Descriptive Network Modeling and Analysis for Investigating User Acceptance in a Learning Management System Context

Autor:	Roberto Rondinelli, Parisa Shayan, Martin Atzmueller, Menno van Zaanen
Přispěvatelé:	Cognitive Science & AI
Rok vydání:	2019
Předmět:	Descriptive statistics Computer science User modeling Educational technology Technology acceptance model Context (language use) Learning Management Data science Network model Network analysis
Zdroj:	ABIS@HT Tilburg University-PURE STARTPAGE=7;ENDPAGE=13;TITLE=ABIS 2019-23rd International Workshop on Personalization and Recommendation on the Web and Beyond
DOI:	10.1145/3345002.3349288
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::31b4c9de3d4c077a8421d7f30b8b2c6e https://doi.org/10.1145/3345002.3349288 Zobrazit plný text záznamu