J. B. Buckley, B. S. Robinson, T. R. Tretter, C. Biesecker, A. N. Hammond, A. K. Thompson
Background
A predictor of student success, sense of belonging (SB) is often inhibited for minoritized students in engineering environments and difficult to foster in online courses. A shift to remote learning formats necessitated by COVID-19, therefore, posed an additive threat to SB for engineering first-year students, especially those with minoritized identities. Research is needed to understand impacts of online learning to SB for engineering students.
Purpose Hypothesis(es)
The study examined factors that promoted or detracted from SB in engineering in remote courses and ways in which identity related to SB.
Design Method
Part of a larger mixed-methods study, this article examines focus group data from 31 first-year engineering students in 2020 to characterize student experiences in engineering courses moved online during COVID-19.
Results
In addition to the mutually reinforcing nature of SB and learning, findings reveal that the major factors of (a) peer interactions, (b) instructor behavior and course design, (c) environmental identity cues, and (d) personal and psychological factors influenced SB. Examples of factors that positively contributed to SB in remote-delivery courses included platforms for open communication with peers, “live” ability to ask complex questions, and a critical mass of peers of similar identity; example factors hindering SB included limited use of cameras in synchronous classes, elitist peer interactions, instructor focus on academic performance (vs. growth), and feelings of self-doubt.
Conclusions
Both identity and COVID-19 impacted SB for students, with results showing four pathways to support SB and learning for diverse students in engineering across course formats.
{"title":"Belonging as a gateway for learning: First-year engineering students' characterizations of factors that promote and detract from sense of belonging in a pandemic","authors":"J. B. Buckley, B. S. Robinson, T. R. Tretter, C. Biesecker, A. N. Hammond, A. K. Thompson","doi":"10.1002/jee.20529","DOIUrl":"https://doi.org/10.1002/jee.20529","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>A predictor of student success, sense of belonging (SB) is often inhibited for minoritized students in engineering environments and difficult to foster in online courses. A shift to remote learning formats necessitated by COVID-19, therefore, posed an additive threat to SB for engineering first-year students, especially those with minoritized identities. Research is needed to understand impacts of online learning to SB for engineering students.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose Hypothesis(es)</h3>\u0000 \u0000 <p>The study examined factors that promoted or detracted from SB in engineering in remote courses and ways in which identity related to SB.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Design Method</h3>\u0000 \u0000 <p>Part of a larger mixed-methods study, this article examines focus group data from 31 first-year engineering students in 2020 to characterize student experiences in engineering courses moved online during COVID-19.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>In addition to the mutually reinforcing nature of SB and learning, findings reveal that the major factors of (a) peer interactions, (b) instructor behavior and course design, (c) environmental identity cues, and (d) personal and psychological factors influenced SB. Examples of factors that positively contributed to SB in remote-delivery courses included platforms for open communication with peers, “live” ability to ask complex questions, and a critical mass of peers of similar identity; example factors hindering SB included limited use of cameras in synchronous classes, elitist peer interactions, instructor focus on academic performance (vs. growth), and feelings of self-doubt.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Both identity and COVID-19 impacted SB for students, with results showing four pathways to support SB and learning for diverse students in engineering across course formats.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50206,"journal":{"name":"Journal of Engineering Education","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jee.20529","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50152707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Patton O. Garriott, Ayli Carrero Pinedo, Heather K. Hunt, Rachel L. Navarro, Lisa Y. Flores, Cerynn D. Desjarlais, David Diaz, Julio Brionez, Bo Hyun Lee, Evelyn Ayala, Leticia D. Martinez, Xiaotian Hu, Megan K. Smith, Han Na Suh, Gloria G. McGillen
Background
Although participation rates vary by field, Latiné and women engineers continue to be underrepresented across most segments of the engineering workforce. Research has examined engagement and persistence of Latiné and White women in engineering; however, few studies have investigated how race, ethnicity, gender, and institutional setting interact to produce inequities in the field.
Purpose
To address these limitations, we examined how Latina, Latino, and White women and men students' engagement in engineering was informed by their intersecting identities and within their institutional setting over the course of a year.
Method
We interviewed 32 Latina, Latino, and White women and men undergraduate engineering students attending 11 different predominantly White and Hispanic Serving Institutions. Thematic analysis was used to interpret themes from the data.
