engages regularly with professional development activities. Dr. Mailen is also the PI of The Writing SySTEM: A Systemic Approach to Graduate Writing Instruction and Intervention, a funded NSF IGE grant.Dr. Jeffrey LaMondia, Auburn University Dr. Jeffrey LaMondia is a Professor in the Civil and Environmental Engineering Department at Auburn University. Dr. LaMondia’s research focuses on modeling transportation systems, developing planning tools, and analyzing travel behavior. In addition to teaching undergraduate and graduate level courses, Dr. LaMondia is the Director of the campus-wide Common Book Program.Dr. Sushil Adhikari P.E., Auburn University Dr. Sushil Adhikari is a Professor in the Biosystems Engineering
innovation [6]. In healthcare, AI's potential to enhance patient care is becoming increasingly apparent. AI-assisted diagnostic tools, personalized treatment plans, and predictive analytics for patientoutcomes are expected to improve overall healthcare delivery. This could not only help doctorsmake more accurate decisions but also reduce healthcare costs, thus improving accessibility. AI'sability to create personalized therapies and targeted interventions holds the promise of betteroutcomes for patients, especially in underserved communities [7]. In the education sector, AI has the potential to transform learning methodologies by creatinghighly personalized learning experiences. Adaptive learning technologies could help tailoreducation to meet
an engineering effort. This includes describing the relationship between systems engineering and other engineering disciplines, describing the relationship between systems engineering and other non- engineering disciplines, listing the different life cycle processes of concern for systems engineering, and explaining the roles of decision management, risk and opportunity management, planning, monitoring, and control, configuration and information control, and modeling and analysis within an engineering effort. • Explain what a systems engineer does. This includes mapping the previous learning outcomes to the tasks of the individual systems engineer within a team. • Describe the fundamental
facilitator engaged in all these activities will approachall student engagement with an eye towards identifying “teachable moments” while alsoendeavoring to exemplify the profession's highest ideals while also being approachable,respectable, and inspirational.Organizing Student Life EventsBuilding community is an essential aspect of quality education. Facilitators at IRE are oftentasked with organizing and leading many student-life and professional development activitiesduring the semester and at the end-of-semester graduation celebrations. These include both in-person and virtual opportunities for the entire population, which may include movie nights,barbecues, kayaking trips, hockey games, etc. The duty of the facilitator in the planning
environment. In this section we discuss prior literature pertaining to both thesetopics.Contextual learning was used in a prior study that emphasized practical applications pertinent tothe area of mechanical engineering by including conservation education into an internshippreparation course [16]. This strategy sought to enhance student learning outcomes and promoteconservation-based behaviors, emphasizing the influence of discipline-specific, useful content onbehavior and student engagement. In another study contextual learning was used by the ChildrenDesigning & Engineering (CD&E) Project, which incorporated design-and-make activities intoK–5 lesson plans that linked science, math, and technology to real-world scenarios modeled afterNew
keyword sets, one discerns three general categories of keywords:design thinking & activity, business topics and technology. Table 1 gives a sampling for allthree categories. Table 1: Sample of AI Identified Keywords for Entrepreneurship in Mechanical Engineering Curricula Category Keywords Design Thinking & Activity Ideation techniques, iterative development, creative problem- solving, design projects, problem-based learning Business Topics Intellectual property, startups, venture capital, business plans, financial modeling, market research, leadership, teamwork Technology
analyses across the items suggested that elementary school teachers were less likelyto perceive benefits to using AI tools for students compared with middle or high school teachers.Teachers described challenges such as lesson planning, grading, and differentiation betweenstudents of different abilities, while suggesting AI tools were less likely to help with issues suchas classroom behavior and behavioral management.DiscussionOur preliminary results suggest that while teachers perceive potential benefits for using AI toolsto facilitate student learning and to decrease teaching workloads, challenges exist in the form ofethical concerns, lack of proficiency with AI tools, and ability to access or learn to use thesetools. Resolving these issues will
, Future Work, and Summary. The Categories section requires students to write oneparagraph for each major category defending the categories chosen and why particular conceptswere grouped in those categories. For the Influence section, students choose two to threeconcepts in each major category that positively influenced them during the semester. They writetwo to three sentences explaining how each chosen concept helped them and are required toinclude specific examples. The Future Work section requires students to write one paragraphexplaining which additional course concepts they plan to utilize in future semesters. The chosenconcepts in this section must differ from those in the Influence section. The Summary sectionrequires students to discuss
