Fundamental Theorem Learning With Optimum Pedagogy for Technology Integration in Quality Control Course

Abstract As technology advances and new software is developed, the education system is being challenged to adapt pedagogical approaches for the smooth integration of such tools into the curriculum. These tools can be beneficial for teaching because they allow students to visualize difficult concepts and can be used to execute functions that would otherwise be time prohibitive. However, there is a concerning trend of students depending too heavily on this technology. Technology provides an avenue through which students can feign comprehension and continue advancing in the curriculum. The purpose of this study is to look at different pedagogical approaches and their effects on student's self-efficacy and topic comprehension. To address this, we worked with a required course (ESI4221C: Industrial Quality Control) in the Industrial and Systems Engineering (ISE) curriculum at the University of Florida (UF). This course focuses on quality control and builds on statistical fundamentals while also introducing new theoretical concepts such as tests statistics, confidence intervals, p values, and ANOVA. Not only does this course teach the fundamental concepts, but it includes teaching common software that is used in industry or higher education, specifically RStudio. Different pedagogical approaches were used to teach fundamental concepts along with software to students in this study and each approach was randomly assigned to a single module. The first pedagogical approach is the Instructor Guided Method in which the instructor taught RStudio to students after each topic. The second pedagogical approach is the Think-Pair-Share Method in which students were assigned mandatory readings and instructor dedicated class time for peer-to-peer discussion. Self-efficacy surveys and conceptual/computational assessments were given for each method to determine how students felt while learning the material and their comprehension. Our preliminary data indicates that there is no statistically significant difference between the teaching methods implemented so far. The data did not reveal a difference between the methods used so far, but additional studies need to be done to assess if this result is due to low sample size or differences in difficulty between the modules that each method was assigned to. This research will be continued and expanded on in the fall 2021 semester to collect more data from additional courses and the methods applied to different modules.