Capstone Projects Mining System for Insights and Recommendations

• Main Authors: GOH, Melvrivk Aik Chun, GOTTIPATI, Swapna, SHANKARARAMAN, Venky
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2015
• Subjects: Capstone projects; Data mining; Recommendation system; Visualization; Text analytics; Classification; Singapore Management University; Asian Studies; Computer Sciences; Higher Education
• Online Access: https://ink.library.smu.edu.sg/sis_research/2887; https://ink.library.smu.edu.sg/context/sis_research/article/3887/viewcontent/GottipatiS_CapstoneProjectMining_CameraV4_0.pdf
• Institution: Singapore Management University

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.