for Advanced Science and Technology. Her research focuses on the use of experimental and computational methods to evaluate the interdependence of mechanical, compositional, structural properties of bone, ligament, and tendon to investigate the progression and treatment of musculoskeletal diseases. Her work has been funded by NSF, NIH, and industry/foundation sponsors. She has received awards from the US and Australian Orthopedic Research Societies and the Beckman Foundation in recognition of her scholarship. ©American Society for Engineering Education, 2025 Reflecting on Ten Years of Building a Community of Practice for Teaching Innovations in Fundamental Mechanics
Paper ID #48273The Relationship Between Student Sentiment and Academic Performanceusing Student Reflections from a Flipped, Mastery-Based Statics CourseDr. Amie Baisley, University of Florida Amie Baisley is currently the Thomas O. Hunter Rising Star Instructional Assistant Professor at the University of Florida teaching primarily 2nd year mechanics courses. Her teaching and research interests are alternative pedagogies, mastery-based learning and assessment, student persistence in their first two years, and faculty development.Chiranjeevi Singh Marutla, University of Florida ©American Society for
where experts werepresented with less structured or familiar problems, studies have observed that experts displayedmore reflective and metacognitive strategies, and were better able to leverage their breadth ofknowledge to solve the problem relative to novice practitioners [8,18-20].The concept of adaptive expertise [21,22] has also been introduced to describe how experts areable to “apply, adapt, and otherwise stretch knowledge” to solve novel problems [18]. Theadaptiveness of the expert is thought to comprise multiple dimensions; (1) the ability to take onmultiple perspectives, (2) metacognition, (3) goals and beliefs, and (4) epistemology [22].Importantly for this particular definition of adaptive expertise, one does not necessarily need
disciplines, including engineering, where traditional assessment methods often focusheavily on quantitative metrics such as exams and problem sets.In engineering education, portfolios have been employed to assess a variety of skills andoutcomes that are not easily captured through conventional means. For example, portfolios areused to evaluate students' design capabilities, teamwork experiences, and communication skills,core competencies emphasized in ABET accreditation criteria [3]. Portfolios provide a structuredplatform for students to document their iterative design processes, reflect on their decision-making, and align their learning artifacts with specific course or program outcomes [4].Furthermore, the reflective component of portfolios has
players ‘take turns’ during the players interact in the game game, competition vs collaborative games, point systems and rewards, etc.Game Elements The “look and feel” of the game Game aesthetics and game themeGamification has been linked to motivational theories such as Self-Determination Theory (SDT)because of the extrinsic motivators (such as points, badges, and leaderboards) and intrinsicmotivators (such as group work and autonomy) provided in gamified environments [14], [15],[16]. More specifically, the game design we intend to implement involves the use of intrinsicmotivators such as stories, challenges, and avatars to enhance self-reflection skills [17
]. This step enabled us to identify recurring themes, patterns, and insights related to students’ perceptions and uses of the OER Deforms textbook, as well as the financial benefits of the textbook. The quantitative data was analyzed using descriptive statistics, which is valuable in education research to describe a situation without trying to address relationships between variables[25]. Additionally, the rank of academic strategies was analyzedu sing a Mann-Whitney U test to compare differences in students' academic strategies between their reflections on Statics and Deforms, assessing whether certain strategies were ranked higher or lower across the different courses[26]. The analysis results are presented
students’ attitude towards learning addressing study habits, preparation,participation, and engagement, among others. However, results of these distinct approachessuggested that these changes had a minimal impact on the students’ academic performance.In previous work in Progress, self-graded homework was implemented, by assigning traditionalpaper-pencil carefully crafted problems. These selected problems were self-graded by thestudents during review sessions before the mid-semester and final exams. The results of that onesemester study (fall 2023) suggested that this change did not significantly impact students’ examscores. However, having students grading their own work fostered reflection. Some studentsfound that the problems were too difficult
