Evaluating the Effects of Online Training on Employee Self-efficacy. A Dilemma from the Banking Industry in Ghana

Authors

  • Fan Mingyue
  • Anastasia Krampah-Nkoom Jiangsu University Business Administration
  • Blessing Dwumah Manu
  • Daniel Oduro

DOI:

https://doi.org/10.18533/journal.v9i2.1832

Keywords:

Elements of online training, Self-efficacy, banking industry, logistic regression

Abstract

Online training has become an essential instrument and the alliance of efficacy. There is a comprehensive and constant discussion in our banking industry about the impact of effective online training on self-efficacy.   This study, therefore, sought to analyze the effects of online training on the probability (likelihood) to enhance self-efficacy in the banking system in Ghana. The study used Individual Employee Perspective, Technology Perspective, Instructor Perspective, Managers Support and training environment as variables measuring the elements of online training.

In this study, the descriptive research design was adopted and data of 510 respondents were collected through a questionnaire survey for analysis. With the application of logistic regression analysis as the key statistical tool, the study centered on Wald test values, p-values and odds ratio values identified used Individual Perspective, Technology Perspective, Instructor Perspective and Managers Support as elements of online training that significantly contributes to the likelihood of enhancing employee self-efficacy. The study recommended that elements of online training with the exception of instructor’s perspective should be intensified in various banking industry so as to enhance employee self-efficacy.

References

Appelbaum, S. H., & Hare, A. (1996). Self-efficacy as a mediator of goal setting and performance: Some human resource applications. Journal of Managerial Psychology, 11(3), 33-47.

Almarashdeh, I. (2016). Sharing instructors experience of learning management system: A technology perspective of user satisfaction in distance learning course. Computers in Human Behavior, 63, 249-255. doi:https://doi.org/10.1016/j.chb.2016.05.013

Almarashdeh, I., & Alsmadi, M. (2016). Investigating the acceptance of technology in distance learning program. Paper presented at the 2016 International Conference on Information Science and Communications Technologies (ICISCT).

Athar, R., & Shah, F. M. (2015). Impact of training on employee performance (banking sector Karachi). IOSR Journal of Business and Management, 17(11), 58-67.

Bandura, A. (2015). Self-efficacy mechanism in human agency. American Psychologist, 37(2), 122.

Bandura, A. (2001). Social cognitive theory: An agentic perspective. Annual Review of Psychology, 52(1), 1-26.

Bandura, A., & Locke, E. A. (2003). Negative self-efficacy and goal effects revisited. Journal of applied psychology, 88(1), 87.

Barbaranelli, C., Paciello, M., Biagioli, V., Fida, R., & Tramontano, C. (2019). Positivity and behaviour: the mediating role of self-efficacy in organisational and educational settings. Journal of Happiness Studies, 20(3), 707-727.

Bajaj, R., & Sharma, V. (2018). Smart Education with artificial intelligence-based determination of learning styles. Procedia Computer Science, 132, 834-842.

doi:https://doi.org/10.1016/j.procs.2018.05.095

Bawa, P. (2016). Retention in online courses: Exploring issues and solutions—A literature review. SAGE Open, 6(1), 2158244015621777.

Bloom, N., Lemos, R., Sadun, R., Scur, D. & Reenen, J. V. (2014). The new empirical economics of management National Bureau of Economic Research Working Paper Series, No. 20102.

Britt, T. W., Shen, W., Sinclair, R. R., Grossman, M. R., & Klieger, D. M. (2016). How much do we really know about employee resilience? Industrial and Organizational Psychology, 9(2), 378-404.

Cascio, W. F. (2019). Training trends: Macro, micro, and policy issues. Human Resource Management Review, 29(2), 284-297.

Chang, Y.-H., Chen, Y.-Y., Chen, N.-S., Lu, Y.-T., & Fang, R.-J. (2016). Yet another adaptive learning management system based on Felder and Silverman's learning styles and Mashup. Eurasia Journal of Mathematics, Science & Technology Education, 12(5).

