Abstract

This study aims to investigate a collaborative synchronous learning environment in terms of students’ community of inquiry perceptions (cognitive, social, and teaching presences) and interaction levels. This quantitative study was conducted with the participation of fifty-nine freshmen (twenty-nine in the control group and thirty in the experimental group) in the department of Information Technologies at a university. The study lasted nine weeks, including two weeks of data collection and seven weeks of implementation procedure. After the implementation, the Community of Inquiry Scale and the Online Course Interaction Level Determination Scale were administered to the participants. The results revealed that co-operative synchronous learning experiences positively influenced students’ community of inquiry perceptions and interaction levels in the experimental group. Further results and implications are discussed at the end. 

Keywords

References

• Adarkwah, M. A. (2021). “I’m not against online teaching, but what about us?”: ICT in Ghana post Covid-19. Education and Information Technologies, 26, 1-21. https://doi.org/10.1007/s10639-020-10331-z
• Aguilera-Hermida, A. P. (2020). College students’ use and acceptance of emergency online learning due to Covid-19. International Journal of Educational Research Open, 1, 1-18. https://doi.org/10.1016/j.ijedro.2020.100011
• Akyol, Z., & Garrison, D. R. (2011). Understanding cognitive presence in an online and blended community of inquiry: Assessing outcomes and processes for deep approaches to learning. British Journal of Educational Technology, 42(2), 233-250. https://doi.org/10.1111/j.1467-8535.2009.01029.x
• Al Lily, A. E., Ismail, A. F., Abunasser, F. M., & Alqahtani, R. H. A. (2020). Distance education as a response to pandemics: Coronavirus and Arab culture. Technology in Society, 63, 1-11. https://doi.org/10.1016/j.techsoc.2020.101317
• Al Mamun, M. A., Lawrie, G., & Wright, T. (2020). Instructional design of scaffolded online learning modules for self-directed and inquiry-based learning environments. Computers & Education, 144, 1-17. https://doi.org/10.1016/j.compedu.2019.103695
• Alfonseca, E., Carro, R. M., Martín, E., Ortigosa, A., & Paredes, P. (2006). The impact of learning styles on student grouping for collaborative learning: a case study. User Modeling and User-Adapted Interaction, 16(3-4), 377-401. https://doi.org/10.1007/s11257-006-9012-7
• Almaiah, M. A., Al-Khasawneh, A., & Althunibat, A. (2020). Exploring the critical challenges and factors influencing the E-learning system usage during COVID-19 pandemic. Education and Information Technologies, 25, 5261-5280. https://doi.org/10.1007/s10639-020-10120-8
• Al-Musharraf, A., & Alkhattabi, M. (2016). An educational data mining approach to explore the effect of using interactive supporting features in an LMS for overall performance within an online learning environment. International Journal of Computer Science and Network Security, 16(3), 1-2.
• Anderson, T. (2003). Getting the mix right again: An updated and theoretical rationale for interaction. International Review of Research in Open and Distance Learning, 4(2), 9–14. https://doi.org/10.19173/irrodl.v4i2.149
• Anderson, T. (Ed.). (2008). The theory and practice of online learning. Athabasca University Press.
• Anderson, T., & Garrison, D. R. (1998). Learning in a networked world: New roles and responsibilities. In C. Gibson (Ed.), Distance learners in higher education (pp. 97–112). Atwood Publishing.
