Document Type : Original Article

Authors

1 Assistant Professor, Department of elementary Education, Farhangian University, Tehran, Iran.

2 Assistant Professor, Institute for research and planning in higher education, Tehran, Iran

Abstract

The COVID-19 pandemic has necessitated a rapid shift to online learning, making the community of inquiry (COI) framework increasingly relevant for creating meaningful and effective online learning experiences. However, the impact of COI presences (i.e., teaching, social, and cognitive presence) on students' learning outcomes has been inconsistent in the literature, and a recent meta-analysis has identified a publication bias in this relationship suggesting the need for further investigation. This study aimed to enhance our understanding of how the COI presence influences college students' learning outcomes and whether it has a mediating role in the effect of self-efficacy and motivation on e-learner’s academic achievement. In this cross-sectional study, using a correlational research design, among all graduate students studying in online courses, a total of 269 graduate students were selected from online programs in seven public universities in Iran between April 2022 and June 2023, to be the sample of the study. The data were obtained from the answers to the community of inquiry (COI) scale, self- efficacy scale, academic motivation scale and students’ last semester grade point average. To examine the questions of the study, a path analysis was applied whose results showed that motivation and self-efficacy affected the community of inquiry positively (p<0.000). Also, the community of inquiry affected learning performance positively (p<0.000). The outcomes can provide significant theoretical and practical contributions to the key stakeholders to design a satisfying and successful online curriculum for the post-COVID-19 era and offer valuable insights into the design of productive online learning communities.

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Main Subjects

Akcaoglu, M., & Akcaoglu, M. O. (2022). Understanding the relationship among self-efficacy, utility value, and the community of inquiry framework in preservice teacher education. International Review of Research in Open and Distributed Learning, 23(2), 86-106.
Akyol, Z., & Garrison, D. R. (2011). Assessing metacognition in an online community of inquiry. The Internet and Higher Education, 14(3), 183–190. https://doi.org/10.1016/j.iheduc.2011.01.005
Alabbasi, D. (2017). Exploring graduate students’ perspectives towards using gamification techniques in online learning. Turkish Online Journal of Distance Education, 18(3), 180–196.
Arbaugh, J. B., Cleveland-Innes, M., Diaz, S. R., Garrison, D. R., Ice, P., Richardson, J. C., & Swan, K. P. (2008). Developing a community of inquiry instrument: Testing a measure of the community of inquiry framework using a multi-institutional sample. The Internet and Higher Education, 11(3–4), 133–136. https://doi.org/10.1016/j.iheduc.2008.06.003
Arbaugh, J. B. (2008). Does the community of inquiry framework predict outcomes in online MBA courses? The International Review of Research in Open and Distance Learning, 9(2), 1–21. Retrieved from http://www.irrodl.org/index.php/irrodl/article/view/490/1045  
Arbaugh, J.B. (2007). An empirical verification of the community of inquiry framework. Journal of Asynchronous Learning Networks, 11(1), 73–85.
Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Prentice-Hall. https://psycnet.apa.org/record/1985-98423-000
Bandura, A. (1997). Self-efficacy: The exercise of control. W. H. Freeman. https://psycnet.apa.org/record/1997-08589-000
Bangert, A. (2008). The influence of social presence and teaching presence on the quality of online critical inquiry. Journal of Computing in Higher Education, 20(1), 34–61.
Bates, A. W. (2005). Technology, e-learning and distance education (2nd ed.). Routledge.
Bozkurt, A., Akgun-Ozbek, E., Yilmazel, S., Erdogdu, E., Ucar, H., Guler, E., Sezgin, S., Karadeniz, A., Sen- Ersoy, N., Goksel-Canbek, N., Dincer, G. D., Ari, S., & Aydin, C. H. (2015). Trends in distance education research: A content analysis of journals 2009–2013. The International Review of Research in Open and Distributed Learning, 16(1), 330–363. https://doi.org/10.19173/irrodl.v16i1.1953
Breivik, J. (2016). Critical thinking in online educational discussions measured as progress through inquiry phases: A discussion of the cognitive presence construct in the community of inquiry framework. International Journal of E-Learning & Distance Education, 31(1). Retrieved from http://www.ijede.ca/index.php/jde/article/view/970/1618
Brown, T. A. (2006). Confirmatory factor analysis for applied research. Guilford Press.