Chang, C.-S., Liu, E. Z.-F., Sung, H.-Y., Lin, C.-H., Chen, N.-S., & Cheng, S.-S. (2014). Effects of online college student’s Internet self-efficacy on learning motivation and performance. Innovations in education and teaching international, 51(4), 366-377.

Cokley, K. (2015). A confirmatory factor analysis of the Academic Motivation Scale with black college students. Measurement and Evaluation in Counseling and Development, 48(2), 124-139.

Chen, G., Gully, S. M., & Eden, D. (2001). Validation of a new general self-efficacy scale. Organizational Research Methods, 4(1), 62-83

DeCenzo, D. A., & Robinson, S. P. (2003). Human resource management. (7th ed.). New York: John Willy & Sons Inc.

Debnath, R. M. (2003). Bank and legal environment (1st ed.). Dhaka: Nabajuga Prokashani.

De Medio, C., Limongelli, C., Sciarrone, F., & Temperini, M. (2020). MoodleREC: A recommendation system for creating courses using the moodle e-learning platform. Computers in Human Behavior, 104, 106168. doi:https://doi.org/10.1016/j.chb.2019.106168

Emery, S., Cooper, L. P. (2003). A research agenda to reduce risk in new product development through knowledge management: a practitioner perspective. Journal of Engineering and Technology Management, 20(1-2), 117-140.

Francescucci, A., & Rohani, L. (2019). Exclusively synchronous online (VIRI) learning: The impact on student performance and engagement outcomes. Journal of marketing Education, 41(1), 60-69.

Gasparetti, F., De Medio, C., Limongelli, C., Sciarrone, F., & Temperini, M. (2018). Prerequisites between learning objects: Automatic extraction based on a machine learning approach. Telematics and Informatics, 35(3), 595-610.

Geraci, M. (2016). Revisiting" Designing Web-based Instruction: A Research Review on Color, Typography, Layout, and Screen Density".

Giran, H., Amin, A., & Halim, B. A. (2014). The impact of self-efficacy towards training motivation at Kolej Poly-Tech MARA Kuantan, Malaysia. Asian Social Science, 10(19), 69.

Griffin, R. W. (2003). Management (5th ed.). New York: Houghton Mifflin Company.

Goldberg, B., Davis, F., Riley, J. M., & Boyce, M. W. (2017). Adaptive training across simulations in support of a crawl-walk-run model of interaction. Paper presented at the International Conference on Augmented Cognition.

Goldstein, I. L. (2001). Training in organizations: Needs assessment, development, and evaluation. (3rd ed.). Pacific Grove, CA: Brooks/Cole.

Huaisheng, Z., Manu, B. D., Mensah, I. A., Mingyue, F., & Oduro, D. (2019). Exploring the Effect of School Management Functions on Student’s Academic Performance: A Dilemma from Public Senior High Schools in Ghana. Journal of Arts and Humanities, 8(6), 33-45.

Huang, E. Y., Lin, S. W., & Huang, T. K. (2012). What type of learning style leads to online participation in the mixed-mode e-learning environment? A study of software usage instruction. Computers & Education, 58(1), 338-349. doi:https://doi.org/10.1016/j.compedu.2011.08.003

Jafari Navimipour, N., & Zareie, B. (2015). A model for assessing the impact of e-learning systems on employees’ satisfaction. Computers in Human Behavior, 53, 475-485.

doi:https://doi.org/10.1016/j.chb.2015.07.026

Jones, B. D., Paretti, M. C., Hein, S. F., & Knott, T. W. (2010). An analysis of motivation constructs with first-year engineering students: Relationships among expectancies, values, achievement and career plans. Journal of Engineering Education, 99(4), 319-336.

Kraut, R., Chandler, T., and Hertenstein, K. (2016). The Interplay of Teacher Training, Access to Resources, Years of Experience and Professional Development in Tertiary ESL Reading Teachers’ Perceived Self-Efficacy. Gist Education and Learning Research Journal. 132-151

Kraiger, K., Ford, J. K., & Salas, E. (1993). Application of cognitive, skill-based, and affective theories of learning outcomes to new methods of training evaluation. Journal of applied psychology, 78(2), 311.

