Integrated Closed-loop Learning Analytics Scheme in a First Year Experience Course

Comprendiendo el potencial y los desafíos del Big Data en las escuelas y la educación

“…A recent intervention scheme for at-risk college students demonstrates this multiple-component process nicely (albeit not in the very order described here). This scheme, called iCLAS (integrated Closedloop Learning Analytics), aims at recognizing and helping students who are not thriving, as measured by low achievements at an early stage of the course (Syed et al, 2019). While focusing on identifying at-risk students and boosting their success, the authors' main focus was on measuring engagement, which corresponds to our component of defining the data to be collected; the authors operationalized this construct by capturing data about the students' online activity in the learning environment (e.g., logging in and out, clicking on resources, attempting and submitting assignments, amount of time spent on watching course videos, and performance indicators).…”

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

“…A recent example of this effort is by Choi et al [15], who identify at-risk students using a simple metric and provide interventions to those students in one small course. This methodology has been more recently employed in a first-year experience course at the University of Notre Dame [16] where they performed identification and intervention on the entire first-year body of students and repeated it for several semesters. This is the same technique employed in the current study.…”

“…The paper is organized using the integrated Closed-loop Learning Analytics Scheme (iCLAS) developed by Syed et al [16] and shown in Figure 1. Section 4 (Architecting for Collection) describes the the first phase of iCLAS, which focuses on the "design", "build", and "capture" steps.…”

“…Following the work of Syed et al [16], the loop intersects in "evaluate" and "identify" steps to demonstrate that the processes of identifying the students that are deemed non-thriving at the end of the semester will continually evolve with each semester as the process is refined. With each Figure 1.…”

“…This process aims to boost students to have positive learning outcomes by first identifying which students should be boosted using historical learning data and trends to predict non-thriving students based on the student's grades collected in the first phase, notifying these students and then boosting the students. Similar to previous studies conducted in a general first-year course at Notre Dame, the messaging was crafted in order to avoid using negative language or words (such as "at-risk" or "intervention"), but rather more supportive, positive language was used (such as ""improve your performance") [16]. Finally, the students were boosted through the use of a personal action plan that was developed on an individualized basis based on the student's responses.…”