Research Article
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Year 2023, Volume: 24 Issue: 3, 21 - 38, 01.07.2023
https://doi.org/10.17718/tojde.1165209

Abstract

References

  • Aikina, T., & Bolsunovskaya, L. (2020). Moodle-based learning: Motivating and demotivating factors. International journal of emerging technologies in learning (iJET), 15(2), 239-248.
  • Aikina, Tatiana Yu, & Liudmila M. Bolsunovskaya. 2020. Moodle-Based Learning: Motivating and Demotivating Factors. International Journal of Emerging Technologies in Learning, 15(2), 239–48.
  • Al-dheleai, Y., Tasir, Z., Al-Rahmi, W., Al-Sharafi, M., & Mydin, A. (2020). Modeling of students online social presence on social networking sites with academic performance. International Journal of Emerging Technologies in Learning, 15(12), 56–71.
  • Almusharraf, N.M., & Khahro, S.H. (2020). Students’ Satisfaction with Online Learning Experiences during the COVID-19 Pandemic. International Journal of Emerging Technologies in Learning, 15(21), 246–267.
  • Andel, S. A., de Vreede, T., Spector, P. E., Padmanabhan, B., Singh, V. K., & De Vreede, G. J. (2020). Do social features help in video-centric online learning platforms? A social presence perspective. Computers in Human Behavior, 113(7).
  • Andrew, L., Wallace, R., & Sambell, R. (2021). A peer-observation initiative to enhance student engagement in the synchronous virtual classroom: A case study of a COVID-19 mandated move to online learning. Journal of University Teaching and Learning Practice, 18(4).
  • Anthonysamy, L., Koo, A.C., & Hew, S.H. (2020). Self-regulated learning strategies and non-academic outcomes in higher education blended learning environments: A one decade review. Education and Information Technologies, 25(5), 3677–3704.
  • 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. Internet and Higher Education, 11(3–4), 133–136.
  • Bedenlier, S., Wunder, I., Gläser-Zikuda, M., Kammerl, R., Kopp, B., Ziegler, A., & Händel, M. (2021). “Generation invisible?. Higher Education Students” (Non)Use of Webcams in Synchronous Online Learning. International Journal of Educational Research Open, 2(8), 100068.
  • Bijani, M., Tehranineshat, B., & Torabizadeh, C. (2019). Professional Values of Nurses and Nursing Students: A comparative study. Nursing ethics, 26(3), 870–883. Bolliger, D.U., & Halupa, C. (2018). Online student perceptions of engagement, transactional distance, and outcomes. Distance Education, 39(3), 299–316.
  • Bowyer, J., & Chambers, L. (2017). Evaluating blended learning: Bringing the elements together. Research Matters: A Cambridge Assessment Publication, 23(1), 17-26.
  • Campbell, C.M., & Cabrera, A.F. (2014). Making the Mark: Are Grades and Deep Learning Related? Research in Higher Education, 55(5), 494–507.
  • Carbajal-Carrera, B. (2021). Mapping connections among activism interactional practices and presence in videoconferencing language learning. System, 99, 102527.
  • Chan, S. L., Lin, C. C., Chau, P. H., Takemura, N., & Fung, J. T. C. (2021). Evaluating online learning engagement of nursing students. Nurse Education Today, 104, 1–7.
  • Chase, P. A., Hilliard, L. J., John Geldhof, G., Warren, D. J., & Lerner, R. M. (2014). Academic Achievement in the High School Years: The Changing Role of School Engagement. Journal of Youth and Adolescence, 43(6), 884–896.
  • Chen, N. S., Ko, H. C., Kinshuk*, & Lin, T. (2005). A model for synchronous learning using the Internet. Innovations in Education and Teaching International, 42(2), 181–194.
  • 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.
  • Clark, C., Strudler, N., & Grove, K. (2015). Comparing asynchronous and synchronous video vs. Text based discussions in an online teacher education course. Online Learning Journal, 19(3), 1–22.
  • Colling, J., Wollschläger, R., Keller, U., Preckel, F., & Fischbach, A. (2022). Need for Cognition and its relation to academic achievement in different learning environments. Learning and Individual Differences, 93, 102110.
