210.
• Barré, J., Michelet, D., Job, A., Truchot, J., Cabon, P., Delgoulet, C., & Tesnière, A. (2019). Does repeated exposure to critical situations in a screen-based simulation improve the self-assessment of non-technical skills in postpartum hemorrhage management?. Simulation & Gaming, 50(2), 102-123.
• Bolkan, S. & Griffin, D. J. (2017). Students’ use of cell phones in class for off-task behaviors: The indirect impact of instructors’ teaching behaviors through boredom and students’ attitudes. Communication Education, 66(3), 313-329.
• Buil, I., Catalán, S. & Martínez, E. (2016). Do clickers enhance learning? A control-value theory approach. Computers & Education, 103, 170-182.
• Burić, I., Sorić, I., & Penezić, Z. (2016). Emotion regulation in academic domain: Development and validation of the academic emotion regulation questionnaire (AERQ). Personality and Individual Differences, 96, 138-147. https://doi.org/10.1016/j.paid.2016.02.074
• Butz, N. T., Stupnisky, R. H., & Pekrun, R. (2015). Students’ emotions for achievement and technology use in synchronous hybrid graduate programmes: A control-value approach. Research in Learning Technology, 23, 1-16. DOI: https://doi.org/10.3402/rlt.v23.26097
• Butz, N. T., Stupnisky, R. H., Pekrun, R., Jensen, J. L. & Harsell, D. M. (2016). The impact of emotions on student achievement in synchronous hybrid business and public administration programs: A longitudinal test of control‐value theory. Decision Sciences Journal of Innovative Education, 14(4), 441-474.
• Castro Rojas, M. D., Bygholm, A. & Hansen, T. G. (2018). Exercising older people´ s brains in Costa Rica: Design principles for using information and communication technologies for cognitive activity and social interaction. Educational Gerontology, 44(2-3), 171-185.
• Chatzara, K., Karagiannidis, C., & Stamatis, D. (2016). Cognitive support embedded in self-regulated e-learning systems for students with special learning needs. Education and Information Technologies, 21(2), 283-299.
• Chen, Z.-H. & Wang, S.-C. (2018). Representations of animal companions on student learning perception: Static, animated and tangible. Educational Technology & Society, 21 (2), 124–133.
• Chernyak, N., & Gary, H. E. (2016). Children’s cognitive and behavioral reactions to an autonomous versus controlled social robot dog. Early Education and Development, 27(8), 1175-1189.
• Chien, C. F., Walters, B. G., Lee, C. Y. & Liao, C. J. (2018). Developing musical creativity through activity theory in an online learning environment. International Journal of Online Pedagogy and Course Design (IJOPCD), 8(2), 57-74.
• Chiu, M. H., Liaw, H. L., Yu, Y. R. & Chou, C. C. (2019). Facial micro‐expression states as an indicator for conceptual change in students' understanding of air pressure and boiling points. British Journal of Educational Technology, 50(1), 469-480.
• Damasio, A. (1995). Descartes’ error: Emotion, reason and the human brain. New York, NY: Penguin Books. Daniels, L. M. & Stupnisky, R. H. (2012). Not that different in theory: Discussing the control-value theory of emotions in online learning environments. Internet and Higher Education, 15, 222–226.
• de Diezmas, E. N. M., & Manzano, P. D. (2016). PLEs in primary school: The learners’ experience in the Piplep Project. Digital Education Review, (29), 45-61.
• Dicheva, D., Dichev C., Agre G., & Angelova G. (2015). Gamification in education: A systematic mapping study. Educational Technology & Society, 18 (3), 75–88.
• Duffy, M. C., Lajoie, S., & Lachapelle, K. (2016). Measuring emotions in medical education: Methodological and technological advances within authentic medical learning environments. In Educational technologies in medical and health sciences education (pp. 181-213). Springer, Cham.
• Dukuzumuremyi, S. & Siklander, P. (2018). Interactions between pupils and their teacher in collaborative and technology-enhanced learning settings in the inclusive classroom. Teaching and Teacher Education, 76, 165-174.