classroom settings. At theLebanese American University, nine faculty members began to experiment with GenAI useimmediately after the release of ChatGPT in November 2022. While the results of that actionresearch allowed participating faculty members to improve upon their application of GenAI intheir second and third iterations of the exercise in their respective classes, this paper focuses on aframework for pedagogical practice that could guide faculty as they critically plan their courseactivities and prepare their students for the use of GenAI in different academic settings. Whileemphasizing academic rigor, faculty using this framework will thoroughly analyze their existingcourse and program learning outcomes to accurately determine the potential
collaborators in the research [9].Group Level Assessment (GLA) is a process that guides participants through brainstorming theirchallenges, thematically analyzing their responses, and developing action plans to address theissues they have identified [10]. The seven-step process of a GLA is shown below in Table 1.Table 1. Description of Group Level Assessment process steps Step Description Climate Setting GLA process is described to participants Generating Participants respond to prompts placed around room on boards Appreciating Participants make notes on the boards to analyze the initial responses Reflecting Participants individually analyze the data and begin to find shared themes Understanding Participants share
Vision, Partnerships, Goals & Metrics, Leadership & Communication, andExpansion & Sustainability (INCLUDES National Network, n.d.). It focuses on identifying STEMparticipation challenges, especially for underrepresented groups, and developing solutions. Strongpartnerships ensure those most affected are involved. Clear goals and data-driven strategies tracksystemic change. Leadership is distributed, emphasizing communication and conflict resolution. Theinitiative also plans for long-term expansion and sustainability to build a more diverse scientific workforce.Statement on Identity-First Language Person-first language (e.g., individual with autism) is intentionally not being used in themanuscript and in the entire project
(APICS), the Transformation Team on the American Society of Engineering Education (ASEE), the Research Committee of Intermodal Freight Transport committee, Freight Transportation Planning and Logistics committee of Transportation Research Board (TRB) among others. Dr. Sarder chaired the Industrial & Systems Engineering Annual Conference in 2016 and 2017, and the Engineering Lean Six Sigma Conference (ELSS) in 2013. ©American Society for Engineering Education, 2025 Mechanical Performance of Additive Manufactured Bioinspired Lattice StructuresAbstract This summary report presents the outcomes and advancements in the field of FusedFilament Fabrication (FFF
University. He also holds a MS in Electrical Engineering from University of Rochester, an MBA from Texas A&M University, and an Ed.D in Leadership & Learning from Vanderbilt University.Tammy M. Mattison Ed.D., Air Force Research Laboratory & Belmont University Dr. Tammy Mattison is currently a Postdoctoral Fellow and Lecturer in the department of psychological science at Belmont University as well as an Adjunct Professor of Psychology at Southern New Hampshire University. Prior to these positions she worked in the fields of human resources, industrial/organizational psychology, employee relations, and career advising and planning for fifteen years. She is a Certified Professional Resume Writer (CPRW), has
are you addressing economic, societal, and/or environmental sustainability challenges in the design process and any potential tradeoffs? b. Problem framework: Who are the primary technical, social, natural, conceptual, and economic actors and how do they affect your process? c. How are you incorporating principles of Universal Design through the process? d. What are the ethical considerations and implications that you will (or did) consider when generating a solutions? e. How do you work effectively as a team member and what tools will you use to help your team be productive? f. How are you planning to effectively document and communicate the merits of
exams. Becauseproblems had to be solved in a group, there was better attendance. So, class participationimproved. Since the in-class problems were based on the current lecture, students paid moreattention to the lecture and asked more questions to clarify doubts. Solutions to the problems hadto be submitted by the end of the day, so it ensured students were better prepared for the nextlecture. This did not change in the Summer 24 semester when the course was offered online withthe intervention. D. Impact on Instructor Performance: self-reflectionBased on self-reflection, we feel that this model improved the instructor’s performance. Theinstructor planned for aligning the in-class problems, lectures and homework for the next weekand realigned
communication overhead, and cost savings of 2$226,500. Inspired by UCSD’s success, the authors sought to apply Lean Six Sigma principleson a smaller scale within our department, recognizing our limited resources. A small-scale LeanSix Sigma project was started in fall 2024, targeting the low hanging fruits within onedepartment of the College of Engineering. This continuous improvement effort is expected tospan several semesters, with plans to share successful results with other departments andcolleges.The goals of this project are twofold: to improve the scheduling process and to use it as a casestudy in the Lean Six Sigma course. Scheduling is a process that directly affects students’academic experiences
fromrevisiting specific lessons or accessing additional resources outside the classroom (Mayer &Moreno, 2003). With the physical models the authors are planning to video tape the use of thephysical models and make it available on the course VLEs on the LMS. A strong understandingof Statics is critical for future courses and real-world applications in engineering and documentingthe experience by the students for future use comes handy.The Need for Innovative Teaching MethodsStatics is often perceived as an abstract and difficult subject for students to comprehendparticularly because it involves complex mathematical models that are sometimes disconnectedfrom the tangible applications that students will eventually face in their careers. The challenge
