an accessible and reliable assessmentsystem for assessing conceptual STEM understanding for colleges and universities that aligns withSTEM curriculum and uses Artificial Intelligence (AI) based assessment methods. Table 1: Operational Definition of Terms Term Operational Definition Example(s) Proficiency The proficiency of a person reflects the probability • Percentage correct on of answering test items correctly. The higher the static exams. individual’s proficiency, the higher the probability • Theta estimate on CATs. of a correct response. Different fields refer to proficiency as ability, latent trait, theta. Content
find efficient solutionsto the problem. When this logical sequence of steps or instructions are developed to form aneffective procedure, this process can be automated to solve similar problems. Debugging refersto identifying and fixing errors in the algorithm, both during the development of the algorithmand when students attempt to transfer the algorithm to a new context. Iteration is the process ofrevisiting effective algorithms to improve their efficiency until an optimum state is reached.Generalization occurs when the algorithms and CT skills are transferred to effectively addressproblems in other domains. Because iteration and generalization require the problem context toallow sufficient time for reflection and modification of the solution
the student,rather on the instructor as the case with the traditional form of leraning [4]. This has brought asignificant improvement during the learning process of many students. Active learning is apedagogical tool that has helped promote ‘students’ cognitive capabilities when it comes tomastery of the content [5]. Meaningful conversations, proper reflection, and content mastery areproducts of this learning mode [6].Experiment-centric-pedagogy (ECP), an instructional technique that facilitates activite learning,offers an alternate route for acquiring technical skills and information both inside and outside ofthe classroom. ECP enabls students with different learning styles to learn at their own pace and intheir own settings. Instructors
advancedcomposition courses.The comparison in Fig. 5 could also be used to reflect back on the framework and its effectivenessin representing the writing skills important to relevant career paths. For example, if one took theLearning Goals used in laboratory courses as representative of the writing skills essential tostudent careers, it would suggest that the framework includes irrelevant concepts. On the otherhand, the coverage of Learning Goals in advanced composition courses shows better alignmentwith the framework, perhaps reflecting their shared focus on development of writing skills.4 Conclusions and Implications • Analysis of course materials for instances referring to writing revealed a broad range of courses involving writing. This
theteaching and learning of a physics course through the students' perception. The modifiedILD has the same three stages as the original ILD, with two main differences in whoperforms the experiment and when it is performed. Specifically, the three phases in themodified ILD are 1) predict, 2) experiment (by students working in groups, not theinstructor), and 3) reflect (in groups, not individually). The first phase, prediction, beginswith the analysis of a physical situation in which students have to predict the behavior ofthe situation based on the knowledge imparted in the session by the instructor. This occursat the end of the instructor's exposition. The second phase occurs in the laboratory sectionof the course and relates to students' experience
8-week intervention period. The survey collected their perceptions regardingan innovative teaching method used for the laboratory course. The pre-and-post comparisonallows for contrasting student opinions in three main areas: type of instruction, teachingstrategies, and student response to the instruction. The study presents some of the laboratoryactivities' outcomes and limitations. One specific activity, the capacitor discharge experiment,will be thoroughly discussed to compare the traditional physical setup with the technology-basedversion. Findings highlight the pros and cons of the teaching method used and reflect on what hasbeen learned. It also suggests potential next steps for further improvement.Keywords: Physics laboratory course
both theoretical and practical aspects.9. Self-Assessment and • Learning Journal: Throughout the course students will maintainReflection a learning journal in which they reflect on their progress, challenges, and areas for improvement. This encourages self- assessment and continuous learning.10. Problem-Solving • Model Optimization Challenge: During several labs studentsChallenges will receive suboptimal PyTorch model code and will work in groups to optimize it, assessing their problem-solving skills. 11. Real-World • Engineering Application Report: Students are tasked with Application Report identifying a
questionsFinally, the results of the open-ended questions in the survey will be presented. The firstquestion invited students to leave additional comments about the importance of the coursein an engineering program. Student response to the engineering course reflects a mixture ofappreciation and criticism. On the one hand, some students value the course for developingand expanding their ability to evaluate everyday situations methodically, which contributesto a better adaptation in the workplace, regardless of the direct use of the syllabus learned.However, others express frustration at being unable to understand key concepts, such asvoltage, resistance, impedance, and coil operation, pointing to a disconnect between theresolution of exercises and the
