An Empirical Study on Student Satisfaction of Smart Classroom Use
Pages 221 - 228
Abstract
The construction of smart classrooms has become the main developing tendency in the present world of higher education. Among them, students, as the main users of smart classrooms in colleges and universities, their satisfaction with smart classrooms and their intention to continue using them are the main basis for the continuous improvement of smart classroom construction. Based on this, this paper takes Technology Acceptance Model (TAM) as the basic analysis framework, combines Task-Technology Fit (TTF) and Expectation Conformation Model (ECM), takes perceived usefulness, perceived ease of use, and expectation confirmation as the basic variables, and according to the actual use of the smart classroom in S University. The research model of satisfaction and willingness to continue using the smart classroom was constructed by introducing technology support resources, task-technology fit, self-efficacy, and social influence as external variables. After that, 492 valid questionnaires from S University were used as sample data sources. Based on reliability and validity tests and descriptive analysis, AMOS24.0 software was used to verify the hypothesis of this research model. The results show that perceived ease of use and expectation confirmation have a significant positive impact on learner satisfaction; Task-technology fit and self-efficacy indirectly affect learner satisfaction through perceived ease of use; The higher the learner satisfaction is, the more inclined to continue to use the smart classroom. Finally, based on the research results and centered on students, this paper puts forward a specific plan to improve the satisfaction of using smart classrooms to provide a valuable reference for the construction of smart classrooms and classroom teaching reform in colleges and universities in the future.
References
[1]
Libing Jiang, Qiming Mao, and Zhen Wan. 2018. Research on the performance of classroom teaching reform in the smart classroom——An analysis based on classroom teaching behaviors. China Educational Technology. 6(June 2018), 52-58.
[2]
Yiming Qu and I-Hua Chen, Are Emotions Important for College Teachers’ Intentions to Use the Online Learning System? An Integrated Model of TAM and PAD. International Journal of Information and Education Technology. 11, 2(January 2021), 73-81.
[3]
Hassan Abuhassna, Noraffandy Yahaya, Megat Aman Zahiri Megat Zakaria, Norasykin Mohd Zaid, Norazrena Abu Samah, Fareed Awae, Chee Ken Nee, and Ahmad H. Alsharif, Trends on Using the Technology Acceptance Model (TAM) for Online Learning: A Bibliometric and Content Analysis. International Journal of Information and Education Technology. 13, 1(January 2023), 131-142.
[4]
Yangqi Ou. 2022. Research on influencing factors of junior middle school teachers' smart classroom teaching behavior based on technology acceptance model——Take Shenzhen P district as an example. M.S. thesis, MAM Department, East China Normal University. https://doi.org/10.27149/d.cnki.ghdsu.2022.002834
[5]
Jiale Li. 2020. A study on the influencing factors of using intention of college students' smart classroom based on TAM model. M.S. thesis, MAM Department, Shanxi Normal University. https://doi.org/10.27287/d.cnki.gsxsu.2020.000281
[6]
Si Zhang, and Yongfan Li. 2014. Study on university teachers' network teaching behavior based on technology acceptance model. Journal of Distance Education. 32, 3(June 2014), 56-63. https://doi.org/10.15881/j.cnki.cn33-1304/g4.2014.03.009
[7]
Daolong Jing. 2013. Research on Mobile Learning based on TTF and TAM Integrated Model. M.S. thesis, Education Theory Department, Nanjing University. https://doi.org/CNKI: CDMD:2.1015.575669
[8]
Yi Liu and Tingsong Zhang. 2020. Research on the factors influencing the intention of continuous use of Mobile News APP– the extension of expectation confirmation Model based on continuous use of Information system. Journal of Southwest Minzu University(Humanities and Social Science). 41, 3(March 2020), 151-156. https://doi.org/CNKI: SUN: XNZS.0.2020-03-020
[9]
Yuqian Zeng, Lin Yang and Xiaohan Wang. 2021. Study the influencing factors of continuous use intention of Mu class users during the epidemic. China Educational Technology & Equipment. 522, 24(December 2021), 92-94+98.
[10]
Yan Lin. 2017. A study on the intention to use the Mobile platform of College students' innovative Entrepreneurship Service– from the perspective of ECM+TAM. Journal of Hebei Agricultural University (Social Sciences). 19, 6(June 2017), 87-91. https://doi.org/CNKI: SUN: HBND.0.2017-06-022
[11]
R. Lance Hogan and Mark A. McKnight. 2007. Exploring burnout among university online instructors: An initial investigation. The Internet and Higher Education. 10, 2(March 2007), 117-124. https://doi.org/10.1016/j.iheduc.2007.03.001
[12]
Albert Bandura. 1978. Self - efficacy: toward a unifying theory of behavioral change. Advances in behaviour research & therapy. 1, 4(April 1978), 139-161. https://doi.org/10.1016/0146-6402(78)90002-4.
Index Terms
- An Empirical Study on Student Satisfaction of Smart Classroom Use
Index terms have been assigned to the content through auto-classification.
Recommendations
Determinants of users' intention to adopt wireless technology: An empirical study by integrating TTF with TAM
This paper reported the results of a survey study and provided evidences of empirically testing a model that integrates both technology acceptance model (TAM) and task-technology fit (TTF) model in understanding the determinants of users' intention to ...
Predicting continuance intention toward mobile branded apps through satisfaction and attachment
Highlights- The relationship between brand attachment and satisfaction is nonrecursive.
- ...
AbstractAn increasing number of companies have created branded apps to communicate with and satisfy the needs of target audiences. The interactive features of smartphone apps strengthen the brand–consumer relationship and help consumers ...
Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model
Much previous research has established that perceived ease of use is an important factor influencing user acceptance and usage behavior of information technologies. However, very little research has been conducted to understand how that perception forms ...
Comments
Information & Contributors
Information
Published In
September 2023
532 pages
ISBN:9798400709111
DOI:10.1145/3629296
Copyright © 2023 ACM.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 15 January 2024
Check for updates
Author Tags
Qualifiers
- Research-article
- Research
- Refereed limited
Conference
ICETC 2023
ICETC 2023: The 15th International Conference on Education Technology and Computers
September 26 - 28, 2023
Barcelona, Spain
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 39Total Downloads
- Downloads (Last 12 months)39
- Downloads (Last 6 weeks)0
Reflects downloads up to 14 Jan 2025
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign inFull Access
View options
View or Download as a PDF file.
PDFeReader
View online with eReader.
eReaderHTML Format
View this article in HTML Format.
HTML Format