instruction; they need opportunities to apply these strategies acrossdiverse contexts. This includes instructors modeling how to recognize when specific strategiesare useful and providing ongoing feedback (Wingate, 2007). Some instructors embed learningstrategies into course activities without explicitly explaining how or why they work. While thisapproach may help students see the relevance of these strategies within specific contexts, it oftenfails to support their transfer to novel situations. Successful transfer of learning requires thedevelopment of reflective expertise (van Merrienboer et al., 1992)—a form of metacognitiveskill that enables students to not only execute a strategy but also understand its underlyingprinciples. This expertise
before.” Participant FThe quotes above reveal that students attributed some of the challenges they experience inengineering statics to their understanding and their ability to apply knowledge from prerequisitessubjects such as physics, centroids and trigonometry.Theme 2: Course Difficulty and Concept MasteryThis theme reflects students' initial perceptions of the difficulty of the course and the challengesthey encounter in mastering key statics concepts. The theme emphasizes both externalperceptions and internal struggles in learning the contents of the course. The theme was furtherdivided into two sub-themes: “Preconceived Notion of Hardness” and “Understanding andApplying Key Statics Concepts”.Preconceived Notion of DifficultyThis subtheme is
, reflection, and low stakes assessment.It is anticipated that this paper will increase dissemination of the Statics Shoebox Kit materialsand result in an increased use of hands-on learning in engineering mechanics classrooms.Another benefit, already observed since the launch of the Canvas platform, is enhancedconnections among statics instructors across the nation.IntroductionAn experience at the American Society for Engineering Education (ASEE) Annual Conference in2017, where the authors presented hands-on activities for statics instructors, motivated thedevelopment of the statics shoebox kits. The presenting author was approached by severalfaculty to share these materials. From this experience, the authors realized there is a need formore hands-on
textbook and lecture notes, providing context beyond aslideshow, but with brevity in mind [7]. The shorter format aligns with students’ penchanttowards concise summaries over lengthy readings — reflected in the popular acronym TL;DR orToo Long; Didn’t Read, usually indicating a person skipped a large piece of text due to itswordiness. The goal is to promote the different aspects laid out in the 3Cs framework.Designed with continuity in mind, the pages reuse and connect concepts, examples, and figuresacross courses. This reinforces core ideas while demonstrating applications in diverse contexts,with the aim to strengthen students’ understanding of concepts and highlight theinterconnectedness of their studies.The online aspect is critical. As
, conducting experiments, and developingproblem-solving and critical thinking abilities [1]. Often, lab courses are offered in the earlyphase of engineering majors to provide students with hands-on experience and a foundationalunderstanding of core engineering principles. For engineering labs, a range of assessmentmethods exists and includes lab reports, quizzes and exams, post-lab assignments, lab practicals, 1and instructor observations. Among these, lab reports are the most dominant assessment methodfor evaluating students’ learning from the labs. Indeed, lab report writing aligns well with the“write to learn” approach - an active learning approach - by encouraging students to reflect ontheir
the process of learning by inquiring about the nature of experience [7].Kolb stated that experiential learning includes all modes of the learning cycle and ensureseffective knowledge acquisition [7]. Experiential learning includes four modes: ConcreteExperience (CE), Reflective Observation (RO), Abstract Conceptualization (AC), and ActiveExperimentation (AE). The concrete experience and active experimentation can be achieved byhands-on experience of a physical model, followed by a recording of experimental observationsand measurements. Afterwards, students should reflect on these observations, facilitated byguided questioning, and then connect their observations to the derived theories (abstractconceptualization). Students can then actively
“Artificial Intelligence” or “AI” in the title. The set can beexpanded to over 100 by adding terms such as “Machine Learning”, “Large Language Models”,or “Generative”. Results are spread across most ASEE divisions, reflecting the intense interestengineering educators have in using modern AI-based tools in the classroom. Proposed uses ofAI are too many to enumerate here, but broad topics include techniques for teaching studentshow to use AI, recommendations to instructors on using AI tools to assist with curriculumdevelopment and assessment, the ethics of AI use in the classroom, and advances in AI forsolving engineering problems.Given the focus on these emerging tools by educators and students alike, it is imprudent toignore their use in any field of
confident that ChatGPT's solution is correct?" If they identifiedany errors in ChatGPT’s solution, they were instructed to circle the incorrect parts and briefly theexplain the issues with the provided solution.Students in Statics were additionally instructed to utilize AI tools with image-processingcapabilities to tackle two challenging problems, such as creating shear force and bending momentdiagrams for a beam under various loads as a class project. They then compared their solutionswith those generated by the AI. Following this exercise, students were asked to identifydiscrepancies between their responses and the AI-generated results and reflect on the AI'sperformance. This activity provided them with valuable knowledge and deeper insights into
