demonstrates aprevalence of studies regarding interactions in the online context. These studies have providedimportant observations of how increased interactions relate to performance for remote and/orhybrid instruction overall [12], [13], [14]. However, we believe that this emphasis on onlineinteraction over f2f interaction may not reflect the scale of research need, but the ease of datacollection for SNA regarding online interactions. Specifically, f2f interactions are a less studied,but major component of students’ interactions.To overcome these issues, our research group, familiar with SNA from small studies, conducteda large-scale (1000+ individuals) SNA study at a large, public university in the United States[15]. This study sought to extend the
help-seeking beliefs among underrepresentedstudents is critical; opinions about pursuing professional treatment for a mental health conditionmay be affected by gender, race, ethnicity, disability status, and socioeconomic status. Further,data was collected from first-year engineering students at the end of their first semester of collegeclasses. Therefore, the results may not reflect the students’ progress through the engineeringprogram. To address this, future directions plan to include a wider range of students from otherinstitutions and a higher proportion of students from racial and ethnic minority groups. As a result,we will be able to learn more about the mental health of marginalized student groups and theeffects of institutional
Matthew M. Grondin1,2, Michael I. Swart2, Claire Huggett1, Kate Fu1, and Mitchell J. Nathan2 Department of Mechanical Engineering1 Department of Educational Psychology-Learning Sciences2 University of Wisconsin-MadisonKeywords: Epistemic Network Analysis, Mechanical Reasoning, Mechanics of Materials,Undergraduate Engineering EducationAbstract:This full paper considers how collaborative discourse can reveal ways upper-class engineeringstudents mechanically reason about engineering concepts. Argumentation and negotiation duringcollaborative, multimodal discourse using speech and gestures helps establish common groundbetween learners and fosters reflection on their conceptual
should provide good opportunities to learn aboutcomplexities and contexts. Similarly, Merriam [9] reminds that the cases need to be selectedbased on relevant criteria, which means the researcher must first determine what selectioncriteria are essential in choosing the people or sites to be studied [17]. The criteria you establishdirectly reflects the purpose of the study and guide in the identification of information-rich cases[17].Additionally, in case study research, it is important to consider two levels of sampling [9].Firstly, the researcher identifies the case, which can be a person, a program, a university, amongothers. Secondly, within each case exists numerous sources of data, so the researcher needs toselect how to better approach that
. Meanwhile, greater attention should be devoted todeveloping advanced assessment techniques to detect dishonesty and academic misconduct.From the perspective of curriculum design, it also suggests investigating how future courses canbe designed to adapt to the development of such technology.AcknowledgmentThis material is based upon work supported by the Nanyang Technological University under theURECA Undergraduate Research Programme and partially supported by the AI.R-NISTH AI forSocial Good Research Grant at Nanyang Technological University in Singapore. Any opinions,findings, conclusions, or recommendations expressed in this material are those of the author(s)and do not necessarily reflect the views of the URECA or AI.R program. We would like
by one researcher, reflecting the exploratory nature of thiswork: this methodological choice is discussed further at the end of this paper.Table 1 - Descriptions and examples of interactional positioning codes, taken from [10].Positional move (code) Description Example from data Firm statements of fact or firm or strong “The least amount of time is gonna be the kidExpert (C1) disagreement [shoveling]”. Softened statements or softened disagreement,Intermediate expert (C2) “Safety should probably be first
, or work presented herein was funded in part by the U.S. Department ofEnergy’s Industrial Assessment Centers, under Award Number DE-EE0009734. The views andopinions of authors expressed herein do not necessarily state or reflect those of the United StatesGovernment or any agency thereof.References[1] S. Truitt, J. Elsworth, J. Williams, D. Keyser, A. Moe, J. Sullivan and K. Wu, "State-Level Employment Projections for Four Clean Energy Technologies in 2025 and 2030," 2022.[2] DOE’s IAC, “Industrial Assessment Centers”. Available: https://iac.university/#overview [Accessed Feb. 12, 2023].[3] C. Kurnik and C. Woodley, "NREL job task analysis: Energy auditor," 2011.[4] M. M. Mohamad, A. R. Jamali, M. I. Mukhtar, L. C. Sern and A
