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1. Examining the Structural Validity of the CD-RISC among Engineering Students

   Mr. Adurangba Victor Oje, Dr. Nathaniel ( April 2020 , Zone 1 Conference of the American Society for Engineering Education)

   null (Ed.)

   This work in progress study examines the structural validation of the Connor-Davidson Resilience Scale (CD-RISC). Resilience, an ability to respond positively to challenging situations, is an essential psychological attribute in responding to stressors. Students often encounter stressful situations that could influence their motivation to remain and succeed in an engineering degree. Developing and strengthening resiliency among engineering students is essential for their academic success in engineering. Participants included 150 undergraduate students enrolled in a foundational engineering course who completed an online survey of the resilience measure. A confirmatory factor analysis was performed to examine the structural validity evidence of the CD- RISC. Model fitness statistics based on CFI, TLI, RMSEA indicated that a five-factor model of the CD-RISC is acceptable. Convergent validity and discriminant evidence were examined using the AVE and MSV estimates. The analysis indicated some concerns with the validity evidence of the instrument. Implications of findings and future directions are discussed. 

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2. Religiosity and Social Support Predict Resilience in Older Adults After a Flood

   https://doi.org/10.1177/00914150221088543  

   Cherry, Katie E. ; Calamia, Matthew R. ; Elliott, Emily M. ; McKneely, Katelyn J. ; Nguyen, Quyen P. ; Loader, Cayman A. ; Miller, Luke R. ; Sampson, Laura ; Galea, Sandro ( March 2022 , The International Journal of Aging and Human Development)

   In this study, we examined religiosity and social support as predictors of resilience after a devastating flood. Three flood exposure groups of primarily middle-aged and older adults were compared: (1) non-flooded adults as controls, (2) once-flooded adults with structural damage to homes and property in the 2016 flood, and (3) twice-flooded adults who had relocated inland because of prior catastrophic losses in the 2005 Hurricanes Katrina and Rita and then flooded again in 2016. Resilience was assessed using the Connor-Davidson Resilience Scale (CD-RISC). Correlation analyses confirmed that older age was correlated with higher religiosity, charitable work done for others, and resilience. Regression analyses indicated that religious beliefs and coping, social support, and charitable work done for others were associated with higher levels of resilience, whereas flood damage was unrelated to resilience. Implications for current views on post-disaster adversity and resilience in later life are discussed.

    

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3. The Development of a Measure of Engineering Identity

   https://doi.org/10.18260/p.26122  

   Godwin, Allison ( January 2016 , ASEE Annual Conference & Exposition)

   Measures of subject-related role identities in physics and math have been developed from research on the underlying constructs of identity in science education. The items for these measures capture three constructs of identity: students’ interest in the subject, students’ feeling of recognition by others, and students’ beliefs about their performance/competence in the subject area. In prior studies with late secondary and early post-secondary students, participants did not distinguish between performance beliefs (e.g., believing that they can do well in a particular subject) and competence beliefs (e.g., believing that they can understand a particular subject); therefore, performance/competence beliefs are measured as a single construct. These validated measures have been successful in predicting STEM career choices including physics, math, and engineering. Based on these measures of identity, literature on engineering identity, and my prior work on understanding engineering choice and belongingness through students’ science and math identities at the transition from high school to college, I developed a set of new engineering identity measures that capture and overall identification as an engineer, future engineering career identification, and students’ engineering-related interest, recognition, and performance/competence beliefs. I conducted a pilot survey of 371 first-year engineering students at three institutions within the U.S. during the spring semester of 2015. An exploratory factor analysis (EFA) was performed to examine the underlying structure of the piloted questions about students’ engineering identity. The measures loaded on three separate constructs that were consistent with the hypothesized constructs of interest, performance/competence and recognition. The developed items were used in a subsequent study deployed in the fall semester of 2015 that measured more than 2500 first-year engineering students’ attitudes and beliefs at four institutions within the U.S. The data on engineering identity measures from this second survey were analyzed using confirmatory factor analysis (CFA). The results indicated that the developed measures do extract a significant portion of the average variance in the latent constructs and the internal consistency of the measures (Cronbach’s α) falls within the acceptable and better range. The development of these items provides ways for engineering education researchers to more deeply explore the underlying self-beliefs in students’ engineering identity formation through quantitative measures with strong evidence for validity. 