• Eden, S., Heiman, T., & Olenik-Shemesh, D. (2016). Bully versus victim on the internet: The correlation with emotional-social characteristics. Education and Information Technologies, 21(3), 699-713.
• Ekman, P. (1992). An argument for basic emotions. Cognition & Emotion, 6(3-4), 169-200.
• Eliot, J. A. R. & Hirumi, A. (2019). Emotion theory in education research practice: An interdisciplinary critical literature review. Education Technology Research and Development 67, 1065-1084.
• Ertmer, P. A. (2005). Teacher pedagogical beliefs: The final frontier in our quest for technology integration?. Educational technology research and development, 53(4), 25-39.
• Everingham, Y. L., Gyuris, E. & Connolly, S. R. (2017). Enhancing student engagement to positively impact mathematics anxiety, confidence and achievement for interdisciplinary science subjects. International Journal of Mathematical Education in Science and Technology, 48(8), 1153-1165.
• Fage, C., Consel, C., Etchegoyhen, K., Amestoy, A., Bouvard, M., Mazon, C. & Sauzéon, H. (2019). An emotion regulation app for school inclusion of children with ASD: Design principles and evaluation. Computers & Education, 131, 1-21.
• Feidakis, M. (2016). A review of emotion-aware systems for e-learning in virtual environments. In S. Caballé, , & R. Clarisó (Eds), Formative assessment, learning data analytics and gamification (pp. 217-242). Academic Press.
• Feidakis, M., Daradoumis, T., CaballÃ, S., & Conesa, J. (2014). Embedding emotion awareness into e-learning environments. International Journal of Emerging Technologies in Learning, 9(7), 39-46.
• Fidan, M., & Tuncel, M. (2019). Integrating augmented reality into problem based learning: The effects on learning achievement and attitude in physics education. Computers & Education, 142, 1-19. https://doi.org/10.1016/j.compedu.2019.103635.
• Fiedler, K., & Beier, S. (2014). Affect and cognitive processes in educational contexts. In R. Pekrun & L. Linnenbrink- Garcia (Eds.), Educational psychology handbook series. International handbook of emotions in education (pp. 36–55). Routledge/Taylor & Francis Group.
• Glass, C. R. (2017). Self-expression, social roles, and faculty members’ attitudes towards online teaching. Innovative Higher Education, 42(3), 239-252.
• Gross, J. J. (2015). Emotion regulation: Current status and future prospects. Psychological Inquiry, 26(1), 1-26.
• Harley, J. M., Lajoie, S. P., Tressel, T., & Jarrell, A. (2018). Fostering positive emotions and history knowledge with location-based augmented reality and tour-guide prompts. Learning and Instruction, (article in press???). https://doi.org/10.1016/j.learninstruc.2018.09.001
• Hatzigianni, M., Gregoriadis, A., & Fleer, M. (2016). Computer use at schools and associations with social-emotional outcomes–A holistic approach. Findings from the longitudinal study of Australian Children. Computers & Education, 95, 134-150.
• Heckel, C., & Ringeisen, T. (2019). Pride and anxiety in online learning environments: Achievement emotions as mediators between learners' characteristics and learning outcomes. Journal of Computer Assisted Learning, 35, 667-677. https://doi.org/10.1111/jcal.12367.
• Henritius, E., Löfström, E., & Hannula, M. S. (2019). University students’ emotions in virtual learning: a review of empirical research in the 21st century. British Journal of Educational Technology, 50(1), 80-100.
• Hew, K. F., Lan, M., Tang, Y., Jia, C., & Lo, C. K. (2019). Where is the “theory” within the field of educational technology research?. British Journal of Educational Technology, 50(3), 956-971.
• Hinostroza, J., Matamala, C., Labbé, C., Claro, M. & Cabello, T. (2014). Factors (not) affecting what students do with computers and Internet at home. Learning, Media and Technology, 40(1), 43-63.
• Ho, T. K., & Lin, Y. T. (2016). The effects of virtual communities on group identity in classroom management. Journal of Educational Computing Research, 54(1), 3-21.
