SentiTAM: Sentiments centered integrated framework for mobile learning adaptability in higher education

Atika Qazi; Najmul Hasan; Christopher M Owusu-Ansah; Glenn Hardaker; Samrat Kumar Dey; Khalid Haruna

doi:10.1016/j.heliyon.2022.e12705

SentiTAM: Sentiments centered integrated framework for mobile learning adaptability in higher education

Heliyon. 2022 Dec 30;9(1):e12705. doi: 10.1016/j.heliyon.2022.e12705. eCollection 2023 Jan.

Authors

Atika Qazi¹, Najmul Hasan², Christopher M Owusu-Ansah^{3

4}, Glenn Hardaker⁵, Samrat Kumar Dey⁶, Khalid Haruna⁷

Affiliations

¹ Centre for Lifelong Learning, Universiti Brunei Darussalam, Brunei Darussalam.
² BRAC Business School, BRAC University, Dhaka, 1212, Bangladesh.
³ Akenten Appiah-Menka University of Skills Training and Entrepreneurial Development, Ghana.
⁴ Department of Information Science, University of South Africa, South Africa.
⁵ King Abdullah University of Science and Technology, Saudi Arabia.
⁶ School of Science and Technology (SST), Bangladesh Open University (BOU), Gazipur, Bangladesh.
⁷ Department of Computer Science, Kaduna State University, Kaduna, Nigeria.

Abstract

Online communities provide facilities to share public opinions and or sentiments on a wide range of subjects, from routine topics to vital issues of critical interest. Nowadays, many higher education institutions (HEIs) recognize the value of students' sentiments and evaluate users' concerns for the successful adaptation of mobile learning applications (MLAs). While digital learning has been extensively studied previously, little has been known about why MLA is underutilized. Therefore, this study extends the literature by proposing the SentiTAM model underlying technology acceptance model (TAM), and students' sentiments on MLA platforms. A self-administered cross-sectional survey of 350 MLA users' data was analyzed through structural equation modeling (SEM) using the AMOS package program. In addition, we have performed sentiment analysis on students' opinions gathered through Google discussion forums and Twitter. The results show that MLA use intention is strongly influenced by sentiments and self-motivation, while perceived usefulness and perceived ease of use directly influence MLA usage. To the best of our knowledge, this study is the first attempt in MLA that investigates several vital factors, including sentiments as a multi-perspective tool and motivational factors with core constructs of TAM. The findings assist developing countries make smart decisions about how to use MLA with emerging technology.

Keywords: Higher education; Mobile learning applications (MLAs); SenitTAM; Sentiment analysis; Technology acceptance model (TAM).