. Whileparticipation in the mentoring program was not required, the instructors of the introductorycourses in each of the three majors emphasized the importance at the start of the semester andincorporated a small portion of the class grade to participation in mentoring. For example, theinstructor of the AST introductory course asked students to write a short reflection on theirparticipation in the mentoring program. The BE introductory course has specific points allocatedbased on participation in the program. In retrospect, some consistency across the courses wouldhave been preferable. Feedback from peer-mentors also highlighted the importance of a morestructured implementation of the peer-mentoring program within the context of the
improvestudent achievement, engagement, and have helped students develop conceptual understandingand problem-solving skills [4] - [14]. Additionally, when students are asked to write short-answer responses to explain their reasoning to concept questions, it has been observed toimprove student performance, engagement, and prepare students for group discussion [15], [16].These responses provide instructors and researchers with a wealth of information regardingstudent thinking [17]. Still, often, it is difficult for instructors and researchers to process all ofthis written information. Machine learning researchers have applied natural language processing(NLP) and large language models (LLMs) to automate the grading and scoring of textualresponses from
to Conceptually Challenging QuestionsIntroductionThis NSF Grantee Poster Session paper describes work on an NSF-funded collaboration betweenengineering education and machine learning researchers to automate the coding of short-answerexplanations written by students to conceptually challenging questions in mechanics andthermodynamics [1], [2]. Concept questions, sometimes called ConcepTests [3], are challengingmultiple-choice questions that allow students to practice utilizing conceptual knowledge in newscenarios. These questions have been used within multiple active learning strategies to promoteconceptual understanding and student engagement [4] - [11]. Furthermore, students can be askedto write short-answer explanations
engineeringstudents with ASD that offers peer mentoring to help with the transition to and engagement incollege life. The mentors offer guidance in honing executive functioning skills, identifyingessential resources, fostering social connections, developing self-advocacy skills, and effectivelynavigating the campus environment. Through an undergraduate research initiative, undergraduateengineering researchers have immersed themselves into this program, conducted research onneurodiverse learning and communication skills, and developed a prototype applicationspecifically for the peer mentoring program. Initially the student researchers developed surveysto determine the needs and interests in a customized application. Using the survey results, theydeveloped a
prior experience in design and the UCD process. In suchinstances, working with an ideation tool to generate blue sky ideas and build upon some or ruleout others [43] augmented the learning experience and paved the way for them to come up withthe design ideas they would initially use. For students who might not have had much experiencewith the UCD process prior to C1, ChatGPT served as a tool for providing them equitable accesssuch that they could keep up with their more experienced peers and not fall behind the class. Additionally, ChatGPT was used as a writing assistant by students, especially in C2, whopossibly were struggling with the heavy writing load that the course provided. Such a writingload is uncommon within the courses in our
feedback provided by the instructor after reviewing their third draft. • Peer evaluations: Students complete three peer evaluations throughout the semester, using the CATME software [7].Individual learning assignments (ILAs)The different ILAs that were submitted throughout the semester are below. ILA1 and ILA2 arebased on assignments since before the author took over this course; the remaining ILAs weredeveloped by the author. With the exception of ILA5, which was expected to be a 300-500 wordsubmission, all ILAs are expected to be 600-1000 words. • ILA1: Students write about a WP of their choice, explain the characteristics of the problem that make it a WP, provide two examples of stakeholders for this problem, and
is planned to enhance the incoming transfer student’s sense of belonging, to prepare their career development (resume writing, interview), and to review the bottleneck course contents (Surveying and Statics).3) Faculty development activities To help in developing and offering more lower-division engineering courses at the three partnering institutions, the project hosts the Faculty Learning Community (FLC) with the faculty from Cal Poly Pomona and community colleges. Then, the faculty from Cal Poly Pomona shares teaching materials (lecture notes, assignments, quizzes, and exams) with the other faculty for their reasonable amount of workload to develop and offer lower- division
once a week throughout a 16-weeksemester. Lectures were structured to promote active-learning through brief warm-ups, frequentdiscussions, and in-class activities that promoted small group collaboration. The instructorspromoted an inclusive, safe environment in which students could share with peers their thoughtsand trepidations about their professional careers. This was done through write-pair-sharediscussions and activities, personal examples of professional successes and failures shared by theinstructional team, and allotted time for questions and comments.Guest speakers who were experts in specific areas were utilized for multiple class sessions,including: the lectures in understanding personal values (faculty member in education) and