  • Cooper, K.S. (2014). Eliciting Engagement in the High School Classroom: A Mixed-Methods Examination of Teaching Practices. American Educational Research Journal, 51(2), 363–402.
  • Croxton, R.A. (2014). The Role of Interactivity in Student Satisfaction and Persistence in Online Learning. Journal of Online Learning and Teaching, 10(2), 314–325.
  • Cunningham, U., & Una Cunningham, S. (2014). Teaching the Disembodied: Othering and Activity Systems in a Blended Synchronous Learning Situation. International Review of Research in Open and Distributed Learning. 15(6), 33–51.
  • Davis, F.D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319–340.
  • Dhaqane, M.K., & Afrah, N.A. (2016). Satisfaction of Students and Academic Performance in Benadir University. Journal of Education and Practice, 7(24), 59–63.
  • Dinh, T.C., & Nguyen, P.B.N. (in press). Impact of Internet Self-Efficacy and Self-Regulated Learning on Satisfaction and Academic Achievement in Online Learning: A Case Study in Vietnam. International Journal of Emerging Technologies in Learning.
  • Ejubović, A., & Puška, A. (2019). Impact of self-regulated learning on academic performance and satisfaction of students in the online environment. Knowledge Management and E-Learning, 11(3), 345–363.
  • Elshami, W., Taha, M. H., Abdalla, M. E., Abuzaid, M., Saravanan, C., & Al Kawas, S. (2022). Factors that affect student engagement in online learning in health professions education. Nurse Education Today, 110, 105261.
  • Feeley, A. M., & Biggerstaff, D. L. (2015). Exam success at undergraduate and graduate-entry medical schools: is learning style or learning approach more important? A critical review exploring links between academic success, learning styles, and learning approaches among school-leaver entry (“traditional”) and graduate-entry (“nontraditional”) medical students. Teaching and learning in medicine, 27(3), 237-244.
  • Fredricks, J.A., Blumenfeld, P.C., & Paris, A.H. (2004). School engagement: Potential of the concept, state of the evidence. Review of Educational Research, 74(1), 59–109.
  • Garrison, D., Anderson, T., & Archer, W. (2000). Critical inquiry in a text-based environment: Computer conferencing in higher education. The Internet and Higher Education, 2(2-3), 87-105.
  • Garratt-Reed, D., Roberts, L.D., & Heritage, B. (2016). Grades, student satisfaction and retention in online and face-to-face introductory psychology units: A test of equivalency theory. Frontiers in Psychology, 7, 1–10. Gómez-Rey, P., Barbera, E., & Fernández-Navarro, F. (2016). Measuring teachers and learners’ perceptions of the quality of their online learning experience. Distance Education, 37(2), 146–163.
  • Gopal, R., Singh, V., & Aggarwal, A. (2021). Impact of online classes on the satisfaction and performance of students during the pandemic period of COVID 19. Education and Information Technologies, 26(6), 6923–6947.
  • Gray, J. A., & DiLoreto, M. (2016). The effects of student engagement, student satisfaction, and perceived learning in online learning environments. International Journal of Educational Leadership Preparation, 11(1). Greene, B.A. (2015). Measuring Cognitive Engagement With Self-Report Scales: Reflections From Over 20 Years of Research. Educational Psychologist, 50(1), 14–30.
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  • Halverson, L. R., Graham, C. R., Spring, K. J., Drysdale, J. S., & Henrie, C. R. (2014). A thematic analysis of the most highly cited scholarship in the first decade of blended learning research. Internet and Higher Education, 20, 20–34.
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  • Kim, D., Lee, Y., Leite, W. L., & Huggins-Manley, A. C. (2020). Exploring student and teacher usage patterns associated with student attrition in an open educational resource-supported online learning platform. Computers and Education, 156, 103961.
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IMPACT OF SYNCHRONOUS ONLINE LEARNING ENVIRONMENT ON STUDENTS’ COGNITIVE ENGAGEMENT AND LEARNING OUTCOMES