Results
Our findings illustrate how Latinas, Latinos, and White women developed a strong engineering identity, which was critical to their engagement in engineering. Students' engineering identity was grounded in their perceived fit within engineering culture, sense of purpose for pursuing their degree, and resistance to the dominance of White male culture in engineering. Latinas described unique forms of gendered, racialized marginalization in engineering, whereas Latinas and Latinos highlighted prosocial motivations for completing their degree.
Conclusions
Findings suggest that institutional cultures, norms, and missions are critical to broadening participation of Latinas, Latinos, and White women in engineering. Disrupting White male culture, leveraging Latiné students' cultural wealth, and counter-framing traditional recruitment pitches for engineering appear to be key in these efforts.
{"title":"How Latiné engineering students resist White male engineering culture: A multi-institution analysis of academic engagement","authors":"Patton O. Garriott, Ayli Carrero Pinedo, Heather K. Hunt, Rachel L. Navarro, Lisa Y. Flores, Cerynn D. Desjarlais, David Diaz, Julio Brionez, Bo Hyun Lee, Evelyn Ayala, Leticia D. Martinez, Xiaotian Hu, Megan K. Smith, Han Na Suh, Gloria G. McGillen","doi":"10.1002/jee.20536","DOIUrl":"https://doi.org/10.1002/jee.20536","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Although participation rates vary by field, Latiné and women engineers continue to be underrepresented across most segments of the engineering workforce. Research has examined engagement and persistence of Latiné and White women in engineering; however, few studies have investigated how race, ethnicity, gender, and institutional setting interact to produce inequities in the field.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>To address these limitations, we examined how Latina, Latino, and White women and men students' engagement in engineering was informed by their intersecting identities and within their institutional setting over the course of a year.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Method</h3>\u0000 \u0000 <p>We interviewed 32 Latina, Latino, and White women and men undergraduate engineering students attending 11 different predominantly White and Hispanic Serving Institutions. Thematic analysis was used to interpret themes from the data.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Our findings illustrate how Latinas, Latinos, and White women developed a strong engineering identity, which was critical to their engagement in engineering. Students' engineering identity was grounded in their perceived fit within engineering culture, sense of purpose for pursuing their degree, and resistance to the dominance of White male culture in engineering. Latinas described unique forms of gendered, racialized marginalization in engineering, whereas Latinas and Latinos highlighted prosocial motivations for completing their degree.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Findings suggest that institutional cultures, norms, and missions are critical to broadening participation of Latinas, Latinos, and White women in engineering. Disrupting White male culture, leveraging Latiné students' cultural wealth, and counter-framing traditional recruitment pitches for engineering appear to be key in these efforts.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50206,"journal":{"name":"Journal of Engineering Education","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jee.20536","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50150454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Aditya Johri, Andrew S. Katz, Junaid Qadir, Ashish Hingle
The recent popularity of generative AI (GAI) applications such as ChatGPT portend a new era of research, teaching, and learning across domains, including in engineering (Bubeck et al., 2023; Kasneci et al., 2023; Lo, 2023; Qadir, 2023). In this guest editorial, we discuss the potential impact of GAI for engineering education as researchers and teachers. We see this editorial as the start of a serious dialogue within the community around how GAI can and will change our practices, and what we can do to respond to these shifts. GAI is built on foundational models (FMs) that can be adapted to various other tasks, such as large language models (LLMs), and they operate by learning from many examples and becoming very good at predicting the subsequent probable output or output sequence. Given the abundance of digitized data, they can quickly learn a wide range of topics and respond to user queries almost instantly. Whether engineering a new software application, writing a code snippet to analyze data, designing a product, or composing a cover letter for a job application, GAI users can leverage the power of LLMs to generate outputs that meet their specific needs (UNESCO, 2023). The ability to learn a skill and adapt it to new contexts is a capability that humans have excelled at for a long time. Some would even argue that the competence to learn original things in new environments to tackle novel problems, and teach it to others, is one of the most unique characteristics of our species (Tomasello, 2009). To assist us in this process, we also have the capability to continually create tools and techniques, another distinct trait of humans and central to the engineering profession (Johri, 2022). What, though, is the potential and limit of developing tools and technologies that can mimic and even go beyond what we have conceived of as human intelligence? What potential consequences do technology that can generate novel outputs have for society, especially education in terms of both benefits and harms (Bommasani et al., 2021; Farrokhnia et al., 2023)? What implications does this have for engineering educators (Johri, 2020)? While we discuss how GAI shapes research and teaching practices within engineering education, we recognize that there are additional implications for the use of GAI for self-motivated and sustained learning initiated by learners on their own. That topic is beyond the scope of this editorial and discussed in some detail in the Menekse et al.0s guest editorial in this issue.