(2021) introduced the concept of person-centered approaches to the engineeringeducation community, which originated in the context of longitudinal analyses. A person-centered approach recognizes heterogeneity and attempts to identify latent groupings amongindividuals in the sample based on the relationships among variables which reflect thecharacteristics of individuals and their environment. In contrast, a variable-centered approach isfocused on prediction and relationships between variables (Laursen & Hoff, 2006). Althoughperson-centered approaches may use data-driven methods to fulfill these tasks, not all data-driven methods can be used in a person-centered fashion without more critical thought (Godwinet al., 2021). For example
internationally trained minoritized women.Our study will expand the ongoing conversation into the Canadian landscape.Theoretical PerspectivesOur study adapted Carlson and team’s [1] conceptual model of professional identity developmentwhich include: 1) Program Expectations; 2) Teaching and Supervision; 3) Research; 4)Publication; 5) Grants and Funding; 6) Service; and 7) Conferences, Networking, and ProfessionalDevelopment. We chose this model because it was suited for examining the professional identitydevelopment of doctoral programs, was extendable to include ECR and allowed specific elementsof the model to be woven into our interview questions and narratives. We choose duoethnography[18] because of its collaborative, reflective, dialogic, and
-structured interview protocol with four sections:introduction and warm-up, engineering identity, teamwork, and conclusion. When timepermitted, we asked the interviewees to reflect on the stories of the practicing engineers. Thesestories were developed from publicly-available accounts of the day-to-day experiences ofpracticing engineers. The interview protocol and other applicable parts of our study design wereapproved by our institution’s human subjects review process.Two mock interviews were performed to evaluate the clarity (or ambiguity) of the questions andthe total time required to perform the interview. It also served as an opportunity for our team tofamiliarize ourselves with the interview process. Two students volunteered for the
assess the perceivedimpact of participating in such centers. The in-progress validation process has providedinsightful reflections on multiple items regarding the way the items were written, theirappropriateness, and their alignment with participants' experiences. This work improvesconsistency in how ERCs evaluate the effectiveness of their education and diversityprogramming.Next steps will involve further distribution of the instrument and increasing its use amonginterested centers to further the validity evaluation of the instrument. It is expected that thisinstrument will facilitate greater cooperation between ERCs and other large, STEM researchcenters. Our future work will continue to gather validity evidence for the use of this instrumentin
-related behaviors.Recent literature suggests active learning strategies in sustainability education can help promotestudents’ sustainability behaviors. The term active learning has been used to describe a broadrange of student- or learner-centered instructional methods. For example, Felder and Brent [11]argued that active learning is “a teaching approach that encompasses anything students might becalled on to do in class besides watching and listening to an instructor and taking notes” (p. 111).While definitions of active learning vary, most scholars agree that active learning involvesstudents’ active engagement, continuous participation, action, and reflection [12-13].For decades, scholars have called for college educators to incorporate more
Frontiers in Education (p. 208). Frontiers.Juntunen, H., Tuominen, H., Viljaranta, J., Hirvonen, R., Toom, A., & Niemivirta, M. (2022).Feeling exhausted and isolated? The connections between university students’ remote teachingand learning experiences, motivation, and psychological well-being during the COVID-19pandemic. Educational Psychology, 1-21.Khraishi, T. (2021). Teaching in the COVID-19 Era: Personal Reflections, Student Surveys andPre-COVID Comparative Data. Open Journal of Social Sciences, 9(2), 39-53.Larcombe, W., Baik, C., & Finch, S. (2022). Exploring course experiences that predictpsychological distress and mental wellbeing in Australian undergraduate and graduatecoursework students. Higher Education Research & Development
analyzing student written responses to conceptually challenging problems. • Gather more text samples that center written responses to conceptually challenging problems from underrepresented groups to adequately train algorithms.AcknowledgmentsWe acknowledge support from the National Science Foundation (NSF) through the NRT DGE2021874 and DUE 2135190. Any opinions, findings, conclusions, or recommendationsexpressed are those of the authors and do not necessarily reflect the views of the NSF.References[1] H. Auby, N. Shivagunde, A. Rumshisky, and M. D. Koretsky, “WIP: Using machine learning to automate coding of student explanations to challenging mechanics concept questions,” presented at the American Society for
