Analytical and problem-solving skills are crucial for thriving in the workplace instead of mere content knowledge. To better prepare our undergraduates for entry into the workforce in this tumultuous time, Experiential Learning Theory (ELT) has been employed in the business programs. A cloud-based simulation game called MonsoonSIM has been deployed in one of the introductory courses in the business school. The simulation game aims to allow students to explore a broad spectrum of business processes ranging from retail, e-commerce, wholesales, manufacturing, procurement, manpower planning, forecasting, accounting, and finance. Through experiential learning and collaboration with teammates via an online portal, students are encouraged to deepen their understanding by playing the game online. In this paper, we aim to analyze the students' activities in the simulation games and use it as a proxy to measure their engagement level and take preemptive action to harness students' problem-solving and data analysis skills. The authors have collected hundreds of students' data from two semesters and used anonymized students’ activities and the pre-class quiz results to predict the student's final scores for the course. The regression model is proposed using input as the students’ activities and one of the pre-class quizzes to predict the students’ final scores. The model accuracy rate is measured using Mean Absolute Percentage Error (MAPE), which is less than 10% and is a good predictive model. It helps the educator to analyse the student's performance early in the course and improve their overall learning experience.

Authors:
Nang Laik Ma, Singapore University of Social Sciences, Singapore
Ivy Sook May Chia, Singapore University of Social Sciences, Singapore

About the Presenter(s)
Dr. Ma, Nang Laik is an Associate Professor in School of Business, Singapore University of Social Sciences (SUSS), Singapore.

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