Conference Proceeding Article
In this paper, we present a classification based system to discover knowledge and trends in higher education students’ projects. Essentially, the educational capstone projects provide an opportunity for students to apply what they have learned and prepare themselves for industry needs. Therefore mining such projects gives insights of students’ experiences as well as industry project requirements and trends. In particular, we mine capstone projects executed by Information Systems students to discover patterns and insights related to people, organization, domain, industry needs and time. We build a capstone projects mining system (CPMS) based on classification models that leverage text mining, natural language processing and data mining techniques. For evaluating our system, we use dataset from Singapore Management University, School of Information Systems, undergraduate final year capstone projects from the schools’ Wiki pages.
Capstone projects, Data mining, Recommendation system, Visualization, Text analytics, Classification, Singapore Management University
Asian Studies | Computer Sciences | Higher Education
Data Management and Analytics; Learning and Information Systems Education
Proceedings of the 23rd International Conference on Computers in Education ICCE 2015, 30 November - 4 December 2015, Hangzhou, China
Asia-Pacific Society for Computers in Education
City or Country
GOH, Melvrick; GOTTIPATI Swapna; and SHANKARARAMAN, Venky.
Capstone Projects Mining System for Insights and Recommendations. (2015). Proceedings of the 23rd International Conference on Computers in Education ICCE 2015, 30 November - 4 December 2015, Hangzhou, China. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/2887