This post is provided by guest blogger, Samerah Saad, graduate student University of St. Francis, MS Talent Development program. 

Arizmendi et al. (2023) highlights how Learning Management Systems and utilization of digital logs can provide insights to student performance and outcomes. This would be utilized to assess e-learning environments and their ability to understand the unique interaction patterns for the student. Moreover, this would also be used to analyze the data to calculate trends among all class members. This will be helpful to see how long each student is spending on coursework in comparison to the grades they are earning. The authors highlight how essential it is to enhance the learning experience through diverse learning approaches, standardization, instructional strategies, and proper use of technological tools/resources. 

I recommend this article’s approach to put into practice many of the theories circling successful approaches to e-learning. However, there are concerns on how these digital logs can gather information to be utilized effectively in an ethical manner. I am concerned about how thoroughly they will need to dive into student data without privacy concerns. Additionally, just because an individualized student demographic is inputted into the algorithm, I worry about overcoming any stereotypical notions and assess the student fairly. Personalized education was a major selling point but, unfortunately, there was no data supporting the same results for diversified in-person learning. 

Reference:

Arizmendi, C. J., Bernacki, M. L., Raković, M., Plumley, R. D., Urban, C. J., Panter, A. T., Greene, J. A., & Gates, K. M. (2022). Predicting student outcomes using digital logs of learning behaviors: Review, current standards, and suggestions for future work. Behavior Research Methods, 55(6), 3026–3054. https://doi.org/10.3758/s13428-022-01939-9Links to an external site.