Factors Influencing Online Professional Skills Training Programs for Lecturers: A Case Study of Vietnam National University, Hanoi, and its Implications on Decision Sciences

Nghiem Xuan Huy; Ngo Tien Nhat; Nguyen Thi Tuyet Anh; Luu Quoc Dat; Luu Huu Van

doi:10.47654/v27y2023i2p145-165

Authors

Nghiem Xuan Huy VNU Institute for Education Quality Assurance, Vietnam National University Author
Ngo Tien Nhat VNU Institute for Education Quality Assurance, Vietnam National University Author
Nguyen Thi Tuyet Anh VNU Institute for Education Quality Assurance, Vietnam National University Author
Luu Quoc Dat VNU University of Economics and Business, Vietnam National University Author
Luu Huu Van Academy of Policy and Development, Ministry of Planning and Investment Corresponding Author

DOI:

https://doi.org/10.47654/v27y2023i2p145-165

Keywords:

TOPSIS, the generalized fuzzy Analytic Hierarchy Process, Generalized trapezoidal fuzzy numbers, Lecturers’ professional competence

Abstract

Purpose: The application of decision science combines qualitative and quantitative frameworks to offer valuable insights into decision-making processes, spanning beyond business, computer science, public health, environmental science, economics, and finance, to include the field of education. Under the impact of the COVID-19 pandemic and digital transformation, online training has become a trend in many universities worldwide. This study aims to develop a new integrated multi-criteria decision-making model to determine the priority levels of factors impacting the effectiveness of online professional skills training programs for lecturers at the Vietnam National University, Hanoi (VNU-Hanoi).

Design/methodology/approach: A novel integrated approach has been developed, which combines the generalized fuzzy Analytic Hierarchy Process (AHP) with the fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). This approach effectively determines the priority levels of influencing factors by using the fuzzy TOPSIS method with generalized trapezoidal fuzzy numbers (TrFNs). The data for this study was collected through in-depth interviews with experts and managers at the VNU-Hanoi.

Findings: The research findings indicate that learners and training program content are the most influential factors in the effectiveness of online training courses in enhancing lecturers' professional competence at the VNU-Hanoi. Drawing on principles from Decision Science, several recommendations have been proposed for the VNU-Hanoi and its member universities and schools: (i) allocate sufficient time and provide resource support to enable lecturers' participation in training courses; (ii) create comprehensive training content for lecturers, encompassing political ideology, ethics, professional knowledge, modern pedagogical skills, and life skills; (iii) strengthen the utilization of scientific, technological, and information technology skills, along with a digital transformation in management, teaching, and learning processes, to meet the broader development needs of society. The study results also demonstrate the feasibility of the proposed model in addressing practical issues.

Originality/value: This study proposes a novel integrated generalized fuzzy AHP-TOPSIS approach to determine the priority levels of factors influencing the effectiveness of online training courses in enhancing lecturers' professional competence at the VNU-Hanoi. The study considers 21 sub-factors across five factors, including the policies of higher education institutions, training program content, learners, instructors, and technology for online training. This is new in the literature.

References

Abdullah, A. G., Shafii, M. A., Pramuditya, S., Setiadipura, T., & Anzhar, K. (2023). Multi-criteria decision making for nuclear power plant selection using fuzzy AHP: Evidence from Indonesia. Energy and AI, 14, 100263.

Abusaeed, S., Khan, S. U. R., & Mashkoor, A. (2022). A Fuzzy AHP-based approach for prioritization of cost overhead factors in agile software development. Applied Soft Computing, 109977.

Ali, W., Gohar, R., Chang, B. H., & Wong, W. K. (2022). Revisiting the impacts of globalization, renewable energy consumption, and economic growth on environmental quality in South Asia. Advances in Decision Sciences, 26(3), 1-23.

Almaiah, M. A., Alamri, M. M., & Al-Rahmi, W. M. (2019a). Analysis the effect of different factors on the development of Mobile learning applications at different stages of usage. IEEE Access, 8, 16139-16154.

Almaiah, M. A., Alamri, M. M., & Al-Rahmi, W. M. (2019b). Applying the UTAUT model to explain the students’ acceptance of mobile learning system in higher education. IEEE Access, 7, 174673-174686.

