graduateresearch assistant attend most sessions as observers and commenters. The seminar met for onehour per week for 15 weeks. Among the eight (8) enrolled students, seven were members of thefirst-year sustainability engineering cohort from 2023 (5 men, 2 women); four of the membersfrom this cohort did not enroll due to schedule conflicts. The other student was an upper divisionstudent (man) not affiliated with the cohort.Some of the goals of the seminar were to raise awareness and comprehension of perspectives thatmay differ of their own, to investigate techniques for promoting JEDI in both personal andprofessional settings, and to create a personal plan for promoting JEDI. Because the audienceconsisted primarily of first-year students, no prior
establishedframeworks. These assessments helped coordinators refine their methods and enhance studentengagement. In this work in-progress that began in the Spring of 2024, we present lessonslearned to guide future programs and their evaluations, focusing on both quantitative andqualitative data collection methods.IntroductionEffectively capturing how science, technology, engineering, and mathematics (STEM) outreachprograms shape participants’ experiences, perceptions of the program, and attitudes towardengineering requires careful considerations and use of research-based methods. This includescareful planning, attentive implementation, the selection of appropriate tools, and rigorousinterpretation of the resulting data. In this study, we explore the necessary
samples are fully frozen. The four different sampleswere analyzed simultaneously on the cold stage system with images being collected with a cameraduring the cooling process to obtain the freezing properties of the water and its suspension. Severalcalibrations were conducted with 80 droplets, 1.0 µL volume per drop. Figure 1(a) shows theschematic of the planned experiment.To ascertain whether the adopted system generated consistent data, the data produced wascompared to another similarly developed device by the environmental department at WTAMU [9].The freezing spectrum from the new cold stage system was also compared with measured datasetsfrom previous studies [4,5,6]. Figure 1(b) shows example freezing spectra (i.e., frozen fraction =frozen
mimic some of the roles of a human tutor— such as hints for improvement [7]. The integration of AI-drivenproviding instant feedback, curriculum planning, content assessment tools also supports competency-based education,recommendation, automated grading and assessment, virtual where evaluations focus on a student’s ability to applyassistance, or creating custom learning materials at an concepts rather than on rote memorization. By continuouslyunprecedented scale, as shown in Fig. 1. monitoring progress and adapting to a learner’s needs, AI helps to create a more holistic picture of student
, planning investigations, and constructing explanations from evidence.Numerous studies have demonstrated that such pedagogies enhance students’ critical thinking,problem-solving, and conceptual understanding [10][11]. Moreover, inquiry-based approachesare a cornerstone of the Next Generation Science Standards (NGSS), which emphasize not onlycontent knowledge but also the practices of science and engineering [12]. Research comparinginquiry-based methods with more traditional, teacher-directed approaches indicates that whenstudents tackle authentic, real-world problems, they are more likely to develop the skills neededfor future STEM careers [13].Rural STEM EducationRural schools often confront challenges such as limited resources, geographical
proprietary or internal institutional practices that impactcredit transfer processes. Finally, regional differences across state systems, shaped by distinctpriorities and structures, may limit the applicability of these findings to California’s context.Despite these limitations, the study provides valuable insights and highlights areas for futureresearch. ReferencesAssociate Degree for Transfer | Academic Planning and Programs. transferprograms.calstate.edu/associate-degree-transfer.Baker, Rachel. “The Effects of Structured Transfer Pathways in Community Colleges.” Educational Evaluation and Policy Analysis, vol. 38, no. 4, 2016, pp. 626–46. JSTOR, www.jstor.org/stable/44984558.CSU Similar
students' perception of AI powered image recognition can monitor decision patterns,intelligence, and their ability to adapt to AI strategies. learning curves, and adaptive strategies. This allows teachers to customize lesson plans based on individual learning trajectories [26][27]. What begins as a simple AI-driven game II. LITERATURE REVIEW transforms into a powerful tool for cognitive skill assessment Tic-Tac-Toe, a classic two-player game, is widely used in and personalized learning.education to introduce logic