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4. Board 90: EAGER: Measuring Student Support in STEM: Insights from Year 2

   Lee, W. C. ; Knight, D. B. ; Godwin, A. ; Hall, J. L. ; Verdín, D. ( June 2019 , ASEE Annual Conference & Exposition)

   The purpose of the project is to identify how to measure various types of institutional support as it pertains to underrepresented and underserved populations in colleges of engineering and science. We are grounding this investigation in the Model of Co-Curricular Support, a conceptual framework that emphasizes the breadth of assistance currently used to support undergraduate students in engineering and science. The results from our study will help prioritize the elements of institutional support that should appear somewhere in a college’s suite of support efforts to improve engineering and science learning environments and design effective programs, activities, and services. Our poster will present: 1) an overview of the instrument development process; 2) evaluation of the prototype for face and content validity from students and experts; and 3) instrument revision and data collection to determine test validity and reliability across varied institutional contexts. In evaluating the initial survey, we included multiple rounds of feedback from students and experts, receiving feedback from 46 participants (38 students, 8 administrators). We intentionally sampled for representation across engineering and science colleges; gender identity; race/ethnicity; international student status; and transfer student status. The instrument was deployed for the first time in Spring 2018 to the institutional project partners at three universities. It was completed by 722 students: 598 from University 1, 51 from University 2, and 123 from University 3. We tested the construct validity of these responses using a minimum residuals exploratory factor analysis and correlation. A preliminary data analysis shows evidence of differences in perception on types of support college of engineering and college of science students experience. The findings of this preliminary analysis were used to revise the instrument further prior to the next round of testing. Our target sample for the next instrument deployment is 2,000 students, so we will survey ~13,000 students based on a 15% anticipated response rate. Following data collection, we will use confirmatory factor analysis to continue establishing construct validity and report on the stability of constructs emerging from our piloting on a new student sample(s). We will also investigate differences across these constructs by subpopulations of students. 

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5. Investigating bifactor modeling of biology undergraduates’ task values and achievement goals across semesters.

   https://doi.org/10.1037/edu0000803  

   Greene, Jeffrey A. ; Bernacki, Matthew L. ; Plumley, Robert D. ; Kuhlmann, Shelbi L. ; Hogan, Kelly A. ; Evans, Mara ; Gates, Kathleen M. ; Panter, Abigail T. ( August 2023 , Journal of Educational Psychology)

   Undergraduate science, technology, engineering, and mathematics (STEM) students’ motivations have a strong influence on whether and how they will persist through challenging coursework and into STEM careers. Proper conceptualization and measurement of motivation constructs, such as students’ expectancies and per- ceptions of value and cost (i.e., expectancy value theory [EVT]) and their goals (i.e., achievement goal theory [AGT]), are necessary to understand and enhance STEM persistence and success. Research findings suggest the importance of exploring multiple measurement models for motivation constructs, including traditional con- firmatory factor analysis, exploratory structural equation models (ESEM), and bifactor models, but more research is needed to determine whether the same model fits best across time and context. As such, we mea- sured undergraduate biology students’ EVT and AGT motivations and investigated which measurement model best fit the data, and whether measurement invariance held, across three semesters. Having determined the best- fitting measurement model and type of invariance, we used scores from the best performing model to predict biology achievement. Measurement results indicated a bifactor-ESEM model had the best data-model fit for EVT and an ESEM model had the best data-model fit for AGT, with evidence of measurement invariance across semesters. Motivation factors, in particular attainment value and subjective task value, predicted small yet statistically significant amounts of variance in biology course outcomes each semester. Our findings provide support for using modern measurement models to capture students’ STEM motivations and potentially refine conceptualizations of them. Such future research will enhance educators’ ability to benevolently monitor and support students’ motivation, and enhance STEM performance and career success. 

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