E-Learning Adoption: Designing a Network-Based Educational and Methodological Course on "Humans and Their Health"

Nurdana Salybekova; Serzhan Abdimalik; Gani Issayev; Gulmira Khalikova; Almagul Berdenkulova; Kulzhakhan Bakirova

doi:10.28991/ESJ-2023-07-06-014

Authors

Nurdana Salybekova
nurdanasalybekova@yandex.ru
Khoja Akhmet Yassawi International Kazakh-Turkish University, Turkistan,, Kazakhstan
Serzhan Abdimalik Khoja Akhmet Yassawi International Kazakh-Turkish University, Turkistan,, Kazakhstan
Gani Issayev Khoja Akhmet Yassawi International Kazakh-Turkish University, Turkistan,, Kazakhstan
Gulmira Khalikova South Kazakhstan Pedagogical University named after O.Zhanibekov, Shymkent,, Kazakhstan
Almagul Berdenkulova Korkyt Ata Kyzylorda University, Kyzylorda,, Kazakhstan
Kulzhakhan Bakirova Abai Kazakh National Pedagogical University, Almaty,, Kazakhstan

Vol. 7 No. 6 (2023): December

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This study aims to explore the factors influencing the adoption of e-learning platforms in biology education and examine the impact of online learning on students' performance. This study investigates the relationships between perceived usefulness, perceived ease of use, attitude toward e-learning, flexibility, content quality, and students' behavioral intention to adopt e-learning activities. A mixed-methods approach was employed consisting of two phases: a questionnaire survey with structural equation modeling (SEM) to analyze data and an experiment with an independent sample t-test to assess the impact of online learning on student performance. Findings disclosed that perceived usefulness, perceived ease of use, attitude toward e-learning, flexibility, and content quality positively impacted students' behavioral intention to adopt e-learning and their performance. This study contributes to the theoretical understanding of the factors influencing e-learning adoption in biology education. Practical recommendations are provided for educators, instructional designers, and policymakers to facilitate the implementation of e-learning platforms in biology education. These recommendations include promoting the perceived usefulness and ease of use of e-learning platforms, fostering a positive attitude toward e-learning, enhancing flexibility, ensuring high-quality content, providing training and support for educators, and considering the needs of students with disabilities.

Doi: 10.28991/ESJ-2023-07-06-014

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Salybekova, N., Abdimalik, S., Issayev, G., Khalikova, G., Berdenkulova, A., & Bakirova, K. (2023). E-Learning Adoption: Designing a Network-Based Educational and Methodological Course on "Humans and Their Health". Emerging Science Journal, 7(6), 2097–2119. https://doi.org/10.28991/ESJ-2023-07-06-014

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Moore, J. L., Dickson-Deane, C., & Galyen, K. (2011). E-Learning, online learning, and distance learning environments: Are they the same? The Internet and Higher Education, 14(2), 129–135. doi:10.1016/j.iheduc.2010.10.001.

Behl, A., Jayawardena, N., Pereira, V., Islam, N., Giudice, M. D., & Choudrie, J. (2022). Gamification and e-learning for young learners: A systematic literature review, bibliometric analysis, and future research agenda. Technological Forecasting and Social Change, 176, 121445. doi:10.1016/j.techfore.2021.121445.

Zhang, Z., Cao, T., Shu, J., & Liu, H. (2022). Identifying key factors affecting college students' adoption of the e-learning system in mandatory blended learning environments. Interactive Learning Environments, 30(8), 1388–1401. doi:10.1080/10494820.2020.1723113.

Fauzi, M. A. (2022). E-learning in higher education institutions during COVID-19 pandemic: current and future trends through bibliometric analysis. Heliyon, 8(5), 9433. doi:10.1016/j.heliyon.2022.e09433.

Rahayu, N. W., Ferdiana, R., & Kusumawardani, S. S. (2022). A systematic review of ontology use in E-Learning recommender system. Computers and Education: Artificial Intelligence, 3, 100047. doi:10.1016/j.caeai.2022.100047.

Mastan, I. A., Sensuse, D. I., Suryono, R. R., & Kautsarina, K. (2022). Evaluation of Distance Learning System (E-Learning): A Systematic Literature Review. Jurnal Teknoinfo, 16(1), 132. doi:10.33365/jti.v16i1.1736.

Rachman, T. T., Komariah, A., Kurniady, D. A., & Rahmawati, I. (2022). Learning Effectiveness Through Utilization Of Technology Acceptance Model (TAM)-Based Google Classroom. Journal of Positive School Psychology, 6(8), 3964–3975.