aged 7 to traditional teaching practices and enhance content to better suit students' no. 2, pp. 303–318, Jan. 2010. 12, offering valuable insights for educators to enhance lesson plans and individual needs. Students engaged with an AI tutor have shown significant
very positive 7Students’ Comments Were Focused On –• Improved Goal Setting: The student plans to be more decisive and set goals early to boost productivity.• Schedule Flexibility: They will loosen their grip on rigid schedules and deadlines to avoid frustration.• Combating Procrastination: They aim to start work earlier and prioritize team considerations over personal delays, especially for difficult tasks.• Enhanced Open-Mindedness: They will actively listen to team members' ideas and be receptive to different perspectives.• Building Trust: They will strive to establish trust within the team through open communication and a collaborative approach
logically and syntactically Education is one of the fields where AI has a great impact. correct. It can add comments to each line of code. TheEducation tends to adopt various modern practices to improve provided explanatory tutorial statements are great forthe overall educational experience, student engagement, and understanding the material. We may notice that a commentlesson planning. Various services and tools based on artificial error was discovered on a simple program of adding twointelligence are already used in the educational process. Some numbers and slightly different outputs based on the wording ofbenefits from the use of AI in education are: the input question. Although the example used is
challenge. Due to the complex geometry, we wanted toreview the possibility of 3D printing the turbines. Initial concerns were raised surrounding thestrength of plastic and degradation while in contact with water. A member of the teamexperienced with 3D printing created a test plan to determine what filament would perform bestProceedings of the 2024 ASEE North Central Section Conference Copyright © 2024, American Society for Engineering Education 5after being soaked in water. Figure 3 shows the results of the experiment, which included tensiletesting on 6 specimens, 3 of which were soaked in water
the usefulness of the material is demonstratedthrough design project learning, and cognitive competence, whereby expertise in the use ofmethods is gained through progressive use of methods. The result is a plan to provide improvementin the feelings about the topic (affect) as the students begin with rote learning, move to morerelevant problems, and receive peer and professor feedback. While difficulty is intrinsicallydifficult to address, since a course has stated learning objectives, through relevant examples andassignments this burden is ideally reduced as well.BackgroundDespite its significance, statistics education across educational levels often faces challenges relatedto content delivery, pedagogy, and student attitudes. The course
, theresa@creus.com jjhu@bridgeport.edu, abhilash@bridgeport.edu, aelsayed@bridgeport.edu Abstract—The University of Bridgeport (UB) received Achieve) is an NSF IUSE: HSI project funded under thefunding from the National Science Foundation's Division of Planning or Pilot Projects (PPP) track for the purposes ofUndergraduate Education through its IUSE: HSI Initiative in thesummer of 2022 to increase retention, persistence, preparedness, planning a process for building capacity and enhancingand graduation rates of students majoring in Computer, undergraduate STEM education at less-resourced institutionsElectrical, Mechanical Engineering, and Computer Science (CS) as a means of increasing
on the results of their studies, Cooperand Colleagues (2000) further provide the following recommendations for future policy andpractice regarding summer bridge programs: a) contain substantial math and readingcomponents, b) include profound evaluations, c) enable local control over curriculumdevelopment and delivery systems, d) start planning for the summer bridge program early in theyear, e) provide professional development opportunities for summer staff, and f) compare theexperience of the summer bridge programs with that of regular school. The primary goals of STEM summer bridge programs are to enhance the enrollment andpersistence of students from disadvantaged backgrounds in STEM and improve their experienceof STEM while they are
