The effects of materials based on ARCS Model on motivation: A meta-analysis

Serkan Dinçer


This meta-analysis examined the relationship between motivation and materials which are designed based on ARCS Model. Twenty six individual studies were included in the analysis and 28 effect size from these studies were calculated (N = 2140). The results showed positive effects of materials on motivation (g=0.57). Attention was found as the largest effect among the components of ARCS Model (g=0.55). Moreover, overall effect size was calculated 0.48 for relevance, 0.49 for confidence and 0.54 for satisfaction. Sample and duration were identified as two possible moderators. It was found that materials had rather effect on younger groups concerning sampling. As for duration, students’ motivation grew as duration of material use increased. Based on the results in terms of duration moderator, it is thought that the results of experimental studies investigating motivation and use or design of materials in literature may not be reliable because they had short duration of implementation. For this reason, it is suggested that future experimental researches should be performed with long-period implementations.


ARCS Model; Motivation; Multimedia learning environments; Digital materials

Full Text:



Ahmed, W., & Bruinsma, M. (2006). A structural model of self-concept, autonomous motivation and academic performance in cross-cultural perspective. Electronic Journal of Research in Educational Psychology, 4(3), 551-576.

Alessi, S.M. & Trollip, S.R. (2001). Multimedia for learning: Methods and development (3rd ed.). Boston, MA: Allyn & Bacon.

* Alhassan, R. (2014). The effect of project-based learning and the ARCS Motivational Model on students’ achievement and motivation to acquire database program skills. Journal of Education and Practice, 5(21), 158–165.

* All, A., Plovie, B., Nuñez Castellar, E. P., & Van Looy, J. (2017). Pre-test influences on the effectiveness of digital-game based learning: A case study of a fire safety game. Computers & Education, 114, 24–37.

Aydın, S., Yerdelen, S., Gürbüzoğlu-Yalmancı, S., & Göksu, V. (2014). Biyoloji öğrenmeye yönelik akademik motivasyon ölçeği: Ölçek geliştirme çalışması. Eğitim ve Bilim, 39(176), 425-435.

Benware, C. A., & Deci, E. L. (1984). Quality of learning with an active versus passive motivational set. American Educational Research Journal, 21(4), 755-765.

Berlyne, D. E. (1949). “Interest” as a psychological concept. The British Journal of Psychology, 39, 184–195.

Blumenfeld, P. C., Soloway, E., Marx, R. W., Krajcik, J. S., Guzdial, M., & Palincsar, A. (1991). Motivating project-based learning: Sustaining the doing, supporting the learning. Educational psychologist, 26(3-4), 369-398.

Borenstein, M., Hedges, L. V., Higgins, J., & Rothstein, H. R. (2010). A basic introduction to fixed‐effect and random‐effects models for meta‐analysis. Research synthesis methods, 1(2), 97-111.

Borenstein, M., Hedges, L. V., Higgins, J.P., & Rothstein, H. R. (2009). Introduction to meta-analysis. West Sussex: John Wiley & Sons, Ltd.

Cameron, B., & Dwyer, F. (2005). The effect of online gaming, cognition and feedback type in facilitating delayed achievement of different learning objectives. Journal of Interactive Learning Research, 16(3), 243–258.

Card, N. A. (2012). Applied meta-analysis for social science research. New York: Guilford Publications.

Carey, L. M., Carey, J. O. & Pearson, L. C. (1991). Using measures of academic motivation for formative evaluation of the instructional strategy. In the Annual Meeting of the American Educational Research Association, Chicago, MI.

Castro-Alonso, J. C., Ayres, P., & Paas, F. (2016). Comparing apples and oranges? A critical look at research on learning from statics versus animations. Computers & Education, 102, 234-243.

Chan, K. W., Wong, K. Y. A., & LO, S. C. E. (2012). Relational analysis of intrinsic motivation, achievement goals, learning strategies and academic achievement for Hong Kong secondary students. The Asia-Pacific Education Researcher, 21(2), 230-243.

Chauhan, S. (2017). A meta-analysis of the impact of technology on learning effectiveness of elementary students. Computers & Education, 105, 14–30.

* Chen, Y. T. (2012). Implementing an interactive powerpoint into a self-controlled learning environment. Research Journal of Applied Sciences, Engineering and Technology, 4(13), 1928–1933.

Cheung, A. C., & Slavin, R. E. (2012). How features of educational technology applications affect student reading outcomes: A meta-analysis. Educational Research Review, 7(3), 198-215.

