STUDENTS'S INTENTION TO USE EMOTION-AWARE VIRTUAL LEARNING ENVIRONMENT: DOES A LECTURER'S INTERACTION MAKE A DIFFERENCE?
DOI:
https://doi.org/10.32890/mjli2021.18.1.8Keywords:
Emotion-Aware VLE, Technology Readiness Index (TRI), Attitude, Intention to Use, Lecturer Interaction, online learning, Smart PLS, Higher Education.Abstract
Purpose: This study explored students’ perspective of using emotion-aware Vertual Learning Environment (VLE) in Malaysia’s higher education institutions. The purpose is to investigate the relationships among dimensions of Technology Readiness Index (TRI), attitude, intention to use VLE, and lecturer interaction. The outcomes concerned the emotions involved in the educational process of Malaysia’s higher education institutions.
Methodology: Quantitative data were collected via an online survey from 260 students. An empirical analysis was then conducted using structural equation modelling (Smart PLS) in two phases: (1) examining the direct effect of students’ attitude on VLE adoption intention and (2) examining the indirect effect of constructs using lecturer interaction as a mediator.
Findings: The findings revealed a significant mediating role of lecturer interaction on the relationship between attitude and intention to use VLE across the student cohort. Inhibitors, such as insecurity and discomfort, were less significant in affecting students’ attitude towards emotion-aware VLE. The results indicate that students are motivated to use VLE when lecturers understand their emotions and react accordingly.
Significance: This is one of the studies pertaining to emotions in VLE and lecturer interaction in higher education institutions. The results facilitate an understanding of the pedagogical role of lecturer interaction as a practical learning motivation. It is of particular interest to curriculum and e-learning stakeholders looking to improve students’ interactions with the VLE systems. Apart from extending the current literature, this study has significant practical implications for education management in higher learning institutions.
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References
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Alotaibi, R., Sandhu, K., & Houghton, L. (2014). A Study of Service Users’ Attitudes towards E-Government Initiatives in the Kingdom Of Saudi Arabia. IJCSIT) International Journal of Computer Science and Information Technologies, 5(6), 6892-6901.
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Anderson, J., C, & Gerbing, D., W. (1992). Assumptions and Comparative Strengths of the Two-Step Approach: Comment on Fornell and Yi. Sociological Methods & Research, 20(3), 321–333.
Arguedas, Daradoumis, & Xhafa. (2016). Analyzing the effects of emotion management on time and selfmanagement in computer-based learning. Computers in Human Behavior(63), 517-529.
Artino Jr, A., R. (2012). Emotions in online learning environments: Introduction to the special issue. Internet and Higher Education( 137–140), 137–140.
Astuti, N. C., & Nasution, R. A. (2014). Technology readiness and e-commerce adoption among entrepreneurs of SMEs in Bandung City, Indonesia. Gadjah Mada International Journal of Business, 16(1), 69-88.
Baron, R., M, & Kenny, D., A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic and statistical considerations. J. Pers. Soc. Psychol, 51, 1173–1182.
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Bhattacherjee, A. (2001a). An empirical analysis of the antecedents of electronic commerce service continuance. Decision Support Systems, 32(2), 201-214.
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Boon-itt, S. (2015). Managing self-service technology service quality to enhance. International Journal of Quality and Service Sciences Managing, 7(4), 373-391. doi:https://doi.org/10.1108/IJQSS-01-2015-0013
Buenaventura-Vera, G. (2017). The impact of leader self-efficacy on the characteristics of work teams. Intangible Capital, 13(4), 824-849. doi:https://doi.org/10.3926/ic.938
Buyle, R., Compernolle, M., Van, Vlassenroot, E., Vanlishout, Z., Mechant, P., & Mannens, E. (2018). “Technology Readiness and Acceptance Model†as a Predictor for the Use Intention of Data Standards in Smart Cities. Media and Communication, 6(4), 127–139.
Caballé, S. (2015). Towards a Multi-modal Emotion-awareness e-Learning System. Paper presented at the International Conference on Intelligent Networking and Collaborative Systems.
Caison, A. L., Bulman, D., Pai, S., & Neville, D. (2008). Exploring the technology readiness of nursing and medical students at a Canadian University. Journal of interprofessional care, 22(3), 283-294.
