The Effect of Online Learning Platforms on Students’ Online Learning in Higher Institutions in Cameroon
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This study investigates the effect of online learning platforms on students’ use of online learning in Cameroon”. The problem of this study emanates from the low quality of knowledge and skill acquired by university students in the context of output and digitalization. which state many students in Higher Institutions in Cameroon are not able to neither participate in online classes nor submit online assignments. The student’s role in the OLP is important on many levels and for any of them to benefit from using the OLP, the student must have an active role when interacting with the OLP systems and seek to learn through engagement in online and not passively absorb information (Halverson & Graham, 2019; Ouyang & Chang, 2019). Students, who engage in large amounts of interaction with course content, using extra learning materials and resources to supplement classes, do so to support work with assignments (Shah & Barkas, 2018). OLPs make it easy to incorporate, disseminate and organize a vast collection of educational resources (Chang & Ouyang, 2019). Shelton et al., 2017) confirmed that login frequency and students’ behavior towards regular study had a significant effect on students’ use of online learning platforms. Two research questions guided the study, • To explore the different online learning platforms in some selected higher institutions in Cameroon? To investigate on how learning content in online learning platforms affects higher institution students’ online learning? The tool used for data collection was the question OLP and regression analysis were used to test Data collected was analyzed using descriptive and inferential statistics with the help of statistics. Analysis of data demonstrated that quality student performance through good instructor’s online presence, learning content, interaction, and perceived use statistically influence students’ performance significantly. A significant regression equation was found to be [f (1,325) = 21.972, p = 0.000], with an R2 of 0.122. Two specific research questions were confirmed. Therefore, it is recommended that higher institutions stakeholders in Cameroon should draft policies and curricula that will favor the creation of a healthy instructor’s online presence, learning content, interaction, and perceived use, organized workshops to OLP staff on course content, teaching style, to ensure the development of good performance skills by graduates and hence promote their positive contribution to online platforms.
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Alavi, M., &Dufner, D. (2005). Technology-mediated collaborative learning: A research perspective. Learning together online: Research on asynchronous learning networks, 28(17), 191-213.
Allen, I. E., & Seaman, J. (2006). Making the grade: Online education in the United States, 2006.
Needham, MA: Sloan-C.
Al-Fraihat, D., Joy, M., & Sinclair, J. (2017, June). Identifying success factors for e-learning in higher education. In International conference on e-learning 10(9), 247-255. Academic Conferences International Limited.
Aloraini, S. (2012). The impact of using multimedia on students’ academic achievement in the College of Education at King Saud University. Journal of King Saud University-Languages and Translation, 24(2), 75-82.
Alqahtani, A. Y., &Rajkhan, A. A. (2020). E-learning critical success factors during the covid-19 pandemic: A comprehensive analysis of e-learning managerial perspectives. Education sciences, 10(9), 216.
Amhag, L., Hellström, L., &Stigmar, M. (2019). Teacher educators' use of digital tools and needs for digital competence in higher education. Journal of Digital Learning in Teacher Education, 35(4), 203-220.
Ames, C. (1984). Achievement attributions and self-instructions under competitive and individualistic goal structures. Journal of Educational Psychology, 76(3), 478–487.
Ames, C. (1992). Classrooms: Goals, structures, and student motivation. Journal of Educational Psychology, 84, 261– 271.
Ames, C., & Archer, J. (1988). Achievement goals in the classroom: Students’ learning strategies and motivation processes. Journal of Educational Psychology, 80(3), 260–267.
Aminatun, D. (2019). ICT in university: How lecturers embrace technology for teaching. Journal Smart, 5(2), 71-80.
Anderman, E., & Anderman, L. H. (1999). Social predictors of changes in students’ achievement goal orientations. Contemporary Educational Psychology, 25, 21–37. 126
Anderson, T., Liam, R., Garrison, D. R., & Archer, W. (2001). Assessing teaching presence in a computer conferencing context, 45(1), 136-149.
