Year: 2021
Type: dissertation
Abstract: Network analysis is one of the decent approaches to categorize student's interaction while solving a group project.The interaction pattern of students can be modeled using a cognitive network.By analyzing the interaction network, it is possible to categorize student's performance changes over time during a course and project.Student interaction analysis can help an instructor judge the student better and design the study module based on its necessity.In this research, we have analyzed student's interaction by using factual data obtained from the Learning Analytics course.Initially, we have designed a coding framework based on the Community of Inquiry coding template.The whole dataset is coded, and a portion is used to crosscheck the inter-rater reliability of coding.Social Network Analysis (SNA) and Epistemic Network Analysis (ENA) are applied to analyze student's degree, centrality values, network pattern, interaction pattern, and cognitive connection.Content analysis is done using the developed coding framework and topic-based coding.It shows student's areas of concentration and quality of interaction.Both qualitative and quantitative method is used in this research.Results of this research are demonstrated using visualization and statistical analysis of data.
Author: J. Hossain
Language: English
Subfield: Computer Science Applications
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
Funder: Itä-Suomen Yliopisto
OpenAlex ID: W3185606203