Displaying all 9 results
- 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
- Conference Session
- Advancing Educational Technologies: VR, AR & Simulation
- Collection
- 2025 ASEE Annual Conference & Exposition
- Authors
- Daniell DiFrancesca, Pennsylvania State University, Behrend College; Christian Enmanuel Lopez, Lafayette College; Omar Ashour, Pennsylvania State University, Behrend College
- Tagged Topics
- Diversity
- Tagged Divisions
- Industrial Engineering Division (IED)
considerations should be embedded into the design of educational tools for industrialengineering. The results provide insights for educators and game developers on how toincorporate these elements into 3D simulation-based learning environments to promoteinclusivity and foster more eq uitable learning experiences. The findings also offer broader oimplications for integrating incl usive digital elements into engineering education, specifically in othe design and development of educational games.1 IntroductionEducational games have emerged as an effective means to enhance engagement and learning inengineering education. Games can bridge the gap between theoretical knowledge and real
- 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)
-specific fine-tuning and the long-term impact of AI-assisted grading on student learning and educator workload.1. IntroductionThe integration of Generative Artificial Intelligence (GenAI) into education offers transformativepotential, especially in crafting and applying grading rubrics for engineering courses. Thesecourses, with their complex assessment demands, ranging from technical proficiency to creativeproblem-solving, stand to gain from GenAI’s scalability, consistency, and efficiency. However,this potential comes with challenges, including preserving academic integrity and aligning withsound pedagogical principles. As educators adopt GenAI, they must balance its benefits withcareful attention to rubric quality and responsible
- 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)
of Industrial and Systems Engineering and Fitts Faculty Fellow in Health Systems Engineering. She previously spent several years on the faculty of the Stephen M. Ross School of Business a ©American Society for Engineering Education, 2025 Study Design and Assessment Framework for Testing Augmented Reality Tools in Engineering EducationGimantha N. Perera1*, Emily Fang2, Robert Kulasingam2, Laura J. Bottomley3, Karen B. Chen2, Julie S.Ivy4 1 Systems and Industrial Engineering, University of Arizona, Arizona, USA 2 Department of Industrial and Systems Engineering, North Carolina State University, North Carolina, USA
- 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)
terminology, definitions and descriptions ofcommonly used GAI tools.BackgroundGAI is a subset of AI that produces novel content by learning patterns from its training data.Unlike traditional AI – primarily machine learning (ML) models- GAI differs in key aspects suchas purpose, learning approach, and output. Traditional AI focuses on performing specific tasksusing programmed rules, often relies on supervised learning, and generates pre-defined or task-specific outputs (e.g. price prediction, fraud detection). In contrast, GAI is characterized bythree main features: (1) taking complex, varied and preferably nuanced prompts, (2) using deeplearning models, and (3) creating new data [1]. One of the most common applications of GAIinvolves processing
- 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)
, recurrent “design seeds” across multiple interviewtranscripts for students to potentially discover. This project may inform industrial engineeringand other faculty who wish to supplement their course design work for students with supportingmaterials using generative AI.IntroductionThe integration of generative artificial intelligence (AI) into industrial engineering educationmarks a transformative shift in pedagogical strategies and the preparation of future engineers.Generative AI, recognized for its capability to generate content such as text, images, and designs,holds substantial promise for enhancing educational experiences [1], [2]. It fosters creativity,enables personalized learning, and supports the resolution of complex problems
- 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)
discussions in higher educationincluding its potential uses in and beyond the classroom. Initially, the focus was primarily onpreventing students from using generative AI tools, but attention is now shifting towardintegrating these tools into teaching and learning [1]. Many educators are exploring ways toincorporate generative AI into instruction [2].Students are often assumed to be tech-savvy [3]. With the widespread use of tools like ChatGPT,they may also be perceived as competent users of generative AI. However, effectively using AIfor learning requires more than just basic digital literacy, which can impact both the learningexperience and its benefit. Therefore, studying students’ interactions with AI is important, as thefindings will shape how
- 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)
-being.Findings from this research can facilitate targeted infrastructure planning and investment, bettermobility, and ultimately improve the quality of life in urban areas. Future research shouldconsider a wider range of environmental and social factors and how different factors interactover time to influence stress levels.Keywords: Sensor-based modeling, empathic design, walkability, human stress, machine learning.1. IntroductionWalkability is a key element in urban design that profoundly impacts quality of life and fosterscommunity engagement. By promoting physical activity, walkable streetscapes contribute tobetter physical health while reducing air pollution and supporting environmental sustainabilitythrough decreased reliance on motorized transport
- 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)
students viewsocial and contextual skills and knowledge as central to careers in IE and their reflections on howtheir required coursework has prepared them for their future careers. Implications for futureresearch and practice are discussed.IntroductionEngineering is increasingly recognized as a discipline that requires attention not only to thetechnical work aspects but also to the social contexts in which the work occurs and the broaderimpacts of engineering on communities and society [1] - [4]. The social and contextual nature ofengineering work has been recognized by the Accreditation Board for Engineering andTechnology (ABET), which outlines student outcomes that recognize the importance ofconsidering the social, cultural, ethical, and