• Howard, S. K., & Gigliotti, A. (2016). Having a go: Looking at teachers’ experience of risk-taking in technology integration. Education and Information Technologies, 21(5), 1351-1366.
• Huang, T. C., Chen, C. C., & Chou, Y. W. (2016). Animating eco-education: To see, feel, and discover in an augmented reality-based experiential learning environment. Computers & Education, 96, 72-82.
• Humphry, D. & Hampden-Thompson, G. (2019). Primary school pupils' emotional experiences of synchronous audio-led online communication during online one-to-one tuition. Computers & Education, 135, 100-112. https://doi.org/10.1016/j.compedu.2019.03.003.
• Jaber, L. Z., & Hammer, D. (2016). Learning to feel like a scientist. Science Education, 100(2), 189-220.
• Jang, E. E., Lajoie, S. P., Wagner, M., Xu, Z., Poitras, E. & Naismith, L. (2017). Person-oriented approaches to profiling learners in technology-rich learning environments for ecological learner modeling. Journal of Educational Computing Research, 55(4), 552-597.
• Jonassen, D., & Reeves, T. (1996). Learning with technology: Using computers as cognitive tools. In D. Jonassen (Eds.), Handbook of research educational on educational communications and technology (pp. 693-719). New York: Macmillan.
• Kazemitabar, M. & Lajoie, S. P. (2019). Examining changes in medical students’ emotion regulation in an online PBL session. Knowledge Management & E-Learning, 11(2), 129–157.
• Kennedy, E., & Gray, M. (2016). ‘You’re facing that machine but there’sa human being behind it’: students’ affective experiences on an online doctoral programme. Pedagogy, Culture & Society, 24(3), 417-429.
• Kim, C., Kim, D., Yuan, J., Hill, R. B., Doshi, P., & Thai, C. N. (2015). Robotics to promote elementary education pre-service teachers' STEM engagement, learning, and teaching. Computers & Education, 91, 14-31.
• Kim, M. K. & Ketenci, T. (2019). Learner participation profiles in an asynchronous online collaboration context. The Internet and Higher Education, 41, 62-76.
• Kim, Y., Thayne, J. & Wei, Q. (2017). An embodied agent helps anxious students in mathematics learning. Educational Technology Research and Development, 65(1), 219-235.
• King, S. O. (2016). Investigating the most neglected student learning domain in higher education: A case study on the impact of technology on student behaviour and emotions in university mathematics learning. Problems of Education in the 21st Century, 72. 31-52.
• Kitchenham, B., & Charters, S. (2007). Guidelines for performing systematic literature reviews in software engineering. EBSE technical Report-2007-01-2007-01. England: Keele University
• Kleinginna, P. R., & Kleinginna, A. M. (1981). A categorized list of emotion definitions, with suggestions for a consensual definition. Motivation and Emotion, 5(4), 345-379.
• Kocaman-Karoglu, A. (2016). Personal voices in higher education: A digital storytelling experience for pre-service teachers. Education and Information Technologies, 21(5), 1153-1168.
• Kohen, Z. (2019). Informed integration of IWB technology, incorporated with exposure to varied mathematics problem-solving skills: its effect on students’ real-time emotions. International Journal of Mathematical Education in Science and Technology, 50(8), 1128-1151. https://doi.org/10.1080/0020739X.2018.1562119
• Kosmas, P., Ioannou, A. & Retalis, S. (2018). Moving bodies to moving minds: A study of the use of motion-based games in special education. TechTrends, 62(6), 594-601.
• Kristina Loderer, Reinhard Pekrun and James C. Lester, Learning and Instruction, https://doi.org/10.1016/j.learninstruc.2018.08.002
• Lacave, C., Velazquez-Iturbide, J. A., Paredes-Velasco, M., & Molina, A. I. (2020). Analyzing the influence of a visualization system on students’ emotions: An empirical case study. Computers & Education, 149 :103817, DOI: 10.1016/j.compedu.2020.103817.
• Lajoie, S. P., Pekrun, R., Azevedo, R., & Leighton, J. P. (2019). Understanding and measuring emotions in technology-rich learning environments. Learning and Instruction, 101272. https://doi.org/10.1016/j.learninstruc.2019.101272
• Landowska, A. & Brodny, G. (2017). Investigation of educational processes with affective computing methods. e-Mentor, 3 (70), 15-24. http://dx.doi.org/10.15219/em70.1304.