* Chin, K.-Y., Lee, K.-F., & Chen, Y.-L. (2015). Impact on student motivation by using a QR-Based u-Learning material production system to create authentic learning experiences. IEEE Transactions on Learning Technologies, 8(4), 367–382.

* Choi, H. J., & Johnson, S. D. (2005). The effect of context-based video ınstruction on learning and motivation in online courses. American Journal of Distance Education, 19(4), 215–227.

Cobb, C. (2013). The use of an animated pedagogical agent as a mnemonic device to promote learning and motivation in online education. Unpublished doctoral dissertation, Walden University, Texas.

* Cook, D. A., Beckman, T. J., Thomas, K. G., & Thompson, W. G. (2009). Measuring motivational characteristics of courses: applying Kellerʼs Instructional Materials Motivation Survey to a web-based course. Academic Medicine, 84(11), 1505–1509.

Cordova, D. I., & Lepper, M. R. (1996). Intrinsic motivation and the process of learning: Beneficial effects of contextualization, personalization, and choice. Journal of Educational Psychology, 88(4), 715-730.

Dalgety, J., Coll, R. K., & Jones, A. (2003). Development of chemistry attitudes and experiences questionnaire (CAEQ). Journal of Research in Science Teaching, 40(7), 649-668.

Davies, R. S., Dean, D. L., & Ball, N. (2013). Flipping the classroom and instructional technology integration in a college- level information systems spreadsheet course. Educational Technology Research and Development, 61(4), 563-580.

Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self-determination in human behavior. New York: Springer Science & Business Media.

Deci, E. L., & Ryan, R. M. (2000). The" what" and" why" of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11(4), 227-268.

Dede, Y. & Yaman, S. (2008). Fen Öğrenmeye Yönelik Motivasyon Ölçeği: Geçerlik ve güvenirlik çalışması. Necatibey Eğitim Fakültesi Elektronik Fen ve Matematik Eğitimi Dergisi, 2(1), 19-37.

* 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.

Dick, W., Carey, L., & Carey, J. O. (2005). The systematic design of instruction. Boston: Pearson.

Dinçer, S. (2014). Eğitim bilimlerinde uygulamalı meta-analiz. Ankara: Pegem A Yayıncılık.

Dinçer, S. (2017). Bilgisayar destekli öğretimde bilgisayar okuryazarlığının, motivasyonun ve öz yeterliliğin öğrenme başarısı üzerindeki etkisi : Değişkenlerin araştırma süresi ile incelenmesi. Uluslararası Eğitim Programları ve Öğretim Çalışmaları Dergisi, 7(14), 147–162.

Dinçer, S. (2018). Are preservice teachers really literate enough to integrate technology in their classroom practice? Determining the technology literacy level of preservice teachers. Education and Information Technologies, 23(6), 2699-2718.

Dinçer, S. & Doğanay, A. (2017). The effects of multiple-pedagogical agents on learners' academic success, motivation, and cognitive load. Computers & Education, 111, 74-100.

Duval, S., & Tweedie, R. (2000). A nonparametric “Trim and Fill” method of accounting for publication bias in meta-analysis. Journal of the American Statistical Association, 95(449), 89-98.

Dweck, C. S. (1986). Motivational processes affecting learning. American Psychologist, 41(10), 1040-1048.

Egger, M., Davey Smith, G., Schneider, M., & Minder, C. (1997). Bias in meta-analysis detected by a simple, graphical test. British Medical Journal, 315, 629–634.

Ersarı, G., & Naktiyok, A. (2012). İş görenin içsel ve dışsal motivasyonunda stresle mücadele tekniklerinin rolü. Atatürk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 16(1), 81-101.

Eryılmaz, A., & Ercan, L. (2014). Ergenler için Ders Çalışmaya Motive Olma Ölçeğinin geliştirilmesi. Başkent Universıty Journal of Education, 1(1), 34-40.

Field, A. P., & Gillett, R. (2010). How to do a meta-analysis. British Journal of Mathematical and Statistical Psychology, 63, 665-694.

Ford, M. E. (1992). Motivating humans: Goals, emotions, and personal agency beliefs. Newbury Park, CA: Sage Publications.

Fryer, D. (1931). The measurement of interest. New York: Holt.

Gagne, R. M., Wager, W. W., Golas, K. C., & Keller, J. M. (2005). Principles of instructional design (Fifth ed.). Belmont, CA: Thomson Wadsworth.

