Integrated Closed-Loop Learning Analytics Scheme in a First-Year Engineering Course
- Conference
- Location
-
Virtual On line
- Publication Date
-
June 22, 2020
- Start Date
-
June 22, 2020
- End Date
-
June 26, 2021
- Conference Session
- Tagged Division
-
First-Year Programs
- Page Count
-
16
- DOI
-
10.18260/1-2--34836
- Permanent URL
-
https://strategy.asee.org/34836
- Download Count
-
436
Paper Authors
Andrew Charles Bartolini University of Notre Dame
Carson Lee Running
University of Notre Dame
orcid.org/0000-0002-5124-6786
Carson Running is a Graduate Research Assistant studying under the direction of Dr. Thomas Juliano. He received his B.S. and M.S. in Aerospace Engineering in 2015 and 2019, respectively. His scholarship is focused on hypersonic aerodynamics and aerothermodynamics with complementary interests in novel experimental surface-measurement techniques and facility design. Previously, he conducted research as a Student Summer Fellow in the Hypersonic Sciences Branch at the Air Force Research Laboratory under the direction of Dr. Roger Kimmel. Carson is a Graduate Associate for the Kaneb Center for Teaching and Learning at the University of Notre Dame, where he designs, prepares, and delivers workshops on effective teaching strategies and pedagogy for faculty, postdoctoral students, and graduate students. He is also a Graduate Fellow with the Research and Assessment for Learning (ReAL) Design Lab at the University of Notre Dame, where he conducts research to create predictive learning analytics and dynamic driven admissions criteria to better serve underprepared and underserved engineering students.
Xiaojing Duan University of Notre Dame
Xiaojing Duan is the learning platform & analytics architect at the Office of Information Technologies, University of Notre Dame. Her primary responsibilities include building a learning record warehouse to collect data and analyzing the data to gain insights for the enhancement of teaching and learning experience.
G. Alex Ambrose University of Notre Dame
G. Alex Ambrose serves as Director of Learning Research and is the founder of the Research & Assessment for Learning (ReAL) Design Lab at the University of Notre Dame Learning's Kaneb Center for Teaching and Learning. He holds the rank of Full Professor of the Practice with concurrent appointments in the Education, Schooling, & Society and Computing & Digital Technologies Departments. In addition, he is a faculty fellow of the Institute for Educational Initiatives and Notre Dame Initiative for Global Development. In both his research and his teaching, Alex works to advance his mission: to fight for and create the conditions necessary for the liberation of learning and the alleviation of unnecessary anxiety and harm in education, for both students and faculty. Alex envisions his role as that of a learning experience architect, pioneering more inclusive and authentic assessment through technology. His current research focuses on applied learning research, design, and evaluation, including learning analytics, flexible learning spaces, digital portfolios and badges. Alex's work has been published in a range of academic and technology-based journals and has earned him the 2015 Campus Technology Innovator Award as well as recognition by Google, IBM, USAID, and the Bill and Melinda Gates and National Science Foundations. He regularly serves as an international learning ambassador, educational developer, consultant, and evaluator for grants, programs, and universities in South America, North America, the Far East, Europe, and the Middle East.
Abstract
This complete research paper works to tie the processes of identifying students that show signs of potentially being non-thriving at the end of the semester with a strategy to boost these students during the early part of the semester. The work in this paper, which applies the integrated closed-loop learning analytics scheme (iCLAS) that was used in previous similar studies at the University of Notre Dame, focuses on a general first-year engineering course. This paper follows the three phases of the iCLAS: (1) Architecting for Collection, (2) Analyzing for Action and (3) Assessing for Improvement. In the first phase, the course is designed and built to be able to capture the data needed to identify the students who show signs of being deemed non-thriving at the end of the semester. The second phase works to determine a method to identify these students who are deemed to be non-thriving at the end of the semester with just four weeks of course data. For the course highlighted in this study, the trigger was less than 80 percent on one-or-more of the first three homework assignments. The students are then notified and boosted with the aim of achieving improved learning outcomes for these students. Finally, the entire process is evaluated in order to determine the method's success. In this study, those students who responded to the boosting efforts achieved higher course performance than those who did not, demonstrating the benefits of conducting a boost effort.
Bartolini, A. C., & Running, C. L., & Duan, X., & Ambrose, G. A. (2020, June), Integrated Closed-Loop Learning Analytics Scheme in a First-Year Engineering Course Paper presented at 2020 ASEE Virtual Annual Conference Content Access, Virtual On line . 10.18260/1-2--34836
ASEE holds the copyright on this document. It may be read by the public free of charge. Authors may archive their work on personal websites or in institutional repositories with the following citation: © 2020 American Society for Engineering Education. Other scholars may excerpt or quote from these materials with the same citation. When excerpting or quoting from Conference Proceedings, authors should, in addition to noting the ASEE copyright, list all the original authors and their institutions and name the host city of the conference. - Last updated April 1, 2015