Collection

2025 Northeast Section Conference

Authors

Shinae Jang P.E.

education and address NACE career The course focuses on the principles of statics using vectorreadiness competencies. This paper details the classroom setup, calculus, covering key topics such as the resolution andactivity design, and course structure, along with assessment composition of forces, equilibrium of force systems, analysisresults based on semester reflections of forces acting on structures and machines, centroids, dry friction, and moments of inertia. Assessment is based on a Keywords—professionalism; Statics; active learning; teamwork combination of midterm exams, homework assignments, pre

Collection

2025 Northeast Section Conference

Authors

Bala Maheswaran; Meghna Sridhar; Yiannis Levendis; Hameed Metghalchi

Northeastern UniversityAbstract environmental impact and potential for long-term sustainability [10].The "heliostat mindset" emphasizes the harnessing of solar energythrough heliostats—devices designed to track the sun and reflect itslight to specific targets, commonly utilized in concentrated solar Through the heliostat project, students are encouraged topower systems. This mindset is vital for engineering students as it think critically about the intersection of technology and thefosters sustainability awareness

Collection

2025 Northeast Section Conference

Authors

Peter F. Cavanaugh

management it is a complete project from concept to • Engagement & Collaboration - Active learning and completion of the planning phase. collaboration are essential components of effective education [8]. Team-based learning by enhancing • Assignment: Reflection recordings – weekly video • What is working well? – that is, achieving learningsubmission 2-3 minutes long submitted before class that objectives as discussed in class?reflects on the lecture topic of the day. • What is not working as well as desired? - not yet achieving learning objectives as discussed in class

Collection

2025 Northeast Section Conference

Authors

B. Kris Jaeger-Helton

-MACHINE SYSTEMS COURSE AND ROLE OF AI Along with the assignment write-up, students were asked tooutline the advantages and drawbacks of using AI for such A. HMS Course Profileacademic work. Of the 56 respondents, there were 115 open-ended responses indicating the merits of using Gen AI for this Human-Machine Systems (HMS) is a 5-credit senior-leveltype of project and 121 responses outlining the less effective and engineering course at Northeastern University, with multipleconcerning aspects of its use. The primary categories of positive assignments and laboratory sessions over a 15-week semester.responses reflected how students felt AI benefited them in This course focuses on the science behind safe

Collection

2025 Northeast Section Conference

Authors

Krystyna Gielo-Perczak; Gina DiGiacomo

that reflects a merely acceptable level of creativity.mastery. 5 - Outstanding: Shows evidence of progress inachieving outcomes that reflects superior mastery. Since the theoretical foundation of the KEEN e-module was not sufficient for this project, we added the golden section The assessment of each student’s level of attainment of the design concept and explained it to students separately. Wemodule outcomes was evaluated by a graduate teaching also added the

Collection

2025 Northeast Section Conference

Authors

Sunil Dehipawala; Guozhen An; Arkadiy Portnoy; Tak Cheung

addition of Python into Excel competes well with Google faculty computers and not student computers in our communityColab and would alleviate the pedagogical challenges in the college setting. The Python applications available on Googleinclusion of first-year experience deployment. A set of reflection Colab and Try-Jupyter.org have been very useful.questions were used for assessment, and with AI assisted writing,the assessment results supported the efficacy of the deployment II. IMPLEMENTATION Ias a second-year experience. Future AI-based examples on theconvolutional neural network (CNN) for synchrotron radiation The AI-based

Collection

2025 Northeast Section Conference

Authors

Lina H. Kloub, University of Connecticut; Vraj Patel; Tina Huey

. Timing of AI Integration in Educationin their use. To achieve these objectives, an online survey wasconducted among instructors at the University of Connecticut. Instructors’ perspectives on the timing of AI integration inThe survey was designed to collect both quantitative and qual- education exhibit considerable variation, reflecting differingitative data, incorporating multiple-choice, Likert-scale, and levels of readiness and concerns about its impact. A sub-open-ended questions. Key areas of focus included instructor set of instructors (27%) expressed reservations, arguing thatfamiliarity with AI tools, current usage patterns, perceived the adoption of AI in education remains premature due toadvantages

Collection

2025 Northeast Section Conference

Authors

Karissa Tilbury; Mohamad Musavi; Cary James; Alex Friess

- rates suggesting that rural and income-based pressures arestructured but encourage students to share their own compounding in this student population. To address theseexperiences. Topics to date have included: 1) Study Skills and pressures, the Building Bridges to Engineering StudentSelf-Reflection, 2) Goal Setting and Individual Development (BBEST) team seeks to create a targeted, personal approach toPlanning, 3) Innovation and Entrepreneurship, 4) counteract the social and financial pressures associated with theUndergraduate Research Experiences, and 5) Career perceptions of technology and advanced degrees in theirPreparation. The mentorship team consists of the associate

