臺灣博碩士論文加值系統

近年來大規模開放線上課堂 (Massive Open Online Course, MOOC) 的興起，使人們能方便地透過網路來學習線上課程，然而，MOOC本身的便利性，卻也造成「高註冊率，低完課率」的現象，加上缺乏學分壓力、中輟不會得到懲罰、證書的獎勵性質大於實用性質等因素，讓無法高度自律的學習者很難堅持完成課程，而許多研究也顯示自我調整學習能力對學習持續性或學習成效有正向的影響，但多數研究對於自我調整學習策略的分類意見分歧，沒有一致性的策略歸納，這對於未來面對更多元的學習變化與挑戰，缺乏成熟且有效的自我調整學習運作機制，來作為學習者的參考。而另一方面，學習者往往無法有效地轉化為MOOC平台之消費者，也鮮少有研究關心MOOC證書在社會的通用性與價值認可。因此，本研究欲探討MOOC學習者的自我調整學習歷程對於學習成效之影響，並透過有學習者體驗後之認知角度，觀察影響其再次使用的購買意願程度。
本研究以問卷調查法為研究方法，針對使用過Coursera、edX為主的MOOC平台資訊科技課程之學習者，作為問卷發放對象，總共回收 361 份有效問卷，再利用結構方程模式進行資料分析。根據研究結果顯示，學習動機對再次使用購買意願並無顯著影響，但對後設認知策略、資源管理策略、認知有用性皆有正向的顯著關係，而兩種自我調整學習策略會進而促進學習成效，另外，學習成效與認知有用性對再次使用購買意願也具有正向的顯著關係。本研究發現若要提升MOOC學習者的學習成效，必須改善學習動機與自我調整學習策略，而要增加再次使用的購買意願，則必須提升課程有用性、改善學習歷程的體驗，使學習意願提升，進而有較好的學習成效，並影響再次使用的購買意願。

The rise of Massive Open Online Course (MOOC) in recent years provides users with varieties of online courses through the Internet. However, for learners who are inadequately self-disciplined, the convenience of MOOC, instead, results in the phenomenon of high enrollment rates with low completion rates due to lacking of pressures or punishments in terms of the structures. Despite the fact that several studies revealed that self-regulated learning strategies have positive impacts on the learning effectiveness, many of which have divergent arguments on the sorts of self-regulated learning strategies. In addition, there are few research focus on the values of MOOC certificates recognized in the society. Therefore, this research aims to investigate the impact of self-regulated learning process of MOOC learners on the learning effectiveness, and to observe the influence on the repurchase intention through the perceived usefulness of leaners.
The study adopted a survey research approach for data collection and targeted on learners who had learned an information technology course on Coursera, edX or other MOOC platforms. A total of 361 valid questionnaires were collected using structural equation modeling (SEM) to validate the model and hypotheses. The results show that learning motivation has nonsignificant effects on the repurchase intention, while positive effects on metacognitive strategies, resource management strategies, and perceived usefulness are observed; meanwhile, self-regulated learning strategies can further improve learning effectiveness. Moreover, learning effectiveness and perceived usefulness have positive effects on repurchase intention significantly. The results revealed that learners must improve learning motivation and self-regulated learning strategies in order to raise the learning effectiveness. Also, for raising repurchase intention, MOOC platforms must promote course usefulness and advance the experience of learning process to achieve better learning effectiveness and finally affect repurchase intention.

