With the increased use of online educational lessons to complement face-to-face instruction in universities and colleges nationwide, it will be important to understand how these forms of instructional aids help students to engage, garner interest in, and excel in their courses. In the areas of science, technology, engineering, and math, little is known about how these electronic instructional tools can be designed to motivate students to engage with concepts that are fundamental, yet difficult to master. In particular, we aim to explore how these types of instructional aids influence the engagement and interest of students from underrepresented groups and women in the field of engineering. Special focus will be given to courses and online instructional aids for topics within engineering where drop-out rates are known to be high among students (e.g., engineering statics).
One unique element of this work is that research methods in fields like neuromarketing will be incorporated into this study where biometric responses will be observed as students engage with online engineering instructional aids. Biometric responses are physiological characteristics of the human body such as eye tracking and skin conductance. The study will explore what motivated or demotivated underrepresented populations to persist in using the instructional aid and how their experience with these educational electronic tools influence the motivations towards continuing in the field of engineering. A broader impact of this work is that by understanding how online instructional aids engage and motivate students, we can understand how to better design electronic tools and apps that will enable a wider range of students to pursue and succeed in engineering. The intellectual merit of this exploratory, mixed-method multi-modal research study is to understand the intertwined mechanisms (i.e. the motivational, affective, attentive, and physiological influences) of underrepresented and non-traditional women in engineering as they engage in online instructional aids and tools. In addition, this work will inform the Technological Acceptance Model to better understand and measure the associations between these constructs. While the model aims to understand the influence of extrinsic motivators such perceived usefulness and ease of use of specific technologies that determine an individual's behavior or choice to use/benefit from a specific technology; it does not meaningfully allow for contextual analysis of subgroups within engineering such as gender, race/ethnicity and age, as well as and their intersectionality within engineering. This exploratory work will help advance the knowledge-base in engineering education around the development of engineering-specific theories and pedagogy for educational electronic learning tools with emphasis on understanding the mechanisms that intersectionality plays in their acceptance, learning and engagement.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