• 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
• Arenas, E. (2015). Affordances of learning technologies in higher education multicultural environments. Electronic Journal of E-Learning, 13(4), 217-227. https://academic-publishing.org/index.php/ejel/article/view/1729/1692
• Bernard, R. M., Abrami, P. C., Borokhovski, E., Wade, C. A., Tamim, R. M., Surkes, M. A., & Bethel, E. C. (2009). A meta-analysis of three types of interaction treatments in distance education. Review of Educational Research, 79(3), 1243-1289. https://doi.org/10.3102/0034654309333844
• Blasco-Arcas, L., Buil, I., Hernández-Ortega, B., & Sese, F. J. (2013). Using clickers in class: The role of interactivity, active collaborative learning and engagement in learning performance. Computers & Education, 62, 102-110. https://doi.org/10.1016/j.compedu.2012.10.019
• Borup, J., West, R. E., & Graham, C. R. (2012). Improving online social presence through asynchronous video. The Internet and Higher Education, 15(3), 195-203. https://doi.org/10.1016/j.iheduc.2011.11.001
• Bower, M. (2019). Technology‐mediated learning theory. British Journal of Educational Technology, 50(3), 1035-1048. https://doi.org/10.1111/bjet.12771
• Burke, J., & Dempsey, M. (2020). COVID-19 Practice in primary schools in Ireland report. National University of Ireland Maynooth, Ireland. https://www.ippn.ie/images/PDFs/Covid-19_Practice_in_Primary_Schools_Report.pdf
• Butler-Henderson, K., & Crawford, J. (2020). A systematic review of online examinations: A pedagogical innovation for scalable authentication and integrity. Computers & Education, 159, 104024. https://doi.org/10.1016/j.compedu.2020.104024
• Chan, T., Chen, C. M., Wu, Y. L., Jong, B. S., Hsia, Y. T., & Lin, T. W. (2010). Applying the genetic encoded conceptual graph to grouping learning. Expert Systems with Applications, 37(6), 4103-4118. https://doi.org/10.1016/j.eswa.2009.11.014
• Chen, C. M., & Kuo, C. H. (2019). An optimized group formation scheme to promote collaborative problem-based learning. Computers & Education, 133, 94-115. https://doi.org/10.1016/j.compedu.2019.01.011
• Cheng, G., & Chau, J. (2016). Exploring the relationships between learning styles, online participation, learning achievement and course satisfaction: An empirical study of a blended learning course. British Journal of Educational Technology, 47(2), 257-278. https://doi.org/10.1111/bjet.12243
• Chi, M. T. H., & Wylie, R. (2014). The ICAP framework: Linking cognitive engagement to active learning outcomes. Educational Psychologist, 49(4), 219–243. https://doi.org/10.1080/00461520.2014.965823
• Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155.
• Coşkun, H. (2009). The interaction anxiousness scale: A study for validity and reliability. Turkish Psychological Articles, 12(23), 41-49.
• Deshmukh, S. R. (2020). Social Realities of Higher Education in the Age of Uncertainties. Smart Moves Journal IJELLH, 8(4), 279-289. https://doi.org/10.24113/ijellh.v8i4.10547
• Eom, S. B., & Ashill, N. (2016). The determinants of students’ perceived learning outcomes and satisfaction in university online education: An update. Decision Sciences Journal of Innovative Education, 14(2), 185-215. https://doi.org/10.1111/dsji.12097
• Fischer, G., Rohde, M., & Wulf, V. (2007). Community-based learning: The core competency of residential, research-based universities. International Journal of Computer-Supported Collaborative Learning, 2(1), 9-40. https://doi.org/10.1007/s11412-007-9009-1
• Garrison, D. R. (2011). E-learning in the 21st century: A framework for research and practice. Taylor & Francis.
• Garrison, D. R., Anderson, T., & Archer, W. (1999). Critical inquiry in a text-based environment: Computer conferencing in higher education. The Internet and Higher Education, 2(2-3), 87-105. https://doi.org/10.1016/S1096-7516(00)00016-6
• 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
• Gonzalez, T., De La Rubia, M. A., Hincz, K. P., Comas-Lopez, M., Subirats, L., Fort, S., & Sacha, G. M. (2020). Influence of COVID-19 confinement on students’ performance in higher education. PloS one, 15(10), 1-23. https://doi.org/10.1371/journal.pone.0239490
• Grau, V., & Whitebread, D. (2012). Self and social regulation of learning during collaborative activities in the classroom: The interplay of individual and group cognition. Learning and Instruction, 22(6), 401-412. https://doi.org/10.1016/j.learninstruc.2012.03.003
• Hawkins, A., Graham, C. R., Sudweeks, R. R., & Barbour, M. K. (2013). Academic performance, course completion rates, and student perception of the quality and frequency of interaction in a virtual high school. Distance Education, 34(1), 64-83. https://doi.org/10.1080/01587919.2013.770430
• Heo, J., & Han, I. (2003). Performance measure of information systems (IS) in evolving computing environments: an empirical investigation. Information & Management, 40(4), 243-256. https://doi.org/10.1016/S0378-7206(02)00007-1