Liaw, S. S., Huang, H. M., & Chen, G. D. (2007). Surveying instructor and learner attitudes toward e-learning. Computers and Education, 49(4), 1066–1080. doi:10.1016/j.compedu.2006.01.001.

Venkatesh, Morris, Davis, & Davis. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425. doi:10.2307/30036540.

Sun, P. C., Tsai, R. J., Finger, G., Chen, Y. Y., & Yeh, D. (2008). What drives a successful e-Learning? An empirical investigation of the critical factors influencing learner satisfaction. Computers & Education, 50(4), 1183–1202. doi:10.1016/j.compedu.2006.11.007.

Kanwar, A., & Mishra, S. (2018). Can technology solve the problems of higher education? Horizons, 23, 20–21.

Sangrí , A., Vlachopoulos, D., & Cabrera, N. (2012). Building an inclusive definition of e-learning: An approach to the conceptual framework. The International Review of Research in Open and Distributed Learning, 13(2), 145. doi:10.19173/irrodl.v13i2.1161.

Nurbekova, Z. K., Mukhamediyeva, K. M., Davletova, A. H., & Kasymova, A. H. (2018). Methodological system of educational robotics training: Systematic literature review. Espacios, 39(15), 28–36.

Abdigapbarova, U., & Zhiyenbayeva, N. (2023). Organization of student-centered learning within the professional training of a future teacher in a digital environment. Education and Information Technologies, 28(1), 647-661. doi:10.1007/s10639-022-11159-5.

Davletova, A. H., Tolganbaiuly, T., Tazhigulova, A. I., Smagulova, L. A., Kasymova, A. H., & Baigozhanova, D. S. (2019). Project-oriented training experience in micro-robot programming in college and its features. Opción: Revista de Ciencias Humanas y Sociales, (22), 292-307.

Camara, J. S. (2020). Philippine Biology Education for a Curricular Innovation towards Industrial Revolution 4.0: A Mixed Method. Asian Journal of Multidisciplinary Studies, 3(1), 41-51.

Choe, R. C., Scuric, Z., Eshkol, E., Cruser, S., Arndt, A., Cox, R., Toma, S. P., Shapiro, C., Levis-Fitzgerald, M., Barnes, G., & Crosbie, R. H. (2019). Student Satisfaction and Learning Outcomes in Asynchronous Online Lecture Videos. CBE-Life Sciences Education, 18(4), ar55. doi:10.1187/cbe.18-08-0171.

Sadikin, A., & Hamidah, A. (2020). Online Learning in the Midst of the Covid-19 Outbreak. BIODIK, 6(2), 214–224. doi:10.22437/bio.v6i2.9759.

Maldarelli, G. A., Hartmann, E. M., Cummings, P. J., Horner, R. D., Obom, K. M., Shingles, R., & Pearlman, R. S. (2009). Virtual Lab Demonstrations Improve Students' Mastery of Basic Biology Laboratory Techniques. Journal of Microbiology & Biology Education, 10(1), 51–57. doi:10.1128/jmbe.v10.99.

Schönborn, K. J., & Anderson, T. R. (2006). The importance of visual literacy in the education of biochemists. Biochemistry and Molecular Biology Education, 34(2), 94–102. doi:10.1002/bmb.2006.49403402094.

Stuckey-Mickell, T. A., & Stuckey-Danner, B. D. (2007). Virtual labs in the online biology course: Student perceptions of effectiveness and usability. MERLOT journal of online learning and teaching, 3(2), 105-111.

Wei, C. A., & Woodin, T. (2011). Undergraduate research experiences in biology: Alternatives to the apprenticeship model. CBE-Life Sciences Education, 10(2), 123–131. doi:10.1187/cbe.11-03-0028.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–339. doi:10.2307/249008.

Guri-Rosenblit, S., & Gros, B. (2011). E-learning: Confusing terminology, research gaps and inherent challenges. International Journal of E-Learning & Distance Education/Revue internationale du e-learning et la formation í distance, 25(1), 729.

Martin, S., Diaz, G., Sancristobal, E., Gil, R., Castro, M., & Peire, J. (2011). New technology trends in education: Seven years of forecasts and convergence. Computers and Education, 57(3), 1893–1906. doi:10.1016/j.compedu.2011.04.003.

Dabbagh, N., & Kitsantas, A. (2012). Personal Learning Environments, social media, and self-regulated learning: A natural formula for connecting formal and informal learning. Internet and Higher Education, 15(1), 3–8. doi:10.1016/j.iheduc.2011.06.002.