Angelo, R., & McCarthy, R. (2018). Group Assignments as a Class Element to Promote Performance in Virtual Groups. Information Systems Education Journal, 16(4), 4-12.
Apandi, A. M., & Raman, A. (2020). Factors affecting successful implementation of blended learning at higher education. International Journal of Instruction, Technology, and Social Sciences, 1(1), 13-23.
Arbaugh, J. B. (2018). One bridge, (at least) two paths: Reflections on “virtual classroom characteristics and student satisfaction in internet-based MBA courses”. Journal of Management Education, 42(4), 524-532.
Armstrong, J., & Franklin, T. (2008). A review of current and developing international practice in the use of social networking (Web 2.0) in higher education.
Arslan, S., Akcaalan, M., &Yurdakul, C. (2017). Science Motivation of University Students: Achievement Goals as a Predictor. Universal Journal of Educational Research, 5(4), 681-686.
Artino, A. R. (2008). Motivational beliefs and perceptions of instructional quality: Predicting satisfaction with online training. Journal of computer assisted learning, 24(3), 260-270.
Arbaugh, J. B., Cleveland-Innes, M., Diaz, S. R., Garrison, G. R., Philip, I., Richardson, J. C., Shea, P., & Swan, K. P. (2008). The community of inquiry framework: Development, validation, and directions for further research. Paper presented at the annual meeting of the American Education Research Association, New York, NY.
Argyle, M., & Cook, M. (1976). Gaze and mutual gaze. London: Cambridge University.
Argyle, M., & Dean, J. (1965). Eye contact, distance and affiliation. Sociometry, 28, 289-304.
Aswir, A., Hadi, M. S., &Dewi, F. R. (2021). Google meet application as an online learning media for descriptive text material. Journal Studi Guru Dan Pembelajaran, 4(1), 189-194.
Ayu, M. (2020). Online learning: Leading e-learning at higher education. The Journal of English Literacy Education: The Teaching and Learning of English as a Foreign Language, 7(1), 47-Aristanto, A., Supriatna, E., Panggabean, H. M., Apriyanti, E., Hartini, H., Sari, N. I., & Kurniawati, W. (2023). The role of Artifcial Intelligence (OLP) at school learning. Consilium: Education and Counseling Journal, 3(2), Article 2. https://doi.org/10.36841/consilium.v3i2.3437
AttOLP, L. (2019). Protecting student data privacy: Classroom fundamentals. Rowman & Littlefeld Publishers.
Baker, S., Warburton, J., Waycott, J., Batchelor, F., Hoang, T., Dow, B., Ozanne, E., & Vetere, F. (2018). Combatting socialisolation and increasing social participation of older adults through the use of technology: A systematic review ofexisting evidence. Australasian Journal on Ageing, 37(3), 184–193. https://doi.org/10.1111/ajag.12572
Bembridge, E., Levett-Jones, T., & Jeong, S.Y.-S. (2011). The transferability of information and communication technologyskills from university to the workplace: A qualitative descriptive study. Nurse Education Today, 31(3), 245–252. https://doi.org/10.1016/j.nedt.2010.10.020
Bostrom, N. (2002). Existential risks: Analyzing human extinction scenarios and related hazards. Journal of Evolution andTechnology, 9. https://ora.ox.ac.uk/objects/uuid:827452c3-fcba-41b8-86b0-407293e6617c
Bostrom, N. (2012). The superintelligent will: Motivation and instrumental rationality in advanced artifcial agents. Mindsand Machines, 22(2), 71–85. https://doi.org/10.1007/s11023-012-9281-3
Gosper, M., Malfroy, J., & McKenzie, J. (2013). Students' experiences and expectations of technologies: An Australian study designed to inform planning and development decisions. Australasian Journal of Educational Technology, 29(2), 109-125.
Guldberg, K., & Pilkington, R. (2007). Tutor roles in facilitating reflection on practice through online discussion. Journal of Educational Technology & Society, 10(1), 61-72.
