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Maurizio Costabile; Connie Caruso; Chris Della Vedova; Sheree Bailey; Layla Mahdi – Advances in Physiology Education, 2025
Science, technology, engineering, and mathematics (STEM) students are typically taught content delivered didactically and closely aligned with the laboratory demonstration of concepts, which facilitates the development of experimental skills. Because of the volume of content delivered across multiple courses, student cognitive abilities can be…
Descriptors: Computer Simulation, Computer Software, Learning Processes, Laboratory Training
Incorporating Coding into the Classroom: An Important Component of Modern Bioinformatics Instruction
Nichole Orench-Rivera; April Bednarski; Paul Craig; Austin Talbot – Journal of College Science Teaching, 2025
Advancements in computation and machine learning have revolutionized science, enabling researchers to address once insurmountable challenges. Bioinformatics, a field that heavily relies on computer-driven analysis of biological data, has greatly benefited from these developments. However, traditional bioinformatics instruction frequently lacks the…
Descriptors: Coding, Computer Science Education, Integrated Curriculum, Programming
Zehavit Kohen; Liron Schwartz-Aviad; Tomer Peleg – International Journal of Mathematical Education in Science and Technology, 2025
This study examines a Technology, Pedagogy, Content Knowledge (TPACK) training framework for pre- and in-service mathematics teachers that enables them to experience inquiry-based learning as learners in a dynamic geometry environment that serves as a mathematics laboratory. We investigate the effect of this experience on the teachers' TPACK,…
Descriptors: Pedagogical Content Knowledge, Technological Literacy, Mathematics Teachers, Preservice Teachers
Rebeckah K. Fussell; Megan Flynn; Anil Damle; Michael F. J. Fox; N. G. Holmes – Physical Review Physics Education Research, 2025
Recent advancements in large language models (LLMs) hold significant promise for improving physics education research that uses machine learning. In this study, we compare the application of various models for conducting a large-scale analysis of written text grounded in a physics education research classification problem: identifying skills in…
Descriptors: Physics, Computational Linguistics, Classification, Laboratory Experiments
Danielle A. Guarracino; Joseph L. Baker; J. Lynn Gazley – Journal of College Science Teaching, 2025
Having a deeper understanding of molecules in their structural forms allows students to grasp biochemical and general chemical concepts in a more profound manner. Through the use of visualization software, we have shown that students gain confidence and insight into the chemical workings of molecular structure and can then utilize this knowledge…
Descriptors: Science Education, Undergraduate Students, Biochemistry, Molecular Structure
Ravikantha Prabhu; Sharun Mendonca; Pavana Kumara Bellairu; Noel Deepak Shiri – Innovations in Education and Teaching International, 2025
In response to evolving engineering education, there is a growing focus on fostering students' practical skills. This study implemented a Mini Project Based Learning (MPBL) approach within the Computer Integrated Manufacturing (CIM) course. The tasks involved SOLIDWORKS modelling, writing CNC code using CADEM seeNC Turn software, and hands-on CNC…
Descriptors: Engineering Education, Student Projects, Active Learning, Computer Uses in Education
Victoria Borish; H. J. Lewandowski – Physical Review Physics Education Research, 2025
As quantum technologies transition from the research laboratory into commercial development, the opportunities for students to begin their careers in this new quantum industry are increasing. With these new career pathways, more and more people are considering the best ways to educate students about quantum concepts and relevant skills. In…
Descriptors: Physics, Science Instruction, Quantum Mechanics, Computer Software