demonstrates thedirect influence of prior knowledge on her problem-solving approaches. In justifying her answeron the instrument, Olivia responded, “Probably not perform calculations, that’s usually not myfirst jump to. I kind of like to physically demonstrate the system. I’m very tactile so I like to seehow something would work.” Olivia’s response reflects a level of self-awareness (recognitionthat she is tactile) as a factor that influences her problem-solving approaches.The other four participants with prior engineering experience similarly appeared influenced bytheir recent engineering experiences in their approach to the problems. Other research has shownthat students often use their lived experiences to approach problem solving [17]. All four
., code of cooperation) to hold each member accountable.At any particular time, I knew each team member's role, so I knew what to expect from them.An outside observer would have concluded our team had an effective process to complete ourassignments.Team members arrived on time to team meetings.Team members were prepared for team meetings.My teammates displayed appropriate interpersonal skills when conflict arose.GOAL SETTINGMy team used clear, long term goals to complete tasks.My team reflected upon its goals in order to plan for future work.My team made use of incremental goals (i.e., we set short term goals) in order to completecourse assignments on time.My input was used to set our team goals.This team helped me accomplish my individual goals
. Andrew Olewnik, University at Buffalo Andrew Olewnik is an Assistant Professor in the Department of Engineering Education at the Univer- sity at Buffalo. His research includes undergraduate engineering education with focus on engineering design, problem-based learning, co-curricular involvement and its impact on professional formation, and the role of reflection practices in supporting engineering undergraduates as they transition from student to professional. ©American Society for Engineering Education, 2023 Using Directional Graphs to Explore the Engineering Co-curricular Navigation Profiles of Student GroupsIntroductionThe goal of this work-in-progress (WIP) paper
themeasurement data were collected, they were asked to conduct related analysis and answerquestions designed to reflect their understanding of the concepts and the ability to draw meaningfulconclusions. This new lab experiment also fulfills one of the seven ABET learning outcomeassessment requirements.Before this new student-designed lab experiment on specific heat, a FE type quiz was given to thestudents during the lecture time. After the new lab experiment, the students were tested again witha similar quiz to gauge the improvement on their learning. Another survey question was also givenbefore and after the new lab experiment to assess their understanding of the concept from thestudents’ perspective.The before and after quiz results showed 20
, Stanford University Helen L. Chen is a Research Scientist in the Designing Education Lab in Mechanical Engineering and co-founder of the Integrative Learning Portfolio Lab in Career Education at Stanford University. She earned her undergraduate degree from UCLA and her PhD in Communication with a minor in Psychology from Stanford. Her scholarship is focused on engineering and entrepreneurship education, portfolio pedagogy, reflective practices, non-degree credentials, and reimagining how learners represent themselves through their professional online presence.Prof. George Toye Ph.D., P.E., is adjunct professor in Mechanical Engineering at Stanford University. While engaged in teaching project based engineering
. Matusovich, and S. R. Brunhaver, “Understanding the socializer influence on engineering students’ career planning,” in ASEE Annual Conference and Exposition, Conference Proceedings, 2018, vol. 2018-June, doi: 10.18260/1-2--31182.[15] J. S. Eccles and A. Wigfield, “Expectancy-Value Theory to Situated Expectancy-Value Theory: Reflections on the Legacy of 40+ Years of Working Together,” Motiv. Sci., vol. 9, no. 1, pp. 1–12, 2023, doi: 10.1037/mot0000275.[16] A. Wigfield and J. S. Eccles, “Expectancy–value theory of achievement motivation,” Contemp. Educ. Psychol., vol. 25, no. 1, pp. 68–81, 2000.[17] J. S. Eccles and A. Wigfield, “Motivational Beliefs, Values, and Goals,” Annu. Rev. Psychol., vol. 53, pp
day the surveys were distributed. All subscales from the StRIP questionnaireprompted participants to reflect on the class activities in which they were asked to engage duringa specific class period. Additionally, students self-reported their gender identity. We present allmeasures used in the present study in Table 1 and descriptive statistics and correlations betweenmeasures for all students and by students' gender identity in Table 2. Table 1. Abbreviations & Sample Items for Measures Measure Abbreviation Sample Item Belongingness BEL “I have a sense of belongingness in this class.” Affective Response AR “I enjoyed the activities.” Behavioral Response
questions wasasked twice—once with the phrase “engineering person” and once with “science person.” Weinitially wanted to adapt these items for “person in my field,” but after expert review it wasdetermined that the items would not capture what we were hoping they would capture. Performance/competence reflects the extent to which students perceive their ownknowledge and abilities in engineering. This dimension comprises five items that capturestudents’ confidence in their understanding of engineering in class and out of class, that they cando well on exams, that they understand concepts in engineering, and that others ask them forhelp. These items were adapted from engineering to “my field” for greater applicability. Missing data were