Almaiah, M. A., & Almulhem, A. (2018). A conceptual framework for determining the success factors of e-learning system implementation using Delphi technique. Journal of Theoretical and Applied Information Technology, 96(17), 5962-5976.

Appana, S. (2008). A review of benefits and limitations of online learning in the context of the student, the instructor and the tenured faculty. International Journal on E-learning, 7(1), 5-22.

Bragg, L. A., Walsh, C., & Heyeres, M. (2021). Successful design and delivery of online professional development for teachers: A systematic review of the literature. Computers & Education, 166, 104158.

Brown, J. A., & Woods, J. J. (2012). Evaluation of a multicomponent online communication professional development program for early interventionists. Journal of Early Intervention, 34(4), 222-242.

Carolan, C., Davies, C. L., Crookes, P., McGhee, S., & Roxburgh, M. (2020). COVID-19: Disruptive impacts and transformative opportunities in undergraduate nurse education. Nurse education in practice, 46, 102807.

Carrillo, C., & Flores, M. A. (2020). COVID-19 and teacher education: a literature review of online teaching and learning practices. European Journal of Teacher Education, 43(4), 466-487.

Chandna, R., Saini, S., & Kumar, S. (2021). Fuzzy AHP based performance evaluation of massive online courses provider for online learners. Materials Today: Proceedings, 46, 11103-11112.

Chang, B., & Kang, H. (2016). Challenges facing group work online. Distance Education, 37(1), 73-88.

Chang, D. Y. (1996). Applications of the extent analysis method on fuzzy AHP. European Journal of Operational Research, 95(3), 649-655.

Cole, A., Anderson, C., Bunton, T., Cherney, M., Fisher, V. C., Featherston, M., Motel, L., Nicolini, K., Peck, B., & Allen, M. (2017). Student predisposition to instructor feedback and perceptions of teaching presence predict motivation toward online courses. Online Learning Journal, 21(4), 245-262.

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.

Dumais, S. A., Rizzuto, T. E., Cleary, J., & Dowden, L. (2013). Stressors and supports for adult online learners: Comparing first-and continuing-generation college students. American Journal of Distance Education, 27(2), 100-110.

Dwivedi, Y. K., Hughes, D. L., Coombs, C., Constantiou, I., Duan, Y., Edwards, J. S., Gupta, B., Lal, B., Misra, S., Prashant, P., & Raman, R. (2020). Impact of COVID-19 pandemic on information management research and practice: Transforming education, work and life. International Journal of Information Management, 55, 102211.

Erickson, A. S. G., & Noonan, P. M. (2010). Late-career adults in online education: A rewarding experience for individuals aged 50 to 65. MERLOT Journal of Online Learning and Teaching, 6(2), 388-397.

Erulgen, A., Rjoub, H., Adalier, A., & Abualrub, A. (2022). Financial Inclusion and Bank Profitability: Evidence from Island Banking Sector. Advances in Decision Sciences, 26(4), 78-97.

Furnborough, C. (2012). Making the most of others: autonomous interdependence in adult beginner distance language learners. Distance Education, 33(1), 99-116.

García-Morales, V. J., Garrido-Moreno, A., & Martín-Rojas, R. (2021). The transformation of higher education after the COVID disruption: Emerging challenges in an online learning scenario. Frontiers in Psychology, 12, 616059.

Gerard, L. F., Varma, K., Corliss, S. B., & Linn, M. C. (2011). Professional development for technology-enhanced inquiry science. Review of Educational Research, 81(3), 408-448.

Geri, N., Winer, A., & Zaks, B. (2017). Challenging the six-minute myth of online video lectures: Can interactivity expand the attention span of learners? Online Journal of Applied Knowledge Management (OJAKM), 5(1), 101-111.

Gohar, R., Bhatty, K., Osman, M., Wong, W. K., & Chang, B. H. (2022). Oil prices and sectorial stock indices of Pakistan: Empirical evidence using bootstrap ARDL model. Advances in Decision Sciences, 26(4), 1-27.

Govindarajan, V., & Srivastava, A. (2020). What the shift to virtual learning could mean for the future of higher ed. Harvard Business Review, 31(1), 3-8.

