Factors Affecting University Students Switching Intention to Mobile Learning: A Push-Pull-Mooring Theory Perspective

Autor/in	Lisana, Lisana
Titel	Factors Affecting University Students Switching Intention to Mobile Learning: A Push-Pull-Mooring Theory Perspective
Quelle	In: Education and Information Technologies, 28 (2023) 5, S.5341-5361 (21 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Lisana, Lisana)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1360-2357
DOI	10.1007/s10639-022-11410-z
Schlagwörter	Handheld Devices; Telecommunications; Technology Integration; Intention; Student Attitudes; College Students; Decision Making; Student Motivation; Foreign Countries; Indonesia + Suchen Sie Ihr Suchwort? Telekommunikationstechnik; Schülerverhalten; Collegestudent; Decision-making; Entscheidungsfindung; Schulische Motivation; Ausland; Indonesien
Abstract	Adopting technology by its intended users is one of the most important contributors to that technology's success. Therefore, the success of mobile learning (ML) depends on the students' acceptance of the method. Regarding this point, this quantitative research aims to identify factors that affect switching intention to adopt ML among university students in Indonesia based on migration theory, Push-Pull-Mooring (PPM) framework. A theoretical model was developed to examine the determinants that affect students' decision to use ML platforms. This study used an online survey questionnaire to obtain 616 valid responses. A comprehensive analysis of the influence factors of users switching behavior, including the moderating factors, was conducted using Structural Equation Modeling (SEM) and Amos software. The results confirmed that the push factor (learning convenience), pull factors (learning autonomy and enjoyment), and mooring factor (student innovativeness) are perceived as significant factors for accepting ML. Concerning the moderating factor, this study also revealed the significance of moderating factor experience in two causal effects of enjoyment and student innovativeness on the students' intention to switch using ML. Furthermore, based on the findings, several recommendations were suggested for the university policy-makers to develop effective strategic plans to get a competitive advantage. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01