. Her research focuses on individuals’ development from students to professional engineers. She is particularly interested in studying co-op/internship programs, experiential learning opportunities, professional skills development, and diverse student experiences in experiential learning settings.Dr. Aaron W. Johnson, University of Michigan Aaron W. Johnson (he/him) is an Assistant Professor in the Aerospace Engineering Department and a Core Faculty member of the Engineering Education Research Program at the University of Michigan. His lab’s design-based research focuses on how to re-contextualize engineering science engineering courses to better reflect and prepare students for the reality of ill-defined
advised 17 UG theses, 29 MS theses, and 10 Ph.D. dissertations. Hammond is the 2020 recipient of the TEES Faculty Fellows Award and the 2011 recipient of the Charles H. Barclay, Jr. ’45 Faculty Fellow Award. Hammond has been featured on the Discovery Channel and other news sources. Hammond is dedicated to diversity and equity, which is reflected in her publications, research, teaching, service, and mentoring. More at http://srl.tamu.edu and http://ieei.tamu.edu. ©American Society for Engineering Education, 2024 FIE 2023: An aggregate and statistical analysis of the results and feedback of the ASEE ERM premier international conference on engineering education
byJensen and Cross.Further Reflection and Future WorkThe programs in this study are still growing and evolving. Consequently, limitations of this workinclude the current small sample size. One of the consequences of our currently low N is that weare not yet able to break down results by ethnicity, gender identity, or other important identity andbackground variables. However, while it’s true that our N is small (both overall and incomparison with Jensen and Cross), our results do show the strong potential impact ofproject-based engineering programs. As our programs grow and our N increases in future studies,we may observe further differentiation in outcomes with the population studied by Jensen andCross.The results of this research stimulates us to
) before treatment5 Demographic characteristics reflect students’ district administrative records; in Maryland students may identifytheir gender as non-binary and as more than one race. Ethnicity is recorded separately from race. n 60 27 Note. Means (and standard deviations) presented. * Group difference significant, p
, and Confidence MOSFET and Effective Resistance 24 Student Enjoyment and ConfidenceResults: One of the major researchquestions we wanted to answer wasthe impact that prerecordeddemonstration videos had on thestudents’ enjoyment of their time inlecture. To assess this, at the end offour of the lectures where studentswere shown videos, we asked themto reflect on whether thedemonstration video improved theirenjoyment of the lecture. We foundthat in all four of the lectures,between 64% and 71% of thestudents indicated that they “Agreed” or “Strongly Agreed” that the video had improved theirenjoyment of the lecture. Furthermore, only 4% to 8% of the students reported “Disagreed” or“Strongly Disagreed” that the video had
prior understanding offluid mechanics and heat transport concepts. A worksheet was given to each participant for useby them during the experiment. The experiment's steps were outlined in the worksheet for theparticipants to follow. The worksheet gave the participants a chance to consider and deliberateabout the ideas being covered. Afterward, each participant was given a post-test to examine howmuch they had learned during the instruction. They were then required to respond to thecognitive engagement survey. Participants received links to the online surveys administered viaQualtrics© at the end of the LCDLMs sessions. The cognitive engagement survey prompts askedparticipants to reflect on their LCDLM facilitated instructions and report how well
scale was retained without reservation for this study. Table 6: Confirmatory Factor Analysis for Autonomy Subscales Item Loading Goodness of Fit Indicators Satisfaction of Autonomy Needs At work, I feel a sense of choice and freedom in degrees of freedom (df) = 2 the things I undertake 0.656 c2 = 1.828 (p = 0.401) I feel that my decisions on my job reflect what I 0.820 RMSEA = 0.000 really want I feel my choices on my job express who I really
: Reflecting on the research process,” The Qualitative Report, Oct. 2014.[48] J. Feldkamp, “The Rise of TikTok: The Evolution of a Social Media Platform During COVID-19,” in Digital Responses to Covid-19: Digital Innovation, Transformation, and Entrepreneurship During Pandemic Outbreaks, C. Hovestadt, J. Recker, J. Richter, and K. Werder, Eds. Cham: Springer International Publishing, 2021, pp. 73–85.[49] A. Bhandari and S. Bimo, “Why’s everyone on TikTok now? The algorithmized self and the future of self-making on social media,” Soc. Media Soc., vol. 8, no. 1, p. 205630512210862, Jan. 2022.[50] E. Simpson, A. Hamann, and B. Semaan, “How to Tame ‘Your’ Algorithm: LGBTQ+ Users’ Domestication of TikTok,” Proc. ACM Hum. Comput