communicate 4. Write your team’s goals from this week and indicate if it was accomplished. If you did not reach your goals, please explain why 5. Was your team able to equally divide the work this week a. Yes b. No c. Other (with comments) 6. Do you have any concerns about your team going forward? Please detail them belowTeam Evaluation Questionnaire for Final Assessment (Required) 1. How would you assess yourself and each of your group members on the effort they put into this project? Write down every group member's name (including your own), give them a rating from 1-5 (1 being the worst) in terms of their effort. Explain as needed. Effort is defined as: Preparation and Readiness to work
students on their writing, presenting and communicating skills, building the professional competencies required for leadership roleKelly Scarff, Virginia Polytechnic Institute and State University Virginia Tech, Collegiate Assistant Professor, Mechanical Engineering DepartmentAngelo Biviano, Virginia Polytechnic Institute and State UniversityMs. Christine Burgoyne, Virginia Polytechnic Institute and State UniversityCaroline Finlay Branscome, Virginia Polytechnic Institute and State UniversityKathleen Carper, Virginia Polytechnic Institute and State UniversityDr. Sara L Arena, Virginia Polytechnic Institute and State University Sara L. Arena received a B.S. in Engineering Science and Mechanics (2007), M.S. in Biomedical Engineering
scholarly work involves a team of students and facultymembers from diverse groups, backgrounds, departments, and institutions. The legal andinstitutional consequences of non-conformance can be disastrous for a researcher’s career,profession, and reputation. A clear understanding of proper citation and fair use of sourcesbecame increasingly challenging as reported by finding agencies evidenced by the increase inimproper use of citations.The objective of this work is to develop a systematic process to manage scholarly literature andensure fair use and proper citations in scholarly writing. The paper will consider three importantelements for managing the literature review of prior works: managing literature, fair use, andteam writing. A checklist for
) Students Self-Identify Group Work Habits Figure 6: Student responses to pre-survey questions. (a) Students self-reported average grades on previous group assignments. (b) Students self-identified their contributions toward group work compared to their peers.’ (c) Students reported how many days before a group assignment they finish their contribution.Post-Survey Students were given a post-survey on the final day of the course to assess their experienceusing the I-in-Team method. The first question in the post-survey asked students to report theirfeelings on writing a group report, specifically in this Chem-E course after implementing the I-in-Team method. Students reported an average of 3.96, falling
students to reflect on their team’s operationalbehavior and their team’s design habits so that they could better understand what was needed forsuccess in this course and beyond. To address these needs, the team of instructors for ENES100developed and implemented a “Team Performance Rubric”.Although there are many tools and software that are available for assessing the performance of ateam and gathering peer evaluations [1], a novel aspect of the rubric is a reflective andresponsive approach for assessing design practices within the team. A rubric was developed forrating a team’s engineering design process habits, such as"effective use of modeling techniques”and “design iteration,” as well as the team’s effectiveness, such as “productive discourse
academic settings. Overall, this study seeks to answer the researchquestion: How do engineering faculty perceive student use of GAI assistance in undergraduatecourse completion?Preface on Grey LiteratureIn the study of new areas such as GAI in engineering education, non-peer-reviewed sources—think tank reports, white papers, and conference papers— are crucial in expanding ourunderstanding [17], especially when peer-reviewed articles are scarce [18], [19]. Peer-reviewedliterature remains the gold standard in academia for its rigor and reliability [20], [21]. However,including carefully selected grey literature is essential for a more thorough and nuancedunderstanding of the latest developments and perspectives in rapidly evolving fields, such
models pertinent to engineering as the semester unfolds.This course stands out due to its inclusion of weekly 75-minute Peer Learning Group (PLG)sessions. These workshops, led by a teaching assistant, offer hands-on programming practicebeyond lectures, reinforcing core concepts. The PLG is a non-credit corequisite, taught by aproficient former student, with all materials provided by the faculty. There is no direct gradeassigned to the PLG because students are completing their Programming assignments during thePLG. The focus is to give students confidence to start writing code from scratch and let themdevelop their own programming style.In addition to the regular coursework, the curriculum is enriched with challenges and modulesfrom the MathWorks
