. Structured deliverables provideguidance as to what elements of a design process may be appropriate to move through theengineering design process. The scaffolding to emphasize prototyping and adoption of aprototyping mindset may help as a pedagogical tool [33]. Artifacts that are created in thesecourses reflect tangible evidence of activity. From the idea to realization, there are means todescribe the role, purpose, and creation of prototypes. Gerber & Carroll [19] describe theconnection and process of prototype creation. Houde & Hill [20] discuss different types ofprototypes as what do prototypes prototype (function, looks-like). Makerspaces also provideadditional context for the tools, mindsets, and community of practice [21-23, 11].Design
Paper ID #42944Unmasking Cognitive Engagement: A Systematized Literature Review of theRelationships Between Students’ Facial Expressions and Learning OutcomesMr. Talha Naqash, Utah State University, Logan Mr.Talha Naqash is currently pursuing his doctoral studies in Engineering Education at Utah State University. With a profound educational background spanning multiple disciplines, he holds an MS in Telecommunication and networking. His extensive research contributions are reflected in numerous publications and presentations at prestigious IEEE; ASEE conferences, Wiley’s & Springer Journals. His research primarily
process, and the inherent value derived from the study’s outcomes. Themes thatemerged and were defined from discussion exercises with participants are the following: ’lost andfound,’ signifying moments of uncertainty and discovery; ’lack of community,’ highlightingfeelings of isolation; ’not surface level,’ underscoring the depth and complexity of the issuesdiscussed; and ’community,’ reflecting participants’ desire for, or efforts toward, building a senseof belonging within the research program. These themes serve as integral components of ourinvestigation into the impact of photovoice on understanding the perspectives of underrepresentedgroups in computing.Keywords: Photovoice, computer science, underrepresentation, student perception1
of a problem through use of applicable knowledge and critical thinkingskills. Interest is the student’s desire or curiosity to learn about engineering: an example of this iswhen a student goes above and beyond to gather understanding on the topic. Finally, recognitionis separated into three subfacets, which reflect the deep work done by Carlone and Johnson onrecognition in science identity: lack of recognition, social/teacher recognition, and self-recognition. While Hazari’s work touched on the idea of self recognition, the focus on areasother than recognition by others have not received as much attention as the identity model hasbeen adapted into engineering. In this work, we seek to renew attention to performance,competence, and interest
onefemale student. Proper human subjects’ approval was obtained prior to conduct of the study.Survey DevelopmentThe engineering graduate EVT instrument was developed based upon the engineering specificEVT instrument from Brown & Matusovich [7]. Brown & Matusovich instrument’s validity wasconfirmed by consulting three experts for content validity and through factor analysis forconstruct validity. Cronbach’s alpha was used as a measure of reliability for internal consistency[7]. In the first step of the survey development process, all original survey prompts werereviewed and rewritten to reflect a graduate program setting. Some examples are found in Table1 where the added words are presented in italics. The wording changes made were simple
U.S. higher education contexts, there are few studies that specificallycenter them to contextualize their experiences. International graduate students experience uniquechallenges, such as acculturation, isolation, and visa status, that impact attrition and student well-being. Previous studies are mainly focused on acculturation or language problems for studentsacross disciplines. For engineering disciplines, the expectation of English language proficiency isdifferent than that of other majors like humanities, and engineering students may rely onmathematical and experimental data more heavily than English proficiency to perform well in theirresearch. Therefore, understanding how international graduate students reflect on their
skills obtained, and PFE activities.These initial categories are obtained based on the theme of the questions combined with theresearch questions of this paper. During the grouping process, it was also necessary to verify thetranscribed data to ensure its accuracy in reflecting the participants’ responses and to avoid anyerrors introduced by the transcription program. Ultimately, the frequency of a specific responsewithin each group is recorded, summarized, and analyzed to obtain the prevailing trend in theparticipants’ answers.Preliminary ResultsThe analysis of student interviews so far reveals a consensus among most participants regardingthe efficacy of Professional Formation in Engineering (PFE) classes in facilitating the acquisitionof
