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Yunus Kökver; Hüseyin Miraç Pektas; Harun Çelik – Education and Information Technologies, 2025
This study aims to determine the misconceptions of teacher candidates about the greenhouse effect concept by using Artificial Intelligence (AI) algorithm instead of human experts. The Knowledge Discovery from Data (KDD) process model was preferred in the study where the Analyse, Design, Develop, Implement, Evaluate (ADDIE) instructional design…
Descriptors: Artificial Intelligence, Misconceptions, Preservice Teachers, Natural Language Processing
Keith Cochran; Clayton Cohn; Peter Hastings; Noriko Tomuro; Simon Hughes – International Journal of Artificial Intelligence in Education, 2024
To succeed in the information age, students need to learn to communicate their understanding of complex topics effectively. This is reflected in both educational standards and standardized tests. To improve their writing ability for highly structured domains like scientific explanations, students need feedback that accurately reflects the…
Descriptors: Science Process Skills, Scientific Literacy, Scientific Concepts, Concept Formation
Nathan Mentzer; Wonki Lee; Andrew Jackson; Scott Bartholomew – International Journal of Technology and Design Education, 2024
Adaptive comparative judgment (ACJ) has been widely used to evaluate classroom artifacts with reliability and validity. In the ACJ experience we examined, students were provided a pair of images related to backpack design. For each pair, students were required to select which image could help them ideate better. Then, they were prompted to provide…
Descriptors: Evaluative Thinking, Design, Engineering Education, Evaluation Methods
Blanka Klimova; Victor Paiva Luz de Campos – Cogent Education, 2024
At present, ChatGPT is penetrating all spheres of human activities, and especially education is no exception. The purpose of this exploratory study is to examine the potentials and pitfalls of using ChatGPT for academic purposes among university students, as well as provide relevant pedagogical implications for its use in academia. The methodology…
Descriptors: Undergraduate Students, Undergraduate Study, Student Attitudes, Artificial Intelligence
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
Krüger, Ralph – Interpreter and Translator Trainer, 2022
This paper intends to illustrate the didactic potential of Python-based Jupyter notebooks in teaching translation technology, machine translation in particular, to translation students. It discusses the basic makeup of Jupyter notebooks and shows how these notebooks can be set up for students who have had little to no prior exposure to the Python…
Descriptors: Translation, Second Language Learning, Second Language Instruction, Natural Language Processing
Kelly, Nick; Thompson, Kate; Yeoman, Pippa – Journal of Learning Analytics, 2015
This paper describes theory-led design as a way of developing novel tools for learning analytics (LA). It focuses upon the domain of automated discourse analysis (ADA) of group learning activities to help an instructor to orchestrate online groups in real-time. The paper outlines the literature on the development of LA tools within the domain of…
Descriptors: Data Analysis, Data Collection, Computer Assisted Instruction, Cooperative Learning