be addressed, which is partially open-ending [2,3].Recognizing the efficacy of project-based lab designs in fostering creative engagement anddeep learning, this modification aims to bridge the gap between traditional, instruction-centriclabs and student-directed projects. The project-based laboratory design is intended to motivatestudents towards deep learning, advanced engineering skills, and high-level learning outcomeswhile preparing them well for open-ended labs at the senior level [4,5]. In addition, studentswill work as a group and focus on provided materials (i.e., graphene oxide membrane, aerogel)in this project-based lab to encourage communication and peer learning. Moreover, theselection of materials for the project is drawn from
entering industry, but recognition only represents base knowledgeacquisition based on Bloom’s Taxonomy principles. Here we describe a set of curricular modulesto enhance students’ understanding of standards in engineering practice that reflect learning at alllevels of Bloom’s Taxonomy (i.e. recognition/understanding, application, revision, and creation).The modules and their implementation will enhance students’ understanding of standards,including 1) searching and identifying appropriate standards, 2) writing appropriate protocols forthe verification of standards, 3) proposing revisions to standards, and 4) developing newstandards. With this methodology applied to different engineering/technical disciplines, we hopeto establish a distinct value
can be accessed easily through the CATME®website [12] as the authors used the default set of questions.The qualitative data in this paper consists of open-ended responses provided by students in their peerevaluations. As part of these evaluations, students are expected to complete peer-to-peer comments, inwhich they provide comments to each teammate, as well as write comments about themselves [14]. Theinstructor then releases these comments so that they are visible to the entire team via CATME®.This paper looks at the peer-to-peer comments submitted by students as part of their third peer evaluationassignment, completed at the end of the semester. Data analysis consisted of open coding, in whichcodes and categories emerged from the data [15
responsibility fortheir learning building up to structured problem-solving through their interests and involvementwith the issue they are solving as engineers. Often these problems are multi-disciplinary requiringknowledge in different fields such as materials, environment, acoustics, air quality, chemicalreactions, and business. This paradigm aims to impact students in multiple learning environmentsand extend their knowledge beyond classroom and technical knowledge.ImpactThe projects developed by the students not only broaden their understanding of their specificproject but also learn and get educated on other topics from their peers in different areas and topics.Students have demonstrated engagement and critical thinking in engineering problems
years.Program goals include: (1) Use the scholarships and programs to improve scholars’ academicperformance in engineering foundational courses; (2) Develop a resiliency program to increaseCollege of Engineering (CoE) student retention by building upon a sense of community createdthrough existing peer-based programs (Geisinger & Raman, 2013; Ikuma et al., 2019); and (3)Increase employers’ recognition of low SES students’ strengths and valuations of their employablecompetencies through a paid internship program.The general objectives were established including; (1) New pathway to success. Scholars areprovided a pathway to complete an engineering degree including direct education and interventionapproaches for their engineering academic career
traditional classroom. A large number of studentspursue undergraduate research, service-learning, and even study abroad experiences, receivingacademic credit documented on a transcript. Students value these experiences even though theircredit hours during these semesters are higher than their peers. University leadership sees valuein micro-credential programs in terms of revenue and professional development opportunities forstudents, staff, faculty, and alumni. Micro-credentials and digital badges have gained popularityin recent years as ways for higher education institutions to provide competencies, knowledge,and skills quickly and effectively, especially when the needs of the workforce change faster thanthe curriculum. However, a recent development
among instructors [13]. These challengesnecessitate thoughtful planning, coordinated execution, and frequent assessment of studentoutcomes to ensure that team teaching remains effective.In engineering education, team teaching takes on additional layers of complexity. The technicalrigor required in engineering courses demands a blend of expert knowledge and pedagogicalunderstanding. However, teaching teams may find it challenging to coordinate professionalinteraction among skilled instructors and ensure that all perspectives are integrated seamlesslyinto the course content [14]. In addition, engineering educators may seem reluctant to share aclassroom with peers or even uncomfortable at being assessed by students and peers alike [15].Looking
