As more and more technological innovations are coming into reality, many educators are starting to use these innovations to meet the different learning styles of students rather than sticking with the conventional book-lecture-example type of teaching methodology. To date, new teaching tools such as smartboards, online learning module templates, videos, animations, audiobooks, e-books, and interactive books have all appeared. One way of looking at it is that each student may have a particular style of learning, and the material learning retention improves significantly if each student is learning the materials via his/her own style or are exposed to multiple learning styles.
This paper discusses the status of an interactive software that was developed to teach concepts of renewable energy and its assessment of student learning performances in several undergraduate courses. The software could help students learn fuel cells, one kind of renewable energy source; using verbal, auditory, and visual methods like animations and videos. The motivation of selecting fuel cells as the course contents throughout the software modules is due to the fact that more and more mechanical engineering students are interested in renewable energies, and fuel cells have higher efficiency and versatility. The software package can serve either as a stand-alone tool about fundamentals, applications, and science behind fuel cells; or as a supplemental teaching tool to be used outside of the classroom to reinforce fuel cell concepts being taught in class.
The effectiveness of the software on student learning outcomes was evaluated two times in undergraduate courses with 200 students on an average, using a set of surveys that measure the learning outcomes and motivations of students based on the ARCS model, prior to and after the intervention with the software tool. The first evaluation was conducted in Fall 2014 in a Senior Design class with students from the Mechanical and Aerospace Engineering Department, followed by the second evaluation conducted in a Thermodynamics course in Summer 2015.
The knowledge of the subject matter improved significantly after the intervention of the software, on an average by M=14.41 (SD = 5.10, p < .001), and the motivation scores increased by M = 2.09 (SD = 9.90, p = .021) assessed by the data from the first round data collection. This assessment results cross-validated the results from the analysis of the second round data with the average student learning outcome increased by M = 9.78 (SD = 5.69, p < .001), and the motivation scores improved by M = 1.38 (SD = 7.26, p = .29).
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