follows: (1) Lesson Plan Curriculum (1947):Although this curriculum was based on Dutch colonial curricula, it had the primary objectiveof fostering Indonesia’s autonomy, sovereignty, and equal opportunity to education after itsindependence in 1945. The curriculum prioritized national interests by allocating a list ofsubject matter and time to build Indonesian characteristics based on the Five Basic Principlesof the state philosophy (Pancasila); (2) Unraveled Lesson Plan Curriculum (1952): Thiswas the first curriculum revision in which provided more emphasis on the relevance ofsubject matter content and students’ daily lives. It also broke new ground by includingphysical education and art education; (3) 1964 Curriculum: It aimed to improve
they provide mentorship and program supportthroughout the duration of the program. During the program, mentors provide up to two (2)hours of mentoring weekly. Mentor topics, see Table 1, expound on research topics and themesthe students complete each week.SUPER near-peer Mentors have the following responsibilities: • Assisting with implementation of the ISR course lesson plan by facilitating in-class lab activities. • Attend weekly trainings and meetings with the program director to prepare for the weekly class meeting. • Host one weekly 30-minute mentor meeting (up to two depending on student availabilities) • Serve as mentors and program support during summer research, as well as assist with the
solve problems while managing andreflecting on their projects. Figure 2 Students think and work on projects to solve real engineering problemsFor example, in the robotics module, experts propose experimental topics, such asdeveloping two-wheeled robots capable of intelligent navigation, human-robotinteraction, and adaptive movement. The project is divided into four stages: researchand design, planning, prototype development, and integration. Students mustcomplete tasks including: Conducting technical route research and producing a systems design report; Developing a project plan; Engaging in division-of-labor-based development, including literature review, learning technical knowledge, refining technical routes, and hands-on
within wider educational settings.Future research development involves focusing on improving the effectiveness of the AR-basedlearning experience identified during interviews to improve the curriculum. One keyimprovement pertains to smoothing the transition from 2D to 3D representations. We noticed thatsome students struggled when switching between 2D and 3D representations, often failing toinclude the third dimension. For example, students who correctly named the vertical axis as they-axis demonstrated confusion about how to incorporate the z-axis into their reasoning. Toaddress this, we plan to design AR examples which explicitly relate 2D and 3D visualizations,and to practice working with all possible 2D vector projections in Axy, Axz, and
, andelectrical engineering. All of them completed the Science, Technology, Mathematics andEngineering (STEM) senior high school track prior to university. Sixty-three (63) students werepart of this study; they were divided into two different groups: the experimental group with 35students and the control group with 28 students. Students came from comparatively similar socio-economic and demographic backgrounds, as determined by the course instructor, who was a co-author of this work.Research Instruments (Diagnostic Tests and Mental Effort) This study utilized mechanics diagnostic tests by Korsunsky in 2005 [11] , learning plans,and a learning management system (LMS). The mechanics diagnostic test is a standardized testadopted by the researchers
to senior strategic planning analyst at major Fortune-200 companies. Following a master’s in applied statistics and a PhD in business and decision sciences (both from Indiana University, Bloomington) she had spent over 10 years in academia. In addition to academic responsibilities of research and teaching, she was the founding director of a network-analytic think tank, and founded and supervised two master’s programs in advanced analytics. She has a lot of experience working for corporate clients such as Coca-Cola, McDonalds, Volkswagen, Association of European Business, and many others, where she has held the roles of PI, co-PI, or advanced analytics methodologist. She is passionate about using science for the
attendance policy, where attendance contributes to a student’s grade. Another way isto lower the bar for attending, usually through asynchronous or synchronous, online modalitieslike Zoom. Allowing students to attend virtually may allow them to keep their plans, but stillattend class. Another way to incentivize students is to give quizzes or exams on Friday so thatbeing absent directly impacts their grade. Other ways to motivate students are to increase socialpressure through the use of group work or to do homework problems together. Working ingroups or as a class has also shown to have a positive impact on overall grades [7].Unfortunately, nearly all incentive techniques have drawbacks that make them difficult to userepeatedly. Mandatory attendance
their 21st century skills with all itemsaveraging above 4.0. They strongly believed in their ability to set their own learning goals, workwith students from different backgrounds and respect the differences of their peers, makechanges when things do not go as planned and produce high quality work.Career Readiness: Students expressed great confidence in their career readiness skills with eachcompetency averaging above 4.0.Persistence: When indicating their intentions to persist in their degree and career, students werevery positive with all items averaging above 4.0 in 2022 and all above 3.75 in 2023. Theystrongly believed they would complete their degree in their current major (M=5.0 in 2022 andM=4.67 in 2023), get a job in the field major (M
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