• Hillman, D. C. A., Willis, D. J., & Gunawardena, C. N. (1994). Learner-interface interaction in distance education: An extension of contemporary models and strategies for practitioners. American Journal of Distance Education, 8, 30–42. https://doi.org/10.1080/08923649409526853
• Hilton, S., & Phillips, F. (2010). Instructor-assigned and student-selected groups: A view from inside. Issues in Accounting Education, 25(1), 15-33. https://doi.org/10.2308/iace.2010.25.1.15
• Huxham, M., & Land, R. (2000). Assigning students in group work projects. Can we do better than random? Innovations in Education and Training International, 37(1), 17-22. https://doi.org/10.1080/135580000362043
• Ishak, T., Kurniawan, R., Zainuddin, Z., & Keumala, C. M. (2020). The role of pre-class asynchronous online video lectures in flipped-class instruction: Identifying students’ perceived need satisfaction. Journal of Pedagogical Research, 4(1), 1-11. https://doi.org/10.33902/jpr.v4i1.145
• Järvelä, S., Järvenoja, H., & Veermans, M. (2008). Understanding the dynamics of motivation in socially shared learning. International Journal of Educational Research, 47(2), 122-135. https://doi.org/10.1016/j.ijer.2007.11.012
• Järvelä, S., & Järvenoja, H. (2011). Socially constructed self-regulated learning and motivation regulation in collaborative learning groups. Teachers College Record, 113(2), 350-374.
• Ji, H., Park, K., Jo, J., & Lim, H. (2016). Mining students activities from a computer supported collaborative learning system based on peer to peer network. Peer-to-Peer Networking and Applications, 9(3), 465-476. https://doi.org/10.1007/s12083-015-0397-0
• 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. https://doi.org/10.1016/j.compedu.2011.02.008
• Kaplan-Rakowski, R. (2020). Addressing students’ emotional needs during the COVID-19 pandemic: a perspective on text versus video feedback in online environments. Educational Technology Research and Development, 69, 133-136. https://doi.org/10.1007/s11423-020-09897-9
• Karaman, G. E. (2015). Development of an online course ınteraction level determination scale and design of automated estimation system [Unpublished doctoral dissertation]. Atatürk University, Erzurum.
• Kopp, B., Matteucci, M. C., & Tomasetto, C. (2012). E-tutorial support for collaborative online learning: An explorative study on experienced and inexperienced e-tutors. Computers & Education, 58(1), 12-20. https://doi.org/10.1016/j.compedu.2011.08.019
• Korkut Owen, F. & Bugay, A. (2014). İletişim becerileri ölçeği'nin geliştirilmesi: Geçerlik ve güvenirlik çalışması. Mersin Üniversitesi Eğitim Fakültesi Dergisi, 10(2), 51-64.
• Kozan, K., & Caskurlu, S. (2018). On the Nth presence for the Community of Inquiry framework. Computers & Education, 122, 104-118. https://doi.org/10.1016/j.compedu.2018.03.010
• Kozan, K., & Richardson, J. C. (2014). Interrelationships between and among social, teaching, and cognitive presence. The Internet and Higher Education, 21, 68-73. https://doi.org/10.1016/j.iheduc.2013.10.007
• Ku, H. Y., Tseng, H. W., & Akarasriworn, C. (2013). Collaboration factors, teamwork satisfaction, and student attitudes toward online collaborative learning. Computers in Human Behavior, 29(3), 922-929. https://doi.org/10.1016/j.chb.2012.12.019
• Kwon, K., Liu, Y. H., & Johnson, L. P. (2014). Group regulation and social-emotional interactions observed in computer supported collaborative learning: Comparison between good vs. poor collaborators. Computers & Education, 78, 185-200. https://doi.org/10.1016/j.compedu.2014.06.004
• Lee, J. K., & Lee, W. K. (2008). The relationship of e-Learner’s self-regulatory efficacy and perception of e-Learning environmental quality. Computers in Human Behavior, 24(1), 32-47. https://doi.org/10.1016/j.chb.2006.12.001
• Lee, R., Hoe Looi, K., Faulkner, M., & Neale, L. (2020). The moderating influence of environment factors in an extended community of inquiry model of e-learning. Asia Pacific Journal of Education, 41(1), 1-15. https://doi.org/10.1080/02188791.2020.1758032
• Lee, S. J., Srinivasan, S., Trail, T., Lewis, D., & Lopez, S. (2011). Examining the relationship among student perception of support, course satisfaction, and learning outcomes in online learning. The Internet and Higher Education, 14(3), 158-163. https://doi.org/10.1016/j.iheduc.2011.04.001
• Liu, C. C., & Tsai, C. C. (2008). An analysis of peer interaction patterns as discoursed by on-line small group problem-solving activity. Computers & Education, 50(3), 627-639. https://doi.org/10.1016/j.compedu.2006.07.002
• Lou, Y., Bernard, R. M., & Abrami, P. C. (2006). Media and pedagogy in undergraduate distance education: A theory-based meta-analysis of empirical literature. Educational Technology Research and Development, 5(2), 141–176. https://doi.org/10.1007/s11423-006-8252-x
• Maddrell, J. A., Morrison, G. R., & Watson, G. S. (2017). Presence and learning in a community of inquiry. Distance Education, 38(2), 245-258. https://doi.org/10.1080/01587919.2017.1322062
• McMillan, J. H., & Schumacher, S. (2010). Research in Education: Evidence-Based Inquiry, MyEducationLab Series. Pearson.
