ICU NS Forum: Challenges and Opportunities for Educational Data Science in Online Environments

I was invited by the Department of Natural Sciences at International Christian University (ICU) to present at their NS Forum as part of a job application process. There, I talked about my research framed from my learnings during my doctoral and postdoctoral work. I particularly touched heavily on David Joyner's presentation during his visit to Tokyo Tech and Justin Reich's work presented at Learning at Scale 2020 which left a deep impression on me.


Online learning by the numbers

A slide from the ICU presentation

For a copy of relevant materials (e.g., presentation, paper) or any questions you may have, please feel free to reach out to me through the Contact Me gadget on this blog's side bar.

Details

Title: Challenges and Opportunities for Educational Data Science in Online Environments
Authors: May Kristine Jonson Carlon
Venue: ICU NS Forum

Abstract

For more than a decade, online education has been receiving increased attention with the proliferation of massive open online courses and, later, emergency remote teaching. With the digital nature of online education, a plethora of data - from the discussions the students make down to every button click they do on learning management systems - are more easily collected. This opens the possibility of being able to understand better when students are engaged and what behaviors are more productive, among others. Several researchers, powered with big data and recent advancements in artificial intelligence and educational technology, are working on educational data science not just to potentially improve
learning outcomes but also to crack the access problem in education. However, this is not the first-time massive data were used to supposedly solve educational problems. The use of nationwide educational data has led to unwanted phenomena such as students and teachers narrowly tailoring their activities to pass exams, and more unfortunately, widening the gap between the haves and have-nots. This lecture will present firstly what exactly is educational data science. Then, how educational data science was able to live up to its aspirations and consequently lead to issues in the past will be discussed. Finally, how the difference between online and on-site education being more than skin-deep provides us
opportunities to use educational data science to see learning in a different light will be tackled.

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