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Achmad Samsudin; Aldi Zulfikar; Duden Saepuzaman; Andi Suhandi; Adam Hadiana Aminudin; Supriyadi Supriyadi; Bayram Costu – Journal of Turkish Science Education, 2024
This study aims to reconstruct Grade 11 students' misconceptions about force through the Conceptual Change Model (CCM) making use of Predict, Discuss, Explain, Observe, Discuss, Explore, Explain (PDEODEE) tasks. This study was conducted using a mixedmethod approach. The participants in this study were 65 students (33 students in the experiment…
Descriptors: Scientific Concepts, Concept Formation, Misconceptions, Foreign Countries
Ferrarelli, Paola; Iocchi, Luca – Technology, Knowledge and Learning, 2021
Novel technology has been applied to improve students' learning abilities in different disciplines. The research in this field is still finding suitable methodologies, tools, and evaluation mechanisms to devise learning frameworks with high impact on students' performance. This article describes an instructional method to perform Newtonian physics…
Descriptors: Physics, Scientific Concepts, Programming, Robotics
Wheatley, Christopher; Wells, James; Pritchard, David E.; Stewart, John – Physical Review Physics Education Research, 2022
The Force Concept Inventory (FCI) is a popular multiple-choice instrument used to measure a student's conceptual understanding of Newtonian mechanics. Recently, a network analytic technique called module analysis has been used to identify responses to the FCI and other conceptual instruments that are preferentially selected together by students;…
Descriptors: Physics, Science Instruction, Concept Formation, Scientific Concepts
Fabian Kieser; Peter Wulff; Jochen Kuhn; Stefan Küchemann – Physical Review Physics Education Research, 2023
Generative AI technologies such as large language models show novel potential to enhance educational research. For example, generative large language models were shown to be capable of solving quantitative reasoning tasks in physics and concept tests such as the Force Concept Inventory (FCI). Given the importance of such concept inventories for…
Descriptors: Physics, Science Instruction, Artificial Intelligence, Computer Software
Kortemeyer, Gerd – Physical Review Physics Education Research, 2023
Massive pretrained language models have garnered attention and controversy due to their ability to generate humanlike responses: Attention due to their frequent indistinguishability from human-generated phraseology and narratives and controversy due to the fact that their convincingly presented arguments and facts are frequently simply false. Just…
Descriptors: Artificial Intelligence, Physics, Science Instruction, Introductory Courses
Cinite, Ilva; Barinovs, Girts – International Baltic Symposium on Science and Technology Education, 2021
Education research has repeatedly shown that active learning in physics is pedagogically more efficient than traditional lecture courses. Widespread application of the active learning is slowed down by the lack of data on the performance of the active learning in widely varying circumstances of different educational systems. We measured the level…
Descriptors: Foreign Countries, Physics, Scientific Concepts, Teaching Methods
Dunleavy, Spencer; Kestin, Greg; Callaghan, Kristina; McCarty, Logan; Deslauriers, Louis – Physical Review Physics Education Research, 2022
The typical introductory physics lecture requires students to consolidate and assimilate a large quantity of complex information that is often novel to them. This can leave students overwhelmed, slow the pace of their learning, and lower their motivation. We find that carefully designed multimedia summaries in the form of one-minute videos and…
Descriptors: Physics, Science Instruction, Teaching Methods, Undergraduate Students