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
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
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
students attend a flexibility, courses with plan structured both modalities but mix of in-person but students hands-on labs (in- Hybrid engagement, do not need to and online must follow person) and balancing online accommodate sessions based on set in-person theoretical and face-to-face individual a
. be transformed using information pedagogy. The numeracy of The AI assisted tools for pedagogy are endorsed by CUNY “height controls time” being quadratic (height distance =Graduate Center with the massive deployment planned for 0.5*9.8*t*t) and “speed controls range” being linear (distance2026. The CUNY AI pedagogy activities have been supported = v0*t) is straight forward when the “simultaneously” isby a Google Grant at One million dollars. Currently our captured as data columns side by side, namely, time column,height column, and range column. With a student’s private can be used as well (Brief Electricity and Magnetismsubscription fee to AI, graphic output is included as well. Our
stronger computational focus, demonstrated supports data analysis, design simulations, and decision-higher confidence in applying prompt engineering to database- making. Prompt engineering fosters critical engagement with AIrelated tasks, with many planning to use these skills for tools even in humanities-oriented contexts, encouraging users toautomating tasks, optimizing queries, and generating sample data. interrogate biases and limitations. However, teaching this skillIn contrast, EEM students, while also showing improvement, were presents challenges: students’ prior
, and is discussed in the body of this paper. The presentations, and other compositions, which is the subject ofassignment allowing the most extensive use of AI was called the much ongoing discussion and debate [1, 2, 3].Expert Seminar for which students were commissioned to create Generative AI has been simultaneously transformative anda scholarly research-based presentation on a human-systems disruptive in the educational domain. Along with AI’sintegration topic and deliver it to the class with a planned emergence
Engineering Marshall University Huntington, WV 25705 zhup@marshall.edu Abstract Medical image segmentation is crucial in diagnostics and treatment planning, enabling precise identification of structures within medical images for accurate analysis and decision-making. However, many medical professionals face challenges in leveraging deep learning models due to the technical coding skills required. This study addresses this gap by providing a practical guide to using three prominent deep learning models—SegNet, U-Net, and YOLO-Seg
Paper ID #49561Evaluating the Impact of a Summer NSF REU Program on UndergraduateStudents’ STEM Career Aspirations and Educational Goals: A Case StudyDr. Sudipta Chowdhury, Marshall University Sudipta Chowdhury is an Assistant Professor at the Department of Mechanical and Industrial Engineering in Marshall University. His area of research includes Critical Infrastructure Resilience, Disaster Restoration Planning, Supply Chain and Logistics, and formal and informal STEM Education. He has published over 20 peer-reviewed journal articles and multiple conference proceedings. He serves as a reviewer of multiple journals such
be modified while adopting a lens related to technology the integration of structured technology in the high schools ofmanagement. This can also help in ensuring the benefits of all Saudi Arabia while focusing on student engagement, lessonthe approaches related to strategic decision-making within all planning, and the strategies of assessments?the policymakers and educational institutions of Saudi Arabia.However, without the involvement of proper evidence on the H02: There is no presence of significance among thelong-term benefits of all the operations investment within the participants of OPD and the inclusion of structural technologytraining programs for the online teacher can further remain
“audible learners”, and hence engineeringcourses (and mathematics, physics and chemistry classes that they also take) are very structured.Therefore, engineering instructors should present material in a very structured manner.In 2015, Russ [9] presented a detailed study discussing the quality that is expected in technicalwriting communications and summarized the recommended features of good technical writing(and brief descriptions and examples of each); they are presented in the following Table 1.Table 1. Recommended features that are expected in good technical writing communications, and brief description or examples of each (as per Russ [9]) Planning Define audience, purpose, topic knowledge, material and sources
Saudi women entrepreneurs in NSPs. Achieving gender further obstacles [39]. Many women hesitate to enter theequality in entrepreneurship could significantly boost the sector due to difficulty obtaining financing, complexglobal economy, reinforcing the importance of addressing government regulations, and financial instability [1]. Poorbarriers to women’s startup success. financial planning and inadequate preparation contribute to