) Reflection section on linking existing information – Students had to reflect on what sortof existing KSAs they had used to solve the task given in (1). They then orally presented thisreflection.The students are evaluated before and after the M&S module to ascertain the effectiveness ofthe intervention in an online survey and hence, determine their needs for transferringlearning.(a) A 14 item Transfer of Learning Questionnaire (TLQ) adapted from [18], provided pre-and post-intervention, measures student perception of the importance, ease, and potentialobstacles to transfer. This questionnaire is composed of three constructs – attitudes totransfer, barriers to transfer, and learning retention. All 14 items are rated on a standardLikert scale from
perspectives. This work-in-progress paper describes the mixed-methods researchdesign considerations in formulating the study with emphasis on the quantitative portion.Detailed development of the qualitative portions of the study are still in progress and will bereported at future date.Positionality Statement The authors openly acknowledge and reflect on their subjective stance and potentialbiases by providing a positionality statement that encompasses our backgrounds and experiencesas they may relate to this work. We begin with this statement to assist readers in understandingpossible influences this bias may have in our process. Bruce Carroll is a white male engineeringeducator with a tendency toward an emic account from the institutional
Calgary report no link between their laboratories and coursecontent or future career development. Therefore the goal of this research endeavour is to identifyactions that can be taken to improve the students’ learning experience in undergraduateengineering laboratories.Critically reflective surveys were developed using Ash and Clayton’s Describe, Examine,Articulate Learning (DEAL) model and the revised Bloom’s taxonomy and released to currentengineering students in a third-year materials science course at the University of Calgary’sMechanical and Manufacturing Engineering program. The purpose of these surveys was toevaluate where students feel their laboratories do not connect to their classes or careers, and whatsteps can be taken to improve
, social constructions and hierarchies, historical background, andsocioeconomic status among other social constructs. As Anzaldúa explored her ownupbringing and lived reality, she deconstructed those spaces she inhabited where she faceddiscrimination and ambiguity to imagine and (re)shape a third space where new realitiescould exist [16]. Through a process of self-reflexivity, Anzaldúa explains, Nepantla becomesa (re)imagined space rather than a dichotomy of worlds [16]. Anzaldúa claims that Nepantlasoften emerge through writing – the writing that comes from deep and critical reflection thateventually leads to a process that catalyzes transformation.Nepantla is also a way to explore the world through lived experience and engage indecolonial
change isneeded, making this change, and then reorienting the change into one’s life [13], [14]. Much ofthis learning is done by self-reflection of the content, process, or context where schemareorientation is required and can lead to a better understanding of diverse perspectives and newideals. By promoting self-reflection and transformative learning, individuals can find themselveswith broader perspectives and open themselves to the promotion of systemic changes. Similarly,transformative learning may also take place through a collaborative or team-oriented processsuch as proposal review panels, particularly where senior reviewers are able to reorientexpectations in younger reviewers [11].Using a lens of transformative learning theory, this
courses are so rigorous that the cost of fully engaging intheir engineering courses is high.Consistent with existing literature that use multiple elements of value to investigate the nuancesin academic outcomes [28], [29], [32], this study uses items that both reflect intrinsic and utilityvalue. In addition to expectancy and value measures, several control variables are relevant to thisstudy of cognitive engagement. Specifically, we control for gender, race, ethnicity, familyincome, first generation status, and international student status in our regression models. We alsostudy the contribution of broad prior interests (to pursue engineering) as well as more specificintrinsic interests to self-efficacy, value, and ultimately to cognitive
to enhance Hispanic/Latino transfer student success. ©American Society for Engineering Education, 2024 Investigating Motivation and Self-Regulated Learning for Students in a Fundamental Engineering CourseAbstractMotivation and self-regulated learning (SRL) are two interconnected constructs that are criticalfor student learning, especially for those in challenging fundamental engineering courses such asThermodynamics. Each of these elements are integral to the learning process and typicallyimpact one another, as fostering motivation can lead to improved self-regulatory skills. SRL isdescribed as a cyclical process where students plan, set goals, monitor learning, and reflect tofurther plan
inquiries and discussions have brought to light several issues with thereliability and validity of SETs as the primary measure of teaching quality. There is mountingevidence that end-of-semester evaluations are biased and represent an imperfect measure of aninstructor's performance. They may not accurately reflect the true quality of teaching, or at thevery least, they are unfair [6], [7], [8].Transitioning from traditional paper-based surveys to electronic ones in higher education, whilecost-effective, presented certain drawbacks, particularly in terms of significantly reducedresponse rates, which led to skepticism about the validity and reliability of SETs [9], [10].The limitations of SETs have led to continuous calls for a more comprehensive and