Year 2023, Volume: 24 Issue: 3, 21 - 38, 01.07.2023
https://doi.org/10.17718/tojde.1165209

Abstract

Although roles of teaching presence have often been neglected in online learning environments, recent research has acknowledged its burgeoning importance. Synchronous online learning mode in which the teaching and learning process occurs in concurrent real-time helps blur the physical boundary hindrance of online learning for students. However, being present in classes, even in brick-and-mortar classes or virtual classes, does not ensure students’ learning occurrence. The purpose of this study was to investigate the effects of synchronous online learning environments (SOLE) on students’ cognitive engagement, satisfaction, and academic achievement as well. Partial Least Square Structural Equation Modeling (PLSSEM) was utilized to examine the issue under investigation. The results from a questionnaire survey from 186 participants indicated that pedagogical instructions had direct positive medium effects on both deep and shallow cognitive engagements; deep cognitive engagement had a direct positive impact on academic achievement while shallow cognitive engagement did not have any impact on academic achievement and satisfaction. Interestingly, technical support had a direct positive impact on both direct impacts on academic achievements and satisfaction. Implications for the teaching and learning in a synchronous online modality and limitations of the study were also discussed.

References

  • Aikina, T., & Bolsunovskaya, L. (2020). Moodle-based learning: Motivating and demotivating factors. International journal of emerging technologies in learning (iJET), 15(2), 239-248.
  • Aikina, Tatiana Yu, & Liudmila M. Bolsunovskaya. 2020. Moodle-Based Learning: Motivating and Demotivating Factors. International Journal of Emerging Technologies in Learning, 15(2), 239–48.
  • Al-dheleai, Y., Tasir, Z., Al-Rahmi, W., Al-Sharafi, M., & Mydin, A. (2020). Modeling of students online social presence on social networking sites with academic performance. International Journal of Emerging Technologies in Learning, 15(12), 56–71.
  • Almusharraf, N.M., & Khahro, S.H. (2020). Students’ Satisfaction with Online Learning Experiences during the COVID-19 Pandemic. International Journal of Emerging Technologies in Learning, 15(21), 246–267.
  • Andel, S. A., de Vreede, T., Spector, P. E., Padmanabhan, B., Singh, V. K., & De Vreede, G. J. (2020). Do social features help in video-centric online learning platforms? A social presence perspective. Computers in Human Behavior, 113(7).
  • Andrew, L., Wallace, R., & Sambell, R. (2021). A peer-observation initiative to enhance student engagement in the synchronous virtual classroom: A case study of a COVID-19 mandated move to online learning. Journal of University Teaching and Learning Practice, 18(4).
  • Anthonysamy, L., Koo, A.C., & Hew, S.H. (2020). Self-regulated learning strategies and non-academic outcomes in higher education blended learning environments: A one decade review. Education and Information Technologies, 25(5), 3677–3704.
  • 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. Internet and Higher Education, 11(3–4), 133–136.
  • Bedenlier, S., Wunder, I., Gläser-Zikuda, M., Kammerl, R., Kopp, B., Ziegler, A., & Händel, M. (2021). “Generation invisible?. Higher Education Students” (Non)Use of Webcams in Synchronous Online Learning. International Journal of Educational Research Open, 2(8), 100068.
  • Bijani, M., Tehranineshat, B., & Torabizadeh, C. (2019). Professional Values of Nurses and Nursing Students: A comparative study. Nursing ethics, 26(3), 870–883. Bolliger, D.U., & Halupa, C. (2018). Online student perceptions of engagement, transactional distance, and outcomes. Distance Education, 39(3), 299–316.
  • Bowyer, J., & Chambers, L. (2017). Evaluating blended learning: Bringing the elements together. Research Matters: A Cambridge Assessment Publication, 23(1), 17-26.
  • Campbell, C.M., & Cabrera, A.F. (2014). Making the Mark: Are Grades and Deep Learning Related? Research in Higher Education, 55(5), 494–507.
  • Carbajal-Carrera, B. (2021). Mapping connections among activism interactional practices and presence in videoconferencing language learning. System, 99, 102527.
  • Chan, S. L., Lin, C. C., Chau, P. H., Takemura, N., & Fung, J. T. C. (2021). Evaluating online learning engagement of nursing students. Nurse Education Today, 104, 1–7.
  • Chase, P. A., Hilliard, L. J., John Geldhof, G., Warren, D. J., & Lerner, R. M. (2014). Academic Achievement in the High School Years: The Changing Role of School Engagement. Journal of Youth and Adolescence, 43(6), 884–896.
  • Chen, N. S., Ko, H. C., Kinshuk*, & Lin, T. (2005). A model for synchronous learning using the Internet. Innovations in Education and Teaching International, 42(2), 181–194.
  • 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.
  • Clark, C., Strudler, N., & Grove, K. (2015). Comparing asynchronous and synchronous video vs. Text based discussions in an online teacher education course. Online Learning Journal, 19(3), 1–22.
  • Colling, J., Wollschläger, R., Keller, U., Preckel, F., & Fischbach, A. (2022). Need for Cognition and its relation to academic achievement in different learning environments. Learning and Individual Differences, 93, 102110.
  • Cooper, K.S. (2014). Eliciting Engagement in the High School Classroom: A Mixed-Methods Examination of Teaching Practices. American Educational Research Journal, 51(2), 363–402.
