conclusions or recommendations expressed in thismaterial are those of the authors and do not necessarily reflect the views of the National ScienceFoundation. The authors thank our project evaluator, Dr. Liz Litzler. We thank advisory boardmember Diana Gonzalez for her support with recruitment on this project. The authors also thankthe year 2 and year 3 participants for supporting this work by sharing their experiences in oursurveys. References[1] T. M. Evans, L. Bira, J. Beltran-Gastelum, L. T. Weiss, and N. L. Vanderford, Evidence for a mental health crisis in graduate education, The FASEB Journal, vol. 36, pp. 282- 284, 2018.[2] J. L. Lott, S. Gardner, and D. A. Powers, Doctoral student
the GPDs to reflect on thelived experiences of graduate students in their program. As part of these questions, we inquiredabout the extent to which students were experiencing trauma during the time in graduate schooland the actions taken by the GPD when a student was experiencing trauma. The interview alsoincluded questions about the role of the department and institution in handling traumatic events.All the interview audio was transcribed by Rev.com for analysis purposes.Preliminary Data AnalysisLeveraging trauma-informed frameworks of care and systems analysis techniques, the dataanalysis has focused on the first two research questions noted in the Project Overview section.To this end, the initial data analysis process involved examining
analyzedalong with data from the other survey instruments to explore the relationships between cognitive,motivational, and emotional processes on self-efficacy as it relates to academic persistence.6. AcknowledgementsThis material is based upon work supported by the National Science Foundation under Grant No.2204892. Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation.7. References[1] H. N. Haron and A. M. Shaharoun, "Self-regulated learning, students' understanding and performance in engineering statics," presented at the IEEE
video game modifies visual selective attention," Nature, Article vol. 423, no. 6939, p. 534, May 2003, doi: 10.1038/nature01647.[13] P. Wang, H.-H. Liu, X.-T. Zhu, T. Meng, H.-J. Li, and X.-N. Zuo, "Action video game training for healthy adults: A meta-analytic study," Frontiers in Psychology, vol. 7, Jun. 2016, doi: 10.3389/fpsyg.2016.00907.[14] S. Kühn, J. Gallinat, and A. Mascherek, "Effects of computer gaming on cognition, brain structure, and function: a critical reflection on existing literature," Dialogues in clinical neuroscience, Periodical vol. 21, no. 3, pp. 319-330, 2019, doi: 10.31887/DCNS.2019.21.3/skuehn.[15] A. J. Toth, N. Ramsbottom, M. Kowal, and M. J. Campbell, "Converging evidence
recommendations expressed in this material arethose of the author(s) and do not necessarily reflect the views of the National ScienceFoundation.References[1] I. Direito et al., “Diversity, Equity, and Inclusion in Engineering Education: an Exploration of European Higher Education Institutions’ Strategic Frameworks, Resources, and Initiatives,” in SEFI 49th Annual Conference Proceedings 2021, SEFI - European Society for Engineering Education; Brussels, Dec. 2021, pp. 189–193. Accessed: Feb. 08, 2024. [Online]. Available: https://lirias.kuleuven.be/3635850[2] K. Fu et al., “Broadening participation: A report on a series of workshops aimed at building community and increasing the number of women and minorities in engineering design,” in
19.3% Nursing 12.5% Psychology 11.9% Psychology 8.8% Nursing 10.4%Programming experience Programming experience No prior prog course 78.5% No prior prog course 80.0% No/very little Python 74.1% No/very little Python 88.0%Note: NB: Non-binary, SD: Self-described, PNR: Prefer not to respond, HI: Hawaiian, PacIsland: Pacific Islander, prog: ProgrammingDemographic data for student participants can be found in Table 1. The race and ethnicity profileof the sample broadly reflects that of the California community colleges from which studentswere recruited. We next evaluated
. 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
work in progress. This increased IAC engagement withcampus was spoken of favorably during the next advisory board meeting. Overall, the responsefrom the IAC members who participated was quite enthusiastic, and most have committed torepeating the process again.The technique is being repeated with the next set of students who started one term later. This setis a much smaller set of students, but again can help to refine the process.Going forward, the intent is to roll the assessment out to all senior design teams and then lookcloser at how this approach impacts the validity of the internal assessment. There is alsoconsideration of having students complete a follow-up reflection on the IAC feedback.References[1] M. El-Sayed and J. El-Sayed
we willobserve their teaching when implementing the game lesson. Data will then be coded andanalyzed using thematic analysis to find out the change in preparedness and engagement towardsteaching computer science.IntroductionIn response to the lack of engineering and computer science education in high school, the NextGeneration Science Standards (NGSS) were created in 2014 by twenty-six states with twentystates adopting these standards [1]. The NGSS shifted science instruction to incorporate cross-cutting (utilizing common themes among STEM disciplines) engineering standards and expandon computational thinking skills [2]. However, as technology and computing have advanced, theNGSS do not reflect the modern skills needed for computing to
using worksheets and students were required to write theirwork into a bound notebook (3-ring binder, science notebook, or spiral bound). This handwrittenhomework approach was used to develop student’s ability to express their work clearly. Duringeach test, the notebooks were collected and scored. The instructor gave feedback on errors thatwere noticed and gave a score that reflected the student’s ability to communicate and execute thematerial. The scores did not impact the student’s course grade; however, if a student earned apassing score on all the notebook checks, then the final’s scaled percentage was able to replacethe lowest exam grade.Second Iteration (Winter 2022-2023)In the second quarter, two sections consisting of 62 students were