Chatzoglou, P., D, Sarigiannidis, L., Vraimaki, E., & Diamantidis, A. (2009). Investigating Greek employees’ intention to use web-based training. Computers & Education(53), 877-889.
Chen, G., Wang, F., & Zhang, C. (2009). Collaborative filtering using orthogonal nonnegative matrix tri-factorization. Information Processing & Management, 45(3), 368-379.
Claudy, M., C, Peterson, M., & O’Driscoll, A. (2013). Understanding the Attitude-Behavior Gap for Renewable Energy Systems Using Behavioral Reasoning Theory. Journal of Macromarketing, 33(4), 273-287. doi:10.1177/0276146713481605
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). London: Routledge.
Creswell, J. W. (2013). Research design: Qualitative, quantitative, and mixed methods approaches: Sage publications.
Dahlan, N., Ramayah, T., & Mei, L. L. (2002). Readiness to adopt data mining technologies: an exploratory study of telecommunication employees in Malaysia. Paper presented at the International Conference on Practical Aspects of Knowledge Management.
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.
Demet, K., Cigdem, A., G, & Fethi, C. (2011). Factors affecting the intention to use a web-based learning system among blue-collar workers in the automotive industry. Computers in Human Behavior(27), 343-354.
Dorasamy, M., Marimuthu, M., Jayabalan, J., Raman, M., & Kaliannan, M. (2010). Critical factors in outsourcing of accounting functions in Malaysian small medium-sized enterprises (SMEs). Kajian Malaysia: Journal of Malaysian Studies, 28(2).
El-Kasheir, D., Ashour, A. S., & Yacout, O. M. (2009). Factors affecting continued usage of internet banking among Egyptian customers. Communications of the IBIMA, 9, 252-263.
Endratno, H. (2018). Technology Readiness Model (Trm) Dan Technology Acceptance Model (Tam) Dalam Memprediksi Niat Individu Dalam Menggunakan E-Learning. Paper presented at the Conference In Business, Accounting, And Management (CBAM).
Erdog'mus, Nihat, & Esen, M. (2011). An Investigation of the Effects of Technology Readiness on Technology Acceptance in e-HRM. Procedia Social and Behavioral Sciences, 24, 487–495.
Feidakis. (2016). A review of Emotion-Aware systems for E-learning in Virtual Environments. In Formative Assessment, Learning Data Analytics and Gamification (pp. 217-241): Elsevier.
Feidakis, Daradoumis, T., Caballé, S., & Conesa, J. (2014). Embedding Emotion Awareness into E-Learning Environments. iJET, 9(7), 39-46.
Feidakis, M., Daradoumis, T., & Caballé, S. (2011). Endowing e-Learning Systems with Emotion Awareness. Paper presented at the 2011 Third International Conference on Intelligent Networking and Collaborative Systems.
Fornell, & Bookstein. (1982). Two structural equation models: LISREL and PLS applied to consumer exit-voice theory. Journal of marketing research, 440-452.
Fornell, & Cha. (1994). Partial Least Squares. Advanced Methods of Marketing Research, 407 52-78.
Fornell, & Larcker. (1981a). Evaluating structural equation models with unobservable variables and measurement error. J. Marketing Res, 18(1), 39–50.
Fornell, & Larcker. (1981b). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of marketing research, 382-388.
Godoe, P., & Johansen, T., S. (2012). Understanding adoption of new technologies: Technology readiness and technology acceptance as an integrated concept. Journal of European Psychology Students(3), 38-52.
Gómez-DÃaz, M., Delgado-Gómez, M., Soledad, & Gómez-Sánchez, R. (2017). Education, emotions and health: Emotional education in Nursing. Procedia - Social and Behavioral Sciences(237), 492 – 498.
Guhr, N., Loi, T., Wiegard, R., & Breitner, M. H. (2013). Technology Readiness in Customers' Perception and Acceptance of M (obile)-Payment: An Empirical Study in Finland, Germany, the USA and Japan. Paper presented at the Wirtschaftsinformatik.
Gunawan, H., Sinaga, B., Langgu, & WP, S., Purnomo. (2019). Assessment of the Readiness of Micro, Small and Medium Enterprises in Using E-Money Using the Unified Theory of Acceptance and Use of Technology (UTAUT) Method. Procedia Computer Science(161), 316–323. doi:10.1016/j.procs.2019.11.129
Hair, Hult, Ringle, & Sarstedt. (2017). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd ed.). Thousand Oaks: Sage.