{"title":"Generative artificial intelligence and engineering education","authors":"Aditya Johri, Andrew S. Katz, Junaid Qadir, Ashish Hingle","doi":"10.1002/jee.20537","DOIUrl":"https://doi.org/10.1002/jee.20537","url":null,"abstract":"The recent popularity of generative AI (GAI) applications such as ChatGPT portend a new era of research, teaching, and learning across domains, including in engineering (Bubeck et al., 2023; Kasneci et al., 2023; Lo, 2023; Qadir, 2023). In this guest editorial, we discuss the potential impact of GAI for engineering education as researchers and teachers. We see this editorial as the start of a serious dialogue within the community around how GAI can and will change our practices, and what we can do to respond to these shifts. GAI is built on foundational models (FMs) that can be adapted to various other tasks, such as large language models (LLMs), and they operate by learning from many examples and becoming very good at predicting the subsequent probable output or output sequence. Given the abundance of digitized data, they can quickly learn a wide range of topics and respond to user queries almost instantly. Whether engineering a new software application, writing a code snippet to analyze data, designing a product, or composing a cover letter for a job application, GAI users can leverage the power of LLMs to generate outputs that meet their specific needs (UNESCO, 2023). The ability to learn a skill and adapt it to new contexts is a capability that humans have excelled at for a long time. Some would even argue that the competence to learn original things in new environments to tackle novel problems, and teach it to others, is one of the most unique characteristics of our species (Tomasello, 2009). To assist us in this process, we also have the capability to continually create tools and techniques, another distinct trait of humans and central to the engineering profession (Johri, 2022). What, though, is the potential and limit of developing tools and technologies that can mimic and even go beyond what we have conceived of as human intelligence? What potential consequences do technology that can generate novel outputs have for society, especially education in terms of both benefits and harms (Bommasani et al., 2021; Farrokhnia et al., 2023)? What implications does this have for engineering educators (Johri, 2020)? While we discuss how GAI shapes research and teaching practices within engineering education, we recognize that there are additional implications for the use of GAI for self-motivated and sustained learning initiated by learners on their own. That topic is beyond the scope of this editorial and discussed in some detail in the Menekse et al.0s guest editorial in this issue.","PeriodicalId":50206,"journal":{"name":"Journal of Engineering Education","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50149531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The complexity and diversity of problems and concepts in different engineering subjects represent a great challenge for students. Traditional approaches to teaching statics are ineffective in helping some students overcome the learning barriers that underlie learning statics and developing problem-solving skills.
Purpose
This article explores how self-explanation activities may support student learning in statics. Specifically, this study examines the characteristics of student self-explanations of worked examples and their relationship with students′ conceptual change.
Design/Method
The study population included 147 undergraduate engineering students enrolled in a statics course. The students wrote their self-explanations at each step of an incomplete or incorrect worked example in the context of static equilibrium. Students′ self-explanations were qualitatively analyzed using content analysis to identify the approaches used. We used descriptive and inferential statistics to identify differences in students′ conceptual understanding of statics, based on their approach to self-explanation.
Results
We identified four self-explaining approaches: restricted explanations, elemental explanations, inferential explanations, and strategic explanations. After completing the activity, students who self-explained incomplete worked examples showed better results in the quality of their explanations and conceptual change than students in the incorrect worked example condition.
Conclusions
The findings suggest a relationship between the type of worked example, students' approaches to self-explaining, and their conceptual change and problem-solving skills in statics. To increase the quality of the students' explanations and to improve their conceptual understanding, additional prompts or initial training in self-explaining may be required within the worked-examples context.