Gillet, N., Vallerand, R. J., & Lafrenière, M. A. K. (2012). Intrinsic and extrinsic school motivation as a function of age: The mediating role of autonomy support. Social Psychology of Education, 15(1), 77-95.

* Gleixner, S., Douglas, E., & Graeve, O. (2008). Engineering project laboratory modules for an ıntroduction to materials course. American Society for Engineering Education, 13(519), 1–13.

Glynn, S. M., Taasoobshirazi, G., & Brickman, P. (2007). Nonscience majors learning science: A theoretical model of motivation. Journal of Research in Science Teaching, 44(8), 1088-1107.

Harter, S. (1981). A new self-report scale of intrinsic versus extrinsic orientation in the classroom: motivational and informational components. Developmental Psychology, 17(3), 300-312.

Hattie, J. (2009). Visible learning: A synthesis of over 800 meta-analyses relating to achievement. London [u.a.]: Routledge

Hawlitschek, A., & Joeckel, S. (2017). Increasing the effectiveness of digital educational games: the effects of a learning instruction on students’ learning, motivation and cognitive load. Computers in Human Behavior, 72, 79-86.

Hayden, A., Lorch, E. P., Almasi, J., & Milich, R. (2017). Lessons learned from the development of a narrative comprehension intervention for third-graders at risk for ADHD. The ADHD Report, 25(6), 1-6.

Hidi, S. (2006). Interest: A unique motivational variable. Educational Research Review, 1(2), 69-82.

Hidi, S., Berndorff, D., & Ainley, M. (2002). Children’s argument writing, interest and self-efficacy: An intervention study. Learning and Instruction, 12(4), 429–446.

* Hu, A., Shewokis, P. A., Ting, K., & Fung, K. (2016). Motivation in computer-assisted instruction. The Laryngoscope, 126, 5–13.

Huang, W. H., Huang, W. Y., Diefes-Dux, H., & Imbrie, P. K. (2006). A preliminary validation of attention, relevance, confidence and satisfaction model-based Instructional Material Motivational Survey in a computer-based tutorial setting. British Journal of Educational Technology, 37(2), 243–259.

* Huett, J. B., Moller, L., Young, J., Bray, M., & Huett, K. C. (2008). Supporting the distant student: The effect of arcs-based strategies on confidence and performance. Quarterly Review of Distance Education, 9(2), 113–126.

* Hung, H. C., & Young, S. S. C. (2017). Applying multi-touch technology to facilitate the learning of art appreciation: From the view of motivation and annotation. Interactive Learning Environments, 25(6), 733–748.

* Hung, H.-C., Shwu-Ching Young, S., & Lin, K.-C. (2017). Exploring the effects of integrating the iPad to improve students’ motivation and badminton skills: A WISER model for physical education. Technology, Pedagogy and Education, 5139, 1–14.

Izard, C. E., & Ackerman, B. P. (2000). Motivational, organizational, and regulatory functions of discrete emotions. In M. Lewis, & J. M. HavilandJones (Eds.), Handbook of emotions (2nd ed., pp. 253–264). New York: Guilford Press

* Jing, T. J., Tarmizi, R. A., Bakar, K. A., & Aralas, D. (2017). Utilization of variation theory in the classroom: Effect on students’ algebraic achievement and motivation. Electronic Journal of Research in Educational Psychology, 15, 1–8.

* Juan, Y.-K., & Chao, T.-W. (2015). Game-based learning for green building education. Sustainability, 7(5), 5592–5608.

* Katsa, M., Sergis, S., & Sampson, D. G. (2016). Investigating the potential of the Flipped Classroom Model in K-12 ICT teaching and learning: An action research study. International Association for Development of the Information Society, 20(1), 210–218.

Keller, J. M. (1983). Motivational design of Instruction. In C. M. Reigeluth (Ed.) Instructional design theories and models: An overview of their current status (pp. 383-434). Hillsdale: Lawrence Erlbaum.

Keller, J. M. (1987a). Development and use of the ARCS Model of instructional design. Journal of Instructional Development, 10(3), 2-10.

Keller, J. M. (1987b). Instructional materials motivation scale (IMMS). Unpublished manuscript. The Florida State University.

Keller, J. M. (1999). Motivation in cyber learning environments. Educational Technology International, 1(1), 7-30.