Hallikainen, H., & Laukkanen, T. (2016). How technology readiness explains acceptance and satisfaction of digital services in b2b healthcare sector? Paper presented at the PACIS 2016 Proceedings.
Harley, Lajoie, S., Frasson, C., & Hall, N. (2015). An Integrated Emotion-Aware Framework for Intelligent Tutoring Systems. In C. C. e. al (Ed.), AIED 2015, LNAI 9112 (pp. 616–619). Switzerland: Springer International Publishing.
Harley, J., Matthew. (2015). Measuring Emotions: A Survey of Cutting-Edge Methodologies Used in Computer-Based Learning Environment Research. In S. T. M. Gartmeier (Ed.), Emotions,Technology, Design, and Learning (pp. 89-114). London, UK: Academic Press, Elsevier.
Hayes, B., E, Perander, J., Smecko, T., & Trask, J. (1998). Measuring perceptions of workplace safety: Development and validation of the work safety scale. Journal of Safety Research, 29(3), 145-161.
Hayes, R., & Carr, C. (2015). Does Being Social Matter? Effects of Enabled Commenting on Credibility and Brand Attitude in Social Media. Journal of Promotion Management, 21, 371–390.
Hernández-Amorós, M., J, & Urrea-Solano, M., E. (2017). Working with emotions in the classroom: Future teachers’ attitudes and education. Procedia - Social and Behavioral Sciences(237), 511 – 519.
Hinkin, T., R, Tracey, J., B, & Enz, C., A. (1997). Scale construction: Developing reliable and valid measurement instruments. Journal of Hospitality & Tourism Research, 21(1), 100-120.
Hong, & Cha, H. (2013). The mediating role of consumer trust in an online merchant in predicting purchase intention. International
Ahmed, A., Abdulahi, Zakaria, N. H., & Elmi, A., Hussein. (2012). An Evaluation of Virtual Learning Environment Readiness in Higher Education Institutions (HEIs). Journal of Information Systems Research and Innovation, 86-94.
Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human decision processes, 50(2), 179-211.
Al-Hujran, O., Al-Debei, M. M., Chatfield, A., & Migdadi, M. (2015). The imperative of influencing citizen attitude toward e-government adoption and use. Computers in Human Behavior, 53, 189-203.
Alateyah, S., Crowder, R. M., & Wills, G. B. (2013). Factors affecting the citizen’s intention to adopt e-government in Saudi Arabia. International Journal of Social, Human Science and Engineering, 7(9), 80-85.
Alenezi, A., R, Abdul Karim, A., M, & Veloo, A. (2010). An empirical investigation into the role of enjoyment, computer anxiety, computer self-efficacy and Internet experience in influencing the students‘ intention to use e-learning: A case study from Saudi Arabian governmental universities. The Turkish Online Journal of Educational Technology, 9(4), 22-34.
Alharbi, N. S. S. (2016). The role of security and its antecedents in e-government adoption. University of Plymouth,
Almarabeh, T. (2014). Students’ Perceptions of E-Learning at the University of Jordan. iJET, 9(3), 31-35.
Alotaibi, R., Sandhu, K., & Houghton, L. (2014). A Study of Service Users’ Attitudes towards E-Government Initiatives in the Kingdom Of Saudi Arabia. IJCSIT) International Journal of Computer Science and Information Technologies, 5(6), 6892-6901.
Alzahrani, Alharthi, a., Alassafi, m., Albugmi, a., Walters, R., & Wills, G., B. (2018). A framework for gamified E-learning systems Acceptance in Saudi Arabian universities: gamified E-learning systems. International Journal of Advances in Electronics and Computer Science, 5(4), 33-37.
Ambali, A. R. (2009). E-government policy: Ground issues in e-filing system. European Journal of Social Sciences, 11(2), 249-266.
Anderson, J., C, & Gerbing, D., W. (1992). Assumptions and Comparative Strengths of the Two-Step Approach: Comment on Fornell and Yi. Sociological Methods & Research, 20(3), 321–333.
Arguedas, Daradoumis, & Xhafa. (2016). Analyzing the effects of emotion management on time and selfmanagement in computer-based learning. Computers in Human Behavior(63), 517-529.
Artino Jr, A., R. (2012). Emotions in online learning environments: Introduction to the special issue. Internet and Higher Education( 137–140), 137–140.