{"title":"Self-explanation activities in statics: A knowledge-building activity to promote conceptual change","authors":"Jose Luis De La Hoz, Camilo Vieira, Carlos Arteta","doi":"10.1002/jee.20531","DOIUrl":"https://doi.org/10.1002/jee.20531","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The complexity and diversity of problems and concepts in different engineering subjects represent a great challenge for students. Traditional approaches to teaching statics are ineffective in helping some students overcome the learning barriers that underlie learning statics and developing problem-solving skills.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>This article explores how self-explanation activities may support student learning in statics. Specifically, this study examines the characteristics of student self-explanations of worked examples and their relationship with students′ conceptual change.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Design/Method</h3>\u0000 \u0000 <p>The study population included 147 undergraduate engineering students enrolled in a statics course. The students wrote their self-explanations at each step of an incomplete or incorrect worked example in the context of static equilibrium. Students′ self-explanations were qualitatively analyzed using content analysis to identify the approaches used. We used descriptive and inferential statistics to identify differences in students′ conceptual understanding of statics, based on their approach to self-explanation.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>We identified four self-explaining approaches: restricted explanations, elemental explanations, inferential explanations, and strategic explanations. After completing the activity, students who self-explained incomplete worked examples showed better results in the quality of their explanations and conceptual change than students in the incorrect worked example condition.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The findings suggest a relationship between the type of worked example, students' approaches to self-explaining, and their conceptual change and problem-solving skills in statics. To increase the quality of the students' explanations and to improve their conceptual understanding, additional prompts or initial training in self-explaining may be required within the worked-examples context.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50206,"journal":{"name":"Journal of Engineering Education","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50124194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
There have been calls to shift how engineering education researchers investigate the experiences of engineering students from racially minoritized groups. These conversations have primarily involved qualitative researchers, but an echo of equal magnitude from quantitative inquiry has been largely absent.
Purpose
This paper examines the data analysis practices used in quantitative engineering education research related to broadening participation. We highlight practical issues and promising practices focused on “racial difference” during analysis.
Scope/Method
We conducted a systematic literature review of methods employed by quantitative studies related to Black students participating in engineering and computer science at the undergraduate level. Person-centered analyses and variable-centered analyses, coined by Jack Block, were used as our categorization framework, backdropped with the principles of QuantCrit.
Results
Forty-nine studies qualified for review. Although each article involved some variable-centered analysis, we found strategies authors used that aligned and did not align with person-centered analyses, including forming groups based on participant attitudes and using race as a variable, respectively. We highlight person-centered approaches as a tangible step for authors to engage meaningfully with QuantCrit in their data analysis decision-making.
Conclusions
Our findings highlight four areas of consideration for advancing quantitative data analysis in engineering education: operationalizing race and racism, sample sizes and data binning, claims with race as a variable, and promoting descriptive studies. We contend that engaging in deeper thought with these four areas in quantitative inquiry can help researchers engage with the difficult choices inherent to quantitative analyses.
{"title":"Person-centered analyses in quantitative studies about broadening participation for Black engineering and computer science students","authors":"David Reeping, Walter Lee, Jeremi London","doi":"10.1002/jee.20530","DOIUrl":"https://doi.org/10.1002/jee.20530","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>There have been calls to shift how engineering education researchers investigate the experiences of engineering students from racially minoritized groups. These conversations have primarily involved qualitative researchers, but an echo of equal magnitude from quantitative inquiry has been largely absent.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>This paper examines the data analysis practices used in quantitative engineering education research related to broadening participation. We highlight practical issues and promising practices focused on “racial difference” during analysis.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Scope/Method</h3>\u0000 \u0000 <p>We conducted a systematic literature review of methods employed by quantitative studies related to Black students participating in engineering and computer science at the undergraduate level. Person-centered analyses and variable-centered analyses, coined by Jack Block, were used as our categorization framework, backdropped with the principles of QuantCrit.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Forty-nine studies qualified for review. Although each article involved some variable-centered analysis, we found strategies authors used that aligned and did not align with person-centered analyses, including forming groups based on participant attitudes and using race as a variable, respectively. We highlight person-centered approaches as a tangible step for authors to engage meaningfully with QuantCrit in their data analysis decision-making.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Our findings highlight four areas of consideration for advancing quantitative data analysis in engineering education: operationalizing race and racism, sample sizes and data binning, claims with race as a variable, and promoting descriptive studies. We contend that engaging in deeper thought with these four areas in quantitative inquiry can help researchers engage with the difficult choices inherent to quantitative analyses.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50206,"journal":{"name":"Journal of Engineering Education","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jee.20530","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50153361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kanembe Shanachilubwa, Gabriella Sallai, Catherine G. P. Berdanier
Background
While studies examining graduate engineering student attrition have grown more prevalent, there is an incomplete understanding of the plight faced by persisting students. As mental health and well-being crises emerge in graduate student populations, it is important to understand how students conceptualize their well-being in relation to their decisions to persist or depart from their program.
