Asee peer logo
advanced search
Displaying all 8 results

Assessing the Impact of the Use of Generative AI in Developing and Using Assessment Grading Rubrics for Engineering Courses

Conference Session
Generative AI and Its Role in Industrial Engineering
Collection
2025 ASEE Annual Conference & Exposition
Authors
THOMAS AMING'A OMWANDO, Simpson University; Adel Alhalawani, Rose-Hulman Institute of Technology; Ashutosh Khandha, University of Delaware; Bhavana Kotla, The Ohio State University
Tagged Topics
Diversity
Tagged Divisions
Industrial Engineering Division (IED)
Paper ID #48249Assessing the Impact of the Use of Generative AI in Developing and UsingAssessment Grading Rubrics for Engineering CoursesDr. THOMAS AMING’A OMWANDO, Simpson University Dr. Thomas Omwando holds a PhD in Industrial Engineering from the University of Wisconsin Milwaukee. He is the Chair and Associate Professor of Engineering at Simpson University and his teaching interests are in statistical quality control, engineering/project management, engineering economy, capstone design and production and operations analysis. His research interests are in sustainable manufacturing, entrepreneurially minded learning
Relevance Score: 0.021846047

Leveraging Student-AI Interaction to Evaluate Competence in Generative AI and Technical Domains in Industrial Engineering

Conference Session
Generative AI and Its Role in Industrial Engineering
Collection
2025 ASEE Annual Conference & Exposition
Authors
Nadiye O. Erdil, University of New Haven
Tagged Topics
Diversity
Tagged Divisions
Industrial Engineering Division (IED)
toassist in solving problems, provided they disclosed any use of such tools. For project assignments,students could use generative AI to help identify project topics and continue using it throughoutthe project to generate content for their work. However, they were required to include transcriptsof all AI interactions from which they extracted information, suggestions, materials, etc. as part oftheir project documentation.Usage data was collected through a simple survey linked to each assignment, asking studentswhether they used AI programs for assistance. Rubrics were developed to assess proficiency ingenerative AI usage and competence in technical domains, with the intent of applying them tothe required transcripts submitted as part of project
Relevance Score: 0.01769732

Generative Artificial Intelligence in Industrial Engineering: Industry Applications and Educational Prospects

Conference Session
Generative AI and Its Role in Industrial Engineering
Collection
2025 ASEE Annual Conference & Exposition
Authors
Nadiye O. Erdil, University of New Haven
Tagged Divisions
Industrial Engineering Division (IED)
design, production planning and control, production Jackson et. al. GAI in projections and more robust and resilient Walmart; Maersk; DHL; strategy, quality management, revenue management, (2024) [19] general SC; enhanced customer experience; more Instacart sales and operations planning, scheduling and robust and effective decision-making. routing, sourcing strategy, supply chain design
Relevance Score: 0.0072249006

The Use of Generative AI for the Rapid Development of Qualitative Interview Transcripts for a Human-Centered Design Problem

Conference Session
Generative AI and Its Role in Industrial Engineering
Collection
2025 ASEE Annual Conference & Exposition
Authors
Edward James Isoghie, University of Louisville; Jason J Saleem, University of Louisville; Thomas Tretter, University of Louisville; Jeffrey Lloyd Hieb, University of Louisville
Tagged Divisions
Industrial Engineering Division (IED)
undergraduates to use aspart of a human-centered design (HCD) problem. The curriculum for undergraduate engineeringstudents is heavily focused on developing quantitative skills. However, engineering professionalsmay want or need to expand their skill set to also include qualitative methods. To that end, thisresearch project introduces and provides qualitative methods training included in an existingindustrial engineering course. A comparison group of students who received standardquantitative-only methods training (Fall 2024), were asked to work through an HCD problemthat includes both quantitative and qualitative data. A mixed-methods group (Fall 2025), whowill receive qualitative methods training in addition to the standard quantitative
Relevance Score: 0.007150797

Improving Virtual Reality Assessment and Accessibility in the Technology Classroom