)The Pilot SKI (SKI 1.0) administered in Spring 2024 consisted of fifteen problems, includingeight MCQs and seven procedural problems. The second problem set, administered in Fall 2024(SKI 2.0), included eleven problems, five MCQs, and six procedural problems. Both problemsets incorporated drawing FBDs and multi-part procedural problems, allowing us to evaluatestudents' conceptual understanding, problem-solving skills, and computational accuracy. We alsoincluded two reflective questions with each problem in both sets to assess students' self-reportedconfidence and perceived difficulty. Additionally, both problem sets concluded with tworeflective prompts asking students to (1) reflect on where/when they had learned the relevantconcepts or
further-work section identifying additional topicareas for model implementation follows a brief discussion on student reception andeffectiveness.Literature ReviewStudents in engineering mechanics courses develop many skills, chief being conceptualawareness of how the created world works. As they pursue the true, the beautiful and the good inan objective world, student engineers demonstrate their conceptual competence throughconcurring representational competence reflected in their descriptions, diagrams, andmathematics [5], [6]. However, far too often students revert to memorized responses to idealizedcontexts rather than rationally exploring real world conditions [7]. To this end, physical modelsin the classroom are a well-established method for
minutes (41minutes average). Recordings of the interviews were transcribed and cleaned before beinguploaded into Dedoose for analysis. 8Data analysisWe conducted in vivo coding, using short phrases from the instructors’ responses as codes (Mileset al., 2014). The codes reflected the instructors’ descriptions and explanations of theirperceptions and practices regarding equity. Then, we used guidance from the framework forequitable and effective teaching in undergraduate STEM education (Holmes et al., 2023) toconduct a thematic analysis that identified themes shared across the two cases and specific to anindividual case (Miles et al., 2014). Finally
impact reactions, asking forthe impact to Ay, By, or Ax might be more suitable.Future WorkOur qualitative analysis of thirteen student think alouds provides initial insights into the rigidbody beam question shown in Figure 1 (ConcepTest #4660). The 13 participants in this work area part of a larger sample of 46 interviews which investigate the box question shown in Figure 3(ConcepTest #4497). Future work will explore the 46 interview sample for common themes andinvestigate the impact of follow-up questions on student confidence.DisclaimerThe views expressed in this paper are those of the author and do not necessarily reflect theofficial policy or position of the Air Force, the Department of Defense, or the U.S. Government.AcknowledgementThe
, 1821445, 1820888, and1821603. Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation.Bibliography[1] I. D. Beatty, W. J. Gerace, W. J. Leonard, and R. J. Dufresne, “Designing effective questions for classroom response system teaching,” Am. J. Phys., vol. 74, no. 1, pp. 31–39, 2006, doi: 10.1119/1.2121753.[2] C. Papadopoulos, A. I. S. Roman, M. J. Perez-Vargas, G. Portela-Gauthier, and W. C. Phanord, “Development of an alternative statics concept inventory usable as a pretest,” in ASEE Annual Conference and Exposition, 2016.[3] P. S. Steif and M. A. Hansen, “New Practices for Administering and
6.10 3.78 5.78 7.64 7.09 6.40 5.50 Understanding Difference (Importance – 1.73 1.82 0.64 2.4 2.3 2.72 2.33 1.45 1.91 2 1.94 Understanding)*For Concept 6 and 11 there was one faculty member that selected “I do not cover this topic” forImportance but gave a numerical rating for the Student Understanding question.The trends revealed that the concepts rated higher in importance often had higher studentunderstanding ratings. This correlation might reflect the emphasis placed on these conceptsduring instruction or a result of the nature of the concept and how accessible it is within thedynamics curriculum. Figure 1 illustrates the relationship between importance and studentunderstanding
scholarship of teaching and learning interests are in motivation and mindset, teamwork and collaboration, and learning through failure and reflection. Her bioengineering research interests and collaborations are in the areas of biomaterials, cellular microenvironments, and tissue engineering and regenerative medicine. She serves on leadership teams for the Whitaker Center of STEM Education and the Lucas Center for Faculty Development at FGCU, and is a member of the Biomedical Engineering Society (BMES) and the KEEN Engineering Unleashed Network as an Engineering Unleashed Fellow.Dr. Anurag Purwar, Stony Brook University Dr. Anurag Purwar is an Associate Professor of Mechanical Engineering at Stony Brook University. His