Haji, S. A. (2020). Exploring the frequent use of the learning management systems (lms) features and learners’ interactions in higher education European Journal of Open Education and E-learning Studies, 5(2), 154-190.
Halverson, L. R., & Graham, C. R. (2019). Learner engagement in blended learning environments: A conceptual framework. Online Learning, 23(2), 145-178.
Han, Z. M., Huang, C. Q., Yu, J. H., & Tsai, C. C. (2021). Identifying patterns of epistemic emotions with respect to interactions in massive online open courses using deep learning and social network analysis. Computers in Human Behavior, 19(4), 122-250.
Harackiewicz, J., Barron, K., & Elliot, A. (1998). Rethinking achievement goals: When are they adaptive for college students and why? Educational Psychologist, 33(1), 1–21.
Harackiewicz, J. M., Barron, K. E., Carter, S. M., Lehto, A. T., & Elliot, A. J. (1997). Predictors and consequences of achievement goals in the college classroom: Maintaining interest and making the grade. Journal of Personality & Social Psychology, 73(6), 1284–1295.
Harackiewicz, J. M., Barron, K. E., Pintrich, P. R., Elliot, A. J., & Th rash, T. M. (2002a). Revision of achievement goal theory: Necessary and illuminating. Journal of Educational Psychology, 94(3), 638–645.
Harackiewicz, J. M., Barron, K. E., Tauer, J. M., & Elliot, A. J. (2002b). Predicting success in college: A longitudinal study of achievement goals and ability measures as predictors of interest and performance from freshman year through graduation. Journal of Educational Psychology, 94(3), 562–575.
Harackiewicz, J. M., & Elliot, A. J. (1993). Achievement goals and intrinsic motivation. Journal of Personality and Social Psychology, 65(5), 904–915.
Horn, M. B., &Staker, H. (2011). The rise of K-12 blended learning. Innosight institute, 5(1), 1-17. 133
Hoskins, S. L., & Van Hooff, J. C. (2005). Motivation and ability: which students use online learning and what influence does it have on their achievement? British journal of educational technology, 36(2), 177-192.
Howland, J. L., & Moore, J. L. (2002). Student perceptions as distance learners in Internet-based courses. Distance education, 23(2), 183-195.
Hsu, M. H., Ju, T. L., Yen, C. H., & Chang, C. M. (2007). Knowledge sharing behavior in virtual communities: The relationship between trust, self-efficacy, and outcome expectations. International journal of human-computer studies, 65(2), 153-169.
Iftakhar, S. (2016). Google classroom: what works and how. Journal of Education and Social Sciences, 3(1), 12-18.
Jiang, A. L., & Zhang, L. J. (2021). University teachers' teaching style and their students' agentic engagement in EFL learning in China: a self-determination theory and achievement goal theory integrated perspective. Frontiers in psychology, 12(5), 187-220.
Kavrayici, C. (2021). The relationship between classroom management and sense of classroom community in graduate virtual classrooms. Turkish Online Journal of Distance Education, 22(2), 112-125.
Kazmer, M. M. (2005). Community-embedded learning. The Library Quarterly, 75(2), 190-212.
Kendall, M. (2001). Teaching online to campus-based students: The experience of using WebCT for the community information module at Manchester Metropolitan University. Education for information, 19(4), 325-346.
Kordrostami, M., & Seitz, V. (2021). Faculty online competence and student affective engagement in online learning. Marketing Education Review, 7(12), 1-15.
Kuna, A. S. (2012). Learner interaction patterns and student perceptions toward using selected tools in an online course management system. Iowa State University14(3), 179-192.
Kuo, Y. C., Walker, A. E., Belland, B. R., Schroder, K. E., &Kuo, Y. T. (2014). A case study of integrating Interwise: Interaction, internet self-efficacy, and satisfaction in synchronous online learning environments. International Review of Research in Open and Distributed Learning, 15(1), 161-181.