Purpose/Hypothesis
The purpose of this article is to characterize the well-being of students who endured overwhelming difficulties in their doctoral engineering programs. The PERMA-V framework of well-being theory proposes that well-being is a multifaceted construct comprised of positive emotion, engagement, relationships, meaning, accomplishment, and vitality.
Design/Method
Data were collected in a mixed-methods research design through two rounds of qualitative semistructured interviews and a survey-based PERMA-V profiling instrument. Interview data were analyzed thematically using the PERMA-V framework as an a priori coding schema and narrative configuration and analysis.
Results
The narratives demonstrated the interconnectedness between the different facets of well-being and how they were influenced by various experiences the participants encountered. The participants in this study faced prolonged and extreme adversity. By understanding how the multiple dimensions of well-being theory manifested in their narratives, we better understood and interpreted how these participants chose to persist.
{"title":"Investigating the tension between persistence and well-being in engineering doctoral programs","authors":"Kanembe Shanachilubwa, Gabriella Sallai, Catherine G. P. Berdanier","doi":"10.1002/jee.20526","DOIUrl":"https://doi.org/10.1002/jee.20526","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>While studies examining graduate engineering student attrition have grown more prevalent, there is an incomplete understanding of the plight faced by persisting students. As mental health and well-being crises emerge in graduate student populations, it is important to understand how students conceptualize their well-being in relation to their decisions to persist or depart from their program.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose/Hypothesis</h3>\u0000 \u0000 <p>The purpose of this article is to characterize the well-being of students who endured overwhelming difficulties in their doctoral engineering programs. The PERMA-V framework of well-being theory proposes that well-being is a multifaceted construct comprised of <i>p</i>ositive emotion, <i>e</i>ngagement, <i>r</i>elationships, <i>m</i>eaning, <i>a</i>ccomplishment, and <i>v</i>itality.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Design/Method</h3>\u0000 \u0000 <p>Data were collected in a mixed-methods research design through two rounds of qualitative semistructured interviews and a survey-based PERMA-V profiling instrument. Interview data were analyzed thematically using the PERMA-V framework as an a priori coding schema and narrative configuration and analysis.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The narratives demonstrated the interconnectedness between the different facets of well-being and how they were influenced by various experiences the participants encountered. The participants in this study faced prolonged and extreme adversity. By understanding how the multiple dimensions of well-being theory manifested in their narratives, we better understood and interpreted how these participants chose to persist.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50206,"journal":{"name":"Journal of Engineering Education","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jee.20526","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50116350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Gabriella M. Sallai, Matthew Bahnson, Kanembe Shanachilubwa, Catherine G. P. Berdanier
Background
While previous work in higher education documents the impact of high tuition costs of attending graduate school as a key motivator in attrition decisions, in engineering, most graduate students are fully funded on research fellowships, indicating there are different issues causing individuals to consider departure. There has been little work characterizing nonfinancial costs for students in engineering graduate programs and the impact these costs may have on persistence or attrition.
Purpose/Hypothesis
Framed through the lens of cost as a component of the expectancy–value theory framework and the graduate attrition decisions (GrAD) model conceptual framework specific to engineering attrition, the purpose of this article is to characterize the costs engineering graduate students associate with attending graduate school and document how costs affect students' decisions to persist or depart.
Design/Method
Data were collected through semistructured interviews with 42 engineering graduate students from R1 engineering doctoral programs across the United States who have considered, are currently considering, or have chosen to depart from their engineering PhD programs with a master's degree.
Results
In addition to time and money, which are costs previously captured in research, participants identified costs to life balance, costs to well-being, and identify-informed opportunity costs framed in terms of what “could have been” if they had chosen to not go to graduate school. As these costs relate to persistence, students primarily identified their expended effort and already-incurred costs as the primary motivator for persistence, rather than any expected benefits of a graduate degree.
