An extended technology acceptance model of a mobile learning technology

被引:62
作者
Yu Zhonggen [1 ]
Yu Xiaozhi [2 ]
机构
[1] Beijing Language & Culture Univ, Fac Foreign Studies, Dept English Studies, Beijing 100083, Peoples R China
[2] Beijing Language & Culture Univ, Fac Humanities & Social Sci, Dept Humanities, Beijing, Peoples R China
关键词
an extended TAM; mobile learning technology; peer influence; Rain Classroom; superior influence; THEORETICAL EXTENSION; PERCEIVED EASE; ATTITUDES; SYSTEM; TAM;
D O I
10.1002/cae.22111
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Rain Classroom, a popular mobile app developed by the most distinguished university in Asia, is a product of mobile technological revolution. Few studies have, however, formulated its acceptance model by including the constructs of peer and superior influences. This study's primary investigation is the impact of peer and superior influences on learners' usage of Rain Classroom within the technology acceptance model (TAM) framework. Both constructs are entered into an extended TAM as external variables impacting on the core constructs in the prevailing TAM literature: perceived usefulness, ease of use, enjoyment, and continuance intention. The investigation is conducted within the context of university students' utilization of Rain Classroom. A sample of 293 students from a higher education institution in East China participated in this study. Using correlation analysis and WarpPLS Structural Equation Modeling, eight hypotheses were tested for Rain Classroom. The results of the analyses reveal that both peer and superior influences play a significant role in the students' continuance intention to use Rain Classroom. Besides peer and superior influences, future research could extend the TAM by including more constructs to provide important references for researchers and practitioners of Rain Classroom.
引用
收藏
页码:721 / 732
页数:12
相关论文
共 55 条
[1]   Investigating faculty decisions to adopt Web 2.0 technologies: Theory and empirical tests [J].
Ajjan, Haya ;
Hartshorne, Richard .
INTERNET AND HIGHER EDUCATION, 2008, 11 (02) :71-80
[2]   Investigating attitudes towards the use of mobile learning in higher education [J].
Al-Emran, Mostafa ;
Elsherif, Hatem M. ;
Shaalan, Khaled .
COMPUTERS IN HUMAN BEHAVIOR, 2016, 56 :93-102
[3]  
Almaiah MA, 2016, J COMPUT EDUC, V3, P453, DOI 10.1007/s40692-016-0074-1
[4]  
[Anonymous], ADV MOBILE DISTANCE
[5]  
[Anonymous], 8 ANN TEACH COMM COL
[6]   Learners' Attitudes toward the Effectiveness of Mobile Assisted Language Learning (MALL) in L2 Listening Comprehension [J].
Azar, Ali Sorayyaei ;
Nasiri, Hassan .
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON CURRENT TRENDS IN ELT, 2014, 98 :1836-1843
[7]   Sample size requirements for testing and estimating coefficient alpha [J].
Bonett, DG .
JOURNAL OF EDUCATIONAL AND BEHAVIORAL STATISTICS, 2002, 27 (04) :335-340
[8]   Informal tools in formal contexts: Development of a model to assess the acceptance of mobile technologies among teachers [J].
Carlos Sanchez-Prieto, Jose ;
Olmos-Miguelanez, Susana ;
Garcia-Penalvo, Francisco J. .
COMPUTERS IN HUMAN BEHAVIOR, 2016, 55 :519-528
[9]  
Crompton H, 2013, HANDBOOK OF MOBILE LEARNING, P3
[10]  
Davis FD, 1986, TECHNOLOGY ACCEPTANC