ABSTRACT
The COVID-19 pandemic transformed STEM learning environments across U.S. institutions. However, the impact of this pandemic on learning and decision-making in students are yet to be fully understood. It is important to gain insights into student experiences during COVID-19 pandemic so that student and institutional resiliency can be improved during future pandemics. This research is part of a larger nationwide inductive research project with the purpose of developing theories to explain the learning experiences and decisions of undergraduate STEM students during the COVID-19 pandemic. A mixed-methods approach with purposive sampling was utilized to enroll 63 undergraduate STEM students from six U.S institutions. Data was collected through recruitment surveys, academic transcripts, and interviews. One-hour ZOOM interviews, gave research participants the opportunity to narrate their salient STEM learning experiences during the spring 2020 semester. Data was analyzed using the NVivo qualitative analysis software and Microsoft Excel for coding, categorizing, memo-ing, constant comparative analysis, and theme development. Also, Microsoft Excel was used to analyze demographic data from recruitment surveys and GPA data from the academic transcripts. Results from the analysis of 30 coded interview transcripts revealed an emergent theme - Professor-Student Interactions Impact Learning and Adaptation Decisions. The three key categories of this theme are: Professor-Student Interactions and Learning Challenges;Adaptation Decisions;and STEM Performance. The seven categories of Professor-Student Interactions are coded as: Online Instructional Delivery Methods;Professor Caring Attitudes;Professor Leniency;Professor Availability;Student Workloads;Professor Technology Proficiency;and Professor Teaching Resources. Positive professor-student interactions improve student learning experiences. Negative professor-student interactions worsen student learning challenges and are coded as: Illusion of Time, Procrastination;Lack of Focus;Challenge of Asking Questions;Poor Understanding;Poor Quality Assignments;Poor Intermediate Grades;Stresses;and Lowered Motivation. While most research participants experienced high stresses, a few of them experienced low or no stresses. To minimize the impact of COVID-related learning challenges on their STEM learning and performance, research participants made effective adaptation decisions coded as: Refined Scheduling;Alternate Learning Resources;Professor Office Hours;Teaching Assistants;Peer Collaboration;Relaxation Strategies;and Pass/Fail Options. Compared to the fall 2019 GPAs, the improved spring 2020 GPAs of research participants may be partially attributed to professor leniency, pass/fail option, and cheating. Findings indicate that while STEM professors were adjusting to COVID-modified teaching and learning environments, many STEM students were developing a sense of self-discipline, self-teaching, and independence. They relied on both professor and non-professor generated resources to improve their own STEM learning and performance. Lessons learned and best practices for improved professor-student interactions and student adaptation decisions are discussed for potential replication in STEM communities for improved adaptability and resiliency during future pandemics. Future research will focus on quantifying the long-term effect of the COVID-19 pandemic on STEM performance. © American Society for Engineering Education, 2021