  • Croxton, R.A. (2014). The Role of Interactivity in Student Satisfaction and Persistence in Online Learning. Journal of Online Learning and Teaching, 10(2), 314–325.
  • Cunningham, U., & Una Cunningham, S. (2014). Teaching the Disembodied: Othering and Activity Systems in a Blended Synchronous Learning Situation. International Review of Research in Open and Distributed Learning. 15(6), 33–51.
  • Davis, F.D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319–340.
  • Dhaqane, M.K., & Afrah, N.A. (2016). Satisfaction of Students and Academic Performance in Benadir University. Journal of Education and Practice, 7(24), 59–63.
  • Dinh, T.C., & Nguyen, P.B.N. (in press). Impact of Internet Self-Efficacy and Self-Regulated Learning on Satisfaction and Academic Achievement in Online Learning: A Case Study in Vietnam. International Journal of Emerging Technologies in Learning.
  • Ejubović, A., & Puška, A. (2019). Impact of self-regulated learning on academic performance and satisfaction of students in the online environment. Knowledge Management and E-Learning, 11(3), 345–363.
  • Elshami, W., Taha, M. H., Abdalla, M. E., Abuzaid, M., Saravanan, C., & Al Kawas, S. (2022). Factors that affect student engagement in online learning in health professions education. Nurse Education Today, 110, 105261.
  • Feeley, A. M., & Biggerstaff, D. L. (2015). Exam success at undergraduate and graduate-entry medical schools: is learning style or learning approach more important? A critical review exploring links between academic success, learning styles, and learning approaches among school-leaver entry (“traditional”) and graduate-entry (“nontraditional”) medical students. Teaching and learning in medicine, 27(3), 237-244.
  • Fredricks, J.A., Blumenfeld, P.C., & Paris, A.H. (2004). School engagement: Potential of the concept, state of the evidence. Review of Educational Research, 74(1), 59–109.
  • Garrison, D., Anderson, T., & Archer, W. (2000). Critical inquiry in a text-based environment: Computer conferencing in higher education. The Internet and Higher Education, 2(2-3), 87-105.
  • Garratt-Reed, D., Roberts, L.D., & Heritage, B. (2016). Grades, student satisfaction and retention in online and face-to-face introductory psychology units: A test of equivalency theory. Frontiers in Psychology, 7, 1–10. Gómez-Rey, P., Barbera, E., & Fernández-Navarro, F. (2016). Measuring teachers and learners’ perceptions of the quality of their online learning experience. Distance Education, 37(2), 146–163.
  • Gopal, R., Singh, V., & Aggarwal, A. (2021). Impact of online classes on the satisfaction and performance of students during the pandemic period of COVID 19. Education and Information Technologies, 26(6), 6923–6947.
  • Gray, J. A., & DiLoreto, M. (2016). The effects of student engagement, student satisfaction, and perceived learning in online learning environments. International Journal of Educational Leadership Preparation, 11(1). Greene, B.A. (2015). Measuring Cognitive Engagement With Self-Report Scales: Reflections From Over 20 Years of Research. Educational Psychologist, 50(1), 14–30.
  • Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. (2019). Multivariate data analysis. Cengage. Hair Jr, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Partial least squares structural equation modeling (PLS-SEM) using R: A workbook. Springer.
  • Halverson, L. R., Graham, C. R., Spring, K. J., Drysdale, J. S., & Henrie, C. R. (2014). A thematic analysis of the most highly cited scholarship in the first decade of blended learning research. Internet and Higher Education, 20, 20–34.
  • Henseler, J., Ringle, C.M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135.
  • Hubbard, P. (2019). Five keys from the past to the future of CALL. International Journal of Computer-Assisted Language Learning and Teaching, 9(3), 1–13.
  • Ji, H., Park, S., & Shin, H.W. (2022). Investigating the link between engagement, readiness, and satisfaction in a synchronous online second language learning environment. System, 105, 102720.
  • Kim, D., Lee, Y., Leite, W. L., & Huggins-Manley, A. C. (2020). Exploring student and teacher usage patterns associated with student attrition in an open educational resource-supported online learning platform. Computers and Education, 156, 103961.
  • Kirschner, P., Strijbos, J. W., Kreijns, K., & Beers, P. J. (2004). Designing electronic collaborative learning environments To cite this version. Educational Technology Research and Development. 52(3), 47–66.
  • Kock, N. (2015). Common method bias in PLS-SEM: A full collinearity assessment approach. International Journal of e-Collaboration, 11(4), 1–10.
  • Lee, S., & Koszalka, T.A. (2016). Course-level implementation of First Principles, goal orientations, and cognitive engagement: a multilevel mediation model. Asia Pacific Education Review, 17(2), 365–375.
  • Liu, S., Liu, S., Liu, Z., Peng, X., & Yang, Z. (2022). Automated detection of emotional and cognitive engagement in MOOC discussions to predict learning achievement. Computers and Education, 181, 104461.
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Details

Primary Language English
Journal Section Articles
Authors

Cao Tuong Dınh This is me 0000-0002-3879-7655

Publication Date July 1, 2023
Submission Date August 22, 2022
Published in Issue Year 2023 Volume: 24 Issue: 3

Cite

APA Dınh, C. T. (2023). IMPACT OF SYNCHRONOUS ONLINE LEARNING ENVIRONMENT ON STUDENTS’ COGNITIVE ENGAGEMENT AND LEARNING OUTCOMES. Turkish Online Journal of Distance Education, 24(3), 21-38. https://doi.org/10.17718/tojde.1165209