skip to main content

Explore Research Products in the NSF-PAR

  • NSF Public Access
  • Search Results
  • An Examination of Professor-Student Interactions, Stem Learning Challenges, and Student Adaptation Decisions During Covid-19 Pandemic
Title: An Examination of Professor-Student Interactions, Stem Learning Challenges, and Student Adaptation Decisions During Covid-19 Pandemic
Professor-student interactions influence student learning experiences and performance. The COVID pandemic transformed STEM learning environments across U.S. institutions; however, its impact on STEM professor-student interactions and STEM student learning experiences are yet to be understood. The purpose of this nationwide inductive research study is to examine the impact of COVID-19 on professor-student interactions, undergraduate STEM student learning, and STEM student performance. To achieve this, a qualitative method is adopted and purposive sampling is utilized to enroll 63 STEM students from six U.S institutions. Data is collected through one-hour ZOOM interviews, giving students the opportunity to narrate their STEM learning experiences and performance during the COVID-19 pandemic. The data is analyzed using the NVIVO qualitative analysis software for coding, categorizing, memo-ing, and constant comparative analysis. Results reveal emergent codes on the STEM professor-student interactions to include professor leniency, caring attitude, availability, communication, instruction style, teaching resources, technology literacy, camera on/off requirements, live/recorded sessions, time zone, and student workload. Limited positive impacts on student learning include improved familiarity with alternate STEM learning resources and development of virtual learning soft skills. Negative learning experiences are extensive and coded as: poor comprehension, keeping up, overdrive, isolation, lowered motivation, schedule conflicts, and anxiety. Consequently, students made adaptation decisions coded as: alternate learning sources, refined scheduling, community support, preferring teaching assistants, working out, reporting professors, procrastination, and tuning out. While proactive students and students with prior virtual learning experiences improved or maintained their grades, many students opted for the pass/fail grade or complete withdrawal due to poor STEM learning and performance. Findings indicate that while STEM professors were adjusting to modified teaching environments, many STEM students were developing a sense of independence, self-study, and peer reliance to improve their own STEM understanding and performance with minimal reliance on STEM professors. Lessons learned and best practices for professor-student interactions and student learning are recommended for potential replication in STEM communities for improved adaptability and resiliency during future pandemics. Future research will focus on measuring the effect of best practices on professor-student interactions, student learning experiences, and performance.  more » « less
Award ID(s):
2028811 1845979
NSF-PAR ID:
10410697
Author(s) / Creator(s):
; ; ; ; ;
Editor(s):
Miller, Eva
Date Published:
Journal Name:
ASEE annual conference exposition
ISSN:
2153-5965
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ; ( , ASEE annual conference exposition)
    Miller, Eva (Ed.)
    The COVID-19 pandemic disrupted global educational systems with institutions transitioning to e-learning. Undergraduate STEM students complained about lowered motivation to learn and complete STEM course requirements. To better prepare for more effective STEM education delivery during high-risk conditions such as pandemics, it is important to understand the learning motivation challenges (LMCs) experienced by students. As part of a larger national research study investigating decision-making in undergraduate STEM students during COVID-19, the purpose of this research is to examine LMCs experienced by undergraduate STEM students. One hundred and ninety students from six U.S. institutions participated in Qualtrics-based surveys. Utilizing a five-point Likert scale, respondents ranked the extent to which they agreed to LMC statements. Using Qualtrics Data Analysis tools and MS Excel, data from 130 useable surveys was analyzed utilizing descriptive and inferential statistics. Results revealed that regardless of classification, GPA, age, or race, STEM students experienced LMCs. The top five