Griffin, C. C., Dana, N. F., Pape, S. J., Algina, J., Bae, J., Prosser, S. K., & League, M. B. (2018). Prime online: Exploring teacher professional development for creating inclusive elementary mathematics classrooms. Teacher Education and Special Education, 41(2), 121-139.

Hao, N. T. N., & Wong, W. K. (2021). Does Bank Liquidity Risk Lead to Bank's Operational Efficiency? A Study in Vietnam. Advances in Decision Sciences, 4, 1-43.

Hofer, M., & Grandgenett, N. (2012). TPACK development in teacher education: A longitudinal study of preservice teachers in a secondary MA Ed. program. Journal of Research on Technology in Education, 45(1), 83-106.

Hollis, R. B., & Was, C. A. (2016). Mind wandering, control failures, and social media distractions in online learning. Learning and Instruction, 42, 104-112.

Hue, T. T., Tuan, N. A., Van, L. H., Lien, L. T., Huong, D. D., Anh, L. T., & Dat, L. Q. (2022). Prioritization of factors impacting lecturer research productivity using an improved fuzzy analytic hierarchy process approach. Sustainability, 14(10), 6134.

Hwang, C. L., & Yoon, K. (1981). Multiple Attribute Decision Making: Methods and Applications. Springer-Verlag, New York.

Jimenez-Silva, M., & Olson, K. (2012). A community of practice in teacher education: Insights and perceptions. International Journal of Teaching and Learning in Higher Education, 24(3), 335-348.

Johari, S. M., Wong, W. K., & LC, A. R. F. A. (2022). Driven Determinants to Indonesia Sharia Commercial Banks' Performance: The Important Role of Diversification Strategy. Advances in Decision Sciences, 26(2), 64-96.

Johnson, E., Morwane, R., Dada, S., Pretorius, G., & Lotriet, M. (2018). Adult learners’ perspectives on their engagement in a hybrid learning postgraduate programme. The Journal of Continuing Higher Education, 66(2), 88-105.

Joo, K. P. (2014). A cultural-historical activity theory investigation of contradictions in open and distance higher education among alienated adult learners in Korea National Open University. International Review of Research in Open and Distributed Learning, 15(1), 41-61.

Julian, J. F. E., & Ruiz, F. B. (2020). Continuing professional development (CPD) among educators in selected Colleges of Nursing: Perceived importance, impact, and challenges. Enfermería Clínica, 30, 60-64.

Kara, M., Erdogdu, F., Kokoç, M., & Cagiltay, K. (2019). Challenges faced by adult learners in online distance education: A literature review. Open Praxis, 11(1), 5-22.

Kien, P. V., Wong, W. K., Moslehpour, M., & Musyoki, D. (2018). Simultaneous Adaptation of AHP and Fuzzy AHP to Evaluate Outsourcing Services in East and Southeast Asia. Journal of Testing and Evaluation, 1-27. https://doi. org/10.1520/JTE20170420. ISSN, 0090-3973.

Knowles, M. S. (1996). Adult Learning. In Robert L. Craig (Ed.), The ASTD Training and Development Handbook (pp. 253-264). NY: McGraw-Hill.

Knowles, M. S., Holton, E. F., & Swanson, R. A. (2015). The Adult Learner. The Definitive Classic in Adult Education and Human Resource Development (8th ed.). Oxon: Routlege.

Kontos, G. (2015). Practical teaching aids for online classes. Journal of Educational Technology Systems, 44(1), 36-52.

Lindeman, E. (2015). The meaning of adult education. Andesite Press.

Marinoni, G., Van’t Land, H., & Jensen, T. (2020). The impact of Covid-19 on higher education around the world. IAU Global Survey Report, 23, 1-17.

Marquez, B., VinCent, C., Marquez, J., Pennefather, J., Smolkowski, K., & Sprague, J. (2016). Opportunities and challenges in training elementary school teachers in classroom management: Initial results from classroom management in action, an online professional development program. Journal of Technology and Teacher Education, 24(1), 87-109.

Mendieta-Aragon, A., & Garín-Muñoz, T. (2020). Foreign Tourism in Andalusia: A Dynamic Panel Data Analysis. Advances in Decision Sciences, 24(3), 1-32.

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, 100012.

Mtebe, J. S., & Raisamo, R. (2014). Investigating perceived barriers to the use of open educational resources in higher education in Tanzania. International Review of Research in Open and Distributed Learning, 15(2), 43-66.