Keller, J. M. (2006). Development of two measures of learner motivation: CIS and IMMS. from

Keller, J. M. (2008). First principles of motivation to learn and e-learning. Distance Education, 29(2), 175-185.

Keller, J. M. (2010). Motivational design for learning and performance: The ARCS Model approach. New York, NY: Springer.

Keller, J. M., & Kopp, T. (1987). An application of the ARCS Model of motivational design. In C. M. Reigeluth (Ed.), Instructional-design theories in action: Lessons illustrating selected theories and models (pp. 289–320). Hillsdale: Lawrence Erlbaum.

Keller, J. M., & Suzuki, K. (1988). Use of the ARCS Motivation Model in courseware design. In D. H. Jonassen (Ed.), Instructional designs for microcomputer courseware (pp. 289–320). Hillsdale: Erlbaum.

* Kostaris, C., Sergis, S., Sampson, D. G., Michail, Ν., Pelliccione, L., Kostaris, C., … Pelliccione, L. (2017). Investigating the potential of the Flipped Classroom Model in K-12 ICT teaching and learning: An action research study. Educational Technology & Society, 20(1), 261–273.

Kriegbaum, K., Becker, N., & Spinath, B. (2018). The relative importance of intelligence and motivation as predictors of school achievement: A meta-analysis. Educational Research Review, 25, 120–148.

Kutlu, H. & Sözbilir, M. (2011). Yaşam temelli ARCS öğretim modeliyle 9. sınıf kimya dersi “Hayatımızda Kimya” ünitesinin öğretimi. Ondokuz Mayıs Üniversitesi Eğitim Fakültesi Dergisi, 30(1), 29-62.

Lau, S. H., & Woods, P. C. (2009). Understanding the behavior changes in belief and attitude among experienced and inexperienced learning object users. Computers & Education, 52(2), 333-342.

Lazarides, R., Gaspard, H., & Dicke, A.-L. (2018). Dynamics of classroom motivation: Teacher enthusiasm and the development of math interest and teacher support. Learning and Instruction, (January), 1–12.

* Lee, N. J., Chae, S., Kim, H., Lee, J., Min, H. J., & Park, D. (2016). Mobile-based video learning outcomes in clinical nursing skill education. CIN: Computers, Informatics, Nursing, 34(1), 8–16.

Lepper, M. R. (1988). Motivational considerations in the study of instruction. Cognition and Instruction, 5(4), 289-309.

Li, K., & Keller, J. M. (2018). Use of the ARCS Model in education: A literature review. Computers & Education, 122, 54-62.

Lipsey, M. W., & Wilson, D. B. (2001). Practical Meta Analysis. Applied Social Research Methods Series (Vol. 49). London: SAGE Publications.

Lowe, R., & Schnotz, W. (Eds.). (2008). Learning with animation: Research implications for design. New York: Cambridge University Press.

Main, R. G. (1993). Integrating motivation into the instructional design process. Educational Technology, 33(12), 37-41.

Malone, T. (1981). Toward a theory of intrinsically motivating instruction. Cognitive Science, 5, 333–369.

Marsh, H. W., Trautwein, U., Lüdtke, O., Köller, O., & Baumert, J. (2005). Academic self-concept, interest, grades, and standardized test scores: Reciprocal effects models of causal ordering. Child Development, 76(2), 397–416.

Maslow, A. H. (1943). A theory of human motivation. Psychological Review, 50(4), 370-396.

Means, T. B., Jonassen, D. H., & Dwyer, F. M. (1997). Enhancing relevance: Embedded ARCS strategies vs. purpose. Educational Technology Research and Development, 45(1), 5-17.

McKeachie, W. J., Pintrich, P. R., & Lin, Y. G. (1985). Teaching learning strategies. Educational Psychologist, 20(3), 153-160.

Moller, L., & Russell, J. D. (1994). An application of the ARCS Model design process and confidence-building strategies. Performance Improvement Quarterly, 7(4), 54–69.

Mor, N., & Winquist, J. (2002). Self-focused attention and negative affect: a meta-analysis. Psychological bulletin, 128(4), 638-662.

Mottaz, C. J. (1985). The relative importance of intrinsic and extrinsic rewards as determinants of work satisfactıon. The Sociological Quarterly, 26(3), 365-385.

