More Like this

1. Valuing Diversity and Enacting Inclusion in Engineering (VDEIE): Validity Evidence for a New Scale

   Rambo-Hernandez, K. E.; Atadero, R. A.:; Morris, M.; Park, S.; Casper, A. M.; Pedersen, B. A.; Schwartz, J.; Hensel, R. (December 2021, IJEE International Journal of Engineering Education)

   Ahmad Ibrahim (Ed.)

   The purpose of this paper is to detail the initial validation of a scale to assess engineering students’ attitudes toward the value of diversity in engineering and their intentions to enact inclusive behaviors. In study 1, we administered the scale four times. We subjected the first administration to exploratory factor analysis (EFA), and the remaining three administrations to both confirmatory factor analysis (CFA) and tests of longitudinal measurement invariance (LMI). All tests indicated strong evidence for the internal structure of the factor structure of the survey. The four factors were: engineers should value diversity to (a) fulfill a greater purpose and (b) serve customers better; and engineers should (c) challenge discriminatory behavior and (d) promote a healthy work environment. In study 2, we again assessed the structure of the data as described in study 1 and then used the scale to assess potential differences between undergraduate students who participated in activities designed to promote diversity, equity, and inclusion (DEI) (n=116) and those who did not (n=137). Students in the intervention classes demonstrated a small statistically significant increase in their intention to promote a healthy team environment in reference to the comparison classes. No differences were observed between the classes on the other factors. Future directions and implications are discussed. 

   more » « less
2. 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. 

   more » « less
3. The Continued Development and Validity Testing of an Engineering Design Value-Expectancy Scale (EDVES) for High School Students

   Youssef, S. (August 2022, ASEE Annual Conference & Exposition)

   As more institutions create first year engineering programs that teach an engineering design process, there is a growing desire to prepare students for this coursework in the high school setting. When exposing such a broad population to these ideas, a primary question arises regarding student attitudes toward engineering and how these attitudes develop over time. That is, how does this exposure to engineering design influence student attitudes toward engineering? Moreover, answering this question will allow educators to better understand what motivates students to learn, how much their motivation impacts their overall mastery of these skills, and how these aspects of engineering self-efficacy and engineering design may differ between those who are on a pre-engineering track and those who are not. To begin answering this question, high school students enrolled in the Olathe City school system of Olathe, Kansas completed Engineering Problem-Framing Design Activities (EPDAs) in participating science courses (AP physics, physics, advanced biotechnology, chemistry, honors chemistry, biology, honors biology, and physical science specifically) of the traditional science and engineering academy curriculums offered by the district. Student engineering self-efficacy and motivation was also measured at the beginning and end of their coursework. This was conducted via a new instrument, the Engineering Design Value-Expectancy Scale (EDVES), which includes 38 items across three primary subscales: expectancy of success in, perceived value of, and identification with engineering and design. The development of this tool was presented and discussed in a previous study where the EDVES instrument was analyzed for validity among first-year undergraduate engineering students. In this work, the responses of high school students on the EDVES were analyzed to establish validity in this new population and to begin exploring trends in student responses based on their sub-population. Validity testing was completed via Cook’s validation evidence model with respect to scoring, generalization, and extrapolation evidence. The pre-course EDVES responses obtained were used to complete validation and trend analysis (note that post-course data was not readily available at the time of analysis). 

   more » « less
4. A Family of Instruments to Measure Data Science Attitudes

   https://doi.org/10.1145/3626253.3635525  

   Kerby-Helm, April; Posner, Michael A; Unfried, Alana; Whitaker, Douglas; Bond, Marjorie E; Batakci, Leyla (March 2024, ACM)

   Attitudes play an important role in students’ academic achievement and retention, yet quality tools to measure them are not readily available in the new field of data science. Through funding from the National Science Foundation, we are developing a family of instruments that measure attitudes toward data science in the context of an introductory, college-level course. This poster will showcase preliminary results discussing pilot instruments to assess instructors’ attitudes toward teaching data science and an inventory which captures classroom characteristics. These instruments, based on Expectancy-Value Theory, will enable data science education researchers to evaluate pedagogical innovations and measure instructional effectiveness relating to student attitudes. We invite instructors of data science courses to join in this discussion and to use these instruments for their own data science education research projects. 

   more » « less
5. Consumer perceptions of information features in healthcare service advertisements and attitudes toward advertising

   https://doi.org/10.1108/IJPHM-02-2022-0016  

   Park, Sung-Yeon; Yun, Gi Woong; Cook, Daniel M.; Coppes, Max J. (February 2023, International Journal of Pharmaceutical and Healthcare Marketing)

   Purpose With the increasing dependence on market-based distribution of health-care resources in the USA, spending on health-care service advertisements directly targeting consumers has also increased. Previous research has shown that the ads fail to deliver information deemed essential by regulators. Nevertheless, the attitude of consumers toward health-care service advertising has been more positive than negative. The purpose of this study is to create a taxonomy of advertising information features to better describe the relationships between information features in the advertisements and consumer attitudes toward them. Design/methodology/approach A cross-sectional survey was conducted with 128 health-care consumers in a western state in the USA. Findings Factor analysis generated seven groups of information features. Among them, information features about access, cost and quality of care were rated as most helpful, whereas providers’ clinical qualifications and communication were rated least helpful. The advertising attitude measure was validated to contain two subscales, one regarding health-care service advertising and the other regarding physicians who advertise. People who highly rated the consumerism features had more positive attitudes toward health-care service advertising and people who highly rated provider clinical qualification features had more negative attitudes toward advertising physicians. Originality/value This study made methodological improvements in health-care service advertising research that would be crucial for its theoretical development. It also shed light on consumer characteristics and perceptions about information features that could influence their attitudes toward health-care service advertising. 

   more » « less