Abu-Rish, E., Kim, S., Choe, L., Varpio, L., Malik, E., White, A. A., Craddick, K., Blondon, K., Robins, L., Nagasawa, P., Thigpen, A., Chen, L. L., Rich, J., & Zierler, B. (2012). Current trends in interprofessional education of health sciences students: A literature review. Journal of Interprofessional Care, 26(6), 444–451. doi:10.3109/13561820.2012.715604.

Borrego, M., Froyd, J. E., & Hall, T. S. (2010). Diffusion of engineering education innovations: A survey of awareness and adoption rates in U.S. engineering departments. Journal of Engineering Education, 99(3), 185–207. doi:10.1002/j.2168-9830.2010.tb01056.x.

Koh, J. H. L., & Divaharan, H. (2011). Developing Pre-Service Teachers' Technology Integration Expertise Through the Tpack-Developing Instructional Model. Journal of Educational Computing Research, 44(1), 35–58. doi:10.2190/ec.44.1.c.

Macfadyen, L. P., & Dawson, S. (2012). Numbers are not enough. Why e-learning analytics failed to inform an institutional strategic plan. Journal of Educational Technology & Society, 15(3), 149-163.

Ossiannilsson, E., & Landgren, L. (2012). Quality in e-learning - a conceptual framework based on experiences from three international benchmarking projects. Journal of Computer Assisted Learning, 28(1), 42–51. doi:10.1111/j.1365-2729.2011.00439.x.

Cole, M. T., Shelley, D. J., & Swartz, L. B. (2014). Online instruction, e-learning, and student satisfaction: A three year study. International Review of Research in Open and Distance Learning, 15(6), 111–131. doi:10.19173/irrodl.v15i6.1748.

Koehler, M., & Mishra, P. (2009). What is technological pedagogical content knowledge (TPACK)?. Contemporary issues in technology and teacher education, 9(1), 60-70.

Graf, S., Liu, T. C., & Kinshuk. (2010). Analysis of learners' navigational behaviour and their learning styles in an online course. Journal of Computer Assisted Learning, 26(2), 116–131. doi:10.1111/j.1365-2729.2009.00336.x.

Yuen, S. C.-Y., Yaoyuneyong, G., & Johnson, E. (2011). Augmented Reality: An Overview and Five Directions for AR in Education. Journal of Educational Technology Development and Exchange, 4(1), 11. doi:10.18785/jetde.0401.10.

Anderson, S. E. (1997). Understanding teacher change: Revisiting the Concerns Based Adoption Model. Curriculum Inquiry, 27(3), 331–367. doi:10.1080/03626784.1997.11075495.

Yan, T., & Deng, M. (2019). Regular education teachers' concerns on inclusive education in China from the perspective of concerns-based adoption model. International Journal of Inclusive Education, 23(4), 384–404. doi:10.1080/13603116.2018.1435741.

Trapani, B., & Annunziato, A. (2018). Using the Concerns Based Adoption Model (CBAM) to Accelerate Understanding by Design Implementation. Journal of instructional pedagogies, 21.

Gabby, S., Avargil, S., Herscovitz, O., & Dori, Y. J. (2017). The case of middle and high school chemistry teachers implementing technology: using the concerns-based adoption model to assess change processes. Chemistry Education Research and Practice, 18(1), 214–232. doi:10.1039/c6rp00193a.

Tobola, M. B. (2015). Utilizing the concerns-based adoption model in a professional development series for teachers implementing new technologies. PhD Thesis, North Dakota State University, Frago, United States.

Straub, E. T. (2009). Understanding technology adoption: Theory and future directions for informal learning. Review of Educational Research, 79(2), 625–649. doi:10.3102/0034654308325896.

Stewart, G. (2015). Teachers' concerns and uses of iPads in the classroom with the concerns-based adoption model. PhD thesis, University of North Texas, Denton, United States.

Voogt, J., Fisser, P., Pareja Roblin, N., Tondeur, J., & van Braak, J. (2013). Technological pedagogical content knowledge - A review of the literature. Journal of Computer Assisted Learning, 29(2), 109–121. doi:10.1111/j.1365-2729.2012.00487.x.

Graham, C. R. (2011). Theoretical considerations for understanding technological pedagogical content knowledge (TPACK). Computers and Education, 57(3), 1953–1960. doi:10.1016/j.compedu.2011.04.010.

Archambault, L. M., & Barnett, J. H. (2010). Revisiting technological pedagogical content knowledge: Exploring the TPACK framework. Computers & Education, 55(4), 1656–1662. doi:10.1016/j.compedu.2010.07.009.