initiative to comprehend and buildmore in-depth information and skills needed for scientific applications. Hence, an undergraduatecourse should incorporate applied laboratory implementation applications. As such, educators areresponsible for ensuring that students acquire a strong sense of learning motivation and scientificinquiry skills [12]. School laboratories are a crucial part of any STEM education. They enhancestudents’ engagement in a variety of experimental learning skills, such as conception andexperimentation followed by reflection, analysis, and data interpretation. Establishing the worthof the laboratory equipment in the department is crucial before starting a comparison of labmodalities. Topics in the laboratory manual for Introduction
Diffusion in Polymer Networks. Her research interests include polymer physics, nanoparticle diffusion, and engineering and physics education.Steven Warth, Austin Peay State University Steven Warth is an undergraduate researcher, who attended a STEM program throughout half of his time in high school. Currently pursuing a bachelors degree in engineering physics.Dr. Bobette Bouton, Austin Peay State University Dr. Bobette Bouton is an associate professor at Austin Peay State University. Her current area of research is socio-emotional development in the domain of empathy. She is a Deweyan Pragmatist who focuses on student-centered teaching and reflection. She also is working toward making higher education a more socially
pandemic, the projectwas not evaluated. In 2022, the “evaluation laboratory” tool of Open LMS was added to theproject in design thinking methodology. Using this tool, students can submit the initial seminarplanning to be evaluated by teachers and at the same time do peer review of other groupsactivities. They can ask questions and make reflections about other groups activities sodeveloping critical thinking during this process before submitting the final seminarpresentation. The project has attended expectations, resulting in better academic performance,as well as contributing to the development of the competencies and skills that were aimed tobe developed.IntroductionThe Physics subject is applied to the First-Year students of the Engineering
decision-making, and an appropriate division of labor in thedevelopment of the software.The resulting computer program with an intuitively designed user interface allows thesimulation of different scenarios due to a variety of adjustable parameters. The visual outputof the program reflects the different model assumptions and thus promotes the understandingof model building in general and of self-organization and swarm behavior in particular. Theprogram is freely available and can be downloaded from our institution’s home page.IntroductionSwarm behavior, often exemplified by the coordinated movement of birds or fish, has longcaptivated the fascination of scientists, engineers, and nature enthusiasts alike. The collectiveintelligence displayed by
the 2D plane. MARVLS provides opportunities for students to reflect on interactions with the physicalcube and digital model by allowing students to rotate digital model by rotating the cube. Thisallows students to manipulate aspects of the digital models by modifying current flow, shape ofcomponents, and orientation of the system to explore complex interactions between objects andfields. Activities then scaffold students to map these interactions to formalisms, such as Lorentzforces, Gauss’s Law, and Ampere’s Law, as well as abstractions, such as mathematical equationslike Maxwell’s equations. By connecting equations and formalisms to a variety of actionsgrounded in conceptual metaphors and intuitive understanding, MARVLS facilitates
classmates in group activities," and item 17: "Have a more proactiveattitude about my learning." These items reflect a decrease in the frequency of various forms ofinteraction, including interactions with teachers and classmates during synchronous sessions andgroup activities. Additionally, there appears to be a decrease in the frequency of discussions withclassmates about course-related work and a decline in proactive attitudes toward learning.While there are positive changes in certain aspects of collaborative engagement and presentationskills, there are negative changes in interactions with teachers and classmates and proactivelearning attitudes. It would be important to explore the reasons behind these changes and considerstrategies to encourage
smartphone's location, which can be used for a variety of purposes such asmaps, tracking, and location-based services.A special feature of these physical data recorded by the internal sensors, however, is that theycan be used beyond their actual purpose with the help of additional programs, so-called apps.This makes it possible to carry out both qualitative and quantitative experiments in a widerange of subject areas, especially in physics. Smartphones thus represent small, transportablemeasurement laboratories. The project presented in this paper focuses on the latter point, inwhich the sensors installed in smartphones are used to carry out quantitative experiments. Themain advantages of the devices are to be exploited, which are reflected in their
on this positive interest from students, a committee of faculty who taught in math andsciences was convened to develop the program. Because of the institution’s historical strengths inthe sciences, the committee recommended that the institution offer a B. S. in EngineeringScience, which was subject to the same ABET criteria as B.S. programs in Engineering andEngineering Physics.[7] It was also believed that the program named Engineering Sciencewould be better accepted at a liberal arts institution where a degree such as engineering might beviewed by some as a strictly vocational major. The intent of the degree to equip students with abroad and general engineering background also reflected key principles of the liberal artsapproach.The