摘要 I
ABSTRACT II
誌謝 VI
表目錄 X
圖目錄 XI
第一章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的 3
第三節 研究範圍與限制 4
第四節 研究流程 5
第二章 文獻探討 6
第一節 自我調整學習理論 (SELF-REGULATED LEARNING THEORY) 6
2.1.1自我調整學習定義 6
2.1.2自我調整學習模型 7
2.1.3自我調整學習策略 14
2.1.4 自我調整學習策略的評估方式 17
第二節 大規模開放式線上課程 (MASSIVE OPEN ONLINE COURSES) 19
2.2.1 大規模開放式線上課程的定義 19
2.2.1 COURSERA平台與課程的介紹 20
第三節 學習動機 (LEARNING MOTIVATION) 28
2.3.1 學習動機的定義 28
2.3.2 學習動機的評估方式 29
第四節 學習成效 (LEARNING EFFECTIVENESS) 30
2.4.1 學習成效的定義 30
2.4.2 學習成效的評估方式 31
第五節 認知有用性 (PERCEIVED USEFULNESS) 34
第六節 再購意願 (REPURCHASE INTENTION) 35
第七節 小結 35
第三章 研究方法 38
第一節 研究假說與衡量構面 38
3.1.1 學習動機與自我調整學習策略 38
3.1.2 自我調整學習策略與學習成效 39
3.1.3 學習動機與認知有用性 40
3.1.4 學習動機與再購意願 41
3.1.5 學習成效與再購意願 41
3.1.6 認知有用性與再購意願 42
第二節 研究架構 43
第三節 問卷設計 44
3.3.1 學習動機 44
3.3.2 自我調整學習策略 46
3.3.3 學習成效 48
3.3.4 認知有用性 49
3.3.5 再購意願 50
第四節 前測與資料分析 50
3.4.1 前測 50
3.4.2 資料蒐集 56
第五節 資料分析方法 57
第四章 資料分析與結果 60
第一節 敘述性統計分析 60
4.1.1 問卷回收狀況 60
4.1.2 資料基本敘述性統計 61
4.1.3 研究變項敘述性統計 63
4.1.4 研究變項常態性檢定 63
第二節 信度分析 67
第三節 結構方程式衡量模型 71
4.3.1 收斂效度 71
4.3.2 區別效度 74
4.3.3 共線性檢定 78
第四節 結構方程式結構模型 79
4.4.1 路徑分析 79
第五節 研究發現 81
第五章 結論 84
第一節 學術貢獻 84
第二節 實務貢獻 85
第三節 研究限制與未來研究方向 86
參考文獻 88
附錄 A、前測問卷 96
附錄 B、正式問卷 103

中文文獻
邱皓政 (2003)。結構方程模式：LISREL 的理論、技術與應用。台北：雙葉書廊有限公司。
吳明隆 (2007)。SPSS 操作與應用：問卷統計分析實務。五南圖書出版股份有限公司。
英文文獻
Ainley, M., Corrigan, M., ＆ Richardson, N. (2005). Students, tasks and emotions: Identifying the contribution of emotions to students reading of popular culture and popular science texts. Learning and Instruction, 15(5), 433–447.
Alexander, P. A., Graham, S., ＆ Harris, K. R. (1998). A perspective on strategy research: Progress and prospects. Educational Psychology Review, 10(2), 129-154.
Alraimi, K. M., Zo, H., ＆ Ciganek, A. P. (2015). Understanding the MOOCs continuance: the role of openness and reputation. Computers and Education, 80(3), 28-38.
Anderson, T., ＆ McGreal, R. (2012). Disruptive pedagogies and technologies in universities. Education Technology and Society, 15(4), 380-389.
Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall.
Banerjee, A., Banerjee, P., Ye, N., ＆ Dech, F. (1999). Assembly planning effectiveness using virtual reality. Presence: Teleoperators ＆ Virtual Environments, 8(2), 204-217.
Barnard, L., Paton, V., ＆ Lan, W. (2010). Profiles in self-regulated learning in the online learning environment. International Review of Research in Open and Distance Learning, 11(1), 61-80.
Bartoletti, R. (2016), Learning through Design: MOOC Development as a Method for Exploring Teaching Methods. Current Issues in Emerging eLearning, 3(1), 9-25.
Boekaerts M. (2010), Motivation and self-regulation: Two close friends. In: Urdan T.C., Karabenick S.A. (Eds.), The Decade Ahead: Applications and Contexts of Motivation and Achievement (pp. 69-108). Bingley, UK: Emerald.
Borkowski, J., Chan, L., ＆ Muthukrishna, N. (2000). A process-oriented model of metacognition: Links between motivation and executive functioning. In G. Schraw ＆ J. C. Impara (Eds.), Issues in the measurement of metacognition. NE: University of Nebraska-Lincoln.
Boven, D. T. (2013). The next game changer: the historical antecedents of the MOOC movement in education. eLearning Papers, 33(1), 1-7.
Bulut, Z. A. (2015). Determinants of repurchase intention in online shopping: A Turkish consumer’s perspective. International Journal of Business and Social Science, 6(10), 55–63.
Bushnell, D. S. (1990). Input, process, output: A model for evaluating training. Training ＆ Development Journal, 44(3), 41-44.