• Medina, R. & Suthers, D. (2008). Bringing Representational Practice From Log to Light. In Kanselaar, G., Jonker, V., Kirschner, P. A., & Prins, F. J. (Eds.), International Perspectives in the Learning Sciences: Cre8ing a learning world. Proceedings of the Eighth International Conference for the Learning Sciences – ICLS 2008, (Vol 2. pp. 59-66). International Society of the Learning Sciences. https://doi.dx.org/10.22318/icls2008.2.59
• Mills, J., Yates, K., Harrison, H., Woods, C., Chamberlain-Salaun, J., Trueman, S., & Hitchins, M. (2016). Using a community of inquiry framework to teach a nursing and midwifery research subject: An evaluative study. Nurse Education Today, 43, 34–39. https://doi.org/10.1016/j.nedt.2016.04.016
• Mishra, L., Gupta, T., & Shree, A. (2020). Online teaching-learning in higher education during lockdown period of COVID-19 pandemic. International Journal of Educational Research Open, 1, 1-8. https://doi.org/10.1016/j.ijedro.2020.100012
• Moore, M. G. (1989). Editorial: Three types of interaction. American Journal of Distance Education, 3, 1–7. doi:10.1080/08923648909526659
• Moreno, J., Ovalle, D. A., & Vicari, R. M. (2012). A genetic algorithm approach for group formation in collaborative learning considering multiple student characteristics. Computers & Education, 58(1), 560-569. https://doi.org/10.1016/j.compedu.2011.09.011
• Oakley, B., Felder, R. M., Brent, R., & Elhajj, I. (2004). Turning student groups into effective teams. Journal of Student Centered Learning, 2(1), 9–34.
• Oliveira, I., Tinoca, L., & Pereira, A. (2011). Online group work patterns: How to promote a successful collaboration. Computers & Education, 57(1), 1348-1357. https://doi.org/10.1016/j.compedu.2011.01.017
• Onrubia, J., & Engel, A. (2012). The role of teacher assistance on the effects of a macro-script in collaborative writing tasks. International Journal of Computer-Supported Collaborative Learning, 7(1), 161-186. https://doi.org/10.1007/s11412-011-9125-9
• Ornellas, A., & Muñoz Carril, P. C. (2014). A methodological approach to support collaborative media creation in an e-learning higher education context. Open Learning: The Journal of Open, Distance and e-Learning, 29(1), 59-71. https://doi.org/10.1080/02680513.2014.906916
• Owusu-Agyeman, Y., & Larbi-Siaw, O. (2018). Exploring the factors that enhance student–content interaction in a technology-mediated learning environment. Cogent Education, 5(1), 1456780. 10.1080/2331186X.2018.1456780
• Ozkan, S., & Koseler, R. (2009). Multi-dimensional students’ evaluation of e-learning systems in the higher education context: An empirical investigation. Computers & Education, 53(4), 1285-1296.
