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نجاتی, رضا. (1402). خود تنظیمی و مشارکت چقدر نتایج یادگیری را پیش‌بینی می‌کنند؟ بررسی کلاس‌های آنلاین انگلیسی در یک دانشگاه ایرانی. فناوری آموزش, 18(1), 111-130. doi: 10.22061/tej.2023.10069.2936
رضا نجاتی. "خود تنظیمی و مشارکت چقدر نتایج یادگیری را پیش‌بینی می‌کنند؟ بررسی کلاس‌های آنلاین انگلیسی در یک دانشگاه ایرانی". فناوری آموزش, 18, 1, 1402, 111-130. doi: 10.22061/tej.2023.10069.2936
نجاتی, رضا. (1402). 'خود تنظیمی و مشارکت چقدر نتایج یادگیری را پیش‌بینی می‌کنند؟ بررسی کلاس‌های آنلاین انگلیسی در یک دانشگاه ایرانی', فناوری آموزش, 18(1), pp. 111-130. doi: 10.22061/tej.2023.10069.2936
نجاتی, رضا. خود تنظیمی و مشارکت چقدر نتایج یادگیری را پیش‌بینی می‌کنند؟ بررسی کلاس‌های آنلاین انگلیسی در یک دانشگاه ایرانی. فناوری آموزش, 1402; 18(1): 111-130. doi: 10.22061/tej.2023.10069.2936

خود تنظیمی و مشارکت چقدر نتایج یادگیری را پیش‌بینی می‌کنند؟ بررسی کلاس‌های آنلاین انگلیسی در یک دانشگاه ایرانی