* Mumtaz, K., Iqbal, M. M., Khalid, S., Rafiq, T., Owais, S. M., & Al Achhab, M. (2017). An E-assessment framework for blended learning with augmented reality to enhance the student learning. Eurasia Journal of Mathematics, Science and Technology Education, 13(8), 4419–4436.

Newstrom, J. W., & Davis, K. (2002). Organizational Behavior human behavior at work. New York: McGraw-Hill.

Niemiec, C. P., & Ryan, R. M. (2009). Autonomy, competence, and relatedness in the classroom Applying self-determination theory to educational practice. Theory and Research in Education, 7(2), 133-144.

Orwin, R. G. (1983). A fail-safe N for effect size in meta- analysis. Journal of Educational Statistics, 8, 157–159.

Paas, F., Tuovinen, J. E., van Merriënboer, J. J. G., & Darabi, A. A. (2005). A motivational perspective on the relation between mental effort and performance: Optimizing learner involvement in instruction. Educational Technology Research & Development, 53(3), 25–34.

Pintrich, P. R. (2003). A motivational science perspective on the role of student motivation in learning and teaching contexts. Journal of Educational Psychology, 95(4), 667–686.

Pintrich, P. R., & Maehr, M. L. (Eds.). (2004). Advances in motivation and achievement: Motivating students, improving schools (Vol. 13). Oxford: JAI, An Imprint of Elsevier Science.

* Podges, M., & Kommers, P. (2013). The effect of problem based learning on the attitude , motivation and reflection of students. In The 2nd Biennial Conference of the South African Society for Engineering Education (pp. 138–150). Cape Town.

* Proske, A., Roscoe, R. D., & McNamara, D. S. (2014). Game-based practice versus traditional practice in computer-based writing strategy training: Effects on motivation and achievement. Educational Technology Research and Development, 62(5), 481–505.

Radel, R., Pelletier, L., Baxter, D., Fournier, M., & Sarrazin, P. (2014). The paradoxical effect of controlling context on intrinsic motivation in another activity. Learning and Instruction, 29, 95-102.

Renninger, A. K., & Hidi, S. (2015). The power of interest for motivation and engagement. New York: Routledge.

Ricci, K. E., Salas, E., & Cannon-Bowers, J. A. (1996). Do computer-based games facilitate knowledge acquisition and retention? Military Psychology, 8(4), 295–307.

Richter, J., Scheiter, K., & Eitel, A. (2016). Signaling text-picture relations in multimedia learning: A comprehensive meta-analysis. Educational Research Review, 17, 19–36.

Rieber, L. (1996). Seriously considering play: Designing interactive learning environments based on the blending of microworlds, simulations, and games. Educational Technology Research and Development, 44(2), 43–58.

* Rigby, K. (2015). Real-time computer-based simulation as an intervention in aerodynamics education. Journal of Aviation/Aerospace Education & Research, 24(2), 1–17.

Roscoe, R. D., Brandon, R. D., Snow, R. L., & McNamara, D. S. (2013). Game-based writing strategy practice with the writing Pal. In K. E. Pytash & R. E. Ferdig (Eds.), Exploring technology for writing and writing instruction (pp. 1–20). Hershey: Information Science Reference.

Rosenthal, R. (1991). Meta- analytic procedures for social research (revised edition). Newbury Park, CA: SAGE Publications.

Rothstein, H. R., Sutton, A. J., & Borenstein, M. (Eds.). (2006). Publication bias in meta-analysis: Prevention, assessment and adjustments. West Sussex: John Wiley & Sons.

Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), 68-78.

Schiefele, U. (1991). Interest, learning, motivation. Educational Psychologist, 26(3-4), 299-323.

Schrader, C., Reichelt, M., & Zander, S. (2018). The effect of the personalization principle on multimedia learning: the role of student individual interests as a predictor. Educational Technology Research and Development, 66(6), 1387-1397.

Schunk, D. H., & Pajares, F. (2001). The Development of Academic Self-Efficacy. In A. Wigfield & J. Eccles (Eds). Development of Achievement motivation (pp.15-31). San Diego: American Pres.

Schunk, D. H., & Swartz, C. W. (1993). Goals and progress feedback: Effects on self-efficacy and writing achievement. Contemporary Educational Psychology, 18(3), 337–354.

Siddiq, F., Hatlevik, O. E., Olsen, R. V., Throndsen, I., & Scherer, R. (2016). Taking a future perspective by learning from the past – A systematic review of assessment instruments that aim to measure primary and secondary school students’ ICT literacy. Educational Research Review, 19, 58–84.

