. ©American Society for Engineering Education, 2023 Interest-Driven Disciplinary Pathways for Middle-Year Undergraduate Engineering StudentsKelsey Scalaro, Indira Chatterjee, Mackenzie Parker, Derrick Satterfield, Ann-Marie Vollstedt, Jeffrey C. LaCombe, Adam Kirn1 IntroductionThis research paper explores how undergraduate engineering students make enrollment decisionsas they identify additional disciplinary interests. Calls have been made to support thedevelopment of students’ engineering identities alongside traditional competencies [1]–[3] ashow students see themselves as engineers has implications for learning, persistence, andmotivation [4]–[6]. Interest has been identified as a key
engineering students to work effectively in teams, writing that“because of the increasing complexity and scale of systems-based engineering problems, there isa growing need to pursue collaborations with multidisciplinary teams of experts across multiplefields” [1, pp. 34–35]. ABET has similarly dedicated one of its seven student outcomes toteamwork, wording it as: “An ability to function effectively on a team whose members togetherprovide leadership, create a collaborative and inclusive environment, establish goals, plan tasks,and meet objectives” [2]. Research studies have also repeatedly underlined the importance ofdeveloping engineering students’ abilities to work in teams to meet industry needs [3], [4].As a result, there has been an increased
within a very short timeframe –it is a task well suited to potentially being automated.Addressing the challenge of such labour-intensive marking has received much attention inrecent years with the significant advances in the field of Artificial Intelligence (AI) andMachine Learning (ML) [1]. In particular, Natural Language Processing (NLP) techniquesare being developed to exploit textual information for a variety of interesting linguisticapplications such as spam email filtering and sentiment analysis [2, 3]. Automated essayassessment model belongs to a class of NLP problems where the main task of the model is tolearn features and relationships between classes of human-marked sample essays and producetheir scores without further intervention of
. Accordingly, we are trying to answer the following: How does the faculty's effective communication affect students' motivation in engineering capstone design projects?I. FRAMEWORK The Assessment Scale for Communication Skills measures 6 Communication Skills Dimensions (Respect, Expression, Value, Impediment, Motivation, and Democratic Attitude). However, we were interested in the four dimensions: 1) Express dimension, which asks if professors can effectively express themselves through examples, proposing solutions, eye contact, and voice tone. 2) Value dimension asks if professors value students' thoughts and opinions. 3) Democratic Attitude dimension asks if professors create a friendly atmosphere that allows students to ask questions and freely
design and implementation of learning objective-based grading for transparent and fair assessment; and the integration of reflection to develop self-directed learners. ©American Society for Engineering Education, 2023 Response Process Validity of the CBE Adaptability Instrument When Used With Engineering InstructorsI. IntroductionThere have been several calls of action to change undergraduate engineering education with onefocus being on the adoption of research-based instructional practices [1]. Adoption of research-based instructional practices have been shown to contribute to attracting and retainingundergraduate STEM students [2]. This is particularly important given that more than
method of assessment of problem-solving skills that may beextended to assist with the process of assessment planning and quantification for accreditation ofundergraduate degree programs in engineering. Accreditation of undergraduate degree programsin engineering, such as by ABET, currently requires programs to demonstrate students’ ability to“identify, formulate, and solve complex engineering problems by applying principles ofengineering, science, and mathematics”[1]. Traditional assessment data can lack reliablegranularity [2] to measure problem-solving skills. Reliable granularity is the reliability (oragreement) of assessment across instructors while quantifying problem-solving processes withaccurate granularity. We propose a new method using
Programs led by Dr. Barr is the Director of Assessment and Evaluation of STEM Programs at Rice University. He has been an evaluator and psychometric expert on several federally funded projects in ©American Society for Engineering Education, 2023 Design and Testing of a Quantitative Instrument to Evaluate Engineering Research Center ParticipationIntroductionThe National Science Foundation’s (NSF) Engineering Research Center (ERC) program aims toimpact society by developing research and innovation in universities across the country [1].Awards granted by this program are the highest-funded, single award from the NSF; a total of 75Research Centers have been funded since the program’s
