Applying the time continuum model of motivation to explain how major factors affect mobile learning motivation: a comparison of SEM and fsQCA

• Published in: Online information review Vol. 46; no. 6; pp. 1095 - 1114
• Main Authors: Fan, Mingyue, Ndavi, Juliet Wanza, Qalati, Sikandar Ali, Huang, Lin, Pu, Zhengjia
• Format: Journal Article
• Language: English
• Published: Bradford Emerald Publishing Limited 26-09-2022; Emerald Group Publishing Limited
• Subjects: Academic libraries; Applications programs; Attitudes; Behavioral Objectives; Cell phones; Continuum modeling; Designers; Distance learning; Education; Educational Practices; Electronic devices; Emotions; Fuzzy sets; Hypotheses; Internet resources; Learner Engagement; Learning Processes; Library catalogs; Mathematical models; Motivation; Multivariate statistical analysis; Online instruction; Portable computers; Qualitative analysis; Research methodology; Smartphones; Social research; Stimulation; Student Motivation; Students; Teaching Methods; Undergraduate Students; China; fsQCA; TCMM; Mobile learning; SEM; Motivation
• ISSN: 1468-4527; 1468-4535
• DOI: 10.1108/OIR-04-2021-0226

PurposeStudying mobile learning – the use of electronic devices (i.e. cellphone and tablets) to engage in learning across multiple contexts via connection to peers, media, experts and the larger world is a relatively new academic enterprise. This study analyzes the influencing factors of mobile learning (M-learning) motivation based on the time continuum model of motivation (TCMM).Design/methodology/approachThe study uses structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) to verify relationships between mobile learning motivation, attitude, need, stimulation, emotion, ability and reinforcement. Justification for the use of both methods lies in the complementarity relationships that existed between the variables and research methodologies. The sample contains 560 mobile learners' feedback.FindingsResults show that attitude, need, emotion, ability and reinforcement are important factors to enhance mobile learning motivation, while stimulation is not.Practical implicationsThis work highlights the importance of training for app designers on how to design an M-learning App with high learning motivation by paying prior attention to learning content, teaching team and online learning communities.Originality/valueThis study proposes three precise solutions (scholars, managers and practitioners) to improve learning motivation based on the categorization of mobile learners.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-04-2021-0226.