Naveed, M., Sindhu, M. I., Ali, S., & Wong, W. K. (2023). To Invest or Not to Invest? Determinants of Low Stock Market Participation: Qualitative Perspective from Pakistan Stock Exchange. Advances in Decision Sciences, 27(1), 113-171.

Ninlawan, G. (2015). Factors which affect teachers’ professional development in teaching innovation and educational technology in the 21st century under the bureau of special education, office of the basic education commission. Procedia-Social and Behavioral Sciences, 197, 1732-1735.

Noman, M., Maydybura, A., Channa, K. A., Wong, W. K., & Chang, B. H. (2023). Impact of cashless bank payments on economic growth: Evidence from G7 countries. Advances in Decision Sciences, 27(1), 0_1-20.

Ozudogru, F., & Hismanoglu, M. (2016). Views of freshmen students on foreign language courses delivered via e-learning. Turkish Online Journal of Distance Education, 17(1), 31-47.

Park, J. H., & Choi, H. J. (2009). Factors influencing adult learners' decision to drop out or persist in online learning. Journal of Educational Technology & Society, 12(4), 207-217.

Pierrakeas, C., Xeno, M., Panagiotakopoulos, C., & Vergidis, D. (2004). A comparative study of dropout rates and causes for two different distance education courses. The International Review of Research in Open and Distributed Learning, 5(2), 1-15.

Quynh, V. T. N. (2023). An Integrated Dynamic Generalized Trapezoidal Fuzzy AHPTOPSIS Approach for Evaluating Sustainable Performance of Bank. Advances in Decision Sciences, 27(1), 0_1-17.

Rao, K., & Giuli, C. (2010). Reaching remote learners: Successes and challenges for students in an online graduate degree program in the Pacific Islands. The International Review of Research in Open and Distributed Learning, 11(1), 141-160.

Saaty, R. W. (1987). The analytic hierarchy process - what it is and how it is used. Mathematical Modelling, 9(3-5), 161-176.

Saleem, F., AlNasrallah, W., Malik, M. I., & Rehman, S. U. (2022). Factors affecting the quality of online learning during COVID-19: Evidence from a developing economy. In Frontiers in Education (Vol. 7). Frontiers Media SA.

Selwyn, N. (2011). ‘Finding an appropriate fit for me’: Examining the (in) flexibilities of international distance learning. International Journal of Lifelong Education, 30(3), 367-383.

Shi, J. L., & Lai, W. H. (2023). Fuzzy AHP approach to evaluate incentive factors of high-tech talent agglomeration. Expert Systems with Applications, 212, 118652.

Singh, A., & Prasher, A. (2019). Measuring healthcare service quality from patients’ perspective: using Fuzzy AHP application. Total Quality Management & Business Excellence, 30(3-4), 284-300.

Tudor, S. L., Stan, M. M., & Paisi-Lazarescu, M. (2015). Integration of the e–learning in teaching/learning courses at preschool and primary pedagogical teacher. eLearning & Software for Education, (2), 340-345

Van Nuland, S., Mandzuk, D., Tucker Petrick, K., & Cooper, T. (2020). COVID-19 and its effects on teacher education in Ontario: a complex adaptive systems perspective. Journal of Education for Teaching, 46(4), 442-451.

Vo, A. T., Van, L. T. H., Vo, D. H., & McAleer, M. (2019). Financial inclusion and macroeconomic stability in emerging and frontier markets. Annals of Financial Economics, 14(02), 1950008.

Wang, Y., Xu, L., & Solangi, Y. A. (2020). Strategic renewable energy resources selection for Pakistan: Based on SWOT-Fuzzy AHP approach. Sustainable Cities and Society, 52, 101861.

Wang, Y. M., Luo, Y., & Hua, Z. (2008). On the extent analysis method for fuzzy AHP and its applications. European Journal of Operational Research, 186(2), 735-747.

Willging, P. A., & Johnson, S. D. (2009). Factors that influence students' decision to drop out of online courses. Journal of Asynchronous Learning Networks, 13(3), 115-127.

Yasmin. (2013). Application of the classification tree model in predicting learner dropout behaviour in open and distance learning. Distance Education, 34(2), 218-231.