Astuti, N. C., & Nasution, R. A. (2014). Technology readiness and e-commerce adoption among entrepreneurs of SMEs in Bandung City, Indonesia. Gadjah Mada International Journal of Business, 16(1), 69-88.
Baron, R., M, & Kenny, D., A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic and statistical considerations. J. Pers. Soc. Psychol, 51, 1173–1182.
Berdykhanova, D., Dehghantanha, A., & Hariraj, K. (2010). Trust challenges and issues of e-government: E-tax prospective. Paper presented at the Information Technology (ITSim), 2010 International Symposium in.
Bessadok, A. (2000). Classification of Student's Belief based on their Technology Readiness for an E-learning System.
Bhattacherjee, A. (2001a). An empirical analysis of the antecedents of electronic commerce service continuance. Decision Support Systems, 32(2), 201-214.
Bhattacherjee, A. (2001b). Understanding information systems continuance. An expectation-confirmation model. MIS Quarterly, 25(3), 351-370.
Boon-itt, S. (2015). Managing self-service technology service quality to enhance. International Journal of Quality and Service Sciences Managing, 7(4), 373-391. doi:https://doi.org/10.1108/IJQSS-01-2015-0013
Buenaventura-Vera, G. (2017). The impact of leader self-efficacy on the characteristics of work teams. Intangible Capital, 13(4), 824-849. doi:https://doi.org/10.3926/ic.938
Buyle, R., Compernolle, M., Van, Vlassenroot, E., Vanlishout, Z., Mechant, P., & Mannens, E. (2018). “Technology Readiness and Acceptance Model†as a Predictor for the Use Intention of Data Standards in Smart Cities. Media and Communication, 6(4), 127–139.
Caballé, S. (2015). Towards a Multi-modal Emotion-awareness e-Learning System. Paper presented at the International Conference on Intelligent Networking and Collaborative Systems.
Caison, A. L., Bulman, D., Pai, S., & Neville, D. (2008). Exploring the technology readiness of nursing and medical students at a Canadian University. Journal of interprofessional care, 22(3), 283-294.
Chatzoglou, P., D, Sarigiannidis, L., Vraimaki, E., & Diamantidis, A. (2009). Investigating Greek employees’ intention to use web-based training. Computers & Education(53), 877-889.
Chen, G., Wang, F., & Zhang, C. (2009). Collaborative filtering using orthogonal nonnegative matrix tri-factorization. Information Processing & Management, 45(3), 368-379.
Claudy, M., C, Peterson, M., & O’Driscoll, A. (2013). Understanding the Attitude-Behavior Gap for Renewable Energy Systems Using Behavioral Reasoning Theory. Journal of Macromarketing, 33(4), 273-287. doi:10.1177/0276146713481605
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). London: Routledge.
Creswell, J. W. (2013). Research design: Qualitative, quantitative, and mixed methods approaches: Sage publications.
Dahlan, N., Ramayah, T., & Mei, L. L. (2002). Readiness to adopt data mining technologies: an exploratory study of telecommunication employees in Malaysia. Paper presented at the International Conference on Practical Aspects of Knowledge Management.
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.
Demet, K., Cigdem, A., G, & Fethi, C. (2011). Factors affecting the intention to use a web-based learning system among blue-collar workers in the automotive industry. Computers in Human Behavior(27), 343-354.
Dorasamy, M., Marimuthu, M., Jayabalan, J., Raman, M., & Kaliannan, M. (2010). Critical factors in outsourcing of accounting functions in Malaysian small medium-sized enterprises (SMEs). Kajian Malaysia: Journal of Malaysian Studies, 28(2).
El-Kasheir, D., Ashour, A. S., & Yacout, O. M. (2009). Factors affecting continued usage of internet banking among Egyptian customers. Communications of the IBIMA, 9, 252-263.
Endratno, H. (2018). Technology Readiness Model (Trm) Dan Technology Acceptance Model (Tam) Dalam Memprediksi Niat Individu Dalam Menggunakan E-Learning. Paper presented at the Conference In Business, Accounting, And Management (CBAM).
Erdog'mus, Nihat, & Esen, M. (2011). An Investigation of the Effects of Technology Readiness on Technology Acceptance in e-HRM. Procedia Social and Behavioral Sciences, 24, 487–495.