Classes by aQuiz-Based Approach," Chemical Engineering Education, vol. 46, pp. 213-217, 2012.[15] Friess W.A., and Davis M.P., "Formative Homework Assessment Strategies to Promote Student Self-Reflection and Improve Time Management: APilot Study," in Proceedings of the ASEE NE 2016 Conference, Rhode Island, RI, 2016.[16] Howard, A. K. T., & Cole, A. D., "Weekly Quizzes in Lieu of Homework in Large Sections," in ASEE Annual Conference & Exposition, Baltimore, MD, 2023.[17] Mawhinney, V.T., Bostow, D.E., Laws, D.R., Blumenfeld, G.J., Hopkins, B.L, "A comparison of students stuying-behavior produced by daily, weekly, and three-week testing schedules," Journal of Applied Behavior Analysis, vol. 4, no. 4, pp. 257-264
how studentssee torque concepts. Recognizing this challenge is the first step toward creating more effectivepedagogy.There are several limitations in the current study. During the interviews, we generally used theterm torque, only occasionally using the equivalent term moment. Because torque is the commonterminology in external force forms, this language may have led to more students to respond withexternal force expressions. Several of those expressions were surprising; upon reflection, someopportunities for follow-up questions were missed.In conclusion, this study brought into focus the conceptual confusion between the external andinternal force forms in which torque (or moment) is expressed and measured. Students expressfrustration with
to explore the relationship between problem-solving skills andconceptual understanding.The three teaching styles examined in this study are: (A) a flipped, recitation-based classroomwith a mastery-based derivation approach, (B) a lecture-style class using the SMART (SupportedMastery Assessment through Repeated Testing) approach, and (C) a lecture-style class with threelevels of student participation to engage both reflective and active learners. We analyzed studentperformance data from exams and concept inventory questions to address the following researchquestions: (I) Do problem-solving skills differ among students taught with different approaches?(II) How does conceptual understanding vary among students in different teachingenvironments
, frame rate, distortion, and providing only planar data capture. However, it had thebenefit of being portable, familiar to use, and readily available. The video captured was analyzedusing open-source software1 to extract information about the position or orientation of objectsvia optical tracking. Variation two used a precision motion capture system consisting of eightVicon Vero 2.2 cameras and reflective markers for position tracking with a mean error of 0.017mm, as per the manufacturer2. The tracking data captured by this system was provided tostudents as a set of position coordinates and orientation of the rigid body or rigid bodies for laterprocessing. The benefits of using the Vicon system were that it provided high-precision data withfewer
learning what we are learning.In a recent offering of this course, we aimed to build a sense of ownership and intuitiveunderstanding of the relationships implied in the equations being discussed. The main idea is totake an equation used in class and show how it relates to real-world situations. We hypothesizethat by relating the equation to a real-world example, the value of the course content is morereadily apparent to students. Here the inclusion of multiple real-world example problems isevaluated via student surveys before and after the semester. The survey ask students to evaluatestatements reflecting how well the course achieved the 3C’s of the KEEN framework: Curiosity,Connections, and Creating Value [5].MethodsThis study was conducted a
jumping into complex application problems without reviewing a simpler problemfirst.This study had several limitations. First, lectures were not included in the course content data. Forthese courses, the core lecture slides are the same between professors, but how a professorintroduces them and incorporates real-world applications is not standardized. Different sectionsof a course within a semester are not exactly the same. Future research could include the lecturecontent. Another limitation is that only one semester was included. Future studies should includemore semesters. Only about a third of the statics students take the whole course, so the end of thestatics course only reflects these students. Including the students that are only required
Figure 3 and 4.Students struggling with vectors performed worse overall on the first exam in Fall of 2024, butperhaps more troubling is the fact that several weeks of instruction about vectors – in the contextof their representation of forces in statics problems – still did not yield mastery of thesefundamental skills at exam time. This result poses questions that get further at root causes of theproblem. While most students post-statics would likely reflect on these basic vectors skills, suchas vector addition and magnitude, as straightforward, it is not clear if or how the transition occursbetween being a novice and being able to apply these operations. The authors have postulatedthat some of the challenge may come down to students being