LMCs were: (1) Assignment Overloads; (2) Lack of In-Person Peer Interactions; (3) Uncaring Professors; (4) Lack of In-Person Professor Interactions; and (5) Lack of In-Person Laboratory Experiences. Significant relationships existed between three characteristics (GPA, classification, and age) and few LMCs to include assignment overloads. Students tended to attribute lowered motivation to Institutional and Domestic challenges which were typically out of their control, rather than to Personal challenges which were typically within their control. Crosstab analysis suggested that Sophomores, Asians, as well as students with GPAs between 2.00 and 2.49 and aged 41 to 50 years may be the most vulnerable due to higher dependence on traditional in-person STEM educational environments. Early identification of the most vulnerable students should be quickly followed by interventions. Increased attention towards sophomores may reduce exacerbation of potential sophomore slump and middle-child syndrome. All STEM students require critical domestic, institutional, and personal resources. Institutions should strengthen students’ self-regulation skills and provide increased opportunities for remote peer interactions. Training of faculty and administrators is critical to build institutional capacity to motivate and educate STEM students with diverse characteristics in e-learning environments. Pass/fail policies should be carefully designed and implemented to minimize negative impacts on motivation. Employers should expand orientation and mentoring programs for entry-level employees, particularly for laboratory-based tasks. Research is needed to improve the delivery of STEM laboratory e-learning experiences. Findings inform future research, as well as best practices for improved institutional adaptability and resiliency. These will minimize disruptions to student functioning and performance, reduce attrition, and strengthen progression into the STEM workforce during high-risk conditions such as pandemics. With caution, findings may be extended to non-STEM and non-student populations. 
    more » « less
  2. ; ; ; ; ( , ASEE annual conference exposition)
    Miller, Eva (Ed.)
    The recent outbreak of COVID-19, considered as being a lethal pandemic by the World Health Organization, has caused profound changes in the educational system within the U.S and across the world. Overnight, universities and their educators had to switch to a largely online teaching format, which challenged their capacity to deliver learning content effectively to STEM students. Students were forced to adapt to a new learning environment in the midst of challenges in their own lives due to the COVID-19 effects on society and professional expectations. The main purpose of this paper is to investigate faculty perceptions of STEM student experiences during COVID-19. Through a qualitative methodology consisting of one-hour zoom interviews administered to 32 STEM faculty members from six U.S. Universities nationwide, faculty narratives regarding student and faculty experiences during COVID-19 were obtained. The qualitative research approach involved identifying common themes across faculty experiences and views in these narratives. Some of the categories of emerging themes associated with faculty perceptions on student and faculty experiences included: student struggles and challenges, student cheating and the online environment, faculty and student adaptability, faculty and student needs and support, and university resources and support. Best practices to facilitate online teaching and learning employed by STEM faculty were also discussed. Key findings revealed that students and faculty had both positive and negative experiences during COVID-19. Additionally, there was a greater need for consistent policies to improve the online student learning experiences. Recommendations to improve STEM student experiences include increased institutional resources and collaboration between faculty and the university administrators to provide a coherent online learning environment. Preliminary findings also provide insights to enhance institutional adaptability and resilience for improving STEM student experiences during future pandemics. Future research should continue to explore institutional adaptation strategies that enhance STEM student learning during pandemics. 
    more » « less
  3. ; ; ; ; ( , ASEE annual conference exposition)
    Miller, Eva (Ed.)