Conclusion
The findings of this work expand the cost component of the GrAD model conceptual framework, providing a deeper understanding of the costs that graduate students relate to their persistence in engineering graduate programs. It evidences that motivation to persist may not be due to particularly strong goals but may result from costs already incurred. Through this research, the scholarly community, students, advisors, and university policymakers can better understand the needs of engineering graduate students as they navigate graduate study.
{"title":"Persistence at what cost? How graduate engineering students consider the costs of persistence within attrition considerations","authors":"Gabriella M. Sallai, Matthew Bahnson, Kanembe Shanachilubwa, Catherine G. P. Berdanier","doi":"10.1002/jee.20528","DOIUrl":"https://doi.org/10.1002/jee.20528","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>While previous work in higher education documents the impact of high tuition costs of attending graduate school as a key motivator in attrition decisions, in engineering, most graduate students are fully funded on research fellowships, indicating there are different issues causing individuals to consider departure. There has been little work characterizing nonfinancial costs for students in engineering graduate programs and the impact these costs may have on persistence or attrition.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose/Hypothesis</h3>\u0000 \u0000 <p>Framed through the lens of cost as a component of the expectancy–value theory framework and the graduate attrition decisions (GrAD) model conceptual framework specific to engineering attrition, the purpose of this article is to characterize the costs engineering graduate students associate with attending graduate school and document how costs affect students' decisions to persist or depart.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Design/Method</h3>\u0000 \u0000 <p>Data were collected through semistructured interviews with 42 engineering graduate students from R1 engineering doctoral programs across the United States who have considered, are currently considering, or have chosen to depart from their engineering PhD programs with a master's degree.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>In addition to time and money, which are costs previously captured in research, participants identified costs to life balance, costs to well-being, and identify-informed opportunity costs framed in terms of what “could have been” if they had chosen to not go to graduate school. As these costs relate to persistence, students primarily identified their expended effort and already-incurred costs as the primary motivator for persistence, rather than any expected benefits of a graduate degree.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>The findings of this work expand the cost component of the GrAD model conceptual framework, providing a deeper understanding of the costs that graduate students relate to their persistence in engineering graduate programs. It evidences that motivation to persist may not be due to particularly strong goals but may result from costs already incurred. Through this research, the scholarly community, students, advisors, and university policymakers can better understand the needs of engineering graduate students as they navigate graduate study.</p>\u0000 </section>\u0000 ","PeriodicalId":50206,"journal":{"name":"Journal of Engineering Education","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jee.20528","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50134812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pre-college engineering education reform documents aim to help students develop engineering literacy. Helping students develop sophisticated epistemological views about engineering makes a significant contribution toward developing engineering-literate citizenry. Despite these widely recognized benefits, research on students' and teachers' epistemological views about engineering, commonly termed nature of engineering (NOE) views, has remained stagnant due to the absence of an open-ended questionnaire whose collected evidence of validity indicates its appropriateness for assessing students' and teachers' NOE understanding.
Purpose
The purpose of this study is threefold: (a) describing the development of a new open-ended instrument, the Views of Nature of Engineering Questionnaire version B (VNOE-B), (b) providing evidence in support of the VNOE-B validity and reliability, and (c) discussing the implications of the newly developed instrument for future research.
Design/Method
We aimed to provide evidence for the content and face validity of the VNOE-B by seeking input from a panel of science/engineering educators. Evidence for the construct validity was determined by analyzing the open-ended questionnaire and semistructured interview responses provided by pre-service and in-service teachers (considered novices in this field) and experts (engineers and engineering educators).
Results
Our findings indicate that the VNOE-B is consistently successful in differentiating between experts' and novices' NOE views. All engineering experts held sophisticated NOE views across all NOE views under study, whereas most novices held partially informed or uninformed NOE views.
Conclusion
Evidence of validity supports the appropriateness of the VNOE-B as an open-ended instrument for assessing adults' NOE views. Its application may guide teacher educators in determining the efficacy of teacher professional development in meeting the aim of improving in-service teachers' NOE understanding. Additionally, VNOE-B may potentially inform the success of pre-service teacher training.