• Lehman, B., D'Mello, S. & Graesser, A. (2012). Confusion and complex learning during interactions with computer learning environments. Internet and Higher Education, 15, 184-194.
• Leony, D., Muñoz-Merino, P. J., Pardo, A., & Kloos, C. D. (2013). Provision of awareness of learners' emotions through visualizations in a computer interaction-based environment. Expert Systems with Applications, 40(13), 5093–5100. https://doi.org/10.1016/j.eswa.2013.03.030
• Lin, H. C. K., Su, S. H., Chao, C. J., Hsieh, C. Y., & Tsai, S. C. (2016). Construction of multi-mode affective learning system: taking affective design as an example. Journal of Educational Technology & Society, 19(2), 132-147.
• Linnenbrink-Garcia, L., & Pekrun, R. (2011). Students’ emotions and academic engagement: Introduction to the special issue. Contemporary Educational Psychology, 36(1), 1-3.
• Liu, C. J., Huang, C. F., Liu, M. C., Chien, Y. C., Lai, C. H., & Huang, Y. M. (2015). Does gender influence emotions resulting from positive applause feedback in self-assessment testing? Evidence from neuroscience. Journal of Educational Technology & Society, 18(1), 337-350.
• Liu, M. C., Huang, Y. M. & Xu, Y. H. (2018). Effects of individual versus group work on learner autonomy and emotion in digital storytelling. Educational Technology Research and Development, 66(4), 1009-1028.
• Loderer, K., Pekrun, R., & Lester, J. C. (2018). Beyond cold technology: A systematic review and meta-analysis on emotions in technology-based learning environments. Learning and instruction, 101162. https://doi.org/10.1016/j.learninstruc.2018.08.002
• Lysenko, L., Rosenfield, S., Dedic, H., Savard, A., Idan, E., Abrami, P. C., Wade C. A., & Naffi, N. (2016). Using interactive software to teach foundational mathematical skills. Journal of Information Technology Education: Innovations in Practice, 15(1), 19-34.
• Makransky, G. & Lilleholt, L. (2018). A structural equation modeling investigation of the emotional value of immersive virtual reality in education. Educational Technology Research and Development, 66, 1141-1164.
• Marchand, G. C., & Gutierrez, A. P. (2012). The role of emotion in the learning process: Comparisons between online and face-to-face learning settings. The Internet and Higher Education, 15(3), 150-160. https://doi.org/10.1016/j.iheduc.2011.10.001
• Mayer, R. E. (2019). Searching for the role of emotions in e-learning. Learning and Instruction, 101213. https://doi.org/10.1016/j.learninstruc.2019.05.010
• McGloin, R., McGillicuddy, K. T. & Christensen, J. L. (2017). The impact of goal achievement orientation on student technology usage in the classroom. Journal of Computing in Higher Education, 29(2), 240-266.
• McKnight, K., O'Malley, K., Ruzic, R., Horsley, M. K., Franey, J. J., & Bassett, K. (2016). Teaching in a digital age: How educators use technology to improve student learning. Journal of research on technology in education, 48(3), 194-211.
• Merwe, V. D. (2019). Exploring The Relationship Between ICT Use, Mental Health Symptoms And Well-Being Of The Historically Disadvantaged Open Distance Learning Student: A Case Study. Turkish Online Journal of Distance Education, 20(1), 35-52.
• Meşe, C. & Dursun, Ö. Ö. (2018). Oyunlaştırma bileşenlerinin duygu, ilgi ve çevrimiçi katılıma etkisi. Eğitim ve Bilim, 43(196), 67-95.
• Meyer, D. K., & Turner, J. C. (2002). Using instructional discourse analysis to study the scaffolding of student self-regulation. Educational psychologist, 37(1), 17-25.