فناوری آموزش
مقاله 7، دوره 18، شماره 1 - شماره پیاپی 69، دی 1402، صفحه 111-130    اصل مقاله (748.9 K)
نوع مقاله: مقاله پژوهشی-شماره انگلیسی
شناسه دیجیتال (DOI): 10.22061/tej.2023.10069.2936
نویسنده
رضا نجاتی*
خود تنظیمی و مشارکت چقدر نتایج یادگیری را پیش‌بینی می‌کنند؟ بررسی کلاس‌های آنلاین انگلیسی در یک دانشگاه ایرانی
تاریخ دریافت: 02 مرداد 1402،  تاریخ بازنگری: 05 مهر 1402،  تاریخ پذیرش: 19 مهر 1402 
چکیده
پیشینه و اهداف: شناخت الزامات منحصر به فرد آموزش برخط به دلیل گستردگی آن بسیار ضروری است. خودتنظیمی در یادگیری برای این رویکرد آموزشی ضروری است، زیرا دانش آموزان و معلمان از نظر فیزیکی از هم جدا هستند. افراد برای مدیریت موثر زمان خود، ایجاد اهداف و حفظ انگیزه، باید راهبردهای عملی اتخاذ کنند. مشارکت فعال در فرآیند یادگیری نیز مهم است و دانشجویان را ملزم به مشارکت فعال، مشارکت و تعامل با مربیان و همسالان می کند. ارزیابی خودتنظیمی و مشارکت دانشجویان می‌تواند به مدیران و استادان کمک کند تا بر روند آموزشی نظارت کنند و در مواقعی که مشارکت دانشجویان کم است، اقدامات لازم را انجام دهند. این مطالعه با هدف بررسی تأثیر مشارکت و خودتنظیمی یادگیری بر نتایج یادگیری درک مطلب دانشجویان ایرانی در کلاس‌های برخط انجام شده است.
روش‌ها‌: این پژوهش با استفاده از دو پرسشنامه و یک آزمون‌ انجام شد. از پرسشنامه خودتنظیمی یادگیری، مقیاس مشارکت دانشجویی برخط و بخش خواندن آزمون زبان انگلیسی به عنوان زبان خارجی استفاده شد. پرسشنامه خودتنظیمی دارای سه سازه با 30 گویه و پرسشنامه مشارکت چهار سازه با 19 گویه بود. این مقیاس ها به فارسی ترجمه و برای 345 دانشجو ارسال شد. از 287 پرسشنامه برگشتی، 21 پرسشنامه به دلیل بی دقتی پاسخ دهندگان حذف شدند. 266 پاسخ باقیمانده، همراه با نمره آزمون آزمون آنها، مورد تجزیه و تحلیل آماری قرار گرفت. آزمون درک مطلب و پرسشنامه ها از طریق سامانه آموزش مجازی دانشگاه در پاییز 1401 اجرا شد.
یافته‌ها: برای ارزیابی پایایی، ضرایب آلفای کرونباخ برای سه متغیر کلیدی مشارکت فعال، خودتنظیمی یادگیری و خواندن و درک مطلب محاسبه شد. ضرایب به دست آمده به ترتیب 89/0، 94/0 و 86/0 بود. این مقادیر نشان می‌دهد که ابزار اندازه‌گیری مورد استفاده برای ارزیابی این سازه‌ها قابل اعتماد هستند. روایی سازه نیز از طریق مقادیر ریشه میانگین مربعات خطای تقریب (RMSEA) برای متغیرها بررسی شد. مقادیر RMSEA گزارش شده به ترتیب 0.08، 0.07 و 0.01 بود. این مقادیر در محدوده قابل قبولی قرار می‌گیرند که نشان می‌دهد مدل‌های اندازه‌گیری به اندازه کافی با داده‌های مشاهده‌شده تناسب دارند . هر سه متغیر (مشارکت فعال، خودتنظیمی و خواندن) مقادیر t آماری معنی‌داری را نشان دادند که بر توانی های فراگیران دلالت می کند. رابطه مثبت معناداری بین مشارکت نظارتی و درک مطلب مشاهده شد. این یافته نشان می‌دهد که سطوح بالاتر مشارکت نظارتی با مهارت‌های درک مطلب بهتر در بین دانش‌آموزان مرتبط است. علاوه بر این، تحلیل رگرسیون نشان داد که سازه های «عملکرد» و «تعامل دانشجو-دانشجو» با درک مطلب ارتباط قوی و مثبتی دارند. ضرایب بتا برای این متغیرها به ترتیب 0.25 و 0.21 بود. این نشان می‌دهد که بهبود عملکرد و افزایش تعاملات دانشجویان با افزایش توانایی‌های درک مطلب مرتبط است.
نتیجه‌گیری: رابطه بین مشارکت نظارتی و درک مطلب، پیام مهمی برای استادان و مدیران دارد. درک این ارتباط به منظور طراحی برنامه های مؤثر و رویکردهای آموزشی برای افزایش توانایی‌های مشارکت نظارتی دانشجویان ضروری است. با این حال، باید اذعان کنیم که مطالعه انجام شده دارای محدودیت‌های خاصی بود که دامنه آن را محدود می‌کرد و از بررسی کامل همه عوامل مؤثر بر مهارت‌های درک مطلب جلوگیری می‌کرد. برای به دست آوردن درک جامع تر از موضوع، تحقیقات آینده باید متغیرهای اضافی فراتر از مشارکت نظارتی را بررسی کند. برای مثال، در نظر گرفتن تأثیر پیشینه فرهنگی بر درک مطلب می‌تواند بینش‌های ارزشمندی در مورد توانایی خواندن زبان‌آموزان ارائه دهد. به همین ترتیب، بررسی روش‌های تدریس مختلف می‌تواند اثربخشی رویکردهای آموزشی خاص در تقویت مهارت درک مطلب را روشن کند. علاوه بر این، عوامل شناختی فردی مانند حافظه فعال و کنترل توجه نقش مهمی در درک مطلب دارند و بررسی آنها می‌تواند به شناسایی راهبردهایی برای حمایت از دانشجویان کمک کند.
کلیدواژه‌ها
خود تنظیمی یادگیری؛ مشارکت فعال؛ مشارکت نظارتی؛ پیشرفت تحصیلی؛ خواندن و درک مطلب
موضوعات
آموزش الکترونیکی
عنوان مقاله [English]
How Well do Self-Regulation and Engagement Predict Learning outcomes? Exploring Online English Classes in an Iranian University
نویسندگان [English]
R. Nejati
English Department, Faculty of Humanities, Shahid Rajaee Teacher Training University, Tehran, Iran
چکیده [English]
Background and Objectives: Recognizing the unique requirements of online education is crucial due to its wide spread use. Self-regulation in learning seems essential for this instructional approach, as students and instructors are physically separated. To effectively manage their time, establish goals, and sustain motivation, individuals must adopt practical strategies. Active engagement in the learning process is also vital, requiring students to actively participate, contribute, and engage with instructors and peers. Assessing students' self-regulation and engagement can help educational managers and professors supervise the educational process and implement necessary measures when student participation is lacking. The objective of this study was to investigate how self-regulated learning and engagement contribute to outcomes of leaning as measured in terms of reading comprehension skills of Iranian students in online classrooms.