Feidakis. (2016). A review of Emotion-Aware systems for E-learning in Virtual Environments. In Formative Assessment, Learning Data Analytics and Gamification (pp. 217-241): Elsevier.
Feidakis, Daradoumis, T., Caballé, S., & Conesa, J. (2014). Embedding Emotion Awareness into E-Learning Environments. iJET, 9(7), 39-46.
Feidakis, M., Daradoumis, T., & Caballé, S. (2011). Endowing e-Learning Systems with Emotion Awareness. Paper presented at the 2011 Third International Conference on Intelligent Networking and Collaborative Systems.
Fornell, & Bookstein. (1982). Two structural equation models: LISREL and PLS applied to consumer exit-voice theory. Journal of marketing research, 440-452.
Fornell, & Cha. (1994). Partial Least Squares. Advanced Methods of Marketing Research, 407 52-78.
Fornell, & Larcker. (1981a). Evaluating structural equation models with unobservable variables and measurement error. J. Marketing Res, 18(1), 39–50.
Fornell, & Larcker. (1981b). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of marketing research, 382-388.
Godoe, P., & Johansen, T., S. (2012). Understanding adoption of new technologies: Technology readiness and technology acceptance as an integrated concept. Journal of European Psychology Students(3), 38-52.
Gómez-DÃaz, M., Delgado-Gómez, M., Soledad, & Gómez-Sánchez, R. (2017). Education, emotions and health: Emotional education in Nursing. Procedia - Social and Behavioral Sciences(237), 492 – 498.
Guhr, N., Loi, T., Wiegard, R., & Breitner, M. H. (2013). Technology Readiness in Customers' Perception and Acceptance of M (obile)-Payment: An Empirical Study in Finland, Germany, the USA and Japan. Paper presented at the Wirtschaftsinformatik.
Gunawan, H., Sinaga, B., Langgu, & WP, S., Purnomo. (2019). Assessment of the Readiness of Micro, Small and Medium Enterprises in Using E-Money Using the Unified Theory of Acceptance and Use of Technology (UTAUT) Method. Procedia Computer Science(161), 316–323. doi:10.1016/j.procs.2019.11.129
Hair, Hult, Ringle, & Sarstedt. (2017). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd ed.). Thousand Oaks: Sage.
Hallikainen, H., & Laukkanen, T. (2016). How technology readiness explains acceptance and satisfaction of digital services in b2b healthcare sector? Paper presented at the PACIS 2016 Proceedings.
Harley, Lajoie, S., Frasson, C., & Hall, N. (2015). An Integrated Emotion-Aware Framework for Intelligent Tutoring Systems. In C. C. e. al (Ed.), AIED 2015, LNAI 9112 (pp. 616–619). Switzerland: Springer International Publishing.
Harley, J., Matthew. (2015). Measuring Emotions: A Survey of Cutting-Edge Methodologies Used in Computer-Based Learning Environment Research. In S. T. M. Gartmeier (Ed.), Emotions,Technology, Design, and Learning (pp. 89-114). London, UK: Academic Press, Elsevier.
Hayes, B., E, Perander, J., Smecko, T., & Trask, J. (1998). Measuring perceptions of workplace safety: Development and validation of the work safety scale. Journal of Safety Research, 29(3), 145-161.
Hayes, R., & Carr, C. (2015). Does Being Social Matter? Effects of Enabled Commenting on Credibility and Brand Attitude in Social Media. Journal of Promotion Management, 21, 371–390.
Hernández-Amorós, M., J, & Urrea-Solano, M., E. (2017). Working with emotions in the classroom: Future teachers’ attitudes and education. Procedia - Social and Behavioral Sciences(237), 511 – 519.
Hinkin, T., R, Tracey, J., B, & Enz, C., A. (1997). Scale construction: Developing reliable and valid measurement instruments. Journal of Hospitality & Tourism Research, 21(1), 100-120.
Hong, & Cha, H. (2013). The mediating role of consumer trust in an online merchant in predicting purchase intention. International
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31-01-2021
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Nassr, R. M., Aldossary, A. A., & Nasir, H. M. (2021). STUDENTS’S INTENTION TO USE EMOTION-AWARE VIRTUAL LEARNING ENVIRONMENT: DOES A LECTURER’S INTERACTION MAKE A DIFFERENCE?. Malaysian Journal of Learning and Instruction, 18(1), 183–218. https://doi.org/10.32890/mjli2021.18.1.8
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