Chang, M. M. (2007). Enhancing web-based language learning through self-monitoring. Journal of Computer-Assisted Learning, 23(3), 187−196.
Chrysafiadi, K., ＆ M. Virvou. (2013). PeRSIVA: an empirical evaluation method of a student model of an intelligent e-Learning environment for computer Programming. Computers and Education, 68(31), 322–333.
Cornally, N., ＆ Mccarthy, G. (2011). Help-seeking behaviour: A concept analysis. International Journal of Nursing Practice, 17(3), 280–288.
Davis, F. D., Bagozzi, R. P., ＆ Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003.
Dhawal, S (2017, January 22). A Review of MOOC Stats and Trends in 2017. Retrieved October 23, 2018, from https://www.class-central.com/moocs-year-in-review-2017
Diefenbach, A., Weinstein, D., ＆ O'Reilly, J. (1993). Scales for assessing perceptions of health hazard susceptibility. Health Education Research, 8(2), 181-192.
Dweck, C. ＆ Leggett, E. (1988), A social-cognitive approach to motivation and personality. Psychological Review, 95(2), 256–273.
Effeney, G., Carroll, A., ＆ Bahr, N. (2013). Self-regulated learning: Key strategies and their sources in a sample of adolescent males1. Australian Journal of Educational and Developmental Psychology, 13(5), 58-74.
Elliot, A.J (1999). Approach and avoidance motivation and achievement goals, Educational Psychologist, 34(3), 169-189.
Engel, J. F., Blackwell, R. D., ＆ Miniard, P. W. (2001). Consumer Behavior, 8th. Fort Worth, Tex: Harcourt College Publishers.
Filcher, C., ＆ G. Miller. (2000). Learning strategies for distance education students. Journal of Agricultural Education, 41(1), 60–68.
Garcia, R., Falkner, K., ＆ Vivian, R. (2018). Systematic literature review: Self-Regulated Learning strategies using e-learning tools for Computer Science. Computers and Education, 123(12), 150–163.
Giannakos, M. N. (2013). Exploring the video-based learning research: A review of the literature. British Journal of Educational Technology, 44(6), 191-195.
Guay, F., Ratelle, C. F., ＆ Chanal, J. (2008). Optimal learning in optimal contexts: The role of selfdetermination in education. Canadian Psychology, 49(3), 233.
Hsu, W. K. K., ＆ Huang, S. H. S. (2006). Determinants of computer
self-efficacy—An examination of learning motivations and learning environments. Journal of Educational Computing Research, 35(3), 245-265.
Hattie, J. ＆ Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(3), 81–112.
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., ＆ Tatham, R. L. (2010). SEM: an introduction. Multivariate Data Analysis: A Global Perspective (7th ed., pp. 629–686). Upper Saddle River, NJ: Pearson Education.
Hair, J. F., Hult, G. T. M., Ringle, C., ＆ Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM). Thousand Oaks: Sage Publications.
Hellier, P. K., Geursen, G. M., Carr, R. A., and Richard, J. A. (2003). Customer repurchase intention: A general structural equation model. European Journal of Marketing, 37(11), 1762-1800.
Holcomb, P. J. (1993). Semantic priming and stimulus degradation: Implications for the role of the N400 in language processing. Psychophysiology, 30(1), 47-61.
Hone, K. S., ＆ El Said, G. R. (2016). Exploring the factors affecting MOOC retention: A survey study. Computers and Education, 98(12), 157–168.
Hubalovsky, S., Hubalovska, M., ＆ Musilek, M. (2018). Assessment of the influence of adaptive E-learning on learning effectiveness of primary school pupils. Computers in Human Behavior, 92(65), 691-705.
Jeffrey, R. Y (2018, June 7). Edsurge: Andrew Ng Is Probably Teaching More Students Than Anyone Else on the Planet. EdSurge. Retrieved October 6, 2018, from https://www.edsurge.com/news/2018-06-07-andrew-ng-is-probably-teaching-more-students-than-anyone-else-on-the-planet-without-a-university-involved
Jordan, K. (2015, June 12). MOOC Completion Rates. Retrieved November 2, 2018, from http://www.katyjordan.com/MOOCproject.html
Jonassen, D.H. (1985). Learning strategies: A new educational technology. Programmed Learning and Educational Technology, 22(1), 26-34.