, apply for grants, manage the center’s operations, conduct strategic planning with the center and university leadership, and overall ensure the center fulfills its mission and goals. She is on the executive committees of the Center for Neuroengineering and Medicine, and of NeuralStorm, collaborating with the director and faculty towards the program’s success.Sadie Jean Davis, Mariko Chang Consulting, Inc. and Sadie J Davis Consulting LLC Sadie Davis, MPP is the Director of Evaluation for Mariko Chang Consulting, Inc. and the President of Sadie J Davis Consulting LLC. Ms. Davis has extensive experience in external evaluation and program assessment, specializing in the evaluation of initiatives intended to broaden
& Changes in Rank from 2023 to 2024 Impact Impact Δ Rank Rank Δ Class Topic 2023 2024 23-24 2023 2024 23-24 Week 9 - Self and Time Management 1.00 1.00 0.00 1 1 0 Week 8 - Stress Management and Mid-term Check-in 0.74 0.71 -0.03 2 2 0 Week 6 - Learning Science & Strategy 0.65 0.63 -0.02 3 4 1 Week 7 - Academic Career Planning & Advising Prep. 0.62 0.66 0.04 4 3 -1 Week 10 - Professional Communications
students across three semesters. Specifically, this study focused on the following mainresearch questions: 1. What is the relationship between time-use and student performance across all related assessments? 2. What are the potential methodological and contextual limitations that must be considered when interpreting digital simulation analytics?This WIP examines the patterns observed in student time on task during the completion ofseveral SIMnet’s Excel modules. The study provides a reminder to be cautious when using onlytime spent on a task as a method to measure student engagement. It also shares plans to usebetter methods, like asking students questions and doing interviews.Experimental MethodsThe study was conducted at a
to expand this work by including more responses from non-tenure-trackfaculty at this and other institutions. At the conference, the authors also intend to collect moreresponses from the faculty in attendance. Additional work is planned to provide more examplesof how instructors implement new concepts in the classroom and how faculty benefit financiallyand professionally.REFERENCES[1] M. Borrego and J. Bernhard, “The Emergence of Engineering Education Research as anInternationally Connected Field of Inquiry,” Journal of Engineering Education, vol. 100, no. 1,pp. 14–47, Jan. 2011, doi: https://doi.org/10.1002/j.2168-9830.2011.tb00003.x.[2] R. A. Streveler and K. A. Smith, “Conducting Rigorous Research in Engineering Education,”Journal of
and learning (5 min) ○ ‘Rigid Beliefs” exercise (5 min) ● Brief presentation on ‘psychological flexibility’ and an alternative approach to connection (5 min) ○ ‘Reframing Beliefs’ exercise (15 min) ● Small group brainstorming discussion on how to apply skills discussed in their settings (20 min) ● Create your personal action plan for how to bring today’s take-aways to your institution. (5 min) ● Large group discussion/debrief (5 min)Who is Encouraged to Attend: We encourage engineering educators and researchers to attend this workshop toconsider practical ways they can support students to find more effective methods ofaccessing connection in this transitionary period.Learning
20 0 0 20 40 60 80 100 120 Attendance (%) Figure 6: Trend of grades with attendances for C2-Sp24Study LimitationsThe findings presented in this study provide a lucrative basis for more extensive follow-up researchusing a larger data set, which would also enable the use of a wider set of other influencing factors.In order to assess students’ starting level and course plans in an appropriate manner, a test and aquestionnaire, respectively, could be used at the start of the course under investigation. Thegeneralizability of the findings of this study is limited to the
Wireless Communication.Andrew Zheng, Texas A&M University Andrew is currently a junior at Texas A&M University pursuing a major in Computer Science with an emphasis in Statistics, and a minor in Mathematics. After graduation, he hopes to continue onwards into graduate school, where he can combine his interests of solving complex problems with his desire to help others. His multidisciplinary research interests are varied, though his prior experience consists of AI/ML, Computer Vision, and Edge Computing.April Guo-Yue, Mississippi State University April Guo-Yue is an undergraduate at Mississippi State University, majoring in Computer Science and Biomedical Engineering. She plans to pursue a Ph.D. in Computer
creating a good writing process for themselves—one termed this as “white-page phobia,” e.g.: • “I struggle to start with an empty page. [….] In short, I am not great at the planning stage of writing when it [the topic] doesn’t just automatically click for me.” • “I need a good writing routine.” • “I will sometimes fall down research holes while writing, which can delay or derail the writing process.”8. Students also said page requirements had negative impacts on their writing: • “I end up having difficulty expressing my thoughts over a long format, and it makes me struggle to meet requirements for length of assignments.” • “I think ‘wordy’ writing is [a] habit formed by many of us having word minimums for essays in
