Using evidence-based decision-making and cognitive apprenticeship approach to develop students' entrepreneurial mindset

Abstract

Developing one's entrepreneurial mindset is important for all students, regardless of discipline. Evidence-based decision-making (which has the potential to lower costs and improve quality of life) is one approach for applying entrepreneurially minded learning in the undergraduate classroom. This approach allows students to understand trends related to data, in general, and big data, specifically. Furthermore, it better prepares graduates to evaluate and identify effective data science-based solutions. The purpose of this study is to report on one pedagogical approach to developing the entrepreneurial mindset through integrating evidence-based decision-making into the engineering and technology classroom using Microsoft Power BI Desktop (a freely available tool released by Microsoft in September 2013, where “BI” implies Business Intelligence). A mixed methods assessment was conducted including a rubric to measure students' effectiveness in applying the entrepreneurial mindset and a metacognitive reflection to better understand student motivation, awareness of learning, and engagement. First, the rubric was applied, and students were categorized by performance group (e.g., high, mid, low). Second, each performance group was analyzed to identify themes within the reflections. Our findings suggest that students in the high-performing group communicated overall high levels of motivation, while students in the low-performing group shared overall moderate levels of motivation. The relationship between performance and motivation among students in the mid-performing group was inconclusive. Findings from our study suggest that there may be a relationship between students' performance and motivation. The key study implications relate to the use of new literacies, such as technological literacy, data literacy, and human literacy, as practices for promoting the development of an entrepreneurial mindset. Our findings suggest that our approach was effective in accomplishing this goal, but there is also room for improvement. Lessons learned and recommendations are provided.