Integrated Closed-Loop Learning Analytics Scheme in a First-Year Engineering Course

This complete research paper works to tie the processes of identifying students that show signs of potentially being non-thriving at the end of the semester with a strategy to boost these students during the early part of the semester. The work in this paper, which applies the integrated closed-loop learning analytics scheme (iCLAS) that was used in previous similar studies at the University of Notre Dame, focuses on a general first-year engineering course. This paper follows the three phases of the iCLAS: (1) Architecting for Collection, (2) Analyzing for Action and (3) Assessing for Improvement. In the first phase, the course is designed and built to be able to capture the data needed to identify the students who show signs of being deemed non-thriving at the end of the semester. The second phase works to determine a method to identify these students who are deemed to be non-thriving at the end of the semester with just four weeks of course data. For the course highlighted in this study, the trigger was less than 80 percent on one-or-more of the first three homework assignments. The students are then notified and boosted with the aim of achieving improved learning outcomes for these students. Finally, the entire process is evaluated in order to determine the method's success. In this study, those students who responded to the boosting efforts achieved higher course performance than those who did not, demonstrating the benefits of conducting a boost effort.