Measuring Students' Acceptance to AI-Driven Assessment in eLearning: Proposing a First TAM-Based Research Model

被引:27
作者
Cruz-Benito, Juan [1 ]
Sanchez-Prieto, Jose Carlos [2 ,4 ]
Theron, Roberto [2 ,3 ,5 ]
Garcia-Penalvo, Francisco J. [2 ,3 ,4 ]
机构
[1] IBM Res, AI & QTJ Watson Res Ctr, Yorktown Hts, NY 10598 USA
[2] Univ Salamanca, GRIAL Res Grp, Salamanca, Spain
[3] Univ Salamanca, Dept Comp Sci, Salamanca, Spain
[4] Univ Salamanca, Res Inst Educ Sci IUCE, Salamanca, Spain
[5] Univ Salamanca, VISUSAL Res Grp, Salamanca, Spain
来源
LEARNING AND COLLABORATION TECHNOLOGIES. DESIGNING LEARNING EXPERIENCES, LCT 2019, PT I | 2019年 / 11590卷
关键词
Artificial intelligence; Technology acceptance model; Education; eLearning; Students; TASK-TECHNOLOGY FIT; ARTIFICIAL-INTELLIGENCE; INFORMATION-TECHNOLOGY; USER ACCEPTANCE; FUTURE; MOOCS; TRUST;
D O I
10.1007/978-3-030-21814-0_2
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Artificial Intelligence is one of the trend areas in research. It is applied in many different contexts successfully. One of the contexts where Artificial Intelligence is applied is in Education. In the literature, we find several works in the last years that explore the application of Artificial Intelligence-related techniques to analyze students' behavior, to enable virtual tutors or to assess the learning. However, what are the students' perceptions on this subject of Artificial Intelligence and Education? Do they accept the use of Artificial Intelligence techniques to assess their learning? Are they reluctant to be influenced by non-human agents in such a human process like education? To try to respond to these questions, this paper presents a novel proposal of a research model based on the Technology Acceptance Model. To describe the model, we present its different main constructs and variables, as well as the hypotheses to analyze, adapted to the object of study. Finally, we discuss the main implications of this research model, the opportunities that could come based on this proposal and the future of this research.
引用
收藏
页码:15 / 25
页数:11
相关论文
共 68 条
[1]  
Ajzen Icek., 1985, ACTION CONTROL COGNI, P11
[2]   Neural network approach to predict mobile learning acceptance [J].
Al-Shihi, Hafedh ;
Sharma, Sujeet Kumar ;
Sarrab, Mohamed .
EDUCATION AND INFORMATION TECHNOLOGIES, 2018, 23 (05) :1805-1824
[3]  
Almohammadi K, 2017, J ARTIF INTELL SOFT, V7, P47, DOI 10.1515/jaiscr-2017-0004
[4]   Physicians' resistance toward healthcare information technology: a theoretical model and empirical test [J].
Bhattacherjee, Anol ;
Hikmet, Neset .
EUROPEAN JOURNAL OF INFORMATION SYSTEMS, 2007, 16 (06) :725-737
[5]  
Brusilovsky P., 2003, International Journal of Artificial Intelligence in Education, V13, P156, DOI DOI 10.5555/1434845.1434847
[6]  
Byrne E, From ethics to accountability, this is how AI will suck less in 2019
[7]  
Rodríguez MC, 2018, IEEE GLOB ENG EDUC C, P2066, DOI 10.1109/EDUCON.2018.8363493
[8]   Break the walls! Second-Order barriers and the acceptance of mLearning by first-year pre-service teachers [J].
Carlos Sanchez-Prieto, Jose ;
Hernandez-Garcia, Angel ;
Garcia-Penalvo, Francisco J. ;
Chaparro-Pelaez, Julian ;
Olmos-Miguelanez, Susana .
COMPUTERS IN HUMAN BEHAVIOR, 2019, 95 :158-167
[9]   Study on Parents' Acceptance of the Augmented Reality Use for Preschool Education [J].
Cascales, Antonia ;
Perez-Lopez, David ;
Contero, Manuel .
2013 INTERNATIONAL CONFERENCE ON VIRTUAL AND AUGMENTED REALITY IN EDUCATION, 2013, 25 :420-427
[10]  
Cenfetelli R.T., 2004, J ASS INFORM SYSTEM, V5, P472, DOI DOI 10.17705/1JAIS.00059