• Moreira-Fontán, E., García-Señorán, M., Conde-Rodríguez, Á., & González, A. (2019). Teachers' ICT-related self-efficacy, job resources, and positive emotions: Their structural relations with autonomous motivation and work engagement. Computers & Education, 134, 63-77.
• Moreno, R., & Mayer, R. E. (2007). Interactive multimodal learning environments. Educational Psychology Review, 19, 309–326
• Muis, K. R., Ranellucci, J., Trevors, G., & Duffy, M. C. (2015). The effects of technology-mediated immediate feedback on kindergarten students' attitudes, emotions, engagement and learning outcomes during literacy skills development. Learning & Instruction, 38, 1-13. https://doi.org/10.1016/j.learninstruc.2015.02.001
• Munezero, M. D., Montero, C. S., Sutinen, E., & Pajunen, J. (2014). Are they different? Affect, feeling, emotion, sentiment, and opinion detection in text. IEEE Transactions on Affective Computing, 5(2), 101-111.
• Muñoz, K., Mc Kevitt, P., Lunney, T., Noguez, J., & Neri, L. (2011). An emotional student model for game-play adaptation. Entertainment Computing, 2(2), 133–141. https://doi.org/10.1016/j.entcom.2010.12.006
• Nakpong, N. & Chanchalor, S. (2019). interactive multimedia games to enhance the emotional intelligence of deaf and hard of hearing adolescents. International Journal of Instruction, 12(2), 305-320. https://doi.org/10.29333/iji.2019.12220a
• Ninaus, M., Greipl, S., Kiili, K., Lindstedt, A., Huber, S., Klein, E., Karnath, H-O., & Moeller, K. (2019). Increased emotional engagement in game-based learning – A machine learning approach on facial emotion detection data. Computers & Education, 142, 103641.ttps://doi.org/10.1016/j.compedu.2019.103641
• Noteborn, G., Carbonell, K. B., Dailey-Hebert, A., & Gijselaers, W. (2012). The role of emotions and task significance in virtual education. The Internet and Higher Education, 15(3), 176-183.
• Oinas, S., Vainikainen, M. P. & Hotulainen, R. (2018). Is technology-enhanced feedback encouraging for all in Finnish basic education? A person-centered approach. Learning and Instruction, 58, 12-21.
• Ouherrou, N., Elhammoumi, O., Benmarrakchi, F. & El Kafi, J. (2019). Comparative study on emotions analysis from facial expressions in children with and without learning disabilities in virtual learning environment. Education and Information Technologies, 24(2), 1777-1792.
• Pacella, D. & López-Pérez, B. (2018). Assessing children's interpersonal emotion regulation with virtual agents: The serious game Emodiscovery. Computers & Education, 123, 1-12.
• Pappas, I. O., Giannakos, M. N. & Mikalef, P. (2017). Investigating students’ use and adoption of with-video assignments: lessons learnt for video-based open educational resources. Journal of Computing in Higher Education, 29(1), 160-177.
• Pekrun, R. (2006). The control-value theory of achievement emotions: Assumptions, corollaries, and implications for educational research and practice. Educational Psychology Review, 18, 315–341.
• Pekrun, R., & Perry, R. P. (2014). Control-value theory of achievement emotions. In R. Pekrun & L. Linnenbrink-Garcia (Eds.), Educational psychology handbook series. International handbook of emotions in education (p. 120–141). Routledge/Taylor & Francis Group.
• Peña, A., Rangel, N., Muñoz, M., Mejia, J., & Lara, G. (2016). Affective behavior and nonverbal interaction in collaborative virtual environments. Journal of Educational Technology & Society, 19(2), 29-41.
• Petersen, K., Vakkalanka, S., & Kuzniarz, L. (2015). Guidelines for conducting systematic mapping studies in software engineering: An update. Information and Software Technology, 64, 1-18.
• Pietarinen, T., Vauras, M., Laakkonen, E., Kinnunen, R., & Volet, S. (2019). High school students' perceptions of affect and collaboration during virtual science inquiry learning. Journal of Computer Assisted Learning, 35(3), 334-348.
