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Tsubasa Minematsu; Atsushi Shimada – International Association for Development of the Information Society, 2024
In using large language models (LLMs) for education, such as distractors in multiple-choice questions and learning by teaching, error-containing content is used. Prompt tuning and retraining LLMs are possible ways of having LLMs generate error-containing sentences in the learning content. However, there needs to be more discussion on how to tune…
Descriptors: Educational Technology, Technology Uses in Education, Error Patterns, Sentences
Martin, Tim; Frisch, Kayt; Zwart, John – Physics Teacher, 2020
Video analysis helps students to connect physical, mathematical, and graphical models with the phenomena that the models represent and improves student kinematic graph interpretation skills. The wide-spread availability of easy to use software packages like Logger Pro (Vernier), Capstone (PASCO), and Tracker have led to many introductory physics…
Descriptors: Video Technology, Science Instruction, Educational Technology, Technology Uses in Education
Miao, Dezhuang; Dong, Yu; Lu, Xuesong – International Educational Data Mining Society, 2020
In colleges, programming is increasingly becoming a general education course of almost all STEM majors as well as some art majors, resulting in an emerging demand for scalable programming education. To support scalable education, teaching activities such as grading and feedback have to be automated. Recently, online judge systems have been…
Descriptors: Programming, Prediction, Error Patterns, Models
Van Inwegen, Eric G.; Adjei, Seth A.; Wang, Yan; Heffernan, Neil T. – International Educational Data Mining Society, 2015
User modelling algorithms such as Performance Factors Analysis and Knowledge Tracing seek to determine a student's knowledge state by analyzing (among other features) right and wrong answers. Anyone who has ever graded an assignment by hand knows that some answers are "more wrong" than others; i.e. they display less of an understanding…
Descriptors: Knowledge Level, Performance Factors, Error Patterns, Mathematics
Retnowati, Endah, Ed.; Suprapto, Ed.; Jerusalem, Mohammad Adam, Ed.; Sugiyarto, Kristian, Ed.; Wagiran, Ed. – Routledge, Taylor & Francis Group, 2018
This proceedings volume of InCoTEPD 2018 covers many ideas for handling a wide variety of challenging issues in the field of education. The outstanding ideas dealing with these issues result in innovation of the system. There are many innovation strategies resulting from recent research that are discussed in this book. These strategies will become…
Descriptors: Educational Innovation, Knowledge Level, Skill Development, Vocational Education
Boyer, Kristy Elizabeth, Ed.; Yudelson, Michael, Ed. – International Educational Data Mining Society, 2018
The 11th International Conference on Educational Data Mining (EDM 2018) is held under the auspices of the International Educational Data Mining Society at the Templeton Landing in Buffalo, New York. This year's EDM conference was highly competitive, with 145 long and short paper submissions. Of these, 23 were accepted as full papers and 37…
Descriptors: Data Collection, Data Analysis, Computer Science Education, Program Proposals