. device efficacy and issues. • Ability to identify & address • Ability to plan a biomedical objectives of biomedical lab project. activities.Post-Lab • None • Knowledge about biomedical • All other topics and skillsSurvey device tests with respect toResults: biomechanics. • Ability to perform industry- level biomedical research.The final lab reports provided valuable insight into the students' progression in self
a frequent presenter and publisher on internationalization, strategic planning, globally focused academics, and Collaborative Online International Learning (COIL). Carrie is a 2019 Fulbright recipient and holds an Ed.D. in the Design of Learning Environments from Rutgers University.James Tippey, Excelsior College ©American Society for Engineering Education, 2025 Technology and Society Incorporating ethics, inclusive belonging for excellence, and societal understanding into computer and technology and engineering education curriculum design(2025). CoNECD Conference, February 9-11, 2025, San Antonio, TX Session Outline
Science 1 The most frequently applied theory was the Theory of Planned American Economic Review 1 Cogent Engineering 1 Behavior (TPB), which appeared in numerous studies, Economics of Transportation 1 indicating its relevance in understanding consumer intentions Renewable Energy: An International Journal 1 and decision-making [32], [33], [34]. These theories provided SAE International Journal of Sustainable frameworks for understanding the psychological and social Transportation, Energy, Environment
them. The projects of Things (IoT) startup company for their final project. Theyalso include a report out to the class so both the student and the were required to present a progress update and project plan atteam can demonstrate their learning in a peer review process. midterm and showcase their results during the final presentation. Corporate culture project: Cross disciplinary teams areformed with both business and engineering students included The startup company, Foot Traffic Stats, offers an IoTon each team. The team goal is to analyze several device that tracks foot traffic in specific locations. This
integration tools, including ETL (Extract,management. From figure 2, good governance begins with the Transform, Load) processes and cloud-based tools, offersestablishment of a well-structured plan that allocates specific scalability and adaptability to support the increase in theroles to the data stewardship to have responsibility to uphold demand for data [7]. Figure 3 showed that automatedthe integrity of the data and protection of the data. To provide pipelines increase efficiency, eliminate the errors associatedaccessibility and usability, the organization must have with manual intervention, and provide smooth transmissionstandard formats of the data that can easily integrate into other between the different
teaching and mentoring practices. The following is the excerption of students andfaculty feedback which supports how the mentoring effectively impacted. Students feedback Special Lecture ▪ Truly fascinating story of the development of the fist microprocessor. ▪ It was a great experience to meet the inventor of the microprocessor in person and to hear about his life, and I am glad to know such an important person in the history of technology is a Christian. I was surprised to learn that he had to keep his achievement classified for thirty years. ▪ One thing from Mr. Ray Holt special lecture that made me excited was that he wasn’t planning on becoming an engineer before he took an
both Universities academic programs. Entergy EXXON CTECH CenterPoint Energy Chevron Future Use of Energy in LA American Electric BP SciPort Power (AEP) SWEPCO Cleco StarBase Table 1: Industrial Partner Information Table Outcomes and ResultsEnrollment and RetentionAs a plan for increased enrollment and completion rates in SUSLA’s Department of Engineering &Technology, the
designed to provideadvanced course content and topics in an embedded Linux environment and to cover machine learningapplications and vision processing applications. After several semesters’ iterations, it was observedand received feedback from students that they found that this course helped them to understand moreabout embedded Linux systems. Some of the students would be able to apply what they learned in thisclass for their data science and data analysis of their master’s theses. The author plans to continue topursue further development of the contents of the graduate-level advanced embedded Linux systemcourse and share the learned lessons. Summary and ConclusionsIn this paper, an ENTC 644 Embedded Intelligent