Burgess, M. L., Slate, J. R., Rojas-LeBouef, A., & LaPrairie, K. (2010). Teaching and learning in Second Life: Using the community of inquiry (COI) model to support online instruction with graduate students in instructional technology. The Internet and Higher Education, 13(1–2), 84–88. https://doi.org/10.1016/j.iheduc.2009.12.003
Chang, C. S., Liu, E. Z. F., Sung, H. Y., Lin, C. H., Chen, N. S., & Cheng, S. S. (2014). Effects of online college student’s Internet self-efficacy on learning motivation and performance. Innovations in Education and Teaching International, 51(4), 366-377. ‏
Chang, Y. C., & Tsai, Y. T. (2022). The effect of university students’ emotional intelligence, learning motivation and self-efficacy on their academic achievement—Online English courses. Frontiers in Psychology, 13, 818929.‏
Cho, M. H., & Jonassen, D. (2009). Development of the human interaction dimension of the Self‐Regulated Learning Questionnaire in asynchronous online learning environments. Educational Psychology, 29(1), 117-138.
Cho, M. H., Demei, S., & Laffey, J. (2010). Relationships between self-regulation and social experiences in asynchronous online learning environments. Journal of Interactive Learning Research, 21(3), 297-316. ‏
Dabbagh, N., & Kitsantas, A. (2004). Supporting self-regulation in student-centered Web-based learning environments. International Journal on E-Learning, 3(1), 40–47.
Enightoola, K., Fraser, S., & Brunton, T. (2014). Exploring the community of inquiry model: Students’ attitudes towards e-learning. The Caribbean Teaching Scholar, 4(2), 81–98. Retrieved from http://libraries.sta.uwi.edu/journals/ojs/index.php/cts/article/view/501
Feiz, P., & Hooman, H. A. (2013). Assessing the Motivated Strategies for Learning Questionnaire (MSLQ) in Iranian students: Construct validity and reliability. Procedia-Social and Behavioral Sciences, 84, 1820-1825. ‏
Ferede, T., Melese, E., Tefera, E., & Mossie, A. (2016). Students’ academic self-efficacy viz-a-viz their academic achievement: Jimma and Hawasa University students in focus. Ethiopian Journal of Education and Sciences, 11(2), 1–16. https://www.ajol.info/index.php/ejesc/article/view/153661
Garrison, D. R. (2009). Communities of inquiry in online learning. In Encyclopedia of distance learning (Second edition) (pp. 352-355). IGI Global. ‏
Garrison, D. R. (2011). E-learning in the 21st century: A community of inquiry framework for research and practice. Taylor & Francis. ‏
Garrison, D. R., & Arbaugh, J. B. (2007). Researching the community of inquiry framework: Review, issues, and future directions. The Internet and Higher Education, 10(3), 157–172. https://doi.org/10.1016/j.iheduc.2007.04.001
Garrison, D. R., Anderson, T., & Archer, W. (2001). Critical thinking, cognitive presence, and computer conferencing in distance education. American Journal of Distance Education, 15(1), 7–23. https://doi.org/10.1080/08923640109527071
Garrison, D. R., Cleveland-Innes, M., & Fung, T. S. (2010). Exploring causal relationships among teaching, cognitive and social presence: Student perceptions of the community of inquiry framework. The Internet and Higher Education, 13(1–2), 31–36.  https://doi.org/10.1016/j.iheduc.2009.10.002
Garrison, D.R. (2013). Theoretical foundations and epistemological insights of the community of inquiry. In Z. Akyol & D.R. Garrison (Eds.), Educational communities of inquiry: Theoretical framework, research, and practice (pp. 1–11). IGI Global.
