Awarded Pilot Project Uses Innovative Data Platform to Look at Effects of Pandemic on Student Learning Environments
- published: 2020/10/20
- contact: Staff - STEM TRAIL Center
- phone: 402.554.4808
- email: jbuzzell@unomaha.edu
- search keywords:
- student learning environments
- pilot project
- grant
- coronavirus
- COVID-19
A new project funded as part of a pilot grant from the Unizin Data Consortium for $10,000 was awarded to UNO earlier this year to examine how the coronavirus pandemic has impacted student learning environments.
The coronavirus pandemic has led to dramatic increases in online and blended-learning environments, bringing new urgency to the need to better understand how to effectively support student learning in such environments. Led by the Principal Investigator, Tracie Reding, Ph.D., UNO STEM Outreach Coordinator, and College of Education, Health, and Human Sciences, the pilot project evaluates instructor-matched, course-matched student-engagement for courses both in-person and online (fall 2019 and spring 2020).
The project is additionally supported from co-PIs: Christine Cutucache, Ph.D., (Department of Biology, College of Arts and Sciences), Chris Moore, Ph.D., (Department of Physics, College of Arts and Sciences), Neal Grandgenett, Ph.D., (Department of Teacher Education, CEHHS), Jason Buzzell (Information Technology Services ITS and UNO Digital Learning, Casey Nugent (ITS), and Jyotsna Ramanan (ITS).
Data for the project is available from the sponsor, via the Unizin Data Platform (UDP). The UDP allows Reding and team to apply social network analysis (SNA) to determine the types of course-specific interactions, using digital trace data, such as discussion board posts. This information provides an algorithm for effective engagement and retention within the course, be that learner-to-learner, learner-to-instructor, and learner-to-content.
The move to online education and the greater subsequent reliance on EdTech companies has increased privacy concerns. Moreover, it’s well-demonstrated in the literature the need to monitor student interaction within a course to identify potential warning signs of disengagement and likelihood of not completing the course.
Reding and group continue to work toward the next iteration of the project, which will build a bonafide dashboard for instructors to monitor engagement and support students more comprehensively. Ultimately, the longer-term successful implementation will also result in the verification and refinement of a dissemination of innovations model within an undergraduate STEM context that can be replicated, modified, and used in various higher education contexts regarding innovation diffusion.
The coronavirus pandemic has led to dramatic increases in online and blended-learning environments, bringing new urgency to the need to better understand how to effectively support student learning in such environments. Led by the Principal Investigator, Tracie Reding, Ph.D., UNO STEM Outreach Coordinator, and College of Education, Health, and Human Sciences, the pilot project evaluates instructor-matched, course-matched student-engagement for courses both in-person and online (fall 2019 and spring 2020).
The project is additionally supported from co-PIs: Christine Cutucache, Ph.D., (Department of Biology, College of Arts and Sciences), Chris Moore, Ph.D., (Department of Physics, College of Arts and Sciences), Neal Grandgenett, Ph.D., (Department of Teacher Education, CEHHS), Jason Buzzell (Information Technology Services ITS and UNO Digital Learning, Casey Nugent (ITS), and Jyotsna Ramanan (ITS).
Data for the project is available from the sponsor, via the Unizin Data Platform (UDP). The UDP allows Reding and team to apply social network analysis (SNA) to determine the types of course-specific interactions, using digital trace data, such as discussion board posts. This information provides an algorithm for effective engagement and retention within the course, be that learner-to-learner, learner-to-instructor, and learner-to-content.
The move to online education and the greater subsequent reliance on EdTech companies has increased privacy concerns. Moreover, it’s well-demonstrated in the literature the need to monitor student interaction within a course to identify potential warning signs of disengagement and likelihood of not completing the course.
Reding and group continue to work toward the next iteration of the project, which will build a bonafide dashboard for instructors to monitor engagement and support students more comprehensively. Ultimately, the longer-term successful implementation will also result in the verification and refinement of a dissemination of innovations model within an undergraduate STEM context that can be replicated, modified, and used in various higher education contexts regarding innovation diffusion.
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