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 Likert-type 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.