Green, J. A., & Azevedo, R. (2007). A theoretical review of Winne and Hadwin's model of self-regulated learning: New perspectives and directions. Review of Educational Research, 77, 334–372.
Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (2006). Multivariate data analysis with reading (6th ed.). Pearson Education Inc.
Hara, N., & Kling, R. (2003). Students’ distress with a web-based distance education course: An ethnographic study of participants’ experiences. Turkish Online Journal of Distance Education, 4(2). http://tojde.anadolu.edu.tr/tojde10/articles/hara.htm.
Hodges, C. B. (2008). Selfefficacy in the context of online learning environments: A review of the literature and directions for research. Performance Improvement Quarterly, 20(3–4), 7–25. https://doi.org/10.1002/piq.20001
Hooper, D., Coughlan, J., & Mullen, M. R. (2008). Structural equation modelling: Guidelines for determining model fit. The Electronic Journal of Business Research Methods, 6(1), 53–60.
Huang, R.H., Liu, D.J., Tlili, A., Yang, J.F., & Wang, H.H. (2020). Handbook on facilitating flexible learning during educational disruption: The Chinese experience in maintaining undisrupted learning in COVID-19 outbreak. Smart Learning Institute of Beijing Normal University.
Joo, Y. J., Lim, K. Y., & Kim, E. K. (2011). Online university students’ satisfaction and persistence: Examining perceived level of presence, usefulness and ease of use as predictors in a structural model. Computers & Education, 57(2), 1654–1664. http://dx.doi.org/10.1016/j.compedu.2011.02.008
Kanuka, H., & Garrison, D.R. (2004). Cognitive presence in online learning. Journal of Computing in Higher Education, 15(2), 30–49.
Karaoglan Yilmaz, F. G. (2017). Predictors of community of inquiry in a flipped classroom model. Journal of Educational Technology Systems, 46(1), 87-102. ‏
Kazanidis, I., Pellas, N., Fotaris, P., & Tsinakos, A. (2018). Facebook and Moodle integration into instructional media design courses: A comparative analysis of students’ learning experiences using the community of inquiry (COI) model. International Journal of Human–Computer Interaction, 34(10), 932–942. https://doi.org/10.1080/10447318.2018.1471574
Keller, J. M. (2008). First principles of motivation to learn and e3-learning. Distance Education, 29(2), 175–185. DOI: 10.1080/01587910802154970.
Keller, J., & Suzuki, K. (2004). Learner motivation and e-learning design: A multinationally validated process. Journal of educational Media, 29(3), 229-239. ‏
Kilis, S., & Yıldırım, Z. (2018). Investigation of community of inquiry framework in regard to self-regulation, metacognition and motivation. Computers & Education, 126, 53-64. ‏
Kim, W. (2015). Learning flow, motivation, and community of inquiry in an online graduate degree program [Unpublished doctoral dissertation]. The Graduate School of Purdue University, USA.
Kline, R. B. (2011). Principles and practice of structural equation modeling (3rd ed.). Guilford Press.
Knowles, E., & Kerkman, D. (2007). An investigation of student’s attitude and motivation toward online learning. Insight: A Collection of Faculty Scholarship, 2, 70-80. ‏
Kozan, K., & Caskurlu, S. (2018). On the Nth presence for the Community of Inquiry framework. Computers & Education, 122, 104-118.
Law, K. M., Geng, S., & Li, T. (2019). Student enrollment, motivation and learning performance in a blended learning environment: The mediating effects of social, teaching, and cognitive presence. Computers & Education, 136, 1-12.‏
Lee, R., & Faulkner, M. (2011). The roles of extrinsic factors in a community of inquiry model of e-learning. E-learning and Digital Media, 8(1), 58–67.