Lee, M. H., & Tsai, C. C. (2010). Exploring teachers' perceived self-efficacy and technological pedagogical content knowledge with respect to educational use of the World Wide Web. Instructional Science, 38(1). doi:10.1007/s11251-008-9075-4.

Harris, J. B., & Hofer, M. J. (2011). Technological pedagogical content knowledge (TPACK) in action: A descriptive study of secondary teachers' curriculum-based, technology-related lnstructional planning. Journal of Research on Technology in Education, 43(3), 211–229. doi:10.1080/15391523.2011.10782570.

Koehler, M. J., Mishra, P., & Yahya, K. (2007). Tracing the development of teacher knowledge in a design seminar: Integrating content, pedagogy and technology. Computers and Education, 49(3), 740–762. doi:10.1016/j.compedu.2005.11.012.

Abbitt, J. T. (2011). Measuring technological pedagogical content knowledge in preservice teacher education: A review of current methods and instruments. Journal of Research on Technology in Education, 43(4), 281–300. doi:10.1080/15391523.2011.10782573.

Harris, J., Hofer, M., Blanchard, M., Grandgenett, N., Schmidt, D., Van Olphen, M., & Young, C. (2010). "Grounded” technology integration: Instructional planning using curriculum-based activity type taxonomies. Journal of Technology and Teacher Education, 18(4), 573-605.

Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Addison-Wesley, Boston, United States.

Lee, Y., Kozar, K. A., & Larsen, K. R. T. (2003). The Technology Acceptance Model: Past, Present, and Future. Communications of the Association for Information Systems, 12, 50. doi:10.17705/1cais.01250.

Venkatesh, V., & Davis, F. D. (2000). Theoretical extension of the Technology Acceptance Model: Four longitudinal field studies. Management Science, 46(2), 186–204. doi:10.1287/mnsc.46.2.186.11926.

Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273–315. doi:10.1111/j.1540-5915.2008.00192.x.

Chatterjee, S., Chakraborty, S., Sarker, S., Sarker, S., & Lau, F. Y. (2009). Examining the success factors for mobile work in healthcare: A deductive study. Decision Support Systems, 46(3), 620–633. doi:10.1016/j.dss.2008.11.003.

Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and tam in online shopping: AN integrated model. MIS Quarterly, 27(1), 51–90. doi:10.2307/30036519.

Hennington, A., & Janz, B. D. (2007). Information Systems and Healthcare XVI: Physician Adoption of Electronic Medical Records: Applying the UTAUT Model in a Healthcare Context. Communications of the Association for Information Systems, 19, 5. doi:10.17705/1cais.01905.

Bagozzi, R. P. (2007). The legacy of the technology acceptance model and a proposal for a paradigm shift. Journal of the Association for Information Systems, 8(4), 244–254. doi:10.17705/1jais.00122.

Cao, X., Masood, A., Luqman, A., & Ali, A. (2018). Excessive use of mobile social networking sites and poor academic performance: Antecedents and consequences from stressor-strain-outcome perspective. Computers in Human Behavior, 85, 163–174. doi:10.1016/j.chb.2018.03.023.

Moon, J. W., & Kim, Y. G. (2001). Extending the TAM for a World-Wide-Web context. Information and Management, 38(4), 217–230. doi:10.1016/S0378-7206(00)00061-6.

Venkatesh, V., & Davis, F. D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision Sciences, 27(3), 451–481. doi:10.1111/j.1540-5915.1996.tb00860.x.

Park, S. Y. (2009). An analysis of the technology acceptance model in understanding university students' behavioral intention to use e-learning. Journal of Educational Technology & Society, 12(3), 150-162.

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management Science, 35(8), 982–1003. doi:10.1287/mnsc.35.8.982.

Teo, T. (2011). Factors influencing teachers' intention to use technology: Model development and test. Computers & Education, 57(4), 2432–2440. doi:10.1016/j.compedu.2011.06.008.

Cho, M. H., & Heron, M. L. (2015). Self-regulated learning: the role of motivation, emotion, and use of learning strategies in students' learning experiences in a self-paced online mathematics course. Distance Education, 36(1), 80–99. doi:10.1080/01587919.2015.1019963.

Al-Fraihat, D., Joy, M., Masa'deh, R., & Sinclair, J. (2020). Evaluating E-learning systems success: An empirical study. Computers in Human Behavior, 102, 67–86. doi:10.1016/j.chb.2019.08.004.