Conference Session
Advancing Educational Technologies: VR, AR & Simulation
Collection
2025 ASEE Annual Conference & Exposition
Authors
Lisa Bosman, Purdue University; Ebisa Wollega, Florida Polytechnic University
Tagged Topics
Diversity
Tagged Divisions
Industrial Engineering Division (IED)
in comparisonto traditional lecture?To address this gap, the teaching team implemented a module using 20 borrowed Quest 1 VRheadsets. During the module, students explored and reflected upon the challenges of VRadoption in education. After students completed an initial onboarding, each week focused on adifferent learning topic. In Week 1, students explored the Iceberg Model, followed by Creativityand Innovation in Immersive Technology in Week 2. In Week 3, the module concluded withGamification for Increased Quality and Productivity. After the three weeks of topics (exploredvia VR and lecture), the final week was a project week. Students received traditional PowerPointlectures and immersive VR experiences for each topic, enabling them to
Relevance Score: 0.0059589976

Examining How Required Courses Shape Industrial Engineering Students’ Career Thinking

Conference Session
Bridging Education and Real-World Impact: Training, Career Development, and Urban Systems
Collection
2025 ASEE Annual Conference & Exposition
Authors
Hayley N. Nielsen, University of Michigan; Vibhavari Vempala, University of Michigan; Berenice Alejandra Cabrera, University of Michigan; Lisa R. Lattuca, University of Michigan; Erika A Mosyjowski, University of Michigan; Joi-Lynn Mondisa, University of Michigan; Shanna R. Daly, University of Michigan
Tagged Topics
Diversity
Tagged Divisions
Industrial Engineering Division (IED)
received $30 ascompensation for their participation. The transcribed recordings of the interviews werede-identified and reviewed for accuracy.Data analysisThree of the authors conducted the analysis of the IE interview data, supervised by anotherauthor serving as a research scientist. The analysis team used a combination of inductive anddeductive methods to analyze the interview data [26], [27]. The project leadership teamdeveloped prompts to focus the initial data analysis. Specifically, they developed guidingquestions that prompted the research team to synthesize information from the interview datarelevant to the research question for subsequent analysis. One of the members of the analysisteam read each of the 30 interview transcripts in full
Relevance Score: 0.0042136475

Urban Walkability and Pedestrian Stress: A Sensor-Based Study Across Three Sites

Conference Session
Bridging Education and Real-World Impact: Training, Career Development, and Urban Systems
Collection
2025 ASEE Annual Conference & Exposition
Authors
Rumena Begum, University of Louisville; Faisal Aqlan, University of Louisville; Jay B. Brockman, University of Notre Dame; Hazel Marie, Youngstown State University - Rayen School of Engineering
Tagged Divisions
Industrial Engineering Division (IED)
urban spaces.This study contributes to engineering education by demonstrating a data-driven approach tourban design using wearable sensors, geospatial analysis, and machine learning. It offerspractical case studies for courses in smart cities, transportation engineering, and human-centereddesign, equipping students with skills in sensor-based data collection, predictive modeling, andstatistical analysis. By integrating engineering, psychology, and urban planning, the researchpromotes interdisciplinary learning and hands-on applications of machine learning andphysiological signal processing in real-world infrastructure design. These insights supportexperiential learning and can be incorporated into project-based coursework, fostering data-driven
Relevance Score: 0.0041712984

Study Design and Assessment Framework for Testing Augmented Reality Tools in Engineering Education

Conference Session
Advancing Educational Technologies: VR, AR & Simulation
Collection
2025 ASEE Annual Conference & Exposition
Authors
Gimantha N Perera, University of Arizona; Karen B Chen, North Carolina State University at Raleigh; Laura Bottomley, North Carolina State University at Raleigh; Robert Kulasingam; Emily H Fang, North Carolina State University at Raleigh; Julie Ivy, University of Michigan
Tagged Topics
Diversity
Tagged Divisions
Industrial Engineering Division (IED)
context-specificalterations to content assessments and tailored experience questions, this assessment framework can beadapted to evaluate tools for teaching in broader engineering contexts. As personalized educationbecomes more prevalent, assessment methodologies such as the framework proposed here will increase invalue.LimitationsThe initial study design for project AREEA was to have eligible participants be separated into threeseparate groups. In addition to the two groups mentioned in the Experimental Plan, we intended to have athird group test a 2D version of the HAILs in a computer lab setting. This group would be a control forGBL, as they would not experience augmented reality but only game-based learning. Unfortunately, dueto time
Relevance Score: 0.0035753986