previous experience in which Phet Simulationswere introduced under a modified version of the ILD methodology. Figure 1 shows a schematicview of the roles, activities, and modalities for the innovation sequence implemented. Notice thatthis instructional strategy requires both individual reflection and group discussion, takingadvantage of each technique [16]. Instructor Students Small groups •Pose a physical •Students •Students use Phet to situation so that individually work on a practice students can make a analyze the related to their prediction under
energy from a basketball backboard, the decision to use piezoelectricgenerators, otherwise known as buzzers, was made shortly after. There were multiple ideas forhow to attach the generators to the board as well as where to place them. The original paperprototype contained three panels of four buzzers each (Figure 1). However, after research into thesizes and ability of the buzzers, the decision was made to construct fewer sensors per panel and totailor the number of panels required to the specific system. Scoreboards that required a higherinput of energy would simply need to obtain more panels to work. The portability factor of thedesign was a priority throughout the project. This was reflected in the paper prototype by the useof Velcro dots to
long-term goals are. Students then re-assessed whether the job they envisioned alignswith what they learned from their informational interview. The final piece of the assignment wasfor students to reflect: Who might be best served by working in this job? What is the futureprognosis of this job, especially in light of climate change? And would this be a job that youwould actually want? The assignment culminated with short (less than 10 minute), in classpresentations where other groups were able to ask questions. I assessed the assignment by quantifying students’ perception of it in four categories. Ialso collected qualitative data by asking students open-ended questions about their experience. In this report, I share students
to create a video presentation knowledge that explains the objective of the project, the proposed solution, and an analysis of the results. Think critically The video should include a comparative and critical analysis of the and reflectively expected results with the theoretical model and the experimental results obtained. Demonstrate Furthermore, the project must be related to the application of physicalEngineering skills concepts in engineering problems.In the laboratory classes, the students were divided into teams of four members. Each teamhad the opportunity to choose a scientific
to pause and reflect on how these experiences may impact our classrooms going forward.In fact, some of these experiences may actually have produced encouraging outcomes and if so,we need to take the time to assess and evaluate how to translate them back into the learningenvironment of our classrooms going forward. One may even be able to argue that the onlineexperience had a positive impact on learners that, for one reason or another, were notcomfortable interacting in an in-person classroom. For these students, we might say that theonline experience gave them a front-row seat and perhaps allowed them to engage morecomfortably. For other students, the exact opposite might be the case. Additionally, with onlinelearning there were also new
-tests to measureoverall learning levels was not feasible. Furthermore, these would necessarily have to beconducted via an online form, which, in turn, would cast doubt on the reliability of the results asit would not be possible to guarantee that student answers fully reflect their accurate knowledgelevels.AcknowledgmentsThe authors want to acknowledge the leadership and financial support of the School ofEngineering of Universidad Andres Bello, Chile. We also thank the Educational and AcademicInnovation Unit (UNIDA) for mentoring and guidance in developing scientific articles in highereducation research.In addition, the authors would like to acknowledge the financial support of Writing Lab, Institutefor the Future of Education, Tecnologico de
shape of spacetime curvature, therelationship between time and gravity, and the direction objects move in curved spacetime.These questions were developed specifically for this study, as the Relativity Concept Inventoryonly contains questions about SR and not GR [13]. For a complete list of survey items used,see Appendix B. The pre-post surveys can be compared between the two groups to see howthe different demonstrations affected participants’ understanding of these topics.Participants’ rate their agreement with nine statements on a standard five-point Likert scale torecord their attitudes toward GR, physics, and science in general. These statements are largelydrawn from [25] but modified for undergraduates and to reflect the focus on
analysis of the and reflectively expected results with the theoretical model and the experimental results obtained.In the laboratory classes, the students were divided into teams of three or four members.Each team was provided with a spring and one type of an elastic bands (each one can beassociated with a specific color): a) The minimum resistance – yellow one; b) Low-intermediate resistance - blue one; c) Upper-intermediate resistance - red one; and d) Themaximum resistance – black one. Both materials were characterized for an interval rangingfrom 0 to 40 cm with a 2.0 cm step. Then the characteristic curves (force as function ofelongation) were obtained and the data was analyzed using