Materials and Methods: The study investigated research questions using two questionnaires and a test, namely, the Online self-regulation questionnaire (OSQ), the Online Student Engagement Scale (OSE), and the reading part of the Test of English as a Foreign Language. The self-regulation questionnaire had three constructs with 10 items each, while the engagement questionnaire had four constructs with 19 items. These scales were translated into Persian and sent to 345 students. Out of the 287 returned questionnaires, 21 were excluded due to inattention. The remaining 266 responses, along with their test scores, were analyzed statistically. Both the questionnaires and the language test were administered via the LMS in 2022.
Findings: The data underwent a rigorous process of statistical analyses to evaluate reliability, construct validity, and the relationships between variables. These analyses aimed to ensure the accuracy and robustness of the findings. To assess reliability, Cronbach's Alpha coefficients were calculated for three key variables: Engagement, Self-regulation, and Reading. The obtained coefficients were .89, .94, and .86, respectively. These values indicate high levels of internal consistency within each variable, suggesting that the measurement instruments used to assess these constructs were reliable. Construct validity was also examined through Root Mean Square Error of Approximation (RMSEA) values for Engagement, Self-regulation, and Reading. The reported RMSEA values were .08, .07, and .01, respectively. These values fall within an acceptable range, indicating that the measurement models adequately fit the observed data and supported the construct validity of the variables. All three variables (Engagement, Self-regulation, and Reading) exhibited statistically significant t-values, providing strong evidence that students' engagement, self-regulation, and reading ability were deemed satisfactory based on the collected data. The analysis revealed a significant positive correlation between regulatory engagement and reading comprehension. This finding suggests that higher levels of regulatory engagement are associated with better reading comprehension skills among students. Additionally, a regression analysis was conducted to explore the associations between specific factors and reading comprehension. The results indicated that both 'performance' and 'student-student interactions' had strong and positive associations with reading comprehension. The beta coefficients for these variables were 0.25 and 0.21, respectively. This implies that improvements in performance and increased student-student interactions are related to enhanced reading comprehension abilities.
Conclusions: The relationship between regulatory engagement and reading comprehension holds significant implications for educators and policymakers. Understanding this connection is essential to develop effective interventions and instructional approaches aimed at enhancing students' regulatory engagement abilities, ultimately leading to improved reading comprehension outcomes. However, it is important to acknowledge that the study conducted had certain limitations that restricted its scope and prevented a thorough examination of all potential factors influencing reading comprehension skills. To gain a more comprehensive understanding of the topic, future research should explore additional variables beyond regulatory engagement. For instance, considering the influence of cultural background on reading comprehension can provide valuable insights into how diverse learners may approach and interpret texts differently. Similarly, investigating various teaching methods employed in different educational settings can shed light on the effectiveness of specific instructional approaches in promoting reading comprehension. Furthermore, individual cognitive factors such as working memory and attentional control warrant attention in future studies. These cognitive processes play integral roles in reading comprehension, and exploring their impact can help identify strategies to support students with specific cognitive profiles or challenges.
کلیدواژه‌ها [English]
Self-Regulatory Learning, Engagement, Online Education, Achievement, Regulatory Engagement
مراجع
[1] Cho MH, Cho Y. Self-regulation in three types of online interaction: a scale development. Distance Education. 2017; 38(1):70–83. https://doi.org/10.1080/01587919.2017.1299563