• Plass, J. L., Homer, B. D., MacNamara, A., Ober, T., Rose, M. C., Pawar, S., Hovey, C. M., Olsen, A. (2019). Emotional design for digital games for learning: The effect of expression, color, shape, and dimensionality on the affective quality of game characters. Learning & Instruction, 101194.
• Poitras, E. G., Harley, J. M., & Liu, Y. S. (2019). Achievement emotions with location‐based mobile augmented reality: An examination of discourse processes in simulated guided walking tours. British Journal of Educational Technology, 50(6), 3345-3360. https://doi.org/10.1111/bjet.12738.
• Rand, J. (2016). Researching undergraduate social science research. Teaching in Higher Education, 21(7), 773-789.
• Rasi, P. & Vuojärvi, H. (2018). Toward personal and emotional connectivity in mobile higher education through asynchronous formative audio feedback. British Journal of Educational Technology, 49(2), 292-304.
• Reid, H. J., Thomson, C., & McGlade, K. J. (2016). Content and discontent: A qualitative exploration of obstacles to e-learning engagement in medical students. BMC Medical Education, 16(188), 1-8. DOI 10.1186/s12909-016-0710-5.
• Rinchen, S., Ritchie, S. M., & Bellocchi, A. (2016). Emotional climate of a pre-service science teacher education class in Bhutan. Cultural Studies of Science Education, 11(3), 603-628.
• Robinson, K., Wehner, T. & Millward, H. (2019). Is the outcome of remote group work using text based CMC suboptimal? A psychobiological perspective. Computers & Education, 134, 108-118. https://doi.org/10.1016/j.compedu.2019.02.009
• Roblyer, M. D., Doering, A. H. (2014). Integrating Educational Technology into Teaching (6th Edition). Harlow, England : Pearson
• Russell, J. A. (2003). Core affect and the psychological construction of emotion. Psychological Review, 110(1), 145–172. https://doi.org/10.1037/0033-295X.110.1.145
• Sánchez-Martín, J., Álvarez-Gragera, G. J., Dávila-Acedo, M. A. & Mellado, V. (2017). What do K-12 students feel when dealing with technology and engineering issues? Gardner's multiple intelligence theory implications in technology lessons for motivating engineering vocations at Spanish Secondary School. European Journal of Engineering Education, 42(6), 1330-1343.
• Sandanayake, T. C., & Madurapperuma, A. P. (2013). Affective e-learning model for recognising learner emotions in online learning environment. In 2013 International Conference on Advances in ICT for Emerging Regions (ICTer) (pp. 266-271). IEEE. https://doi.org/10.1109/ICTer.2013.6761189
• Scherer, K. R., Shuman, V., Fontaine, J. J. R., & Soriano, C. (2013). The GRID meets the Wheel: Assessing emotional feeling via self-report. In J. J. R. Fontaine, K. R. Scherer, & C. Soriano (Eds.), Series in affective science. Components of emotional meaning: A sourcebook (p. 281–298). Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199592746.003.0019
• Schouten, D. G., Venneker, F., Bosse, T., Neerincx, M. A. & Cremers, A. H. (2017). A digital coach that provides affective and social learning support to low-literate learners. IEEE Transactions on Learning Technologies, 11(1), 67-80.
• Shadiev, R., Hwang, W. Y. & Liu, T. Y. (2018). A study of the use of wearable devices for healthy and enjoyable english as a foreign language learning in authentic contexts. Educational Technology & Society, 21(4), 217–231.
• Shank, D. B. (2014). Technology and emotions. In Handbook of the Sociology of Emotions: Volume II (pp. 511-528). Springer, Dordrecht.
• Shouse, E. (2005). Feeling, emotion, affect. M/C Journal, 8(6), Retrieved from <http://journal.media-culture.org.au/0512/03-shouse.php>.
• Siu, K. W. M., & Wong, Y. L. (2016). Fostering creativity from an emotional perspective: Do teachers recognise and handle students’ emotions?. International Journal of Technology and Design Education, 26(1), 105-121.
• Stark, L., Malkmus, E., Stark, R., Brünken, R., & Park, B. (2018). Learning-related emotions in multimedia learning: An application of control-value theory. Learning and Instruction, 58, 42-52.
