ASEE Annual Conference & Exposition
Engineering Education | Mechanical Engineering
In a pilot study supported by NSF, an instructional model that uses brain based learning principles as instructional protocols has been developed and successfully implemented in the course Introduction to Fluid Mechanics at a HBCU. Motivated by that success, we extended a similar intervention to another course, Dynamics, in the same school. In this paper, we report preliminary data from this intervention. The main strategies implemented in this intervention include: organization of the course into specific concepts and sub-concepts, which are concisely presented by short (limited to 2-6 minutes) content-rich lectures (diagrams, animations, narrations), active learning through in-class worksheets, and prompt (next class) feedback. The lectures, by design, included brain-based protocols like connection to relevant old/prior knowledge, creating of neural networks, and repeated use of neurons. Results from this implementation showed that students’ engagement and efficacy were significantly enhanced by this approach. That confirms the findings of our previous study and shows that the model effectiveness is independent of the instructor who develops and implements the model, as long as the brain-based learning principles are followed. One third of the participating students strongly agreed that the approach is more engaging both inside and outside the classroom and that the overall learning of the presented concepts was improved. Additionally this study investigated the contribution of the various components of the brain-based approach, when compared to the traditional delivery of the same course, to the improved learning and engagement. Teaching using concept-oriented short premade lectures rich with illustrations and animations was an essential contributor to the observed improvements in the opinion of about 40% of the participating students. Similarly, the active work on in-class worksheets based on the presented concept(s) during class time and availability of the lectures to the students anytime/anywhere beyond the class time were essential elements over traditional teaching in the opinion of 33% and 77% of the students, respectively. Further results and analysis will be presented based on the data currently being collected. Nevertheless, there is sufficient evidence that substantiates the benefits of brain-based learning principles in improving basic engineering mechanics education.
Firas Akasheh, John Solomon, Eric Hamilton, Chitra Nayak, and Vimal Viswanathan. "Application of Brain-based Learning Principles to Engineering Mechanics Education: Implementation and Preliminary Analysis of Connections Between Employed Strategies and Improved Student Engagement" ASEE Annual Conference & Exposition (2018).