[2] King RB. Sense of relatedness boosts engagement, achievement, and well-being: A latent growth model study. Contemporary Educational Psychology. 2015; 42:26–38. https://doi.org/10.1016/j.cedpsych.2015.04.002

[3] Azevedo R, Moos DC, Greene JA, Winters FI, Cromley JG. Why is externally-facilitated regulated learning more effective than self-regulated learning with hypermedia? Educational Technology Research and Development. 2007;56(1):45–72. https://doi.org/10.1007/s11423-007-9067-0

[4] Kehrwald B. Understanding social presence in text‐based online learning environments. Distance Education. 2008;29(1):89-106. https://doi.org/10.1080/01587910802004860

[5] Robinson CC, Hullinger H. New benchmarks in higher education: Student engagement in online learning. Journal of Education for Business. 2008;84(2):101-9.

[6] Schunk, Dale H., and Ellen L. Usher, ' Social Cognitive Theory and Motivation', in Richard M. Ryan (ed.), The Oxford Handbook of Human Motivation, Oxford Library of Psychology 2012; [Available Online]. 2012),

https://doi.org/10.1093/oxfordhb/9780195399820.013.0002, accessed 21 July 2023.

[7] Usher EL, Schunk DH. Social cognitive theoretical perspective of self-regulation. In: Schunk DH. and Greene JA. (eds.) Handbook of self-regulation of learning and performance. Routledge; 2017. Pp. 19-35. https://doi.org/10.4324/9781315697048-2

[8] Winne PH. Cognition and metacognition within self-regulated learning. In: Schunk DH and. Greene JA. (eds.)  Handbook of self-regulation of learning and performance. Routledge; 2017. Pp. 36-48.

https://doi.org/1010.4324/9781315697048.ch3

[9] Azevedo R, Johnson A, Chauncey A, Burkett C. Self-regulated learning with MetaTutor: Advancing the science of learning with metacognitive tools. In New Science of Learning: Cognition, Computers and Collaboration in Education. Springer New York; 2010. Pp. 225-47.

https://doi.org/10.1007/978-1-4419-5716-0_11

[10] Azevedo R, Aleven V, Editors. International Handbook of Metacognition and Learning Technologies. Springer International Handbooks of Education. New York, NY: Springer New York; 2013.

https://doi.org/10.1007/978-1-4419-5546-3_1

[11] Hadwin A, Järvelä S, Miller M. Self-regulation, co-regulation, and shared regulation in collaborative learning environments. In: Schunk DH and Greene JA. (eds.)  Handbook of self-regulation of learning and performance. Routledge; 2017. Pp. 83-106).

[12] Reimann P, Bannert M. Self-Regulation of Learning and Performance in Computer-Supported Collaborative Learning Environments. In: Schunk DH and Greene JA (eds.)  Handbook of self-regulation of learning and performance. Routledge; 2017. Pp. 285–303.‌

https://doi.org/10.4324/9781315697048-19

[13] Tang M, Neber H. Motivation and self‐regulated science learning in high‐achieving students: differences related to nation, gender, and grade‐level. High Ability Studies. 2008;19(2):103–16. https://doi.org/10.1080/13598130802503959

[14] Zhu C, Valcke M, Schellens T. A cross-cultural study of Chinese and Flemish university students: Do they differ in learning conceptions and approaches to learning? Learning and Individual Differences. 2008;18(1):120–7.

https://doi.org/10.1016/j.lindif.2007.07.004

[15] Ommundsen Y, Haugen R, Lund T. Academic self‐concept, implicit theories of ability, and self‐regulation strategies. Scandinavian Journal of Educational Research. 2005;49(5):461-74. https://doi.org/10.1080/0031383057838.

