Learning Management Systems (LMSs) play a significant role in educational technology. In this paper, we analyze different approaches in order to investigate the acceptance of an LMS. Utilizing questionnaire information structured on the Technology Acceptance Model (TAM), we apply descriptive network modeling and analysis complementing basic statistical analysis in order to identify specific patterns in the user data. We present the applied analysis methodology in detail, and demonstrate the connection to user modeling: here, descriptive statistics indicate student satisfaction with the usage (acceptance level) as a whole; network analysis indicates the level of variability w.r.t. the user questions, while specific patterns or motifs show the satisfaction levels for the different networks.
Descriptive network modeling and analysis for investigating user acceptance in a learning management system context / Shayan, P.; Rondinelli, R.; Van Zaanen, M.; Atzmueller, M.. - (2019), pp. 7-13. (Intervento presentato al convegno 23rd International Workshop on Personalization and Recommendation on the Web and Beyond, ABIS 2019, in conjunction with the 30th ACM International Conference on Hypertext and Social Media, HT 2019 tenutosi a Hof University, deu nel 2019) [10.1145/3345002.3349288].
Descriptive network modeling and analysis for investigating user acceptance in a learning management system context
Rondinelli R.;
2019
Abstract
Learning Management Systems (LMSs) play a significant role in educational technology. In this paper, we analyze different approaches in order to investigate the acceptance of an LMS. Utilizing questionnaire information structured on the Technology Acceptance Model (TAM), we apply descriptive network modeling and analysis complementing basic statistical analysis in order to identify specific patterns in the user data. We present the applied analysis methodology in detail, and demonstrate the connection to user modeling: here, descriptive statistics indicate student satisfaction with the usage (acceptance level) as a whole; network analysis indicates the level of variability w.r.t. the user questions, while specific patterns or motifs show the satisfaction levels for the different networks.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
