the primary focus is directing students toengage with the tool to reflect on their experiential learning activities such as project teams,study abroad or research so they can build a story bank of their growth and development toprepare for interviews or other employer interactions. In the business school, the tool isintegrated into the undergraduate curriculum, and students achieve different levels of eachcompetency through the courses they take, with some direct interaction with the tool. Lastly,public health has fully integrated the tool with a masters program, where students use the tool toexplore the pathways to different careers as they gain proficiency in various skills, and much ofwhat happens in the tool is automated through the
profession. Previous research has explored the use of artifact elicitation as a qualitative researchmethod in engineering education, building on the principles of photo elicitation, where visualprompts are used to evoke more profound, reflective responses [1]. This method allows for morecomprehensive insights than traditional semi-structured interviews, connecting participants'creations to their personal experiences. Artifact elicitation, similar to informational interviews,enables students to connect their theoretical knowledge to real-world contexts. This approachcould provide a framework for understanding how student interactions, such as informationalinterviews, might elicit more profound reflections and personal insights. Biases
; Jenkins, 2000; Kolb & Kolb, 2005, 2022) for its emphasis of a cyclical learningprocess that recognizes individual learning styles (Kolb & Kolb, 2005). The theory structureslearning through a cycle of concrete experience, reflective observation, abstractconceptualization, and active experimentation (Healey & Jenkins, 2000). In engineeringeducation, this approach enhances understanding of complex concepts and promotes activelearning (Widiastuti & Budiyanto, 2018; Abdulwahed & Nagy, 2009). It has been successfullyimplemented in various contexts, including laboratory education (Abdulwahed & Nagy, 2009),design competitions (Gadola & Chindamo, 2019), and construction engineering courses (Lee etal., 2008). The theory
not be a necessary participant. It can be defined as “individual transformationresulting from reflection on direct experiences, leading to the development of new abstract and appliedskills in the learner” [19]. In 1984, based on the learning theories of John Dewey, Kurt Lewin, and JeanPiaget, Kolb proposed a four-stage experiential learning cycle model (Figure 1): “concrete experience,reflective observation, abstract conceptualization, and active experimentation.” This model clarified thefundamental process of experiential learning [20]. Kolb categorized these four stages into twofundamental dimensions: the comprehension dimension and the transformation dimension. Concreteexperience and abstract conceptualization belong to the comprehension
fall internship, and all fourstudents persisted in their engineering major or minor coursework.Data Collection and Analysis We conducted four semi-structured interviews approximately one year after theyparticipated in the program. Each interview was conducted virtually and lasted approximatelyone hour. The protocol for the semi-structured interviews can be found Table 1.Table 1. Protocol Questions Target Information Interview Guiding Questions Program reflection Can you tell me a little about your experience with the program and overall, how you feel now about that semester? Reflection on Can you tell me what you have been doing in the months since coursework post
discussion, overarching trends were identified and students were asked to reflect again ontheir perceptions of KSAs and work-integrated learning. After the focus group, individualsurveys were disseminated to ask follow up questions to the participants. Thematic analysis was used to guide the data analysis and identify preliminary findings[15], [16]. The focus group and accompanying handouts were used to identify trends andtensions in students' perceptions before discussing them with their peers. The initial findings ofthis data analysis in the early-stages of the program will be used to guide future research andpractice in the work-integrated program.Preliminary Findings Through the focus group and preliminary analysis we saw that
, and personal goals as key constructs shaping their reflections. Byinvestigating these elements, the study seeks to gain insights into how co-op experiences impactstudents' confidence in their abilities, their career expectations, and the personal goals theyestablish and accomplish during these practical work experiences. The primary research questionwas: “How do engineering students participating in a co-op program navigate their careerinterests, decisions, and outcomes through the constructs of Social Cognitive Career Theory?”Theoretical FrameworkMany studies explore co-op and work placement learning using Social Cognitive Career Theory(SCCT) (Reisberg et al., 2012; Raelin et al., 2013; Raelin et al., 2014; Chukwuedo & Ementa,2022). SCCT
Engineering at The Ohio State Universitywere asked to complete an anonymous survey about their experiences with the teams they havebeen a part of. The survey asks students about their background, role and level of involvementand their motivation to join the project. They were asked to reflect about their experience in theproject team (Figure 2). There were also questions about their perception on how well-supportedthey feel by team organization/leadership and faculty advisors (Figure 3). Students were asked toreflect on the impact of their involvement in the project on their social life, leisure time, andmental health (Figure 4). Additionally, they were asked questions about the outcomes of theirparticipation, their team’s performance at competitions
-wise compared to the Vanilla cohort, and ii) Scrum cohort performed markedly bettercompared to the Vanilla exactly in the test topics practiced using the above techniques.Interestingly, despite the objective gains, the Expected Learning Outcome (ELO) survey resultsindicate that the Scrum cohort was more critical about their abilities, including those achievedwhile practicing Scrum methodologies. While we do not have a conclusive explanation for thisphenomenon, we provide several plausible hypotheses for the underlying rationales for suchresults. These include a heightened students’ awareness of the challenges and their knowledgegaps due to Scrum’s reflective practices, cognitive load and time constraints, and reducedcoverage of some technical