[16] Huang J, Prochner L. Chinese Parenting Styles and Children’s Self-Regulated Learning. Journal of Research in Childhood Education. 2003;18(3):227–38. https://doi.org/10.1080/02568540409595037

[17] King RB, Ganotice FA. Does family obligation matter for students’ motivation, engagement, and well-being? It depends on your self-construal. Personality and Individual Differences. 2015;86: 243–8. https://doi.org/10.1016/j.paid.2015.06.027

[18] Cengiz-Istanbullu, B. and Sakiz, G., 2022. Self-Regulated Learning Strategies Impact Fourth-Grade Students' Positive Outcomes in Science Class. Journal of Baltic Science Education; 21(2): 192-206. Doi:10.33225/jbse/22.21.192

[19] Davis SK, Hadwin AF. Exploring differences in psychological well-being and self-regulated learning in university student success. Frontline Learning Research. 2021;9(1):30–43.  https://doi.org/10.14786/flr. v9i1.581

[20] Boekaerts M, Pintrich P, Zeidner M. Self-Regulation: An Introductory Review. In: Boekaerts M, Pintrich P, Zeidner M, editors. Handbook of Self-Regulation. San Diego, CA: Academic Press.; 2000. p. 1–9.

http://dx.doi.org/10.1016/B978-012109890-2/50030-5

[21] Wandler J, Imbriale WJ. Promoting College Student Self-Regulation in Online Learning Environments. Online Learning. 2017;21(2). https://doi.org/10.24059/olj.v21i2.881

[22] Chiu YL, Liang JC, Tsai CC. Internet-specific epistemic beliefs and self-regulated learning in online academic information searching. Metacognition and Learning. 2013;8(3):235–60. https://doi.org/10.1007/s11409-013-9103-x

[23] Chen CM, Huang SH. Web-based reading annotation system with an attention-based self-regulated learning mechanism for promoting reading performance. British Journal of Educational Technology. 2013;45(5):959–80. https://doi.org/10.1111/bjet.12119

[24] Dunn KE, Rakes GC, Rakes TA. Influence of academic self-regulation, critical thinking, and age on online graduate students’ academic help-seeking. Distance Education. 2014;35(1):75–89. https://doi.org/10.1080/01587919.2014.891426

[25] Cleary TJ. Emergence of Self-Regulated Learning Microanalysis. Handbook of Self-Regulation of Learning and Performance [Available Online].

http://dx.doi.org/10.4324/9780203839010.ch21

[26] Cleary TJ, Zimmerman BJ, Keating T. Training Physical Education Students to Self-Regulate During Basketball Free Throw Practice. Research Quarterly for Exercise and Sport. 2006;77(2):251–62. http://dx.doi.org/10.1080/02701367.2006.10599358

[27] M K DiBenedetto and Zimmerman, BJ. Differences in self-regulatory processes among students studying science: a microanalytic investigation. International Journal of Educational & Psychological Assessment. 2010; 5(1): 2–24

[28] Zhang, Shilei, Rui Shi, Liping Yun, Xuefei Li, Yun Wang, Hongbin He, and Danmin Miao. Self-regulation and study-related health outcomes: A structural equation model of regulatory mode orientations, academic burnout and engagement among university students. Social Indicators Research. 2015; 123: 585-599. https://doi.org/10.1007/s11205-014-0742-3 

[29] Bagozzi RP. The self-regulation of attitudes, intentions, and behavior. Social psychology quarterly. 1992; 1:178-204. https://doi.org/10.2307/2786945 

[30] Cho MH, Shen D. Self-regulation in online learning. Distance education. 2013;34(3):290-301. https://doi.org/10.1080/01587919.2013.835770

[31] Li S, Chen G, Xing W, Zheng J, Xie C. Longitudinal clustering of students’ self-regulated learning behaviors in engineering design. Computers & Education. 2020; 153: 103899. https://doi.org/10.1016/j.compedu.2020.103899 .