• Su, S. H., Lin, H. C. K., Wang, C. H., & Huang, Z. C. (2016). Multi-modal affective computing technology design the interaction between computers and human of intelligent tutoring systems. International Journal of Online Pedagogy and Course Design (IJOPCD), 6(1), 13-28.
• Sulaymani, O. & Fleer, M. (2019). Perezhivanie as a phenomenon and a unit of analysis for studying children’s interactions with iPads in the early years of school in Saudi Arabia. Early Child Development and Care, 189(2), 255-269.
• Susanne P. Lajoie, et al., Learning and Instruction, https://doi.org/10.1016/j.learninstruc.2019.101272)
• Tajeddin, Z. & Aghababazadeh, Y. (2018). Blog-mediated reflection for professional development: Exploring themes and criticality of l2 teachers' reflective practice. TESL Canada Journal, 35(2), 26-50.
• 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.
• Tonguç, G., & Ozkara, B. O. (2020). Automatic recognition of student emotions from facial expressions during a lecture. Computers & Education, 148, 1-12. https://doi.org/10.1016/j.compedu.2019.103797.
• Usluel, Y. K., & Atal, D. (2013). Students’ approach to social network in educational context. The International Journal of Web Based Communities, 9(2), 188-198.
• Verkijika, S. F., & De Wet, L. (2015).. Using a brain-computer interface (BCI) in reducing math anxiety: Evidence from South Africa. Computers & Education, 81, 113-122. https://doi.org/10.1016/j.compedu.2014.10.002
• Wang, C. H. & Lin, H. C. K. (2018a). Emotional design tutoring system based on multimodal affective computing techniques. International Journal of Distance Education Technologies (IJDET), 16(1), 103-117.
• Wang, C. H. & Lin, H. C. K. (2018b). Constructing an affective tutoring system for designing course learning and evaluation. Journal of Educational Computing Research, 55(8), 1111-1128.
• Weiser, O., Blau, I. & Eshet-Alkalai, Y. (2018). How do medium naturalness, teaching-learning interactions and Students' personality traits affect participation in synchronous E-learning?. The Internet and Higher Education, 37, 40-51. https://doi.org/10.1016/j.iheduc.2018.01.001.
• Wu, L. & Kim, M. (2019). See, touch, and feel: Enhancing young children's empathy learning through a tablet game. Mind, Brain, and Education, 13(4), 341-351.https://doi.org/10.1111/mbe.12218.
• Wu, Z., & Chen, J. (2018). Teachers’ emotional experience: Insights from Hong Kong primary schools. Asia Pacific Education Review, 19(4), 531–541. https://doi.org/10.1007/s12564-018-9553-6.
• Xu, J. (2018). Emotion regulation in mathematics homework: An empirical study. The Journal of Educational Research, 111(1), 1–11. https://doi.org/10.1080/00220671.2016.1175409
• Yadegaridehkordi, E., Noor, N. F. M., Ayub, M. N., Affal, H., & Hussin, N. (2017). Affective computing: A closer view of self-reported instruments in education. Journal of Soft Computing and Decision Support Systems, 4(2), 7-13. https://doi.org/10.1016/j.compedu.2019.103649
• Yeh, Y. C., Chang, H. L. & Chen, S. Y. (2019). Mindful learning: A mediator of mastery experience during digital creativity game-based learning among elementary school students. Computers & Education, 132, 63-75.
• Yilmaz, R. M., Kucuk, S., & Goktas, Y. (2017). Are augmented reality picture books magic or real for preschool children aged five to six?. British Journal of Educational Technology, 48(3), 824-841.
• Yuen, A. H. K., Lau, W. W. F., Park, J. H., Lau, G. K. K. & Chan, A. K. M. (2016). Digital equity and students’ home computing: A Hong Kong study. Asia-Pacific Educational Research, 25(4), 509–518.
• Zheng, R., Hicken, B. L., Hill, R. D., Luptak, M., Daniel, C. M., Grant, M., & Rupper, R. (2016). Digital technology and caregiver training for older persons: Cognitive and affective perspectives. Educational Gerontology, 42(8), 540-550.