Lee, Y., & Choi, J. (2011). A review of online course dropout research: Implications for practice and future research. Educational Technology Research and Development, 59, 593-618.‏
Lopez, D. R. S., Ayuela, M. A. D., Gonzalez-Burgos, E., Serrano-Gil, A., & Lalatsa, K. (2019). Technology enhanced learning in Higher Education: how to enhance student engagement through blended learning. European Journal of Education, 00, 1-14. DOI: 10.1111/ejed.12330
Ma, J., Han, X., Yang, J., & Cheng, J. (2015). Examining the necessary condition for engagement in an online learning environment based on learning analytics approach: The role of the instructor. The Internet and Higher Education, 24, 26–34.
Marsh, H. W., Balla, J. R., & McDonald, R. P. (1988). Goodness-of-fit indexes in confirmatory factor analysis: The effect of sample size. Psychological Bulletin, 103(3), 391–410.
Mohammadali, S., Manavipor, D., & Sedaghatifard, M. (2020). Psychometric properties of the student version of the academic motivation scale. Quarterly of Applied Psychology, 14 (4), 415-434. ‏
Nakayama, M., Mutsuura, K., & Yamamoto, H. (2021). Impact of learner’s characteristics and learning behaviour on learning performance during a fully online course. Note Taking Activities in E Learning Environments, 15-36. ‏
Paulus, T., & Scherff, L. (2008). “Can anyone offer any words of encouragement?” Online dialogue as a support mechanism for preservice teachers. Journal of Technology and Teacher Education, 16(1), 113–136.
Pintrich, P. R., Smith, D. A. F., Garcia, T., & McKeachie, W. J. (1991). A Manual for the use of the motivated strategies for learning. University of Michigan. (ERIC Document Reproduction Service No. ED338122).
Ponton, M., Derrick, G., Hall, J. M., Rhea, N., & Carr, P. (2005). The relationship between self-efficacy and autonomous learning: The development of new instrumentation. International Journal of Self-Directed Learning, 2(1), 50–61.
Powell, A., Roberts, V., & Patrick, S. (2015). Using online learning for credit recovery: Getting back on track to graduation. International Association for K-12 Online Learning. https://aurora- institute.org/resource/using-online-learning-for-credit-recovery-getting-back-on-track-to- graduation/
Putarek, V., & Pavlin-Bernardić, N. (2020). The role of self-efficacy for self-regulated learning, achievement goals, and engagement in academic cheating. European Journal of Psychology of Education, 35(3), 647–671. https://doi.org/10.1007/s10212-019-00443-7 Retrieved from http://linkresearchlab.org/PreparingDigitalUniversity.pdf
Rubin, B., Fernandes, R., & Avgerinou, M. D. (2013). The effects of technology on the community of inquiry and satisfaction with online courses. The Internet and Higher Education, 17, 48–57.  https://doi.org/10.1016/j.iheduc.2012.09.006
Schunk, D. H., Meece, J. L., & Pintrich, P. R. (2014). Motivation in education: Theory, research, and applications (4th ed.). Pearson.
Seaman, J. E., Allen, I. E., & Seaman, J. (2018). Grade Increase: Tracking distance education in the United States. Babson Survey Research Group.
Shea, P., & Bidjerano, T. (2009). Community of inquiry as a theoretical framework to foster “epistemic engagement” and “cognitive presence” in online education. Computers & Education, 52(3), 543-553. ‏
Siemens, G., Gašević, D., & Dawson, S. (2015). Preparing for the digital university: a review of the history and current state of distance, blended, and online learning. Retrieved from http://linkresearchlab.org/PreparingDigitalUniversity.pdf
Song, L., & Hill, J. R. (2007). A conceptual model for understanding self-directed learning in online environments. Journal of Interactive Online Learning, 6(1), 27–42. http://www.ncolr.org/jiol/issues/pdf/6.1.3.pdf
Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics (5th ed.). Allyn and Bacon.