[32] Viberg O, Khalil M, Baars M. Self-regulated learning and learning analytics in online learning environments. Proceedings of the Tenth International Conference on Learning Analytics & Knowledge. 202; 13.

https://doi.org/ 10.1145/3375462.3375483 .

[33] Reddy LA, Cleary TJ, Alperin A, Verdesco A. A critical review of self-regulated learning interventions for children with attention-deficit hyperactivity disorder. Psychology in the Schools. 2018; 55(6):609–28.

https://doi.org/10.1002/pits.22142

[34] Cleary TJ, Kitsantas A, Pape SL, Slemp J. Integration of socialization influences and the development of self-regulated learning (SRL) skills: A social-cognitive perspective. In: Alief GAD, McInerney D (ed.). Big theories revisited (2nd ed). Information Age Publishing; 2018. Pp. 269–94.

[35] Thomas, N, Rose, H. Do Language Learning Strategies Need to Be Self‐Directed? Disentangling Strategies from Self‐Regulated Learning. TESOL Quarterly. 2018;53(1):248–57. https://doi.org/10.1002/tesq.473

[36] Dornyei Z. The psychology of the language learner: Individual differences in second language acquisition. New Jersey: Mahwah; 2005.

[37] Tseng WT, Dörnyei Z, Schmitt N. A new approach to assessing strategic learning: The case of self-regulation in vocabulary acquisition. Applied linguistics. 2006;27(1):78-102.

https://doi.org/10.1093/applin/ami046

[38] Dent AL, Koenka AC. The Relation Between Self-Regulated Learning and Academic Achievement Across Childhood and Adolescence: A Meta-Analysis. Educational Psychology Review. 2015;28(3):425–74. 

https://doi.org/10.1007/s10648-015-9320-8

[39] Weinstein CE, Acee TW, Jung J. Self-regulation and learning strategies. New Directions for Teaching and Learning. 2011; 126:45–53. https://doi.org/10.1002/tl.443 .

[40] Cleary TJ, Slemp J, Reddy LA, Alperin A, Lui A, Austin A, Cedar T. Characteristics and uses of SRL microanalysis across diverse contexts, tasks, and populations: A systematic review. School Psychology Review. 2023;52(2):159-79. https://doi.org/10.180/2372966X.2020.1862627 

[41] Cleary TJ, Zimmerman BJ. A cyclical self-regulatory account of student engagement: Theoretical foundations and applications. In: Timothy J,.Cleary B, and Zimmerman J. (eds.) Handbook of research on student engagement. Boston, MA: Springer US; 2012. Pp. 237-257.

https://doi.org/10.1007/978-1-4614-2018-7_11

[42] Pohl AJ. Strategies and Interventions for Promoting Cognitive Engagement. In: Reschly AL, Pohl AJ, Christenson SL, editors. Student Engagement. Cham.: Springer; 2020. p. 253–80. https://doi.org/10.1007/978-3-030-37285-9_14

[43] Lewis AD, Huebner ES, Malone PS, Valois RF. Life satisfaction and student engagement in adolescents. J. Youth. Adolesc. 2011; 4: 249–262.

https://doi.org/10.1007/s10964-010-9517-6 .

[44] Connell JP, Halpem-Felsher BL, Clifford E, Crichlow W, Usinger P. Hanging in there: Behavioral, psychological, and contextual factors affecting whether African American adolescents stay in high school. Journal of Adolescent Research. 1995; 10: 41– 63.

https://doi.org/10.1177/0743554895101004

[45] Reschly AL, Pohl A, Christenson SL, Appleton J J. Engaging adolescents in secondary schools. In B. Schultz, J. Harrison, & S. Evans (Eds.), School mental health services for adolescents. New York: Oxford University Press; 2017.  Pp. 45–77 https://doi.org/10.1093/med- sych/9780199352517.003.0003

[46] Khan A, Egbue, O, Palkie, B, Madden J. Active learning: Engaging students to maximize learning in an online course. Electronic Journal of E-Learning. 2017; 15(2): 107–115.