* Skromme, B. J., Rayes, P. J., Whitlatch, C. D., Wang, Q., Barrus, A., Quick, J. M., … Frank, T. S. (2013). Computer-aided instruction for introductory linear circuit analysis. In 2013 IEEE Frontiers in Education Conference (FIE) (pp. 314–319). IEEE.

Slavin, R. E. (2003). Educational psychology: Theory into practice (7th ed.). Boston: Allyn & Bacon.

Song, S. H., & Keller, J. M. (1999). The ARCS Model for developing motivationally-adaptive computer-assisted instruction. In ERIC, Retrieved from

Song, S. H., & Keller, J. M. (2001). Effectiveness of motivationally adaptive computer-assisted instruction on the dynamic aspects of motivation. Educational Technology Research & Development, 49(2), 5–22.

Steers, R. M., & Porter, L. W. (1991). Motivation and work behavior (5th ed.). New York, NY: McGraw-Hill.

* Stefaniak, J. E., & Tracey, M. W. (2015). An exploration of student experiences with learner-centered instructional strategies. Contemporary Educational Technology, 6(2), 95–112.

* Stepan, K., Zeiger, J., Hanchuk, S., Del Signore, A., Shrivastava, R., Govindaraj, S., & Iloreta, A. (2017). Immersive virtual reality as a teaching tool for neuroanatomy. International Forum of Allergy & Rhinology, 7(10), 1006–1013.

Sun, J. C. Y., & Yeh, K. P. C. (2017). The effects of attention monitoring with EEG biofeedback on university students' attention and self-efficacy: The case of anti-phishing instructional materials. Computers & Education, 106, 73-82.

Sun, P. C., Tsai, R. J., Finger, G., Chen, Y. Y., & Yeh, D. (2008). What drives a successful e-Learning? An empirical investigation of the critical factors influencing learner satisfaction. Computers & education, 50(4), 1183-1202.

Sureka, A., Gupta, M., Sarkar, D., & Chaudhary, V. (2013). A Case-study on teaching undergraduate-level software engineering course using inverted-classroom, large-group, real-client and studio-based instruction model. Retrieved from

Şimşek, A. (2014). Interview with John M. Keller on motivational design of instruction. Contemporary Educational Technology, 5(1), 90–95.

Tuan, H. L., Chin, C. C., & Shieh, S. H. (2005). The development of a questionnaire to measure students' motivation towards science learning. International Journal of Science Education, 27(6), 639-654.

Vallerand, R. J., & Blssonnette, R. (1992). Intrinsic, extrinsic, and amotivational styles as predictors of behavior: A prospective study. Journal of personality, 60(3), 599-620.

Vancouver, J. B., & Kendall, L. N. (2006). When self-efficacy negatively relates to motivation and performance in a learning context. Journal of Applied Psychology, 91(5), 1146-1153.

Visser, L., Plomp, T., Amirault, R. J., & Kuiper, W. (2002). Motivating students at a distance: The case of an international audience. Educational Technology Research and Development, 50(2), 94-110.

Watters, J. J., & Ginns, I. S. (2000). Developing motivation to teach elementary science: Effect of collaborative and authentic learning practices in preservice education. Journal of Science Teacher Education, 11(4), 301-321.

Weiner, B. (1990). History of motivational research in education. Journal of Educational Psychology, 82(4), 616-622.

* Yilmaz, F. G. K., & Keser, H. (2016). The impact of reflective thinking activities in e-learning: A critical review of the empirical research. Computers & Education, 95, 163–173.

* Yoon, J.-O., & Kim, M. (2011). The effects of captions on deaf students’ content comprehension, cognitive load, and motivation in online learning. American Annals of the Deaf, 156(3), 283–289.

Zepeda, C. D., Richey, J. E., Ronevich, P., & Nokes-Malach, T. J. (2015). Direct instruction of metacognition benefits adolescent science learning, transfer, and motivation: An in vivo study. Journal of Educational Psychology, 107(4), 954-970.

Zimmerman, B. J., & Risemberg, R. (1997). Becoming a self-regulated writer: A social cognitive perspective. Contemporary Educational Psychology, 22(1), 73–101.

Zusho, A., Pintrich, P. R., & Coppola, B. (2003). Skill and will: The role of motivation and cognition in the learning of college chemistry. International Journal of Science Education, 25(9), 1081-1094.


  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

 ISSN: 1305-3515