4.33 I felt comfortable sharing my thoughts and questions during gameQ10 sessions. 4.09 4.07Q11 The game covered all necessary topics related to hydrogen production. 4.13 4.14 The topics covered in the game were relevant to my overall courseQ12 understanding. 4.30 3.71Q13 The assessments within the game were clear and fair. 4.21 4.14 My performance in the game accurately reflects understanding ofQ14 content. 4.09
goes beyond explicit content, aiming to identify underlying concepts, patterns, and thus themes that are not at first apparent; it entails interpreting data to uncover the implicit, or hidden, meanings and insights in a particular text. We analyzed this secondary dataset in repeated and systematic movements between these different phases in a spirit of inquiry and interpretation toward answering our proposed research questions[79], [80], [81], [82], [83], and viewed our reflection and activeroles as both researchers and IDR program members as crucially important to addressing the inevitable subjectivity of the Qualitative paradigm. pecifically, we first established Familiarization based on
components involves strategic utilization ofBlender and SolidWorks software. Blender's “. blend" file format seamlessly integrates into Unity'sassets for designing the fan. SolidWorks-generated components are reimagined in Blender forcompatibility with Unity as shown in Figure 2. The wind turbine model is sourced from the Unity3D Asset Store, providing a pre-built foundation [3].Within Unity 3D, the design process continues with the creation of essential elements, leveragingmesh colliders and scripting for user interaction as shown in Figures 3, 4, 5, and 6. The additionof reflections enhances visual appeal, contributing to a more immersive and realistic userexperience. The design process seamlessly integrates Blender, SolidWorks, and Unity 3D
the parallel and series combinations 2. Ohm’s law 3. Voltage and current dividers 4. Time-dependent effects such as R-C chargingThe math and physics required for explaining these topics is relatively straightforward and canbe built intuitively. This approach is reflected in the selection of lab topics which are thenfollowed by applications, such as using a timer IC NE555 and linear voltage regulator LM317.While these applications may look intimidating at first glance, they require only a handful ofcomponents. The LM317 lab illustrates the application of voltage division and Kirchoff’s laws,and results in a useful circuit. Similarly, the application of NE555 illustrates a practical designthat utilizes R-C charging and voltage division
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
of the post-quiz, correct responses had impressively increased to 60%, and incorrect responseshad decreased to 30 %. This overall improvement reflects positively on the effectiveness of theeducational video applied between the assessments, particularly in enhancing the understanding ofdislocations in materials science.ConclusionsIn conclusion, this paper highlights the significance of addressing the challenges students face invisualizing complex concepts in materials science education, particularly pertaining to dislocationsand their influence on material properties. The development of animated visual aids emerged as apromising solution to enhance understanding and engagement in the classroom setting.Through meticulous planning and
and asked to act as a consultant and interview their partner with thefollowing prompt, “How would you redesign the curricular collaboration experience for yourpartner?” Each person then interviewed their partner to gain insight to their needs. A second roundof interviews was conducted to dig deeper into the ideas developed in the first round. After theinterview, the individuals used their notes to define an actionable problem statement based on theneeds and insights collected in the interviews. The attendees then ideated by sketching five radicalways to solve their partner’s needs. The ideas were then shared with their partner to get feedback.The individuals then reflected and generated a sketch of a big idea solution to the need
fine-tune the complexity of questions to suit different levels of student understanding. For example,prompts can be adjusted to generate questions ranging from basic knowledge checks to more intricate,analytical challenges. This capability ensures that assessments can be customized to accurately reflect thelearning stages of students, making them more effective across both introductory and advanced courses.Additionally, AI-generated quizzes can be tailored to focus on specific topics by refining the prompts toemphasize particular learning objectives. This allows educators to align assessments directly with thegoals of their courses, whether it’s to reinforce core principles in a subject or to delve deeper intospecialized areas. For instance, a
throughout different stages and majority of students responded Q8,accordingly. They all claimed that they worked their best with their team except one student (Q10).Responses to technical skills improvement are given in Figure 3 (c). These questions (Q11-Q19)reflect students experience and their learning thought the project. Responses to Q11 to Q14 showsthey “Strongly Agree/Agree” with their learnings. It seems the timing diagram had been the mostchallenging part of the design as four students responded with “No Opinion” with level three outof five and one student did not learn about the I2C protocol at all. More than ten students responded“Strongly Agree” to the rest of the questions (Q15-Q19) which are overall questions on the projecttechnical
