Transitioning to Analytics: PUP San Pedro Campus’ Business Students Induction to Analytics Courses

Abstract

This research observes and examines the state of acceptance and adaptability of PUP San Pedro Campus’ business students following the new curriculum (CHED Memorandum Order No. 17 S. 2017) implementation where business students are required to take Analytic Courses. Adding Data Analytics courses equip students with skills and knowledge in exploring data in meaningful ways. However, a program that focused for many years on administration and management courses is expected that the first batch of students to undertake this analytics-infused curriculum requires time for adjustment. Originally, data preparation, modeling, and programming are required courses for computer-related programs such as Information Technology, Computer Science, and the likes. Likewise, with the release and implementation of the new curriculum, these courses also became core subjects in Business Programs. The study is qualitative research, which investigates PUPSPC students’ induction to Analytics Courses, their accumulated learnings from these courses, their perceived importance of taking these courses, and their adaptation methods. This study focused on three areas: First, it identifies different analytics courses the Business Administration Programs in PUP are currently implementing. It delves into the importance and roles of these courses to the competency level of students. The researcher established the students’ understanding of these topics through a question-and-answer survey. Second, the paper shows the importance of Analytics courses to students’ future careers as practitioners. Data analytics helps businesses maximize their performances. Through implementations, business models could help companies lessen costs by recognizing more efficient ways of operating business and teaching ways of storing a large amount of data. Lastly, this paper exhibits PUP San Pedro business students’ adaptation procedure and how Piaget’s Theory of Development performs a role in this adaption. The study also gathers students’ recommendations on what and how they believe could make learning analytics more productive and fun.