Taghizade, A., Hatami, J., Fardanesh, H., & Noroozi, O. (2018). Validating the Persian version of the Community of Inquiry framework survey instrument in web-based learning environments. Quarterly of Educational Measurement, 8(31), 47-63. DOI: 10.22054/jem.2018.30681.1716
Taipjutorus, W., Hansen, S., & Brown, M. (2012). Investigating a relationship between learner control and self-efficacy in an online learning environment. Journal of Open, Flexible, and Distance Learning, 16(1), 56–69. https://files.eric.ed.gov/fulltext/EJ1079899.pdf
Taylor, M., Vaughan, N., Ghani, S. K., Atas, S., & Fairbrother, M. (2018). Looking back and looking forward: A glimpse of blended learning in higher education from 2007-2017. International Journal of Adult Vocational Education and Technology(IJAVET), 9(1), 1-14. DOI: 10.4018/IJAVET.2018010101
Thompson, B. (2004). Exploratory and confirmatory factor analysis: Understanding concepts and applications. American Psychological Association.
Tu, C.H. (2002). The measurement of social presence in an online learning environment. International Journal on E-learning, 1(2), 34–45.
Vallerand, R.J., Pelletier, L.G., Blais, M.R., & Briere, N.M. (1992). The academic motivation scale: measure of intrinsic, extrinsic, and amotivation in education. Educational and Psychological Measurement, 52(4), 1003-1007. DOI: 10.1177/0013164492052 004025.
Valverde-Berrocoso, J., Garrido-Arroyo, M. D. C., Burgos-Videla, C., & Morales-Cevallos, M. B. (2020). Trends in educational research about e-learning: A systematic literature review (2009–2018). Sustainability, 12(12), Article 5153. https://doi.org/10.3390/su12125153.
Van Niekerk, M. P. (2015). Students’ perceptions on IWB through the lens of the community of inquiry framework. South African Journal of Education, 35(4), 1–10. https://doi.org/10.15700/saje.v35n4a1212.
Veletsianos, G. (Ed.). (2016). Emergence and innovation in digital learning: Foundations and applications. Computers & Education, 122, 104-118.
Vogel, F. R., & Human-Vogel, S. (2016). Academic commitment and self-efficacy as predictors of academic achievement in additional materials science. Higher Education Research & Development, 35(6), 1298–1310. https://doi.org/10.1080/07294360.2016.1144574
Wang, L., & Finch, H. (2018). Motivation variables mediate the relationship between socioeconomic status and academic achievement. Psychology and Education: An Interdisciplinary Journal, 55, 123–136. https://www.researchgate.net/publication/329516367_Motivation_Variables_Mediate_the_Relationship_between_Socioeconomic_Status_and_Academic_Achievement
Wenger, E., McDermott, R. A., & Snyder, W. (2002). Cultivating communities of practice: A guide to managing knowledge. Harvard Business Press.
Wicks, D.A., Craft, B.B., Mason, G.N., Gritter, K., & Bolding, K. (2015). An investigation into the community of inquiry of blended classrooms by a faculty learning community. The Internet and Higher Education, 25, 53–62.
Wighting, M. J., Liu, J., & Rovai, A. P. (2008). Distinguishing sense of community and motivation characteristics between online and traditional college students. Quarterly Review of Distance Education, 9(3), 285–295.
Yandra, F. P., Alsolami, B., Sopacua, I. O., & Prajogo, W. (2021). The role of community of inquiry and self-efficacy on accounting students’ satisfaction in online learning environment. Jurnal Siasat Bisnis, 1-16. ‏
Yavuzalp, N., & Bahcivan, E. (2020). The online learning self-efficacy scale: Its adaptation into Turkish and interpretation according to various variables. Turkish Online Journal of Distance Education, 21(1), 31–44. https://files.eric.ed.gov/fulltext/EJ1238987.pdf
Yu, T., & Richardson, J.C. (2015). Examining reliability and validity of a Korean version of the community of inquiry instrument using exploratory and confirmatory factor analysis. The Internet and Higher Education, 25, 45–52.
Yukselturk, E., & Bulut, S. (2007). Predictors for student success in an online course. Educational Technology & Society, 10(2), 71–83. Retrieved from http://www.ifets.info/.
Yusuf, M. (2011). The impact of self-efficacy, achievement motivation, and self-regulated learning strategies on students’ academic achievement. Procedia-Social and Behavioral Sciences, 15, 2623-2626.