Mining capstone project wikis for knowledge discovery
Conference Proceeding Article
Wikis are widely used collaborative environments as sources of information and knowledge. The facilitate students to engage in collaboration and share information among members and enable collaborative learning. In particular, Wikis play an important role in capstone projects. Wikis aid in various project related tasks and aid to organize information and share. Mining project Wikis is critical to understand the students learning and latest trends in industry. Mining Wikis is useful to educationists and academicians for decision-making about how to modify the educational environment to improve student's learning. The main challenge is that the content or data in project Wikis is unstructured in nature. The data formats are in both text and images. In this work, we propose an automated project Wiki mining solution that leverages data mining, text mining and optical character recognition techniques for discovering insights from Project Wikis. The results of mining process are presented as visual summaries which can be useful for the capstone project coordinators and academicians for education pedagogy decisions. We use dataset from Singapore Management University, School of Information Systems' undergraduate capstone projects for our solution evaluation. We evaluated our model on 314 capstone projects over a period of 8 years.
Electronic publishing, Information services, Internet, Data mining, Education, Collaboration, Optical character recognition software
Databases and Information Systems | Data Storage Systems
Data Management and Analytics
Proceedings of 41st IEEE Annual Computer Software and Applications Conference: COMPSAC 2017, Torino, Italy, 2017 July 4-8
IEEE Computer Society
City or Country
GOTTIPATI, Swapna; SHANKARARAMAN, Venky; and GOH, Melvrivk Aik Chun.
Mining capstone project wikis for knowledge discovery. (2017). Proceedings of 41st IEEE Annual Computer Software and Applications Conference: COMPSAC 2017, Torino, Italy, 2017 July 4-8. 371-380. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/3819
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