    COVID-19 is a continuing global pandemic causing significant changes and modifications in the ways we teach and learn here in the U.S as well as around the world. Most universities, faculty members, and students modified their learning system by incorporating significant online or mixed learning methods/modes to reduce in person contact time and to reduce the spread of the virus. Universities, faculty and students were challenged as they adapted to new learning modules, strategies and approaches. This adaption started in the Spring of 2020 and has continued to date through the Spring of 2022. The main objective of this project was to investigate faculty perception of STEM student experiences and behavior during the Fall 2020 semester as compared to the Spring 2020 semester as COVID-19 impacts were prolonged. Through a qualitative methodology of zoom interviews administered to 32 STEM faculty members across six U.S. Universities nationwide and a theming scheme, the opinion and narratives of these faculty members were garnered in a round one and round two sets of interviews, in Summer 2020 and then in Spring 2021 (following the semesters of interest). Some of the main new themes that were detected in faculty interviews during the Fall 2020 semester and which reflect faculty perceptions are represented as follow: COVID-19 impact on student and faculty motivation, COVID-19 impacts on labs and experiential learning, COVID-19 impact on mental health, COVID-19 impact on STEM students' involvement in STEM experiential learning opportunities and research. Other previous themes detected and which are revisited to analyze major differences with those themes obtained during the Spring 2020 are presented and not limited to: extra efforts from professors, student cheating behavior, cheating factors and prevention, student behavioral and performance changes, student struggles and challenges, University response and efforts to the COVID-19 pandemic. We explored the differences in these themes between the semesters to look at noticed adaptations and modifications. Presented will also be recommendations to improve student and faculty motivation along with strategies to enhance the student learning experience during the COVID-19 pandemic. We report on common findings and suggest future strategies. 
    more » « less
  4. ; ; ; ; ; ; ( , ASEE annual conference proceedings)
    Our team has developed Low-Cost Desktop Learning Modules (LCDLMS) as tools to study transport phenomena aimed at providing hands-on learning experiences. With an implementation design embedded in the community of inquiry framework, we disseminate units to professors across the country and train them on how to facilitate teacher presence in the classroom with the LC-DLMs. Professors are briefed on how create a homogenous learning environment for students based on best-practices using the LC-DLMs. By collecting student cognitive gain data using pre/posttests before and after students encounter the LC-DLMs, we aim to isolate the variable of the professor on the implementation with LC-DLMs. Because of the onset of COVID-19, we have modalities for both hands-on and virtual implementation data. An ANOVA whereby modality was grouped and professor effect was the independent variable had significance on the score difference in pre/posttest scores (p<0.0001) and on posttest score only (p=0.0004). When we divide out modality between hands-on and virtual, an ANOVA with an F- test using modality as the independent variable and professor effect as the nesting variable also show significance on the score difference between pre and posttests (p-value=0.0236 for hands- on, and p-value=0.0004 for virtual) and on the posttest score only (p-value=0.0314 for hands-on, and p-value<0.0001 for virtual). These results indicate that in all modalities professor had an effect on student cognitive gains with respect to differences in pre/posttest score and posttest score only. Future will focus on qualitative analysis of features of classrooms yield high cognitive gains in undergraduate engineering students. 
    more » « less
  5. ; ; ; ; ; ( , ASEE annual conference)
    Our team has developed Low-Cost Desktop Learning Modules (LCDLMS) as tools to study transport phenomena aimed at providing hands-on learning experiences. With an implementation design embedded in the community of inquiry framework, we disseminate units to professors across the country and train them on how to facilitate teacher presence in the classroom with the LC-DLMs. Professors are briefed on how create a homogenous learning environment for students based on best-practices using the LC-DLMs. By collecting student cognitive gain data using pre/posttests before and after students encounter the LC-DLMs, we aim to isolate the variable of the professor on the implementation with LC-DLMs. Because of the onset of COVID-19, we have modalities for both hands-on and virtual implementation data. An ANOVA whereby modality was grouped and professor effect was the independent variable had significance on the score difference in pre/posttest scores (p<0.0001) and on posttest score only (p=0.0004). When we divide out modality between hands-on and virtual, an ANOVA with an Ftest using modality as the independent variable and professor effect as the nesting variable also show significance on the score difference between pre and posttests (p-value=0.0236 for handson, and p-value=0.0004 for virtual) and on the posttest score only (p-value=0.0314 for hands-on, and p-value<0.0001 for virtual). These results indicate that in all modalities professor had an effect on student cognitive gains with respect to differences in pre/posttest score and posttest score only. Future will focus on qualitative analysis of features of classrooms yield high cognitive gains in undergraduate engineering students. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email