Jurisevic, M., Glazar, S. A., Pučko, C. R., ＆ Devetak, I. (2008). Intrinsic motivation of pre‐service primary school teachers for learning chemistry in relation to their academic achievement. International Journal of Science Education, 30(1), 87-107.
Kannan, V. R., ＆ Tan, K. C. (2005). Just in time, total quality management, and supply chain management: understanding their linkages and impact on business performance. Omega, 33(2), 153-162.
Kirkpatrick, D. L., ＆ Kirkpatrick, J. D. (2009). Evaluating Training Programs: The Four Levels (3rd ed.). San Francisco, CA: Berrett-Koehler.
Kotler, P. (2000). Marketing management:Analysis, planning implementation and control (9th ed.). Englewood Cliffs, NJ: Prentice-Hall Inc.
Kline, R. B. (2011). Principles and Practice of Structural Equation Modeling (3th ed.). New York: The Guilford Press.
Kizilcec, R. F., ＆ Schneider, E. (2015). Motivation as a lens to understand online Learners: Toward data-driven design with the OLEI scale. ACM Transactions on Computer-Human Interactions, 22(2), 1-24.
Kizilcec, R. F., Perez-Sanagustín, M., ＆ Maldonado, J. J. (2017). Self-regulated learning strategies predict learner behavior and goal attainment in Massive Open Online Courses. Computers and Education, 104(2), 18–33.
Kuhl, J. (2000). A functional-design approach to motivation and self-regulation: The dynamics of personality systems and interactions. In M. Boekaerts ＆ P. R. Pintrich (Eds.), Handbook of self-regulation (pp. 111-169). San Diego, CA: Academic Press.
Lee, S. W. Y., ＆ Tsai, C. C. (2011). Students’ perceptions of collaboration, self-regulated learning, and information seeking in the context of Internet-based learning and traditional learning. Computers in Human Behavior, 27(2), 905–914.
Littlejohn, A., Hood, N., Milligan, C., ＆ Mustain, P. (2016). Learning in MOOCs: Motivations and self-regulated learning in MOOCs. Internet and Higher Education, 29(5), 40–48.
Lynch, R., ＆ Dembo, M. (2004). The relationship between self-regulation and online learning in a blended learning context. International Review of Research in Open and Distance Learning, 5(2), 1−16.
Mahmoodi, M. H., Kalantari, B., ＆ Ghaslani, R. (2014). Self-Regulated Learning (SRL), Motivation and Language Achievement of Iranian EFL Learners. Procedia - Social and Behavioral Sciences, 98(137), 1062–1068.
McKeachie, W. J., Pintrich, P.R., Lin, Y., and Smith, D. (1986). Teaching and learning in the college classroom: A review of the research literature. Michigan, USA: University of Michigan National Center for Research to Improve Postsecondary Teaching and Learning. (ERIC Document Reproduction Service No. ED 314999).
Means, B., Toyama, Y., Murphy, R., Bakia, M., Jones, K. (2010, September). Evaluation of Evidence-Based Practices in Online Learning: A Meta-Analysis and Review of Online Learning Studies. U.S. Department of Education. Retrieved November 15, 2018, from https://www2.ed.gov/rschstat/eval/tech/evidence-based-practices/finalreport.pdf
Meyer, L. M. ＆ Heather, A. M. (1997). Understanding Motivation and Schooling: Where We’ve Been, Where We Are, and Where We Need to Go. Educational Psychology Review, 12(11–12), 961–962.
Mochon, D., Norton, M. I., ＆ Ariely, D. (2012). Bolstering and restoring feelings of competence via the IKEA effect. International Journal of Research in Marketing, 29(4), 363–369.
Nicosia, F. M. (1968). Consumer Decision Processes: Marketing and Advertising Implication (pp. 29), New Jersey: Prentice-Hall Inc.
Northcutt, C. G., Ho, A. D., ＆ Chuang, I. L. (2016). Detecting and preventing “multiple-account cheating in massive open online courses. Computers ＆ Education, 100(6), 71–80.
Nunnally, J. C., ＆ Bernstein, I. H. (1994). Psychometric Theory (3rd ed.). New York: McGraw- Hill.
Oscar, L., Jorge, D., ＆ Antonio, B. (2018). A peer assessment method to provide feedback, consistent grading and reduce students' burden in massive teaching settings. Computers ＆ Education, 126(21), 283-295.
Pavlou, P, A. (2003). Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model. International Journal of Electronic Commerce, 7(3), 101-133.