{"title":"Toward developing a valid and reliable assessment of adults' nature of engineering views","authors":"Erdogan Kaya, Hasan Deniz, Ezgi Yesilyurt","doi":"10.1002/jee.20524","DOIUrl":"https://doi.org/10.1002/jee.20524","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Pre-college engineering education reform documents aim to help students develop engineering literacy. Helping students develop sophisticated epistemological views about engineering makes a significant contribution toward developing engineering-literate citizenry. Despite these widely recognized benefits, research on students' and teachers' epistemological views about engineering, commonly termed nature of engineering (NOE) views, has remained stagnant due to the absence of an open-ended questionnaire whose collected evidence of validity indicates its appropriateness for assessing students' and teachers' NOE understanding.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>The purpose of this study is threefold: (a) describing the development of a new open-ended instrument, the Views of Nature of Engineering Questionnaire version B (VNOE-B), (b) providing evidence in support of the VNOE-B validity and reliability, and (c) discussing the implications of the newly developed instrument for future research.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Design/Method</h3>\u0000 \u0000 <p>We aimed to provide evidence for the content and face validity of the VNOE-B by seeking input from a panel of science/engineering educators. Evidence for the construct validity was determined by analyzing the open-ended questionnaire and semistructured interview responses provided by pre-service and in-service teachers (considered novices in this field) and experts (engineers and engineering educators).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Our findings indicate that the VNOE-B is consistently successful in differentiating between experts' and novices' NOE views. All engineering experts held sophisticated NOE views across all NOE views under study, whereas most novices held partially informed or uninformed NOE views.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Evidence of validity supports the appropriateness of the VNOE-B as an open-ended instrument for assessing adults' NOE views. Its application may guide teacher educators in determining the efficacy of teacher professional development in meeting the aim of improving in-service teachers' NOE understanding. Additionally, VNOE-B may potentially inform the success of pre-service teacher training.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50206,"journal":{"name":"Journal of Engineering Education","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jee.20524","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50147276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Benjamin C. Heddy, Robert W. Danielson, Kelly Ross, Jacqueline A. Goldman
Background
Promoting engagement and motivation in early engineering experiences is important for fostering interest and retention in engineering. One method that has been effective for doing so is facilitating transformative experiences (TEs), which occurs when students apply academic content to everyday experience. Our goal was to explore the effectiveness of an intervention to encourage TE, positive emotions, and interest in middle school engineering courses in two differentially resourced schools.
Purpose/Hypothesis
We explored the effectiveness of using the video software Flipgrid as a supplement to a TE intervention to impact TE, emotions, and interest. In addition, we sought to model a theorized predictive relationship between TE, emotions, and interest.
Design/Method
Two hundred seventy-four engineering students across two middle schools with differing levels of resources participated. A cluster-randomized pretest–posttest survey design was used to explore the variables of interest. ANOVA and SEM were implemented to investigate the research questions and hypotheses.
Results
We found mixed results, with the intervention facilitating significantly more TEs and maintaining high levels of positive emotions in a school with access to fewer resources. Furthermore, in alignment with hypotheses about interest development (Renninger and Su, Oxford handbook of human motivation 2012; pp. 167–187), the results showed that initial positive and negative emotions predicted initial interest and post-TE. However, only post-positive emotions and post-TE predicted post-interest. Negative emotions after the intervention did not predict post-intervention interest.
Conclusions
The findings have theoretical implications for interest development and practical implications for targeted interventions in early engineering education, especially for schools with access to fewer resources.
