Analysis of students’ digital activities via a learning analytics approach
Jiang, Chao (2021)
Diplomityö
2021
School of Engineering Science, Tuotantotalous
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe2021100449298
https://urn.fi/URN:NBN:fi-fe2021100449298
Tiivistelmä
The trend of digitalization is unstoppably spreading in all industries and aspects of our life including education. Remote education was picked by most universities and institutions after the outbreak of Covid-19, however, the evaluation of students’ performance in the virtual learning environments (VLEs) became a challenge to the teacher.
This research was carried out to investigate the feasibility of solving the problem with tools from Learning Analytics (LA). Network attributes, centrality, and positional analysis under Social Network Analysis (SNA) were selected as parameters for evaluation of students’ behaviours in discussion forum.
Graph, and matrix were studied as media to present and communicate the result of analysis, techniques such as hierarchical clustering, Multidimensional Scaling, and Blockmodeling were tested for visualization of results.
This research was carried out to investigate the feasibility of solving the problem with tools from Learning Analytics (LA). Network attributes, centrality, and positional analysis under Social Network Analysis (SNA) were selected as parameters for evaluation of students’ behaviours in discussion forum.
Graph, and matrix were studied as media to present and communicate the result of analysis, techniques such as hierarchical clustering, Multidimensional Scaling, and Blockmodeling were tested for visualization of results.