Can Multimedia Tools Promote Big Data Learning and Knowledge in a Diverse Undergraduate Student Population?

Abstract

Background and Purpose: Multimedia tools are an integral part of teaching and learning in today’s technology-driven world. The present study explored the role of a newly-developed video introducing the emerging field of big data to a diverse undergraduate student population. Particularly, we investigated whether introduction of a multimedia tool would influence students’ self-perceived knowledge related to various big data concepts and future interest in pursuing the field, and what factors influence these. Methods: Students (n = 331) completed a survey on-line after viewing the video, consisting of Likerttype and quantitative questions about students’ learning experience, future interest in big data, and background. The dataset was analyzed via ANOVA and multiple linear regression methods. Results: Gender, major, and intended degree were significantly associated with students’ learning experience and future interest in big data. Moreover, students who had no prior exposure to big data reported a better learning experience, although they also reported less likelihood to pursue it in the future. Conclusion: Multimedia tools may serve as an effective learning tool in introducing and creating interest in a diverse group of students related to introductory big data science concepts. Both similarities and differences were observed regarding such behaviors among different student sub-groups.