by: Michael Lopez II
The Ateneo Laboratory for the Learning Sciences (ALLS) has hosted Dr. Valdemar Švábenský, a visiting scholar who obtained his doctorate degree from Masaryk University of the Czech Republic. Dr. Švábenský paid a visit to the Ateneo to collaborate with Dr. Maria Mercedes T Rodrigo on modeling the University’s analytics from its learning management system (LMS). His prior collaborations as part of his postgraduate endeavors were from Sorbonne University and the University of Pennsylvania.
On November 17, 2023, Dr. Švábenský held a discussion with students in Faura Hall to raise the interdisciplinary field of learning analytics research. He first emphasized the importance of educational data mining so that it may leverage practitioners such as instructors and academic authorities to support their respective students. In other words, determining the best practices for learning and teaching purposes are important for assessing student behavior. One of the factors to quantify a student’s performance could be about their GPA (or QPI) and the time it took for them to finish a certain course.
He then voiced out his concern on how algorithmic bias may skew these data on machine learning models predicting student success. The problem in the current literature is that there are countless studies about learners in the United States and other Western countries. Yet the foundation is weak for underrepresented sectors and minorities. Thus, the motivation to diversify demographic groups about predicting student success would be beneficial.
Dr. Rodrigo thanked the scholar for his time allotted here in the country and for imparting his expertise with the students. Besides learning analytics, Dr. Švábenský’s current plans involve cybersecurity pedagogy with the goal of optimizing how students should be trained to combat against cyber-crime attacks.