Dimitrova, M., Sadler, C., Hatzipanagos, S., & Murphy, A. (2003). Addressing learner diversity by promoting flexibility in e-learning environments. 14th International Workshop on Database and Expert Systems Applications, 2003, Prague, Czech Republic. doi:10.1109/dexa.2003.1232037.

Alrawi, K., & Jaber, K. H. (2008). How flexible is e-learning in the educational institutions: the Arab universities' case study. International Journal of Trade and Global Markets, 1(2), 118. doi:10.1504/ijtgm.2008.018442.

Ehlers, U.-D. (2018). Quality in e-Learning from a Learner's Perspective. Distances et Médiations des Savoirs, Oldenburg, Germany. doi:10.4000/dms.2707.

Pham, L., Limbu, Y. B., Bui, T. K., Nguyen, H. T., & Pham, H. T. (2019). Does e-learning service quality influence e-learning student satisfaction and loyalty? Evidence from Vietnam. International Journal of Educational Technology in Higher Education, 16(1), 1–26. doi:10.1186/s41239-019-0136-3.

Mccutcheon, K., Lohan, M., Traynor, M., & Martin, D. (2015). A systematic review evaluating the impact of online or blended learning vs. face-to-face learning of clinical skills in undergraduate nurse education. Journal of Advanced Nursing, 71(2), 255–270. doi:10.1111/jan.12509.

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. doi:10.1007/s10639-021-10523-1.

Parasuraman, A., & Colby, C. L. (2015). An Updated and Streamlined Technology Readiness Index: TRI 2.0. Journal of Service Research, 18(1), 59–74. doi:10.1177/1094670514539730.

Huang, H. M., & Liaw, S. S. (2018). An analysis of learners' intentions toward virtual reality learning based on constructivist and technology acceptance approaches. The International Review of Research in Open and Distance Learning, 19(1), 91–115. doi:10.19173/irrodl.v19i1.2503.

Kuo, Y. K., Kuo, T. H., Wang, J. H., & Ho, L. A. (2022). The Antecedents of University Students' E-Learning Outcome under the COVID-19 Pandemic: Multiple Mediation Structural Path Comparison. Sustainability (Switzerland), 14(24), 16794. doi:10.3390/su142416794.

Rovai, A., Ponton, M., Wighting, M., & Baker, J. (2007, July). A comparative analysis of student motivation in traditional classroom and e-learning courses. International Journal on E-learning, 6(3), 413-432.

Mayer, R. E. (2014). Incorporating motivation into multimedia learning. Learning and Instruction, 29, 171–173. doi:10.1016/j.learninstruc.2013.04.003.

Soekamto, H., Nikolaeva, I., Abbood, A. A. A., Grachev, D., Kosov, M., Yumashev, A., Kostyrin, E., Lazareva, N., Kvitkovskaja, A., & Nikitina, N. (2022). Professional Development of Rural Teachers Based on Digital Literacy. Emerging Science Journal, 6(6), 1525–1540. doi:10.28991/ESJ-2022-06-06-019.

Mukataeva, Z., Dinmukhamedova, A., Kabieva, S., Baidalinova, B., Khamzina, S., Zekenova, L., & Aizman, R. (2022). Comparative characteristics of developing morphofunctional features of schoolchildren from different climatic and geographical regions. Journal of Pediatric Endocrinology and Metabolism, 36(2), 158–166. doi:10.1515/jpem-2022-0474.

Bernard, R. M., Abrami, P. C., Lou, Y., Borokhovski, E., Wade, A., Wozney, L., Wallet, P. A., Fiset, M., & Huang, B. (2004). How does distance education compare with classroom instruction? A meta-analysis of the empirical literature. Review of Educational Research, 74(3), 379–439. doi:10.3102/00346543074003379.

Means, B., Toyama, Y., Murphy, R., Bakia, M., & Jones, K. (2009). Evaluation of evidence-based practices in online learning: A meta-analysis and review of online learning studies. Policy and Program Studies Service, Office of Planning, Evaluating, and policy Development, U. S. Department of education, Washington, United States.

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E-Learning Adoption: Designing a Network-Based Educational and Methodological Course on "Humans and Their Health"

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E-Learning Adoption: Designing a Network-Based Educational and Methodological Course on "Humans and Their Health"

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Most Cited Articles

Digital Transformation: Opportunities and Challenges for Leaders in the Emerging Countries in Response to Covid-19 Pandemic

Impediments of Green Finance Adoption System: Linking Economy and Environment

Optical and Structural Characterization of Bi2FexNbO7 Nanoparticles for Environmental Applications

Thermal Regeneration and Reuse of Carbon and Glass Fibers from Waste Composites