More Like this

1. "I'm looking at you, you're a perfectly good person …”: Describing non-apparent disability in engineering

   https://doi.org/https://strategy.asee.org/36059  

   Zongrone, C. ; McCall, C. ; Paretti, M. C. ; Shew, A. ; Simmons, D. R. ; McNair, L. D. ( January 2021 , Collaborative Network for Engineerign and Computing Diversity)

   In recent years, studies in engineering education have begun to intentionally integrate disability into discussions of diversity, inclusion, and equity. To broaden and advocate for the participation of this group in engineering, researchers have identified a variety of factors that have kept people with disabilities at the margins of the field. Such factors include the underrepresentation of disabled individuals within research and industry; systemic and personal barriers, and sociocultural expectations within and beyond engineering education-related contexts. These findings provide a foundational understanding of the external and environmental influences that can shape how students with disabilities experience higher education, develop a sense of belonging, and ultimately form professional identities as engineers. Prior work examining the intersections of disability identity and professional identity is limited, with little to no studies examining the ways in which students conceptualize, define, and interpret disability as a category of identity during their undergraduate engineering experience. This lack of research poses problems for recruitment, retention, and inclusion, particularly as existing studies have shown that the ways in which students perceive and define themselves in relation to their college major is crucial for the development of a professional engineering identity. Further, due to variation in defining ‘disability’ acrossmore »national agencies (e.g., the National Institutes of Health, and the Department of Justice) and disability communities (with different models of disability), the term “disability” is broad and often misunderstood, frequently referring to a group of individuals with a wide range of conditions and experiences. Therefore, the purpose of this study is to gain deeper insights into the ways students define disability and disability identity within their own contexts as they develop professional identities. Specifically, we ask the following research question: How do students describe and conceptualize non-apparent disabilities? To answer this research question, we draw from emergent findings from an on-going grounded theory exploration of professional identity formation of undergraduate civil engineering students with disabilities. In this paper, we focus our discussion on the grounded theory analyses of 4 semi-structured interviews with participants who have disclosed a non-apparent disability. Study participants consist of students currently enrolled in undergraduate civil engineering programs, students who were initially enrolled in undergraduate civil engineering programs and transferred to another major, and students who have recently graduated from a civil engineering program within the past year. Sensitizing concepts emerged as findings from the initial grounded theory analysis to guide and initiate our inquiry: 1) the medical model of disability, 2) the social model of disability, and 3) personal experience. First, medical models of disability position physical, cognitive, and developmental difference as a “sickness” or “condition” that must be “treated”. From this perspective, disability is perceived as an impairment that must be accommodated so that individuals can obtain a dominantly-accepted sense of normality. An example of medical models within the education context include accommodations procedures in which students must obtain an official diagnosis in order to access tools necessary for academic success. Second, social models of disability position disability as a dynamic and fluid identity that consists of a variety of physical, cognitive, or developmental differences. Dissenting from assumptions of normality and the focus on individual bodily conditions (hallmarks of the medical model), the social model focuses on the political and social structures that inherently create or construct disability. An example of a social model within the education context includes the universal design of materials and tools that are accessible to all students within a given course. In these instances, students are not required to request accommodations and may, consequently, bypass medical diagnoses. Lastly, participants referred to their own life experiences as a way to define, describe, and consider disability. Fernando considers his stutter to be a disability because he is often interrupted, spoken over, or silenced when engaging with others. In turn, he is perceived as unintelligent and unfit to be a civil engineer by his peers. In contrast, David, who identifies as autistic, does not consider himself to be disabled. These experiences highlight the complex intersections of medical and social models of disability and their contextual influences as participants navigate their lives. While these sensitizing concepts are not meant to scope the research, they provide a useful lens for initiating research and provides markers on which a deeper, emergent analysis is expanded. Findings from this work will be used to further explore the professional identity formation of undergraduate civil engineering students with disabilities. These findings will provide engineering education researchers and practitioners with insights regarding the ways individuals with disabilities interpret their in- and out-of-classroom experiences and navigate their disability identities. For higher education, broadly, this work aims to reinforce the complex and diverse nature of disability experience and identity, particularly as it relates to accommodations and accessibility within the classroom, and expand the inclusiveness of our programs and institutions.« less
2. Mastery Learning in Undergraduate Engineering Courses: A Systematic Review