Kurila, J., Lazuras, L., & Ketikidis, P. H. (2016). Message framing and acceptance of branchless banking technology. Electronic Commerce Research and Applications, 17, 12-18.

Lim, H., Lee, S.-G., & Nam, K. (2007). Validating E-learning factors affecting training effectiveness. International Journal of Information Management, 27(1), 22-35.

Manu, B. D., Zhang, H., Oduro, D., Krampah-Nkoom, A., Mensah, I. A., Anaba, O. A., & Isaac, A. (2019). School Board Efficiency in Financial Management and Human Resource in Public Senior High Schools: An Evidence from Ashanti Region, Ghana. International Journal of Social Science Studies, 8(1), 79-89.

Manu, B. D., & Huaisheng, Z. (2017) A Fitted Logistic Regression Analysis of Factors Influencing Teachers’ Learning and Professional Development. Evidence from Selected Schools in Ghana.

Mathis, R. L., & Jackson, J. H. (2004). Human resource management (10th ed.). Mason: South-Western.

McGehee, M., & Thayer, P. W. (1999). Training in business and industry. New York: John Wiley & Sons.

Mohammadi, H. (2015). Investigating users’ perspectives on e-learning: An integration of TAM and IS success model. Computers in Human Behavior, 45, 359-37

Navimipour, N. J., & Zareie, B. (2015). A model for assessing the impact of e-learning systems on employees’ satisfaction. Computers in Human Behavior, 53, 475-485.

Newman, A., Herman, H. M., Schwarz, G., & Nielsen, I. (2018). The effects of employees' creative self-efficacy on innovative behavior: The role of entrepreneurial leadership. Journal of Business Research, 89, 1-9.

Nunnally, Jum C, & Bernstein, Ira H. (2014). Psychometric theory

Orodho, J.A. (2012). Elements of Education and Social Science Research Methods. Bureau of Educational Research. Institute of Research and Development. Ph.D Dissertation, Kenyatta University, Nairobi Kenya

Punch, K. F. (1998). Introduction to Social Research: Quantitative and Qualitative Approaches (1st ed.). London, Thousand Oaks California, New Delhi: SAGE Publications.

Rothwell, W. J. (2002). Beyond training and development: State-of-the-art strategies for enhancing performance. New York: AMACOM.

Saleem, N. E., Al-Saqri, M. N., & Ahmad, S. E. (2016). Acceptance of Moodle as a teaching/learning tool by the faculty of the department of information studies at Sultan Qaboos University, Oman based on UTAUT. International Journal of Knowledge Content Development & Technology, 6(2), 5-27

Safeena, R., Date, H., Kammani, A., & Hundewale, N. (2012). Technology adoption and Indian consumers: study on mobile banking. International Journal of Computer Theory and Engineering, 4(6), 1020.

Sherer, M., & Carol, H. A. (2016). Construct validation of the self-efficacy scale. Psychological Reports, 53(3), 899-902.

Strother, J. B. (2002). An assessment of the effectiveness of e-learning in corporate training programs. The International Review of Research in Open and Distributed Learning, 3(1).

Sun, S. Y. (2014). Learner perspectives on fully online language learning. Distance education, 35(1), 18-42.

Sriprasertpap, K. (2015). The development of online training model for Srinakharinwirot university in Thailand. Procedia-Social and Behavioral Sciences, 197, 1913-1917.

Shen, D., Cho, M. H., Tsai, C. L., & Marra, R. (2013). Unpacking online learning experiences: Online learning self-efficacy and learning satisfaction. The Internet and Higher Education, 19, 10-17.

Sulehria, A. Q. K., Abrar, J. O. I. N. D. A., Shah, A. H., & Malik, M. A. (2015). Effect of algae and other food types on population growth of rotifers. Biologia, 61(2), 263-270.

Imonson, M., Zvacek, S. M., & Smaldino, S. (2019). Teaching and Learning at a Distance: Foundations of Distance Education 7th Edition: IAP

Sitzmann, T., & Weinhardt, J. M. (2019). Advancing training for the 21st century. Human Resource Management Review, 29(2), 137-139. doi:https://doi.org/10.1016/j.hrmr.2018.07.005

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2020-02-14

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