describe the family life of their co-workeror employer as part of their answer. This background information benefits the interviewer as itwill help frame the context and dynamics the participant had to contend with. However, thisinformation would be omitted from the final narrative as this background is unnecessary for thereader. It is important to remember that although this information would not be included in thefinal constructed narrative, its influence persists through the remainder of the data collection andinterpretation.Smoothing is inherently an iterative and reflective process that researchers often refine throughexperience [11]. Most literature on narrative methods typically discusses the philosophicalunderpinnings of narrative analysis
,reflection notes writing, fits the objectives of the present study of finding whether the machinelearning-based data analysis resulting in similar and usable results as compared with the analysisresults from the inductive process of the grounded theory. Raised as a theory-construction methodthat takes data as the basis for theories to emerge, grounded theory has a unique fit with themachine learning-based analysis approach in that both are inductive in nature.Machine learning (ML)-based or mixed approachesPreviously researchers have conducted ML-based analysis on the sentiment of financial newsreports or labeled information of survey questions [7]. Sentiment analysis is a classification taskthat can be handled by manual labeling of a small set of
, I feel it is valuable to disclose my position as an author, including the identities I hold,the privileges I am afforded, and the perspective I bring to understanding engineering researchculture. I am a Black, cisgender man, and a Ph.D. student studying engineering education. I amalso a recipient of a stipend from the National Science Foundation (NSF), so I am a directbeneficiary of the engineering research “culture,” or system as it stands. This work-in-progresspaper is directly tied to my own experience and the experiences of colleagues that are alsoengaging in engineering research culture. Through rich conversations and reflection about thespaces in which engineering researchers operate, I began to question the underlying valuesystems
instructional decision making in a middle school informalengineering summer program; this research is intended to highlight ways in which middle schooleducators in informal science institutions and classroom settings might facilitate engineeringknowledge, skills, and practices. This is in response to recent advances in precollege science,technology, engineering, and mathematics (STEM) education. The evolving engineeringeducation landscape has necessitated new ways of teaching and learning that reflect rapidtechnological advances in the global economy. The Next Generation Science Standards (NGSS)have ushered in an era of STEM integration in K-12 science in the U.S. [1]. These standards,based upon A Framework for K-12 Science Education [2], proposed a
. • Campus life offered by the department is very stimulating. • If I am/were going to college next year, I would continue with this department. • There’s a real sense of community here. 2. Reflection Survey. Besides the above survey, we also created another open-ended anonymous survey with the following reflection questions to gain deeper insight into students’ experiences in the departmental learning community. • Do you find the presentations/workshops conducted by the ExCITE Program students helpful? Why or why not? If helpful, in what ways? If not, please explain why. • How did participating (or not participating) in the ACM and ACM-W club meetings/activities (including the take-apart
, business, and political science [2]. In EER, CIhas been used in this way to improve the design of measures of many topics, includingprofessional skills development [3], social capital resources [4], and student responses toinstructional strategies [5].Cognitive interviewing requires participants to think aloud while completing a task. Drawingfrom reviews of the method, we here define thinking aloud as “requesting participants toopenly reflect on their answers to survey questions and the processes by which they reachthose answers, with limited interviewer interaction.” [1], [6], [7]. CI interviewers need notnecessarily follow a uniform format; these researchers may choose to engage with participantsvia concurrent probing, where questions are asked
members within the same team. Perhaps most of the time, the student teamsfunction just fine. Yet instructors might actively or passively notice the existence ofdysfunctional teams, where team dynamics were impaired, and team members developednegative attitudes towards one another [4-5]. Furthermore, in other situations, social loafingmight exist within student teams but sometimes hardly get instructors’ attention [6]. When suchsituations happen, the benefits of cooperative learning are compromised and at risk [7]. Scholars and practitioners have proposed ways of trainings to support student team success.Using Goal-Role-Process-Interpersonal-Relationship models, students wrote memos to reflect ontheir team dynamics and development [8]. Students
