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

Research output: Contribution to conferencePaperOther research output

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.
Original languageEnglish
Pages7-13
Publication statusPublished - 17 Sep 2019

Fingerprint

Educational technology
Electric network analysis
Statistical methods
Statistics
Students

Cite this

@conference{49448e7d62c544b9bef5856d3d486fa7,
title = "Descriptive Network Modeling and Analysis for Investigating User Acceptance in a Learning Management System Context",
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 specificpatterns 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.",
author = "Parisa Shayan and Roberto Rondinelli and {van Zaanen}, Menno and Martin Atzmueller",
year = "2019",
month = "9",
day = "17",
language = "English",
pages = "7--13",

}

Descriptive Network Modeling and Analysis for Investigating User Acceptance in a Learning Management System Context. / Shayan, Parisa; Rondinelli, Roberto; van Zaanen, Menno; Atzmueller, Martin.

2019. 7-13.

Research output: Contribution to conferencePaperOther research output

TY - CONF

T1 - Descriptive Network Modeling and Analysis for Investigating User Acceptance in a Learning Management System Context

AU - Shayan, Parisa

AU - Rondinelli, Roberto

AU - van Zaanen, Menno

AU - Atzmueller, Martin

PY - 2019/9/17

Y1 - 2019/9/17

N2 - 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 specificpatterns 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.

AB - 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 specificpatterns 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.

M3 - Paper

SP - 7

EP - 13

ER -