Phan, T., Mcneil, S. G., ＆ Robin, B. R. (2016). Computers ＆ Education Students’ patterns of engagement and course performance in a Massive Open Online Course. Computers ＆ Education, 95(3), 36–44.
Piech, C., Huang, J., Chen, Z., Do, C., Ng, A., ＆ Koller, D. (2013) Tuned models of peer assessment in MOOCs. In Proceedings of The 6th International Conference on Educational Data Mining (EDM 2013) (pp. 153–160). International Educational Data Mining Society. Memphis, USA. July 6-9.
Pike, G. R., Smart, J. C., ＆ Ethington, C. A. (2012). The mediating effects of student engagement on the relationships between academic disciplines and learning outcomes: An extension of Holland’s theory. Research in Higher Education, 53(5), 550-575.
Pintrich, P. R., Smith, D. A. F., Garcia, T. ＆ Mckeachie, W. J. (1991). A Manual for the Use of the Motivated Strategies for Learning Questionnaire (MSLQ). MI: National Center for Research to Improve Postsecondary Teaching and Learning. (ERIC Document Reproduction Service No. ED 338122).
Pintrich, P. R., Smith, D. A., Garcia, T., ＆ McKeachie, W. J. (1993). Reliability and predictive validity of the Motivated Strategies for Learning Questionnaire (MSLQ). Educational and Psychological Measurement, 53(3), 801-813.
Pintrich, P. R. (2000). The role of goal orientation in self-regulated learning. In M. Boekaerts, P. R. Pintrich, ＆ M. Zeidner (Eds.), Handbook of self-regulation (pp. 451-502). San Diego: Academic Press.
Pintrich, P. R. (2004). A conceptual framework for assessing motivation and self-regulated learning in college students. Educational Psychology Review, 16(4), 387-388.
Porter, C. E., ＆ Donthu, N. (2008). Cultivating trust and harvesting value in virtual communities. Management Science, 54(1), 113-128.
Pressley, M., Borkowski, J. G., ＆ Schneider, W. (1990). Good information processing: What it is and how education can promote it. International Journal of Educational Research, 13(8), 857-867.
Richardson, M., Abraham, C., ＆ Bond, R. (2012). Psychological correlates of university students' academic performance: A systematic review and meta- analysis. Psychological Bulletin, 138(2), 353-387.
Rosipal, R., ＆ Kramer, N. (2006). Overview and recent advances in partial least squares. Lecture Notes in Computer Science, 3940, 34-51.
Ross, J., Sinclair, C., Knox, J., Bayne, S., ＆ Macleod, H. (2014). Teacher Experiences and Academic Identity: The Missing Components of MOOC Pedagogy. MERLOT Journal of Online Learning and Teaching, 10(1), 57–69.
Sandeen, C. (2013). Assessment’s place in the new MOOC world. Journal of Research and Practice in Assessment, 8(1), 5–12.
Schuemer, R. (1993). Some Psychological Aspects of Distance Education. Hagen, Germany: Institution for Research into Distance Education (ED 357 266).
Schunk, D. H. (1986). Verbalization and Children’s Learning. Contemporary Educational Psychology, 11(4), 347–369.
Schunk, D. H. (1989). Self-efficacy and achievement behaviors. Educational Psychology Review, 1(3), 173-208.
Schunk, D. H. (2005). Self-regulated learning: The educational legacy of Paul R. Pintrich. Educational Psychologist, 40(2), 85-94.
Schunk, D. H. (2007). Attributions as motivators of self-regulated learning. In D. H. Schunk ＆ B. J. Zimmerman (Eds.), Motivation and self-regulated learning: Theory, research, and applications (pp. 245–266). New York, NY: Lawrence Erlbaum Associates.
Strφmsφ, H. I., ＆ Braten, I. (2010). The role of personal epistemology in the self-regulation of internet-based learning. Mecoginition Learning, 5(1), 91-111.
Shea, P., ＆ Bidjerano, T. (2012). Learning presence as a moderator in the community of inquiry model. Computers and Education, 59(2), 316–326.
Stewart, B. (2013). Massiveness + Openness = new literacies of participation? Journal of Online Learning and Teaching, 9(2), 228-238.
Spyropoulou, N., Demopoulou, G., Pierrakeas, C., Koutsonikos, I., ＆ Kameas, A. (2015). Developing a Computer Programming MOOC. Procedia Computer Science, 65(21), 182–191.