understandings of stress andparticipants’ decisions to depart. The results are transformative in gaining insight for themonitoring and understanding attrition in higher education.Introduction, Literature Review, and Theoretical FramingThe rate of attrition in engineering doctoral programs is substantial, with 44% of women and 36%of men leaving their Ph.D. programs, according to the Council of Graduate Schools [1]. Theattrition across disciplines and in the US has received attention due to heightened competitivenesswithin global higher education [2]. Several crises, including financial/economic crises, Covid-19,and systemic racism (the combination of Covid-19 and racism being called the ‘dual pandemic’[3]) together have decreased students’ certainty
diverseengineering workforce that is adequately prepared with a range of skills required to solvecomplex, interdisciplinary, sociotechnical engineering problems. Questionnaire data from 314undergraduate engineering students at a small private university were used for psychometricanalysis. Exploratory factor analysis (EFA) revealed a six-factor structure. Three factors relate tostudents’ attitudes: (1) academic self-confidence and self-efficacy; (2) sense of belonging inengineering; and (3) attitudes toward persisting and succeeding in engineering. The other threefactors focus on: (4) students’ understanding of the broad nature of engineering; and how theyappreciate the importance of (5) non-technical and (6) technical skills in engineering
mentors, and their motivations and/or persistence. The first part of her career was spent designing residential split system HVAC equipment and Indoor Air Quality (IAQ) unitsfor Trane in Tyler, TX. Kristin has taught about design, engineering, and manufacturing to students of all ages in various places including to preschoolers via Schaefer Engineering’s STEM outreach, to senior mechanical engineering undergraduates at TAMU, to eighth graders in KatyISD at Beckendorff Junior High, and to freshmen mixed major undergraduates at UH. Kristin is also the mom of one smart teenage boy whose journey through learning differences and Type 1 Diabetes (T1D) has enabled her to connect with and support students with a broad spectrum
Career Theory StudyAbstractThe present paper assessed the attributes that could influence career decisions amongundergraduate engineering students in Singapore. The social cognitive career theory (SCCT)was employed as the theoretical guideline for the investigation. This paper was directed bythree main research questions: (1) How do self-efficacy (SE), outcome expectation (OE),social support (SS), barriers (BR), and interests (IN) affect career decisions amongengineering students? (2) How do SS, OE, SS, BR, IN, and career goals (CG) correlate? (3)Are there any differences in the psychological factors between freshmen and seniorundergraduate students? 27 participants were recruited from an internationally recognizedresearch institution in
networking, wikis, and alternate reality worlds have grown significantly. Some instructorsshare their course materials and teaching ideas broadly, which expands learning and educationequity. Online content such as open educational resources (OERs) have been developed to supporthigher education students. Open educational resources are teaching, learning, and researchmaterials, commonly in the digital medium and public domain; an open educational resource maybe released under an open license [1]. In other words, an OER allows others to access, use, adaptand redistribute the materials at no cost. An OER may include complete courses, individual courseunits or modules, textbooks, lesson plans, syllabi, lectures, assignments, game-based learningprograms
forsome kind of grade replacement [1]. In general, the second-chance exam covers the same coursematerial as the first-chance exam at the same difficulty level, but uses new questions.Second-chance testing can be viewed as a form of mastery testing [2], but students are provided asingle re-take attempt.Previous research has found that second-chance testing leads to improved student performancebecause it provides students feedback on the shortcomings of their knowledge and an incentivefor students to remediate those shortcomings [1, 3, 4]. Students can address gaps in theirunderstanding, take a second version of an assessment to demonstrate their mastery, and boosttheir score.In this paper, we investigate whether second-chance testing has affective
Associate Professor in the Experiential Engineering Education Department at Rowan University. Her research interests relate to the incorporation of active learning techniques such as game- based learning in undergraduate classes as well as innovation and entrepreneurship. ©American Society for Engineering Education, 2023Work in Progress: Designing a Survey Instrument to Assess Graduate Student MotivationTowards Degree CompletionIntroductionThe doctoral degree process can be arduous and time-consuming; often requiring students tomaintain a high level of motivation to obtain their degree [1], [2]. In King [3], attrition rates fordoctoral programs were found to average 43% in the USA, between the years of 1992 and
