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1. Mendelian or Multifactorial? Current Undergraduate Genetics Assessments Focus on Genes and Rarely Include the Environment

   https://doi.org/10.1128/jmbe.00093-22  

   Schmid, Kelly M.; Lee, Dennis; Weindling, Monica; Syed, Awais; Agyemang, Stephanie-Louise Yacoba; Donovan, Brian; Radick, Gregory; Smith, Michelle K. (December 2022, Journal of Microbiology & Biology Education)

   Wright, L. Kate (Ed.)

   ABSTRACT Undergraduate genetics courses have historically focused on simple genetic models, rather than taking a more multifactorial approach where students explore how traits are influenced by a combination of genes, the environment, and gene-by-environment interactions. While a focus on simple genetic models can provide straightforward examples to promote student learning, they do not match the current scientific understanding and can result in deterministic thinking among students. In addition, undergraduates are often interested in complex human traits that are influenced by the environment, and national curriculum standards include learning objectives that focus on multifactorial concepts. This research aims to discover to what extent multifactorial genetics is currently being assessed in undergraduate genetics courses. To address this, we analyzed over 1,000 assessment questions from a commonly used undergraduate genetics textbook; published concept assessments; and open-source, peer-reviewed curriculum materials. Our findings show that current genetics assessment questions overwhelmingly emphasize the impact of genes on phenotypes and that the effect of the environment is rarely addressed. These results indicate a need for the inclusion of more multifactorial genetics concepts, and we suggest ways to introduce them into undergraduate courses. 

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2. Broadening the Participation of Rural Students in Engineering: Exploring Community Perspectives

   Vaziri, S.L.; Paretti, M.C.; Grohs, J.R.; Baum, L.M.; Lester, M.M.; Newbill, P.L. (July 2020, Zone 1 Conference of the American Society for Engineering Education)

   Interest in increasing both the number and diversity of students enrolling in engineering has resulted in significant research on students’ career choice decisions. Notably, however, while general trends have emerged, many of the models that have been developed focus on majority students. But an increasing body of work on students from a variety of specific demographic groups highlight unique socio-cultural experiences that influence individuals’ career choice decisions. Most relevant to this study, literature on rural students suggests that the lack of high-level STEM courses in rural schools and a desire to stay close to home played key roles in limiting students’ consideration of engineering as a potential career. However, little work has explored how rural communities support and promote engineering as a career choice for their students. Therefore, this study explored the ways in which rural communities provide support to help students make fully informed decisions about engineering as a college major. The findings presented here come from Phase 2 of a three-phase study exploring engineering career choice among rural students. Using interview and focus group data collected from current engineering students in Phase 1, Phase 2 turned to community members, including high school personnel, local industry leaders, members of local governments, and members of key community organizations (e.g., 4-H). Using interviews with 16 participants across 3 communities, we address the following question: What beliefs, experiences, and practices characterize community members or organizations who support or encourage rural students to choose engineering? The interviews explored the participants’ perceptions of their community overall, resources that helped students explore postsecondary options, barriers students faced to enrolling in postsecondary education/engineering, understanding of engineering as a field both generally and for students from that community, and ways Virginia Tech can be a better community partner and fulfill its mission as a public institution. This project aims to broaden participation in engineering by gaining a holistic understanding of the communities that effectively support engineering major choice for rural students and provide contextual methods of increasing support for students from these rural areas. 

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3. Best 2019 PIC III Paper: Do They Understand Your Language? Access Their Fluency with Vector Representation

   https://doi.org/10.18260/1-2--34205  

   Davishahl, Eric; Haskell, Todd; Davishahl, Jill; Singleton, Lee; Goodridge, Wade (June 2020, 2020 ASEE Virtual Annual Conference Content Access)

   In teaching mechanics, we use multiple representations of vectors to develop concepts and analysis techniques. These representations include pictorials, diagrams, symbols, numbers and narrative language. Through years of study as students, researchers, and teachers, we develop a fluency rooted in a deep conceptual understanding of what each representation communicates. Many novice learners, however, struggle to gain such understanding and rely on superficial mimicry of the problem solving procedures we demonstrate in examples. The term representational competence refers to the ability to interpret, switch between, and use multiple representations of a concept as appropriate for learning, communication and analysis. In engineering statics, an understanding of what each vector representation communicates and how to use different representations in problem solving is important to the development of both conceptual and procedural knowledge. Science education literature identifies representational competence as a marker of true conceptual understanding. This paper presents development work for a new assessment instrument designed to measure representational competence with vectors in an engineering mechanics context. We developed the assessment over two successive terms in statics courses at a community college, a medium-sized regional university, and a large state university. We started with twelve multiple-choice questions that survey the vector representations commonly employed in statics. Each question requires the student to interpret and/or use two or more different representations of vectors and requires no calculation beyond single digit integer arithmetic. Distractor answer choices include common student mistakes and misconceptions drawn from the literature and from our teaching experience. We piloted these twelve questions as a timed section of the first exam in fall 2018 statics courses at both Whatcom Community College (WCC) and Western Washington University. Analysis of students’ unprompted use of vector representations on the open-ended problem-solving section of the same exam provides evidence of the assessment’s validity as a measurement instrument for representational competence. We found a positive correlation between students’ accurate and effective use of representations and their score on the multiple choice test. We gathered additional validity evidence by reviewing student responses on an exam wrapper reflection. We used item difficulty and item discrimination scores (point-biserial correlation) to eliminate two questions and revised the remaining questions to improve clarity and discriminatory power. We administered the revised version in two contexts: (1) again as part of the first exam in the winter 2019 Statics course at WCC, and (2) as an extra credit opportunity for statics students at Utah State University. This paper includes sample questions from the assessment to illustrate the approach. The full assessment is available to interested instructors and researchers through an online tool. 