• Öztürk, E. (2012). An adaptation of the community of inquiry index: The study of validity and reliability. Elementary Education Online, 11(2), 408-422. https://doi.org/10.1016/j.compedu.2009.06.011
• Özyurt, Ö., & Özyurt, H. (2013). An examination of computer engineering students’ perceptions about asynchronous discussion forums. EURASIA Journal of Mathematics, Science and Technology Education, 9(4), 371-378. https://doi.org/10.12973/eurasia.2013.941a
• Pal, D., & Patra, S. (2020). University Students’ Perception of Video-Based Learning in Times of COVID-19: A TAM/TTF Perspective. International Journal of Human–Computer Interaction, 1-19. https://doi.org/10.1080/10447318.2020.1848164
• Pallant, J. (2016). SPSS survival manual a step by step guide to data analysis using SPSS program (6th ed.). McGraw-Hill Education.
• Paswan, A. K., & Young, J. A. (2002). Student evaluation of instructor: A nomological investigation using structural equation modeling. Journal of Marketing Education, 24(3), 193-202. https://doi.org/10.1177/0273475302238042
• Pérez-Mateo, M., & Guitert, M. (2012). Which social elements are visible in virtual groups? Addressing the categorization of social expressions. Computers & Education, 58(4), 1234-1246. https://doi.org/10.1016/j.compedu.2011.12.014
• Petronzi, R., & Petronzi, D. (2020). The Online and Campus (OaC) model as a sustainable blended approach to teaching and learning in higher education: A response to COVID-19. Journal of Pedagogical Research, 4(4), 498-507. https://doi.org/10.33902/JPR.2020064475
• Pinsk, R., Curran, M.J., Poirier, R., & Coulson, G. (2014). Student perceptions of the use of student-generated online discussions as a mechanism to establish social presence for non-traditional students: A case study. Issues in Information Systems, 15(1), 267-276. https://iacis.org/iis/2014/49_iis_2014_267-276.pdf
• Prince, M. (2004). Does active learning work? A review of the research. Journal of Engineering Education, 93(3), 223-231.
• Redmond, P. & Lock, J. V. (2006). A flexible framework for online collaborative learning. The Internet and Higher Education, 9(4), 1-10. https://doi.org/10.1016/j.iheduc.2006.08.003
• Scheuerell, S. (2010). Virtual Warrensburg: Using cooperative learning and the internet in the social studies classroom. The Social Studies, 101(5), 194-199. https://doi.org/10.1080/00377990903493861
• Shire, S. Y., Worthman, L. B., Shih, W., & Kasari, C. (2020). Comparison of face-to-face and remote support for interventionists learning to deliver JASPER intervention with children who have autism. Journal of Behavioral Education, 29, 317–338. https://doi.org/10.1007/s10864-020-09376-4
• Sun, L., Tang, Y., & Zuo, W. (2020). Coronavirus pushes education online. Nature Materials, 19(6), 687-687. https://doi.org/10.1038/s41563-020-0678-8
• Szeto, E. (2015). Community of Inquiry as an instructional approach: What effects of teaching, social and cognitive presences are there in blended synchronous learning and teaching? Computers & Education, 81, 191-201. https://doi.org/10.1016/j.compedu.2014.10.015
• Tareef, A. B. (2014). The effects of computer-assisted learning on the achievement and problem solving skills of the educational statistics students. European Scientific Journal, 10(28), 271-279.
• Tomcho, T. J., & Foels, R. (2012). Meta-analysis of group learning activities: Empirically based teaching recommendations. Teaching of Psychology, 39(3), 159-169. https://doi.org/10.1177/0098628312450414
• Turgut, Y., & Karal, H. (2015). Factors affecting interaction in a distance education via video conferencing. Journal of Instructional Technologies & Teacher Education, 4(1), 1-12.
• UNESCO Report (2020). UNESCO Report, ‘National learning platforms and tools’. https://en.unesco.org/covid19/educationresponse/nationalresponses.
• Yang, X., Zhang, M., Kong, L., Wang, Q., & Hong, J. C. (2020). The effects of scientific self-efficacy and cognitive anxiety on science engagement with the “question-observation-doing-explanation” model during school disruption in COVID-19 pandemic. Journal of Science Education and Technology, 1-14. https://doi.org/10.1007/s10956-020-09877-x
• Zhang, J. H., Zhang, Y. X., Zou, Q., & Huang, S. (2018). What learning analytics tells us: Group behavior analysis and individ-ual learning diagnosis based on long-term and large-scale data. Journal of Educational Technology & Society, 21(2), 245-258.

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