[47] Sheridan K, Kelly MA. The indicators of instructor presence that are important to students in online courses. MERLOT Journal of Online Learning and Teaching. 2010; 6(4): 767–779.

[48] Umbach P D, Wawrzynski M R. Faculty do matter: The role of college faculty in student learning and engagement. Research in Higher Education. 2005; 46(2): 153–184 https://doi.org/10.1007/s11162-004-1598-1

[49] Fisher K. Online student engagement: CCSSE finds enrollment status and online experience are key. Community College Week. 2010; 22(20): 7-9.

[50] Taplin M. Problem-based learning in distance education: Practitioners’ beliefs about an action learning project. Distance Education. 2000; 21(2): 284–307.

https://doi.org/10.1080/0158791000210206

[51] Hoffman B, Ritchie D. Using multimedia to overcome the problems with problem-based learning. Instructional Science. 1997; 25: 97–115. https://doi.org/10.1023/A:1002967414942

[52] Layne M, Boston W E, Ice P. A longitudinal study of online learners: Shoppers, swirlers, stoppers, and succeeders as a function of demographic characteristics. Online Journal of Distance Learning Administration. 2013; 16(2).

[53] Allen TO, Zhang Y. Dedicated to their degrees. Community College Review. 2016; 44(1): 70–86.

https://doi.org/10.1177/0091552115617018

[54] Phillips N. Forced learning theory. Training. 2005; 42(6): 46.

[55] Pintrich PR, Smith DA, Garcia T, McKeachie WJ. Reliability and predictive validity of the Motivated Strategies for Learning Questionnaire (MSLQ). Educational and psychological measurement. 1993; 53(3):801-13.

https://doi.org/10.1177/0013164493053003024

[56] Hodges CB, Kim C. Email, self-regulation, self-efficacy, and achievement in a college online mathematics course. Journal of Educational Computing Research. 2010;43(2):207-23. https://doi.org/10.2190/ec.43.2.d

[57] Klingsieck KB, Fries S, Horz C, Hofer M. Procrastination in a distance university setting. Distance Education. 2012;33(3):295-310. https://doi.org/10.1080/01587919.2012.723165

[58] Dixson MD. Measuring student engagement in the online course: The online student engagement scale (OSE). Online Learning. 2015; 19(4): 143–157.  

https://doi.org/10.24059/olj.v19i4.561

[59] Yuan J, Kim C. Guidelines for facilitating the development of learning communities in online courses. Journal of Computer Assisted Learning. 2014; 30: 220– 232. https://doi.org/10.1111/jcal.12042

[60] Browne MW, Cudeck R. Alternative ways of assessing model fit. In: Bollen KA, Long JS, editors. Testing structural equation models. Newbury Park, CA: Sage; 1993. Pp. 136–62.‌

[61] Pallant JF. SPSS Survival Manual: A step by step guide to data analysis using the SPSS program. Crows Nest, Nsw: Allen & Unwin; 2011.

[62] Cleary TJ, Lui AM. Using Self-Regulated Learning (SRL) Self-regulated learning (SRL) Assessment Data to Promote Regulatory Engagement in Learning Engagement in learning and Performance Performances Contexts. In: Cleary B and Lui AM (eds.) Handbook of Research on Student Engagement. 2022 Oct 20. Cham: Springer International Publishing. Pp. 171-193. https://doi.org/10.1007/978-3-031-07853-8_9

[63] Tabachnick BG, Fidell LS. Using multivariate statistics. 7th ed. Harlow: Pearson Education Limited; 2019.

[64] Cohen J. Statistical power analysis for the behavioral sciences. 2nd ed. Hillsdale, N.J: L. Erlbaum Associates; 1988.

[65] Kreijns K, Kirschner PA, Vermeulen M. Social Aspects of CSCL Environments: A Research Framework. Educational Psychologist. 2013; 48(4):229–42.

https://doi.org/10.1080/00461520.2012.750225  .

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