Graduate education in engineering often requires graduate students to balance multipleroles that shape their academic and professional identities. Indeed, in addition to developing theirresearch skills, graduate students are often asked to assume teaching and mentorshipresponsibilities. These responsibilities are seen as opportunities that can significantly contribute tothe student’s personal and professional growth [1]. However, these roles are sometimes viewed assecondary when compared to their research within the academic environment, reflecting a broadertendency to prioritize the latter over teaching in STEM opportunities/programs [2]. This limitationhas been reported to hinder the development of pedagogical skills in graduate students [3
in thefollowing document provides transparent documentation of content modules and evaluation, andmethods of assessment. A reflective survey is also provided as part of the learner work in everydedicated micro badge in this pathway, allowing learners to rate and comment on the utility of thematerial and activities in developing the skill in question and evaluate perceived benefits in theirfuture work/employment.3. Pathway Requirements For each level of the micro-credential, a list of pathway requirements has been identifiedto assess student skills and knowledge. These requirements are presented in Table 1, Table 2, andTable 3 for Level 1, 2, and 3 respectively. Three categories of requirements have been identifiedas shown below
% %Status Generation Not reported 12% - 3% - - - - % R1 University 65% 57% 71% 57% 65% 48% 52% %CarnegieClassification Non-R1 35% 43% 29% 43% 35% 52% 48% % Universities1 NHERI did not host an REU program in 2020 due to the COVID-19 pandemic.2 Reflects one student who participated twice and one student who left the program withoutcompleting it.MentorsFaculty mentors were selected every year by each site and were dependent on the projectsassigned to NHERI REU students. Faculty mentors’ mentoring experiences ranged fromunexperienced to highly experienced mentors. Faculty mentors were early career faculty, pre-tenured
interests while participating in high-impact experiential learning. The threecollaborating institutions offering the STEM Research for Social Change REU program each havemissions and identities centered on using education for knowledge creation to advance social change forthe common good, and the REU’s theme reflects the collaborating institutions’ connected educationalmissions. The four programmatic objectives of the REU are to: ● improve understanding of science and engineering research that promotes social change; ● increase interest in and awareness of graduate school opportunities; ● increase personal networks and collaboration; and ● increase competence in STEM researchIn compliance with the 2023 Supreme Court
assessment bydiversifying the sources of metrics. This diversity includes tools that are specifically designed toassess SO achievement and others that infer SO achievement.Engineering education literature contains many examples of using internship experiences as anindirect means for assessing SOs. However, nearly all of these assessment tools were developedfor the ABET 2000 “a through k” SOs, which have since been replaced by the new “1-7” SOs.Examples include linking products from students’ internship experiences (reflection papers andportfolios) to SOs [6], mapping student and employer survey data to SOs [7-9], and evaluatinginternship competency assessments to infer achievement of continuous student [10].Student and Mentor SurveysThe student and
coursework and co-op experience. This finding willbe discussed further in the gaps section. In terms of learning and skill development, we also found that most papers, bothdescriptive and research, included discussions of learning that had practical implications forengineering educators and industry practitioners. Two common implications were (1) The 6importance of general reflection and goal setting during the co-op experience and (2) the rolethat pre-co-op professional development courses can play in uncovering the “hiddencurriculum.” While most authors were from academic institutions, this finding shows that workpublished at ASEE still has
professionalisminstruction to develop their skills in these areas. While getting real-time experience in theirengineering work, they need support in learning to navigate the ins and outs of the profession.All staff and faculty members select workshops and assessments based on their expertise andinterest levels. The instruction in these spaces is delivered in various formats, includinginteractive live seminar sessions, workshops, podcast content [9], and videos. In order to assesstheir learning in these areas, a variety of methods are utilized. They write papers that includeboth literature reviews on the areas and reflecting on how their personal experience connects,complete learning journals on various design and professionalism topics, record videos of
. Mashuri, M. S. A. Rasak, F. Alhabsyi, and H. Syam, “Semi-StructuredInterview: A Methodological Reflection on the Development of a Qualitative ResearchInstrument in Educational Studies,” IOSR Journal of Research & Method in Education, vol. 12,no. 1, pp. 22–29, 2022.[16] O. A. Adeoye‐Olatunde and N. L. Olenik, “Research and Scholarly Methods: Semi‐Structured Interviews,” Journal of the American College of Clinical Pharmacy, vol. 4, no. 10, pp.1358–1367, Apr. 2021.[17] C. Glesne, Becoming Qualitative Researchers: An introduction, 5th ed. Boston: Pearson,2016.[18] J. W. Creswell and C. N. Poth, Qualitative Inquiry & Research Design: Choosing AmongFive Approaches, 4th ed. Los Angeles: SAGE Publications, 2018.[19] J. Saldana, The Coding Manual
Tech. Her research and service interests include teaching and learning experiences in fundamental engineering courses, faculty development and support initiatives – including programs for the future engineering professoriate, and leveraging institutional data to support reflective teaching practices. She has degrees in Electrical Engineering (B.S., M.Eng.) from the Ateneo de Davao University in Davao City, Philippines, where she previously held appointments as Assistant Professor and Department Chair for Electrical Engineering. She also previously served as Director for Communications and International Engagement at the Department of Engineering Education at Virginia Tech, Lecturer at the Department of Engineering
) identifying any behaviorally ingrained actions that leadto that behavior, and (3) consciously switching to a new, more effective behavior. Practice withnew behaviors in the classroom, along with conscious reflection, can prepare students to morereadily adapt to the workplace environment.3. RealnessAs discussed above, differences in the school and workplace environments present challenges forstudents making the transition from one to the other. Relevant differences exist, for example inthe nature of problems addressed [9] and the socio-technical performances required [4]. These,and other differences, contribute to the issue of “realness” in the educational experiences.Realness is defined here as the degree to which assigned work has a direct and