Virtual
April 16, 2021
April 16, 2021
April 17, 2021
Workshops and Posters
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10.18260/1-2--38274
https://peer.asee.org/38274
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Hongye Liu joined the Illinois Department of Computer Science after years of research experience in Biomedical informatics primarily in the Boston Longwood Medical area including Harvard Medical School and its affiliated hospitals. She received her B. E. in Precision Machinery and Instrumentation from the Univ of Science and Technology of China and her PhD from MIT in the area of computer aided design for 3-D Printing. Dr. Liu was driven by the interest of helping cure diseases and have done research in diverse Data Science related areas such as Bioinformatics, Computational Biology, Biostatistics, and Machine learning.
Over a 4-year period of encountering/interacting with students, reviewing academic works and college teaching, she discovered her passion for teaching undergraduate students and training next generation of computer scientists and data-centered professionals.
She is compassionate about helping undergraduate students do research and mentoring underrepresented students. Her research interests are Biomedical applications that involve large high dimensional data analysis and machine learning and data-driven education improvement for underrepresented students.
Dr Amos joined the Bioengineering Department at the University of Illinois in 2009 and is currently a Teaching Associate Professor in Bioengineering and an Adjunct Associate Professor in Educational Psychology. She received her B.S. in Chemical Engineering at Texas Tech and Ph.D. in Chemical Engineering from University of South Carolina. She completed a Fulbright Program at Ecole Centrale de Lille in France to benchmark and help create a new hybrid masters program combining medicine and engineering and also has led multiple curricular initiative in Bioengineering and the College of Engineering on several NSF funded projects.
Zhilin Zhang is a 5-year BS-MS student in Computer Science at the University of Illinois at Urbana-Champaign (UIUC). His research interests are in Human-Computer Interaction and Learning Sciences. He studies, designs, and builds intelligent systems to support scalable and accessible teaching and learning through a computational lens.
Lawrence Angrave is an award winning Fellow and Teaching Professor at the department of computer science at the University of Illinois at Urbana-Champaign (UIUC). His interests include (but are not limited to) joyful teaching, empirically-sound educational research, campus and online courses, computer science, engaging underrepresented students, improving accessibility and creating novel methods that encourage new learning opportunities and foster vibrant learning communities.
Among all college students, students with disabilities are particularly at risk due to a high percentage of underreporting. We conducted a survey across several large courses in engineering and computing at the University of Illinois at Urbana-Champaign to identify course components that engage students with and without disabilities. The survey collected students’ disability status, demographics information, and their usability and satisfaction with more than ten types of course modalities including live Zoom lectures, recordings of lectures, small group discussion, instructor notes, transcripts of lectures, discussion boards etc. The study spans 4 different departments with a total enrollment of 1800 students and had 220 respondents. The survey was followed by semi-structured interviews for selected students to delve deeper into reasons behind the quantitative information. We were motivated to identify course improvements for all students but also greater equity for students with disability. For the semi-structured interviews, we recruited a diverse group of 19 students out of the 220 students who took the survey. The 9 students who participated in the interview included students with disability (5 students) and students without disability (4 students) with diversity in gender (4 Male, 2 Female, 3 Non-Binary) and race (3 Mixed race, 4 White, 2 Asian).The semi-structured interviews focused on identifying what students liked and disliked about various modalities and representations and whether having multiple modalities and representations influenced their study habits and motivation to study. Preliminary results show that students with disabilities prefer live interactions in small groups, recorded lectures, and instructor notes/slides that they can engage with offline, while students without disabilities prefer the live lecture and textbook readings. Through the interviews, we found that few students feel that having multiple representations can cause them to procrastinate the learning and reduce the motivation to study but many students prefer having multiple means of representations as it helps them develop positive attitude towards the courses and makes studying less daunting. These results demonstrate the importance of multiple resources, supporting Universal Design Principles.
Liu, H., & Amos, J. R., & Vanwani, K., & Zhang, Z., & Angrave, L. (2021, April), Qualitative Analysis of college students’ perception of multiple representations and modalities in courses Paper presented at 2021 Illinois-Indiana Regional Conference, Virtual. 10.18260/1-2--38274
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