   Perez Leon, C. ; Verdin, D. ( August 2022 , Zone 1 Conference of the American Society for Engineering Education)

   This theory paper focuses on understanding how mastery learning has been implemented in undergraduate engineering courses through a systematic review. Academic environments that promote learning, mastery, and continuous improvement rather than inherent ability can promote performance and persistence. Scholarship has argued that students could achieve mastery of the course material when the time available to master concepts and the quality of instruction was made appropriate to each learner. Increasing time to demonstrate mastery involves a course structure that allows for repeated attempts on learning assessments (i.e., homework, quizzes, projects, exams). Students are not penalized for failed attempts but are rewarded for achieving eventual mastery. The mastery learning approach recognizes that mastery is not always achieved on first attempts and learning from mistakes and persisting is fundamental to how we learn. This singular concept has potentially the greatest impact on students’ mindset in terms of their belief they can be successful in learning the course material. A significant amount of attention has been given to mastery learning courses in secondary education and mastery learning has shown an exceptionally positive effect on student achievement. However, implementing mastery learning in an undergraduate course can be a cumbersome process as it requires instructors tomore »significantly restructure their assignments and exams, evaluation process, and grading practices. In light of these challenges, it is unclear the extent to which mastery learning has been implemented in undergraduate engineering courses or if similar positive effects can be found. Therefore, we conducted a systematic review to elucidate, how in the U.S., (1) has mastery learning been implemented in undergraduate engineering courses from 1990 to the present time and (2) the student outcomes that have been reported for these implementations. Using the systematic process outlined by Borrego et al. (2014), we surveyed seven databases and a total of 584 articles consisting of engineering and non-engineering courses were identified. We focused our review on studies that were centered on applying the mastery learning pedagogical method in undergraduate engineering courses. All peer-reviewed and practitioner articles and conference proceedings that were within our scope were included in the synthetization phase of the review. Most articles were excluded based on our inclusion and exclusion criteria. Twelve studies focused on applying mastery learning to undergraduate engineering courses. The mastery learning method was mainly applied on midterm exams, few studies used the method on homework assignments, and no study applied the method to the final exam. Students reported an increase in learning as a result of applying mastery learning. Several studies reported that students’ grades in a traditional final exam were not affected by mastery learning. Students’ self-reported evaluation of the course suggests that students prefer the mastery learning approach over traditional methods. Although a clear consensus on the effect of the mastery learning approach could not be achieved as each article applied different survey instruments to capture students’ perspectives. Responses to open-ended questions have mixed results. Two studies report more positive student comments on opened-ended questions, while one study report receiving more negative comments regarding the implementation of the mastery learning method. In the full paper we more thoroughly describe the ways in which mastery learning was implemented along with clear examples of common and divergent student outcomes across the twelve studies.« less
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 commonlymore »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.« less
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 commonlymore »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.« less
5. Ways of Experiencing Ethics in Engineering Practice: Variation and Factors of Change

   https://doi.org/10.18260/1-2--35495  

   Zoltowski, Carla B Fila ( June 2020 , ASEE Annual Conference & Exposition)

   Engineering education researchers have identified a lack of alignment between the complexities of professional engineering contexts and the ways that we train and evaluate the ethical abilities and dispositions of engineers preparing for professional practice. The challenges that engineers face as practitioners are multifaceted, wicked problems situated in unique and varied disciplinary and industry contexts. Understanding the variations in ways of experiencing ethics by practicing engineers in these complex professional contexts will support a better alignment between engineering ethics instruction and what students might experience in professional practice. While there is a need for richer and more contextually-specific ethics training for many areas, our initial focus is the healthcare products industry. Thus, our NSF-funded CCE STEM project will enable us to analyze the alignment of relationships among frameworks for ethics education in engineering and the reality of engineering practice within the health products industry. As a first phase, the project has focused on understanding the different ways in which practicing engineers experience ethical issues in the health products industry using phenomenography, an empirical research methodology for investigating qualitatively different ways people experience a phenomenon. In the second phase, we have analyzed critical incidents that potentially cause the variation in experiencingmore »ethics in practice. The findings of these studies are anticipated to serve as a guidepost for aligning educational strategies and developing effective training for future ethical practitioners. In our paper, we present an overview of the study (background and methods), progress to date, and how we expect the results to inform engineering ethics education and industry ethics training.« less