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4. Do They Understand Your Language? Assess Their Fluency with Vector Representations

   Davishahl, E.; Haskell, T. R.; Davishahl, J.; Singleton, L.; Goodridge, W. H. (June 2019, ASEE Annual Conference proceedings)

   In teaching mechanics, we use multiple representations of vectors to develop concepts and analysis techniques. These representations include pictorials, diagrams, symbols, numbers and narrative language. Through years of study as students, researchers, and teachers, we develop a fluency rooted in a deep conceptual understanding of what each representation communicates. Many novice learners, however, struggle to gain such understanding and rely on superficial mimicry of the problem solving procedures we demonstrate in examples. The term representational competence refers to the ability to interpret, switch between, and use multiple representations of a concept as appropriate for learning, communication and analysis. In engineering statics, an understanding of what each vector representation communicates and how to use different representations in problem solving is important to the development of both conceptual and procedural knowledge. Science education literature identifies representational competence as a marker of true conceptual understanding. This paper presents development work for a new assessment instrument designed to measure representational competence with vectors in an engineering mechanics context. We developed the assessment over two successive terms in statics courses at a community college, a medium-sized regional university, and a large state university. We started with twelve multiple-choice questions that survey the vector representations commonly employed in statics. Each question requires the student to interpret and/or use two or more different representations of vectors and requires no calculation beyond single digit integer arithmetic. Distractor answer choices include common student mistakes and misconceptions drawn from the literature and from our teaching experience. We piloted these twelve questions as a timed section of the first exam in fall 2018 statics courses at both Whatcom Community College (WCC) and Western Washington University. Analysis of students’ unprompted use of vector representations on the open-ended problem-solving section of the same exam provides evidence of the assessment’s validity as a measurement instrument for representational competence. We found a positive correlation between students’ accurate and effective use of representations and their score on the multiple choice test. We gathered additional validity evidence by reviewing student responses on an exam wrapper reflection. We used item difficulty and item discrimination scores (point-biserial correlation) to eliminate two questions and revised the remaining questions to improve clarity and discriminatory power. We administered the revised version in two contexts: (1) again as part of the first exam in the winter 2019 Statics course at WCC, and (2) as an extra credit opportunity for statics students at Utah State University. This paper includes sample questions from the assessment to illustrate the approach. The full assessment is available to interested instructors and researchers through an online tool. 

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5. Survey Development to Measure the Gap Between Student Awareness, Literacy and Action to Address Human Caused Climate Change

   Shealy, T.; Godwin, A; Gardner, H. (June 2017, ASEE Annual Conference proceedings)

   The United Nation’s Sustainable Development Goals state climate change could irreversibly affect future generations and is one of the most urgent issues facing society. To date, most education research on climate change examines middle and high school students’ knowledge without considering the link between understanding and interest to address such issues in their career. In research on students’ attitudes about sustainability, we found that half of first-year college engineering students, in our nationally representative sample of all college students at 4-year institutions (n = 937), do not believe climate change is caused by humans. This lack of belief in human-caused climate change is a significant problem in engineering education because our results also indicate engineering students who do not believe in human caused climate change are less likely to want to address climate change in their careers. This dismal finding highlights a need for improving student understanding and attitudes toward climate change in order to produce engineers prepared and interested in solving complex global problems in sustainability. To advance understanding about students’ understanding of climate change and their agency to address the issue, we developed the CLIMATE survey to measure senior undergraduate engineering students’ Climate change literacy, engineering identity, career motivations, and agency through engineering. The survey was designed for students in their final senior design, or capstone course, just prior to entering the workforce. We developed the survey using prior national surveys and newly written questions categorized into six sections: (1) career goals and motivation, (2) college experiences, (3) agency, (4) climate literacy, (5) people and the planet, and (6) demographic information. We conducted focus groups with students to establish face and content validity of the survey. We collected pilot data with 200 engineering students in upper-level engineering courses to provide validity evidence for the use of these survey items to measure students and track changes across the undergraduate curriculum for our future work. In this paper, we narrate the development of the survey supported by literature and outline the next step for further validation and distribution on a national scale. Our intent is to receive feedback and input about the questions being asked and the CLIMATE instrument. Our objective is to share the nationally representative non-identifiable responses (the estimated goal is 4,000 responses) openly with education researchers interested in students understanding about climate change, their engineering identity, career motivations, and agency through engineering. Ultimately, we want this research to become a catalyst for teaching about topics related to climate change in engineering and its implications for sustainability. 

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