Collection

2025 Northeast Section Conference

Authors

Rachmadian Wulandana

collaborated with powered cybersecurity solutions enhance enterprise securitywith Microsoft Copilot by detecting threats and automating IT individual assignments such as reflections, concept questions,workflows for safer operations [15]. In short, AI holds quiz, homework, and one individual design project.significant transformative potential, especially in education, butrequires a structured, ethical approach. In education, AI should III. METHODbe designed with pedagogical principles, data privacy, andethical guidelines at its core, supporting personalized learning We used Likert scale surveys to assess the extent to which[16

Collection

2025 Northeast Section Conference

Authors

Mamshad Musharaf Mohammed; Sumith Yesudasan

efficient cooling systems for various applications. the cylinder axis, which largely reflects the predictions of a model of free diffusion in a cylinder [7]Keywords: Molecular Dynamics, Radial Distribution Functions(RDF). The real water further divides into different water models. I. Introduction The purpose of this study is to provide a physical and thermal analysis comparison between SPC/E (ExtendedMolecular Dynamics is a computational simulation Simple point

Collection

2025 Northeast Section Conference

Authors

Mohammad Rafiq Muqri; Simon Obeid; Gusteau Duclos, DeVry University

, “Design meetings and designneural network architectures, including transformers and notebooks as tools for reflection in the engineering design course”, IEEEgenerative models like GANs and VAEs, will further advance 36th Annual Conference, Frontiers in Education, pp. 165-184, Santhe capabilities of AI in education. As reported by HolonIQ, Diego, CA, USA, 27-31 October 2006.the global ed-tech market is projected to reach $404 billion by [3] Robin S. Adams, Jennifer Turns, and Cynthia J. Atman, “Educating effective engineering designers: the role of reflective practice,” Design2025, highlighting the growing impact of AI in this

Collection

2025 Northeast Section Conference

Authors

Haneen Alzahrani; Arthur C. McAdams

boundaries between theartist, his audience, and the city. There is limited research on creativity. While artificial intelligence significantly influences innovation in artisticParaphrased another way, the artist created a series of AI- institutions, its impact on divergent thinking, artistic creativity,dreamt data paintings composed of algorithmically generated and museum organization remains less explored. Therefore,data sculptures reflecting the city that serves as an ever- this study relied on multiple sources from different disciplineschanging data source. The system learns to reflect data in an to

Collection

2025 Northeast Section Conference

Authors

Mohamed Elwakil; Tooran Emami Ph. D.

changes toward AI tools (Q5). Responses werecontexts. By doing so, it aims to contribute to the growing body anonymized to encourage candid reflections. The these trends: DB students emphasized technical automation, question used are: “Debugging code faster with AI,” whereas EEM students noted challenges in domain-specific applications: “AI can’t solve Q1. What do you hope to learn from the prompt problems itself.” engineering unit in this course? Q2. What challenges do you anticipate in learning prompt engineering? Q3. How do you think prompt

Collection

2025 Northeast Section Conference

Authors

Lina H. Kloub, University of Connecticut; Christina Smith, University of Connecticut; Faiyhaa-Sydra Saulat, University of Connecticut

speaking and verbal communica-success across various industries, including engineering. The tion skills. At Maastricht University, students utilized Virtu-eight NACE competencies are: alSpeech, an AI-powered virtual reality platform, to practice public speaking in immersive, real-world scenarios[20]. The • Career and Self-Development: Engaging in continuous platform provided students with simulated audience interac- learning, self-reflection, and professional growth. tions, real-time feedback on

Collection

2025 Northeast Section Conference

Authors

Teresa Piliouras; Steffi Crasto; Chinmay Dharap; Pui Lam Yu; Navarun Gupta

, participatorySimultaneously, data breaches, algorithm-driven content citizens in a democracy [5], [6]. Their ideas continue tomanipulation, and persistent security risks expose people to influence modern approaches to reflective, analytical thinking.continuous vulnerabilities. Yet, most individuals lack theknowledge and skills to recognize these dangers, let alone C. The Cognitive Science Revolution: Understandingmitigate them effectively. Thinking Errors Critical thinking, digital literacy, and cybersecurity While early philosophers focused on principles of soundawareness are vital defenses against manipulation, reasoning, modern cognitive

Collection

2025 Northeast Section Conference

Authors

Kalyan Khatry; Reihaneh Samsami

personalized project work that AI cannot easily replicate – toalternate explanation for a complex circuit analysis problem, ensure that grades truly reflect student learning.offer real-time feedback, and even generate custom practicequestions mimicking one-on-one tutoring [5]. Advanced Additionally, tools for AI detection are emerging, but theirmultimodal Gen AI models process and generate images and accuracy is uncertain, and they raise ethical questions (e.g.,animations to support diverse learning styles. This multimodal false accusations or invasion of privacy if student submissionsare sent to third-party detectors). Therefore, the consensus in necessary. If a tool is to be used responsibly