, 2023 WIP: Developing a Guide to Support Engineering Student Out-of-Class Participation and Professional LearningIntroductionMany co-curricular engineering research studies have connected students’ participation to specificprofessional (e.g., communication, teamwork [1]–[4]) and personal outcomes (e.g., identity,retention [1], [5]–[7]). This approach has established a foundation for claims that co-curricularengagement is important for engineering students’ overall development but leaves questions aboutwhat drives students’ engagement in these activities. This study leverages a pilot survey to explorestudent reasoning for engaging in co-curriculars and develop an institution-specific co-curricularengagement guide to
the academy. We pursue this endeavor through anexplicit standpoint of feminist epistemology, recognizing that our collective positionalitiesimpact our methodological approaches and analyses of these methodologies. As women inSTEM, we utilize two of the four dimensions of Black feminist standpoint theory (BFT): (1)lived experiences viewed as a criterion of meaning and (2) the use of dialogue to accessknowledge claims. We expand these dimensions to all women by leveraging feminist theory,which emerged from BFT. The method presented allows each panelist to contribute their distinctbut overlapping personal, professional, and research experiences to create one unified message.Together, we believe our individual experiences revealed unique insights
success in pair programming? We analyze keyfactors—gender, prior programming experience, confidence in programming, as well aspreferences toward deadlines, communication, and leadership. We then provide several bestpractice suggestions toward the optimization of pair programming.2. Related Work/BackgroundResearchers have generally assessed pair programming to be positive for both in person [11, 20,25, 27] and remote [1, 3, 5] modalities. In one meta-analysis of 18 studies, positive effects foundincluded decreased time spent on low-complexity programming projects and increased quality ofcode for high-complexity programming projects [15]. However, there is reason to be cautious inthinking of out-of-the-box pair programming as a panacea for
indicates the presence of all fourpathways. All results taken together demonstrate how understanding individuals’ experiencesthrough early childhood and high school can evolve or stagnate with age and development.1. IntroductionIt is the unique experiences and perceptions of an individual which develop personal identity;often each of those experiences are heavily influenced by others surrounding us [1-2]. One’schoice in a college, or major, or even a particular career path is shaped by both positive andnegative perceptions of prior experiences, often emerging from passions or interests developedthroughout childhood [3]. Perception is a subjective evaluation of these experiences, and thus,positive and negative experiences differ from person to
activities that are nottypically seen as “engineering” by engineering culture and curriculum (in opposition to acceptedactivities such as engineering club participation, engineering service, etc.), but that studentsidentify as connected to their goals in engineering. Examples of these activities could includestudents’ participation in competitive or recreational sports, artistic hobbies, and other leisure-based activities, though nearly any activity could be identified in this way by a student.Literature shows that students’ participation in on- and off-campus activities influence their senseof belonging and conceptions of themselves as engineers [1], [2]. Amongst these activities,students are exposed and integrated into cultures of engineering that
positive relationship betweenactive learning strategies and students’ likelihood of engaging in organizing behaviors forsustainability. Furthermore, we found a positive relationship between futures thinking andsustainability-related activism behaviors, indicating that students who reported spending timethinking about climate change and its future impact also reported being more likely to engage inactivism behaviors.Keywords: active learning; sustainability Introduction and BackgroundWhile educators and policymakers give much attention to issues such as workforce development,global competitiveness, and economic advancement as important long-term outcomes of highereducation [1-3], colleges and universities should
aspects of engineering work andin teaching engineering. According to Rittle-Johnson et al. [1], conceptual knowledge is definedas “understanding of the principles that govern a domain,” while procedural skill is “the ability toexecute action sequences to solve problems.” This distinction is commonly discussed inmathematics education [1, 2, 3, 4] but also in other fields, including biology [5], chemistry [6],engineering design [7], electrical engineering [8], structural engineering [9], and statics [10]. Inthis work, we investigate conceptual understanding in statics, a core course in undergraduatemechanical and civil engineering education that is also often taken by students in otherengineering majors. Engineering problems presented to college
adaptive goals to be successful such as academic or professional achievements.Secondly, in order to be successful, an individual actively engages in behaviors that maximizetheir goal accomplishments. Thirdly, being successful is unintuitive and hard as humans havenatural limitations and biases that can distract them from achieving their adaptive goals.Byrnes’s self-regulated model of decision-making (SRMDM) (Byrnes, 1998) includes phases ofGeneration, Evaluation, and Learning (Figure 1), each potentially influenced by ModeratingFactors. During the Generation phase, the decision-maker generates several alternatives to worktoward a particular goal. Then these choices enter the Evaluation phase for further evaluation.The Generation and Evaluation
