Virtual Conference
July 26, 2021
July 26, 2021
July 19, 2022
Educational Research and Methods
Diversity
12
10.18260/1-2--38152
https://peer.asee.org/38152
350
Aparajita Jaiswal is a Ph.D. student in Purdue Polytechnic at Purdue University, West Lafayette. Her research interests are in datascience education, computational thinking, student engagement and motivation in active learning environments.
Joseph A. Lyon is a Ph.D. student in the School of Engineering Education and a M.S. student in the School of Industrial Engineering at Purdue University. He earned a B.S. in Agricultural and Biological Engineering from Purdue University. His research interests include models and modeling, computational thinking, and computation in engineering education.
Viranga Perera is a postdoctoral researcher at Purdue University. He obtained his Ph.D. from Arizona State University in 2017. His research interests are in STEM education and planetary physics.
Alejandra Magana is the W.C. Furnas Professor in Enterprise Excellence in the Department of Computer and Information Technology and an affiliated faculty at the School of Engineering Education at Purdue University. She holds a B.E. in Information Systems, a M.S. in Technology, both from Tec de Monterrey; and a M.S. in Educational Technology and a Ph.D. in Engineering Education from Purdue University. Her research is focused on identifying how model-based cognition in STEM can be better supported by means of expert technological and computing tools such as cyber-physical systems, visualizations, and modeling and simulation tools.
Ellen Gundlach is Managing Director of The Data Mine at Purdue University. She has an MPH degree from Purdue and an M.S. in Physical Chemistry from Ohio State. She enjoys helping students gain skills and explore new opportunities to suit their passions. In addition to Statistics Education, she is especially interested in projects related to Public Health.
Mark Daniel Ward is a Professor of Statistics and (by courtesy) of Agricultural & Biological Engineering, Computer Science, Mathematics, and Public Health at Purdue University. He is also Director of The Data Mine and Interim Co-Director of the Integrative Data Science Initiative. He is especially committed to empowering students from backgrounds that are traditionally underrepresented in the data sciences.
A residential learning community (RLC) is an integration of academic and social settings that assists learners to create meaningful learning experiences. An RLC allows students with similar interests to live and learn together. Living in an RLC improves retention by helping students develop a sense of belonging and disciplinary identity. As such, RLCs can be a solution to student attrition and low graduation rates among college students, which is negatively impacting economic growth across the United States. Developing effective RLCs involves providing authentic contexts to learners allowing them to socialize with mentors and peers while engaging in knowledge construction. In this work-in-progress (WIP) paper we evaluated student experiences in an RLC specific to data science: Data Mine Learning Community (DMLC). The DMLC is an interdisciplinary learning community that welcomes students from diverse backgrounds to live and learn data science skills. We used the situated learning perspective as our theoretical framework. The primary research question for the study was: How do students who are enrolled in the corporate partner cohort of the DMLC describe their social interactions and their learning in the context of the learning community? We used a qualitative research approach to evaluate the experiences of first-year students enrolled in the DMLC. Students enrolled in the corporate partner cohort of the DMLC were asked to voluntarily share their experiences in the form of written reflections as a part of an open-response survey at the end of each semester. To understand student experiences, we conducted a thematic analysis of student reflections after they completed their first semester. We analyzed reflections and we discussed our findings through the lens of the situated learning theory, specifically addressing its three key tenets: authentic context, social interaction, and authentic learning.
Jaiswal, A., & Lyon, J. A., & Perera, V., & Magana, A. J., & Gundlach, E., & Ward, M. D. (2021, July), Work in Progress: Evaluating Student Experiences in a Residential Learning Community: A Situated Learning Perspective Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. 10.18260/1-2--38152
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