the studentsCreative Thinking, Critical Thinking, and Oral Communication [4]. Brooks, Benton-Kupper, andSlayton concluded that assessment of capstone performance is on the reflection and contributionby each team member [5]. These ideas for a capstone class are the foundation for the ECE SeniorDesign course sequence at Missouri S&T (Senior Design is a two-semester sequence in whichthe first semester focuses on the design and organization of the project and the second semesterimplements the concept).Typically, each team is allowed to pick their project independently and no two teams could dothe same project. However, in Fall 2023 the instructor introduced a slight wrinkle in that teamswere allowed to select a coil gun project in which they
. Here, faculty were able to analyze the data and beginidentifying where change would be most needed, impactful, and practical.Faculty had the chance to meet internally with a trained learning community facilitator toanalyze and reflect on their own program’s data. After faculty were able to analyze their ownstudent performance and curricular complexity data, faculty had the opportunity to meet indiscipline-specific groups. For example, all participating mechanical engineering faculty at eachuniversity met to share their data and how they made sense of the data.The faculty will continue meeting internally and in discipline specific learning communities overthe course of a year. During this process faculty will be able to ask more clarifying
practice" [5, p. 11]. For example, popular K-12 engineering activities like designinga tower to hold weight or building a roller coaster to meet criteria are often repeated acrosselementary, middle, and high school grades without clear learning progressions [5]. Whileengaging, such building projects generally promote a tinkering approach to develop a workingprototype [6], [7], [8] that does not reflect the work of expert engineers [9], [10]. To support thedevelopment of more authentic engineering learning outcomes and goals in K-12 settings,previous studies have engaged engineering experts, such as professional engineers [11] andphilosophers of engineering [12]. This study builds on that work by exploring the perspectives ofengineering university
visitors were invited to vote for the projects. Out of allthe student projects, visitors have selected the most popular mini-world Slice Of Earth (Figure 1left), the most complex design Dante's Inferno (Figure 1 middle), and the most interesting designField of Stars (Figure 1 right). These projects were also kept in our department for one moresemester for additional visits. Figure 1: Slice Of Earth (left), Dante's Inferno (middle), and Field of Stars (right)CHALLENGES AND REFLECTION We gained insights from this semester-long project on the challenges and opportunities facedby CAD education. While the design of our curriculum was successful, we observed differentchallenges faced by our students during implementation. Commitment to a long-term
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
call (28.1%), and send an email (7.0%) (Figure 3).Figure 2: Introduction to Engineering Students Perception of EmailFigure 3: Introduction to Engineering Students Communication PreferenceTo further clarify, respondents were asked if communication styles reflected communicationtype, using a multiple response type question. For PERSONAL communication (survey definedas with friends & family), respondents preferred sending a text message (34.8%), over making aphone call (34.8%), direct or instant messaging (19.6%), sending an email (1.8%), or via socialmedia by posting content (6.3%). When asked if they had access to their PERSONAL emailaccount via an APP on their phones, all of the responses indicated “Yes.”For BUSINESS communication (survey
the mean fell between the 2.5 – 2.99 range, choice3 for both men and women, with the greater number of women choosing higher GPA ranges, thusthe higher mean. Mean scores for CSE, GCM, and FCM were computed from survey choiceswhere the value labels were as follows: Strongly Disagree (1), Disagree (2), Neither Agree norDisagree (3), Agree (4), Strongly Agree (5). Thus, the higher scores in Table 3 for CSE, GCM,and FCM reflect the strength of agreement with the question.Tests of Relationships: F-test, t-test, and Correlations. Levine’s test for inequality ofvariances (F-test) and independent t-tests (95% confidence interval) were performed for GPArange, CSE, GCM, and FCMs. Findings are depicted in Table 3 and summarized in Table 5.Findings from
Number [EEC-1849430 & EEC-2120746]. Any opinions, findings andconclusions, or recommendations expressed in this material are those of the author(s) and do notnecessarily reflect those of the NSF. The authors acknowledge the support of the entire e4usaproject team.References[1] “The Standards | Next Generation Science Standards.” Accessed: Feb. 07, 2024. [Online]. Available: https://www.nextgenscience.org/standards[2] “Employment in STEM occupations : U.S. Bureau of Labor Statistics.” Accessed: Feb. 07, 2024. [Online]. Available: https://www.bls.gov/emp/tables/stem-employment.htm[3] “Motivational factors predicting STEM and engineering career intentions for high school students | IEEE Conference Publication | IEEE Xplore
studies. Then, wewill delve into the discussion section, where we will interpret the results within the context ofexisting literature and theory. This section will also explore the practical implications of ourfindings for educational institutions. Finally, we will conclude by offering a reflective summaryof the significance of the study and its contributions to entrepreneurial education research.MethodologySurveyA Cronbach's Alpha of 0.890 was attained during the survey validation process for theEntrepreneurial Competencies dimension and 0.876 for the Entrepreneurial Intention dimension.Table 1 shows the corresponding Cronbach´s Alpha reliability analysis by dimensions.Descriptive statistics were used in sample characterization for data analysis