How virtual reality affects perceived learning effectiveness: a task-technology fit perspective

被引:75
作者
Zhang, Xi [1 ]
Jiang, Shan [1 ]
Ordonez de Pablos, Patricia [2 ]
Lytras, Miltiadis D. [3 ]
Sun, Yongqiang [4 ]
机构
[1] Tianjin Univ, Coll Management & Econ, Tianjin, Peoples R China
[2] Univ Oviedo, Dept Business Adm, Oviedo, Spain
[3] Amer Coll Greece, Deree Coll, Aghia Paraskevi, Greece
[4] Wuhan Univ, Sch Informat Management, Wuhan, Peoples R China
基金
中国国家自然科学基金;
关键词
Virtual reality; task-technology fit; technology quality; technology accessibility; perceived learning effectiveness; USER ACCEPTANCE; EASE; ENVIRONMENTS; VALIDATION;
D O I
10.1080/0144929X.2016.1268647
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The application of virtual reality (VR) in improving users' learning outcomes, especially in perceived learning effectiveness, is a new area. VR provides visualisation and interaction within a virtual world that closely resembles a real world, bringing an immersive study experience. It also has two special features: representational fidelity and immediacy of control. However, only when the technology fits the tasks that users are performing will it be adopted. In addition, technology itself cannot improve learning outcomes; certain learning behaviours, such as reflective thinking, should be prompted first so that learning outcomes can be improved. The research hypotheses derived from this model have empirically been validated using the responses to a survey among 180 users. These responses have been examined through SmartPLS 2.0. Surprisingly, task-technology fit does not moderate the relationship between VR and technology quality and the relationship between VR and technology accessibility. From this study, we can conclude that VR will influence reflective thinking and further indirectly improve perceived learning effectiveness.
引用
收藏
页码:548 / 556
页数:9
相关论文
共 54 条
[31]   A task-technology fit view of learning management system impact [J].
McGill, Tanya J. ;
Klobas, Jane E. .
COMPUTERS & EDUCATION, 2009, 52 (02) :496-508
[32]  
Medellin-Castillo H. I., 2015, ASME 2015 INT MECH E
[33]  
Merrill M.D., 1983, Instructional-Design Theories and Models: An Overview of Their Current Status, V1, P282
[34]  
Merrill M.D., 1994, Instructional Design Theory
[35]   Virtual reality for collaborative e-learning [J].
Monahan, Teresa ;
McArdle, Gavin ;
Bertolotto, Michela .
COMPUTERS & EDUCATION, 2008, 50 (04) :1339-1353
[36]   Beyond self-efficacy: Measuring pre-service teachers' Instructional Technology Outcome Expectations [J].
Niederhauser, Dale S. ;
Perkmen, Serkan .
COMPUTERS IN HUMAN BEHAVIOR, 2010, 26 (03) :436-442
[37]  
Oghazi P., 2012, Services Marketing Quarterly, V33, P195, DOI DOI 10.1080/15332969.2012.689937
[38]   A contribution to the understanding of what makes young students genuinely engaged in computer-based learning tasks [J].
Ott, Michela ;
Tavella, Mauro .
WORLD CONFERENCE ON EDUCATIONAL SCIENCES - NEW TRENDS AND ISSUES IN EDUCATIONAL SCIENCES, 2009, 1 (01) :184-188
[39]   An examination of reflective thinking, learning approaches, and self-efficacy beliefs at the university of the South Pacific: A path analysis approach [J].
Phan, Huy P. .
EDUCATIONAL PSYCHOLOGY, 2007, 27 (06) :789-806
[40]  
Roussou M., 2004, COMPUT ENTERTAIN, V2, P10, DOI [10.1145/973801.973818, DOI 10.1145/973801.973818]