Collection

2025 Northeast Section Conference

Authors

Shruti Brahma, University of New Haven; Siddhant Alhat Rajendra, University of New Haven; Ardiana Sula, University of New Haven

reflective of the diverseinternational student enrollment with economic and policy pool of applicants, consisting of 31.2% from Connecticut,influences at a Midwestern U.S. university using the Seasonal 35% from other United States states, and 33.7% international.Autoregressive Integrated Moving Average (SARIMA) model. In order to maintain student privacy, all institutional recordsThe study discovered that tuition increases had a relatively were anonymized, or all personally identifiable informationlow impact on international student enrollment, suggesting was deleted. The dataset was also audited for regional bias,that factors such as academic reputation and career prospects and no statistically

Collection

2025 Northeast Section Conference

Authors

Lina H. Kloub, University of Connecticut

, studentsD. Post-Course Survey are required to document and acknowledge their AI At the end of the semester, students completed a follow-up tool usage in all relevant coursework, fostering criticalsurvey to assess the impact of AI integration on their learning reflection on AI’s role in academic work.experience. This survey provided insights into how students’ 2) Prompt Engineeringfamiliarity with and attitudes toward AI tools evolved over This dimension introduces students to prompt engineer-the course. Students were asked to reflect on their ability to ing—the practice of crafting precise inputs to optimizeuse AI tools effectively in academic

Collection

2025 Northeast Section Conference

Authors

Elyas Irankhah; Sashank Narain; Kelilah L. Wolkowicz

, adaptive AI difficulty levels, and competition createdistinguishing between player and AI moves. This method an engaging experience that improves curiosity and deeperprovided a detailed dataset for evaluating player strategies and cognitive processing [6]. One example of this approach is Tic-decision-making patterns. While we observed the gameplay Tac-Toe, a simple yet strategic game that reflects fundamentalperformance of all participants across different grade levels, our AI decision-making processes [7]. The game provides adetailed strategy analysis focused specifically on first-grade structured environment where students can observe how AIstudents due to the availability of screen recording data

Collection

2025 Northeast Section Conference

Authors

Samuel Servati; PS. Dhanasekaran

between theory and application [7]. Onestatistically significant difference in student student reflected that he learned more during thisachievement between the two groups. However, by the single project than in an entire semester of physics,third year, students in STEM PBL schools exhibited reinforcing the effectiveness of problem-solvingsignificantly higher scores in subjects such as through hands-on experimentation [2].geometry, probability, and problem-solving [2]. These III. LONG-TERM EDUCATIONAL IMPACTsubjects, which require high levels of spatial reasoning OF PBLand conceptual thinking, directly benefit

Collection

2025 Northeast Section Conference

Authors

Boluwatife E. Faremi; Javier O. Pinzon-Arenas; Amir Mohammad Karimi Forood; Josef Kundrat; Hugo F. Posada-Quintero; Ann Marie Hoyt-Brennan; Wendy A. Henderson

-AIby enabling automated assessments, personalized learning, interaction necessitates examining trust across threereal-time content updates, clinical simulations, and dimensions: dispositional, situational, and learned trust [5].adaptation of educational materials to reflect current Dispositional trust is a stable tendency to trust AI, shaped byresearch and practice [1]. This technological shift comes personality traits and past experiences. Situational trust, byat a time

Collection

2025 Northeast Section Conference

Authors

Hasan Baig; Phillip Bradford

orqueries. Kostick-Quenet and Gerke [20] underscore the complete assignments, it becomes difficult for educators to assess a student's actual understanding and competency basedsignificance of assessing the real-world ramifications ofChatGPT and similar LLMs to mitigate the risk of any adverse on the submitted work. The work might be technically correctoutcomes arising from their misuse. Despite being and sophisticated, but it might not accurately reflect thegroundbreaking and revolutionary tools, ChatGPT and other student's actual skill level.LLMs have the potential to cause substantial harm if not Another most

Collection

2025 Northeast Section Conference

Authors

Seyedeh Elham Kamali; Reihaneh Samsami

the AI knowledge as moderately essential, while 12 (14%) reported it as slightly essential, and 4 (5%) as not essential. The average scale for this question is 2.96, which reflects that the majority of the respondents believe that AI knowledge is somehow Fig.7. AI Tools Used by Students essential.Section 3: Perceptions and Impact of AI on Education Students rated the effectiveness of AI tools positively,with 14 (16%) believing them to be very effective

