Search for: All records

Engaging African American middle school girls in out-of-school-time (OST) Architecture, Engineering, and Construction (AEC) programs can significantly boost their knowledge and awareness of these traditionally male-dominated fields. This study adopts Lent’s Social Cognitive Career Theory (SCCT) and Bandura’s self-efficacy theory to assess the impact of a femalized AEC kinesthetic learning model (fAEC-KLM) on the AEC career knowledge, selfefficacy, and outcome expectations (KSO) of African American middle school girls. Fourteen (14) African American middle school girls from Guilford County, NC, participated in pre- and post-intervention interviews, evaluating how the fAEC-KLM model influenced their AEC career knowledge, self-efficacy, and outcome expectations. Inductive thematic analysis of transcribed interviews using NVIVO qualitative software revealed key components of the fAEC-KLM that impacted KSO. Components such as lectures, peer interactions, and kinesthetic/experiential learning interacted with participants’ learning experiences (prior OST educational programs, familial social support, deficient/adequate mathematical pedagogy, and pre-collegiate engineering education). These factors collectively enhanced participants’ AEC career knowledge, bolstered their self-efficacy, and shaped their outcome expectations. The findings highlight the efficacy of targeted AEC activities within the fAEC-KLM in boosting career knowledge, selfefficacy, and outcome expectations, offering critical insights for developing OST programs that encourage African American middle school girls to pursue careers in AEC fields. These results emphasize the need for such initiatives to reduce the gender gap in STEM and AEC professions, contributing to broader efforts to diversify these vital sectors. 

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. 

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.