women representing more than half of the US population, they remain underrepresentedin Computing fields. An introductory programming course (CS1) is critical for progression in theComputer Science (CS) degrees. It often presents challenges for retention and graduation,especially among underrepresented students. Previous research has indicated that women may bemore likely to leave or lose interest in computing due to various challenges. The computingclassroom culture needs to improve engagement and create a welcoming environment forwomen. As more schools are using peer instruction, such as LA (Learning Assistant), PLTL(Peer-Led Team Learning), and UTA (Undergraduate Teaching Assistants), some researchindicates that such practice for recitation
10-17 who were novice learners in introductory programming. Comparing the group that usedOpenAI’s code generator Codex and the baseline group that did not use Codex for their learning,the authors found that the Codex group performed better at generating code during the evaluationand post-test. In another study, Kazemitabaar et al. [20] developed CodeAid, a Large LanguageModel-based programming assistant for undergraduate students similar to a teaching assistant.CodeAid was designed to support students in programming by answering questions about code,helping to write code, and helping to fix code. Through studying the class deployment ofCodeAid over a semester, the authors proposed design implications for designing AI assistants ineducational
well as variations in familial and community understandings of neurodiversity [20].Existing literature shows a pattern of disparities in formal diagnosis rates and access to supportsbetween individuals from minoritized racial groups and their White peers [21]-[24].Additionally, neurodiverse women frequently receive a diagnosis of anxiety or depression, whileADHD or autism diagnoses are delayed or unrecognized [25], [26]. The demographic data of the31 participants are summarized in Table 1. Table 1: Summary of Demographic Information (Total N = 31) Field of Study N (%) Biology 5 (16.1%) Biomedical/Health Sciences
content generation assignment intwo sections of a senior computer science and engineering (CSCE) capstone course. In these twosections, 49 students were asked how interactive ethics assignments helped them becomeknowledgeable about ethical issues, analyze the ethical implications of their projects, and thevalue of choosing their own ethics topics. Students in both sections on average rated the ethicsassignments highly for learning ethics issues and being able to choose topics, with more mixedratings of the ability to analyze their own capstone projects. From written responses, we foundthat students valued assignments for bringing awareness of relevant ethical issues in society, forproviding opportunities to learn with and from peers, and for
Skills, (e) Networking, Finding Mentors &Mentoring, (f) Understanding and Exploring Pathways to Interdisciplinary Careers, (f)Leadership and Entrepreneurship Skills for career success, (g) Professional & ResponsibleConduct, (h) Mental Health & Wellbeing. These topics were tailored specifically for the needs ofcomputational science students with a goal to increase their awareness and preparation forinterdisciplinary careers. This paper discusses the modifications and adaptations made to fosterthe success of first year graduate students from diverse academic backgrounds throughnavigating interdisciplinary computational science and developing peer cohorts and pathways tocareers.Course learning outcomes and students’ development were
, students were “challenged to convey scientific information in a different, moreengaging way.” Aiming to engage a reader beyond an instructor or peer encouraged them to, “change[their] writing style and employ more media, such as YouTube videos, in the project.” Furthermore,freedom to organize the module outside the framework of a traditional paper helped students “understanda better chronology to explain sustainability issues.” Overall, The knowledge that the module “could bebeneficial to someone in the future” motivated students to write more freely and create a story.In addition to the self-evaluation form, interviews were conducted to better capture students’ case-writingexperience and learn about their prior exposure to sustainability. Table 1
Iron Range Engineering on the Mesabi Range College Campus. Dr. Christensen received her Ph.D. in Engineering Education from Utah State University in the Summer of 2021. The title of her Dissertation is ”A Mixed-Method Approach to Explore Student Needs for Peer Mentoring in a College of Engineering.” Darcie holds a Master of Engineering degree in Environmental Engineering (2019) and Bachelor of Science degree in Biological Engineering (2017), both from Utah State University. She is passionate about student success and support, both inside and outside of the classroom.Dr. Elizabeth Pluskwik, Minnesota State University, Mankato Elizabeth leads the Engineering Management and Statistics competencies at Iron Range
project, anticipated capstone specific products and deliverables, design and testingapproaches, timelines, and plans for demonstrating each of the ABET Student Outcomes. EPICScourse standard assessment practices applied to capstone projects include notebook documentationof work and accomplishments, weekly and summative reflections, design review presentations,transition documents, and peer evaluations. The notebook is filled with data on all the project-related activities the students are actively involved in, often with links to specific work artifacts,explanations of them, and concise narratives explaining the student's specific individualcontribution to them. The weekly and summative semester reflections ask students to write brieflyabout