{"title":"Everyday engineering: The effects of transformative experience in middle school engineering","authors":"Benjamin C. Heddy, Robert W. Danielson, Kelly Ross, Jacqueline A. Goldman","doi":"10.1002/jee.20527","DOIUrl":"https://doi.org/10.1002/jee.20527","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Promoting engagement and motivation in early engineering experiences is important for fostering interest and retention in engineering. One method that has been effective for doing so is facilitating transformative experiences (TEs), which occurs when students apply academic content to everyday experience. Our goal was to explore the effectiveness of an intervention to encourage TE, positive emotions, and interest in middle school engineering courses in two differentially resourced schools.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose/Hypothesis</h3>\u0000 \u0000 <p>We explored the effectiveness of using the video software Flipgrid as a supplement to a TE intervention to impact TE, emotions, and interest. In addition, we sought to model a theorized predictive relationship between TE, emotions, and interest.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Design/Method</h3>\u0000 \u0000 <p>Two hundred seventy-four engineering students across two middle schools with differing levels of resources participated. A cluster-randomized pretest–posttest survey design was used to explore the variables of interest. ANOVA and SEM were implemented to investigate the research questions and hypotheses.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>We found mixed results, with the intervention facilitating significantly more TEs and maintaining high levels of positive emotions in a school with access to fewer resources. Furthermore, in alignment with hypotheses about interest development (Renninger and Su, <i>Oxford handbook of human motivation</i> 2012; pp. 167–187), the results showed that initial positive and negative emotions predicted initial interest and post-TE. However, only post-positive emotions and post-TE predicted post-interest. Negative emotions after the intervention did not predict post-intervention interest.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The findings have theoretical implications for interest development and practical implications for targeted interventions in early engineering education, especially for schools with access to fewer resources.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50206,"journal":{"name":"Journal of Engineering Education","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50146498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To avoid the spread of COVID-19, most engineering programs rapidly shifted to emergency online education, and prior research has associated online education with academic overload. Before the pandemic, engineering curricula were already packed with content and course assignments, so more studies should explore how the unprecedented conditions of remote learning affected the intensive academic workload of engineering programs.
Purpose/Hypothesis
This study addresses the following research question: How did the COVID-19 pandemic affect the perceptions of engineering instructors and students regarding their academic workload? Thus, the main research objective is to explore the influence of COVID-19 on the perceived academic workload, extrapolating lessons learned for engineering education settings.
Design/Method
During 2020, we developed a single-case study to understand academic workload in 22 engineering majors at a large Latin American university. We triangulated different sources of institutional and research-focused evidence, including two instructor surveys (n = 110), two student surveys (n = 2218), two student focus groups (n = 18), and workload measurement surveys (n = 3131).
Results
Both instructors and students experienced academic overload since the outbreak of the COVID-19 pandemic. Throughout the first year, instructors became capable of accommodating course activities and assignments to students' particular circumstances. Regardless of these efforts, students continue perceiving academic overload, particularly affecting those who experience connectivity issues or frequent problems with their personal computer or tablet.
Conclusions
Further efforts are needed to support course planning and self-regulated learning in engineering education. In these lines, lessons learned were captured and shared to inform engineering education research and practice beyond the COVID-19 pandemic.
{"title":"Lacking time: A case study of student and faculty perceptions of academic workload in the COVID-19 pandemic","authors":"Isabel Hilliger, Gabriel Astudillo, Jorge Baier","doi":"10.1002/jee.20525","DOIUrl":"https://doi.org/10.1002/jee.20525","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>To avoid the spread of COVID-19, most engineering programs rapidly shifted to emergency online education, and prior research has associated online education with academic overload. Before the pandemic, engineering curricula were already packed with content and course assignments, so more studies should explore how the unprecedented conditions of remote learning affected the intensive academic workload of engineering programs.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose/Hypothesis</h3>\u0000 \u0000 <p>This study addresses the following research question: How did the COVID-19 pandemic affect the perceptions of engineering instructors and students regarding their academic workload? Thus, the main research objective is to explore the influence of COVID-19 on the perceived academic workload, extrapolating lessons learned for engineering education settings.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Design/Method</h3>\u0000 \u0000 <p>During 2020, we developed a single-case study to understand academic workload in 22 engineering majors at a large Latin American university. We triangulated different sources of institutional and research-focused evidence, including two instructor surveys (<i>n</i> = 110), two student surveys (<i>n</i> = 2218), two student focus groups (<i>n</i> = 18), and workload measurement surveys (<i>n</i> = 3131).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Both instructors and students experienced academic overload since the outbreak of the COVID-19 pandemic. Throughout the first year, instructors became capable of accommodating course activities and assignments to students' particular circumstances. Regardless of these efforts, students continue perceiving academic overload, particularly affecting those who experience connectivity issues or frequent problems with their personal computer or tablet.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Further efforts are needed to support course planning and self-regulated learning in engineering education. In these lines, lessons learned were captured and shared to inform engineering education research and practice beyond the COVID-19 pandemic.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50206,"journal":{"name":"Journal of Engineering Education","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50154793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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