career were integral to engineering selection and success. Genogramsreflected use of family system communication to resolve the stressors of career pursuit. Thefindings have the potential to inform undergraduate engineering recruitment and retentionplanning efforts, enhancing academic career services, advising, and counseling.1. IntroductionTraditional conceptualizations of engineering success have included aptitude tests,demographics, and high school performance [1]. However, outstanding achievement, orexemplary student performance, has been attributed to additional factors including personalmotivation, emotional development, and influence of family and teachers [2]. Exemplaryresearch suggests exemplar students can serve as a source of
providing support for studentsgoing through difficult times in high-enrolment courses. WTAs are regular members of theteaching assistant staff, but they use an early warning system to identify potential students at riskof failure, initiate communication using supportive language, and take action by suggestingflexibilization or providing academic support for students facing challenges. WTAs have beenincorporated into 27 courses at a large school of engineering in Latin America, during 2022, andhave been positively evaluated by students. One of the main current challenges of the approach isscalability.1 MotivationStudents regularly deal with the effects of health and emotional situations faced by themselves orby family members. Aware of those
the programs in which they participate”. This article highlights the importance oflearning assessment as a component of the learning management process and is aligned with thedefinition postulated by Palomba and Banta (1999, p. 4): learning assessment corresponds to theprocesses of “collection, review and systematic use of information about educational programs carriedout with the purpose of improving student learning and development” (Palomba and Banta, 1999, p.4). Table 1 presents the six strategies established by Palomba and Banta (1999) for assessingstudent learning: Table 1 – Strategies for assessing students’ learning. Set goals and objectives of learning Design and implement a thoughtful approach to
University Milo Koretsky is the McDonnell Family Bridge Professor in the Department of Chemical and Biological Engineering and in the Department of Education at Tufts University. He received his B.S. and M.S. degrees from UC San Diego and his Ph.D. from UC Berkeley, ©American Society for Engineering Education, 2023 WIP: Using Machine Learning to Map Student Narratives of Understanding and Promoting Linguistic JusticeIntroductionThis work-in-progress paper expands on a collaboration between engineering educationresearchers and machine learning researchers to automate the analysis of written responses toconceptually challenging questions in statics and dynamics courses [1]. Using the
. Her research efforts at at the Center for Engineering Education and Out- reach focus on supporting discourse and design practi ©American Society for Engineering Education, 2023 Work in Progress: Using the Formative Assessment Enactment Model to Characterize Instructor Moves in a Learning Assistant Supported Mechanics CourseThe LA model, developed by the University of Colorado- Boulder, has been gaining momentumin engineering departments [1]–[4]. LAs are undergraduate students who facilitate studentthinking and encourage inclusive active learning in the classroom. They participate in weeklypreparation sessions with their supervising faculty, where they provide
educationresearch, in part because it has the advantage of collecting stories and giving voice toexperiences that have perhaps been silenced in prior scholarship. For example, in recentengineering education literature, narrative methods have been used to explore subjects like howand why students choose to study engineering [1], the emotional trajectories of engineeringstudents [2], learner agency in intercultural project based learning environments [3], and theinfluence of race and gender in engineering education in the US [4]. Narrative inquiry has twodistinct advantages compared to other research techniques. First, it capitalizes on humans' naturalinclination to think and share their experiences in the form of stories, thus making data
Understand StudentProblem-Solving ApproachesMotivation and BackgroundProblem-solving is an essential skill needed in the field of engineering [1]. The ability toeffectively solve complex engineering problems can be the difference between project successand failure, but problem solving differs based on expertise. Experts are known to employdifferent problem-solving strategies compared to novices [2, 3]. Experts’ greater informationprocessing capacity [4] allows them to approach a problem in a non-systematic manner [5].Specific skills that allow experts to effectively solve a problem are the ability to mentallyrepresent a situation and the ability to employ different problem-solving approaches for differenttypes of engineering problems [6]. Expertise