Collection

2025 Northeast Section Conference

Authors

Zebin Pepin; Douglas E. Dow

In Figure I, each box labeled ‘CAMX’ represents athat any deviations are detected promptly. Provide real-time, camera in the system along the queue line. Arrows simulateautomated wait time calculations that reflect the current the flow of traffic through the queue path. All cameras in theconditions of the queue. This includes accounting for prototype were linked centrally to the Windows PC runningvariations in queue length, processing times, and any all 3 cameras simultaneously. Figure I is a flowchartdisruptions such as line cutting. Detect and address instances representing the process of the automated queueing system.of line-cutting by comparing the order in which individuals The flow

Collection

2025 Northeast Section Conference

Authors

Christopher Brown; Sumith Yesudasan

gathered from [11].higher frequencies which represent smaller surface Once the GPHS module model was completed its Yung’sirregularities modulus of elasticity as well as its Poisson’s ratio was found[8]. This function is reflected in the Department of analytically using stress and strain simulation in COMSOLDefense’s PSD which is defined in their testing method Multiphysics. The density of the GPHS was calculated usingstandards MIL-STD-810G COMSOL’s [10] random the recorded weight and dimensions of the assembly [12].vibration study uses a PSD as well as vibrational input data These values were then applied to a box of the sameduring

Collection

2025 Northeast Section Conference

Authors

Gowtham Raj Vuppari; Navarun Gupta; Ahmed El-Sayed; Xingguo Xiong

-based The Wildfire Dataset Method classification for 96.10% (2025) wildfire detection Fig. 8 Training vs Validation Loss Graph TABLE 2. Comparison of Proposed and Other AlgorithmsThe model used 1089.92 MB of memory shown in “Fig. 9”, Percentage of Accuracydemonstrating efficient GPU usage. Reflecting computationalchallenge, the backward pass required 0.0243 seconds; the Model Accuracyforward pass took 0.0072 seconds for each batch

Collection

2025 Northeast Section Conference

Authors

Bushra Rayyan Qadri; Arthur McAdams; Peter Cavanaugh; Dan Tenney; Ali Baker

deviceorganizational cultures that they have personal experience connects to local Wi-Fi, enabling businesses to analyze trafficwith. The analysis must include organizational beliefs and trends, optimize staffing, and gain deeper insights intovalues. and artifacts. Students work on a single organization customer movement patterns. Students worked closely with aindividually, then share the team and reflect on how each data engineer from Foot Traffic Stats to complete three stagesorganization is represented in their artifact’s values and beliefs. of the project. The first stage involved developing a projectEach group assesses the strength of each culture studied. plan. The second stage required installing

Collection

2025 Northeast Section Conference

Authors

Saddam Alkhamaiesh; Peter Cavanugh

validation strategies, including: • Triangulation: The integration of interviews, policy documents, and secondary data sources to enhance 3) Communication and Stakeholder Collaboration credibility [36]. • Reflexivity: Continuous researcher reflection to • Stakeholders, including educational institutions, mitigate biases in data interpretation [37]. labor unions, dealerships, and government agencies, • Peer Review: Independent coding verification by a played pivotal roles in EV training initiatives. second researcher to ensure consistency and • Most states engaged stakeholders using a mix of accuracy [38

Collection

2025 Northeast Section Conference

Authors

Nusrat Zahan; Sidike Paheding

++ [8] X. Zhang, R. Ng, and Q. Chen, “Single image reflection with attention mechanism (aug, 10.1080/0952813x. separation with perceptual losses,” in Proceedings of 2024.2383659, 2024),” JOURNAL OF EXPERIMEN- the IEEE conference on computer vision and pattern TAL & THEORETICAL ARTIFICIAL INTELLIGENCE, recognition, 2018, pp. 4786–4794. 2024. [9] R. Feng, J. Gu, Y. Qiao, and C. Dong, “Suppressing model overfitting for image super-resolution networks,” in Proceedings of the IEEE/CVF Conference on Com- puter Vision and Pattern Recognition Workshops, 2019, pp. 0–0.[10] R. Timofte, R. Rothe, and L. Van Gool, “Seven ways to

Collection

2025 Northeast Section Conference

Authors

Elizabeth O'Connell; Sarath Chandra Kumar Jagupilla; Muhammad Hajj

offered by the Department of Defense. This In Fall 2023, $92,773 in external scholarship funds were scholarship is awarded directly to students and covers theirreceived by 21 department students through 26 full tuition for the remainder of their academic careers, as wellscholarships. In Spring 2024, $75,750 external scholarships as an estimated yearly stipend of $30,000. In the 2024-2025funds were received by 19 students through 23 scholarships, academic year, two additional students received thisbringing the total to $168,523 for the academic year, reflecting scholarship. Likewise, in the summer of 2022, two departmenta 20.06% increase from the previous academic year and an students