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
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
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
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
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
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
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
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