will detail our methodology, present our findings, and discuss the benefitsand limitations of integrating ChatGPT into qualitative analysis for engineering educationresearch.MethodsTo gather qualitative data, our team devised a semi-structured interview protocol comprisingfour segments: introduction and warm-up, engineering identity, teamwork, and conclusion.When time permitted, we asked the interviewees to reflect upon stories of practicing engineers,which were compiled from publicly accessible accounts of the day-to-day experiences ofpracticing engineers. This interview framework and other relevant aspects of our research designreceived approval from our institution’s Institutional Review Board.Throughout the RIEF project, we conducted a
parallel study of this project, we aim to further investigate the findings from thisstudy by examining engineering doctoral students’ perceptions on their preparedness to teach varybased on their demographic characteristics, prior teaching experiences and trainings, etc. [16]. Inanother study, we analyze engineering doctoral students’ expectations, reflections, and concernsregarding their future in academia [17].Theoretical FrameworkThe survey instrument developed is grounded in the self-efficacy and self-perception theory. Theself-efficacy theory provides a framework to act as a predictor of how individuals may perform inthe future based on their confidence in their ability in a certain task or domain [18]. According toBandura [19], [20], a
faculty and industry 100 sponsor) Project Charter 100 *Should be signed by your industry sponsor as commitment of resources toward your project and authorization of work. Methodology 150 Submit PowerPoint slides for Project Plan to Communication professor n/a Project Plan Presentation (Capstone & Communication faculty and industry 100 sponsor) Project Plan 200 Midterm Reflection 50 TOTAL TCMT631. Capstone I
and in non-POGIL classes was even greater (87% vs 46%). This patternstayed relatively constant across instructors and the three sets of observations and reflectsPOGIL principles, which might be an indicant to construct validity.These preliminary findings were reflected in the student ratings. While ratings of the difficultyand length of POGIL and non-POGIL classes were similar (3.8 vs 4.0 on a scale of 1 “too easy”to 7 “too hard”; 4.0 vs 4.1 on a scale of 1 “too long” to 7 “too short”), students were much moreapt to rate the POGIL classes as more collaborative (5.8 vs 4.9), another POGIL principle. Againthere weren’t major differences across the three sets of observations. While there were expecteddifferences by instructor, there were minimal
which one’s self-efficacy belief is related to a specific situation or context.According to Bandura (1997), one’s self-efficacy is more accurately perceived when the contextis more specific. Accordingly, we adapted and created the ESE-E to reflect these threedimensions. In terms of the dimension of magnitude, the ESE-E scales included items that measuredentrepreneurial-related skills and activities at various difficulties, such as product ideation,business planning, and customer discovery. Furthermore, in terms of the dimension of generality,we adapted the items and created additional items based on the specific content topics taught inan entrepreneurship education course. In addition, in terms of the dimension of strength, eachESE-E
essential for developing an agile and adaptable mind in the 21st century, wheretechnology is ubiquitous. The importance of CT is reflected in the growing interest in exploringits potential role in various fields, including engineering. While CT in engineering education hasbeen discussed in previous research, there needs to be more understanding of how CT may differin the context of different engineering disciplines. Rich qualitative research on how studentsengage in CT and engineering can show how they can support each other [5]. Research has beenconducted to investigate the implementation of CT in middle school education internationally.The studies emphasize the importance of CT in interdisciplinary education to foster students'critical thinking
students’ agentic engagement, self-efficacy, growth mindset, and other related aspects. 1In recent years, there has been increasing attention paid to students’ epistemic beliefs and theirimpact on learning efficacy. Epistemic belief, which reflects students’ views on the nature ofknowledge and knowing, plays a crucial role in the cognitive, metacognitive, and affectivedimensions of students’ learning. Research has demonstrated that interventions targeting epistemicbeliefs can significantly enhance learning outcomes (Greene et al., 2018). Epistemic cognition -mostly measured in terms of belief (Greene et al., 2018) – is identified as the apex of
mentalrotation and spatial visualization, and the Purdue Spatial Visualization Test: Visualization ofRotations (PSVT:R) which measures mental rotation.Throughout recent years, a large number of new or adapted spatial ability instruments have beendeveloped to reflect more diverse populations involved in spatial ability research. Thissystematized literature review provides a synthesis of how valid and reliable spatial abilityinstruments measure specific constructs of spatial thinking. This work is guided by the followingresearch questions.1. How do existing spatial ability tests measure spatial thinking?2. How do spatial ability instruments available in the literature demonstrate validity andreliability?Positionality StatementThe first author is a