Combining Technology Readiness and Acceptance Model for Investigating the Acceptance of M-Learning in Higher Education in India

Autor/in	Kampa, Raj Kishor
Titel	Combining Technology Readiness and Acceptance Model for Investigating the Acceptance of M-Learning in Higher Education in India
Quelle	In: Asian Association of Open Universities Journal, 18 (2023) 2, S.105-120 (16 Seiten) PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Kampa, Raj Kishor)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
DOI	10.1108/AAOUJ-10-2022-0149
Schlagwörter	Foreign Countries; Electronic Learning; Readiness; Open Education; Distance Education; Computer Attitudes; Usability; Positive Attitudes; Student Attitudes; College Students; Intention; Security (Psychology); India + Suchen Sie Ihr Suchwort? Ausland; Offene Erziehung; Offener Unterricht; Distance study; Distance learning; Fernunterricht; Schülerverhalten; Collegestudent; Security; Psychology; Sicherheit; Indien
Abstract	Purpose: The study aims to validate a mobile learning readiness scale through the technology readiness and acceptance model (TRAM), thereby assessing students' readiness to adopt m-learning in teaching and learning, including its acceptance. Design/methodology/approach: A structured questionnaire was administered to open and distance learning (ODL) students in Odisha, India, to assess their readiness and acceptance of m-learning. 665 valid responses were collected, and collected data was analysed using statistical packages for social sciences (SPSS) and SmartPLS. Findings: The findings of the study reveal that optimism contributes positively to perceived ease of use (PEOU) and perceived usefulness (PU) of m-learning ([beta] = 7.921, p < 0.001; [beta] = 2.123, p < 0.05), whereas innovativeness positively contributes to PEOU of m-learning ([beta] = 2.227, p < 0.05), but not PU of m-learning. ODL student's optimism improves his/her PEOU and PU of m-learning, but innovativeness improves only his/her PEOU. Further, the impact of innovativeness is higher than that of optimism in the TRAM and innovativeness is the strong predictor to adopt m-learning. It also shows that the PU of m-learning positively influences behavioural intention to use m-learning ([beta] = 4.757, p < 0.001). Integrating technology readiness (TR) with technology acceptance model (TAM) to predict students' acceptance of m-learning is very useful. Practical implications: The paper will help decision-makers to adopt and use m-learning in higher educational institutions. Originality/value: This paper is the first to explore the readiness and acceptance of m-learning in higher education in India. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01