TY - JOUR
T1 - SentiTAM: Sentiments centered integrated framework for mobile learning adaptability in higher education
AU - Qazi, Atika
AU - Hasan, Najmul
AU - Owusu-Ansah, Christopher M.
AU - Hardaker, Glenn
AU - Dey, Samrat Kumar
AU - Haruna, Khalid
N1 - KAUST Repository Item: Exported on 2023-01-26
Acknowledgements: The work is supported by Universiti Brunei Darussalam under research grant UBD/RSCH/URC/RG(b)/2020/023.
PY - 2023/1/13
Y1 - 2023/1/13
N2 - 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.
AB - 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.
UR - http://hdl.handle.net/10754/687297
UR - https://linkinghub.elsevier.com/retrieve/pii/S2405844022039937
U2 - 10.1016/j.heliyon.2022.e12705
DO - 10.1016/j.heliyon.2022.e12705
M3 - Article
C2 - 36685464
SN - 2405-8440
VL - 9
SP - e12705
JO - Heliyon
JF - Heliyon
IS - 1
ER -