Schaap A. (2018) E-Learning as Tool to Feed the World. In: Azeiteiro U., Leal Filho W., Aires L. (Eds.) Climate Literacy and Innovations in Climate Change Education. Climate Change Management (pp. 49-66). Heidelberg, Berlin: Springer, Cham.
Stipek, D., Feiler, R, Daniels, D, ＆ Milburn, S (1995). Effects of different instructional approaches on young children’s achievement and motivation. Child Developmet , 66(1), 209-223.
Tanaka, J. S. (1987). How big is big enough?: Sample size and goodness of fit in structural equation models with latent variables. Child Development, 58(1), 134-146.
Tayie, S. (2005). Research methods and writing research proposals. Quezon City, Philippines: Pathways to Higher Education.
Veletsianos, G., Collier, A., ＆ Schneider, E. (2015). Digging deeper into learners' experiences in MOOCs: Participation in social networks outside of MOOCs, notetaking and contexts surrounding content consumption. British Journal of Educational Technology, 46(3), 570–587.
Wang, Y., ＆ Baker, R. (2015). Content or platform: Why do students complete MOOCs? Journal of Online Learning and Teaching, 11(1), 17–30.
Warr, P., ＆ Downing, J. (2000). Learning strategies, learning anxiety and knowledge acquisition. British Journal of Psychology, 91(3), 331-333.
Weinstein, C.E., ＆ Mayer, R.E. (1986). The teaching of learning strategies. In M. Wittrock (Ed.), Handbook of research on teaching (pp. 315-327). New York, NY: Macmillan.
Winne, P. H., ＆ Hadwin, A. F. (1998). Studying as self-regulated learning. In D. J. Hacker ＆ J. Dunlosky (Eds.), Metacognition in educational theory and practice, The Educational Psychology Series. Mahwah, NJ: Erlbaum Associates.
Wolf, F., Curran, F., Pflaum, E., Ramic, H. (2018) Education for Sustainability: Integrating Climate Change and Energy into Lifelong Learning Initiatives for Small Island Developing States. In Azeiteiro U., Leal Filho W., Aires L. (Eds.) Climate Literacy and Innovations in Climate Change Education. Climate Change Management (pp. 1-18). Heidelberg, Berlin: Springer, Cham.
Yousef, A. M. F., Chatti, M. A., Schroeder, U., Wosnitza, M., Jakobs, H. (2014). MOOCs - A Review of the State-of-the-Art. In Proceedings of the CSEDU 2014 conference (pp. 9-20). Barcelona, Spain. April 1-3.
Zimmerman, B. J. (1986). Becoming a self-regulated learner: Which are the key subprocesses? Contemporary Educational Psychology, 11(4), 307-313.
Zimmerman, B. J. (1998). Academic studying and the development of personal skill: A self- regulatory perspective. Educational Psychologist, 33(2), 73-86.
Zimmerman, B. J. (2001). Theories of self-regulated learning and academic achievement: an overview and analysis. In D.H. Schunk ＆ B. J. Zimmerman (2nd eds.), Self-regulated learning and academic achievement theoretical perspectives (pp. 2-37). Mahwah, NJ: Lawrence Erlbaum Associates Publishers.
Zimmerman, B. J., Bandura, A., ＆ Martinez-Pons, M. (1992). Self-motivation for academic attainment: The role of self-efficacy beliefs and personal goal setting. American Educational Research Journal, 29(3), 663–676.
Zimmerman, B. J. ＆ Kitsantas, A. (1997). Developmental phases in self-regulation: Shifting from process goals to outcome goals. Journal of Educational Psychology, 89(1), 29–36.
Zimmerman, B. J., ＆ Moylan, A. R. (2009). Self-regulation: Where metacognition and motivation intersect. In D. J. Hacker, J. Dunlosky, ＆ A. C. Graesser (Eds.), Handbook of metacognition in education (pp. 299–315). New York, NY: Routledge.
Zimmerman, B. J., ＆ Pons, M. M. (1986). Development of a Structured Interview for Assessing Student Use of Self-Regulated Learning Strategies. American Educational Research Journal, 23(4), 614–628.
Zimmerman, B. J., ＆ Schunk, D. H. (1989). Self-regulated learning and academic achievement: Theory, research, and practice (pp. 83–110). New York: Springer-Verlag.