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Bogdan Yamkovenko; Charlie A. R. Hogg; Maya Miller-Vedam; Phillip Grimaldi; Walt Wells – International Educational Data Mining Society, 2025
Knowledge tracing (KT) models predict how students will perform on future interactions, given a sequence of prior responses. Modern approaches to KT leverage "deep learning" techniques to produce more accurate predictions, potentially making personalized learning paths more efficacious for learners. Many papers on the topic of KT focus…
Descriptors: Algorithms, Artificial Intelligence, Models, Prediction
Carranza Rogerio, Brenda; Yan, Yu; Cooper, Eric Wallace – International Journal of Technology in Education, 2023
The growing integration of technology into education, particularly in the STEM fields, has tended to focus on its objective advantages, ignoring its affective potential. To explore this potential, based on some principles of "Kansei/Affective Engineering," an initial analysis was conducted considering 501 interventions in a conversation…
Descriptors: Affective Behavior, Feedback (Response), STEM Education, Electronic Learning
Adrienne K. Golden; Mary Louise Hemmeter; Jennifer R. Ledford – Journal of Positive Behavior Interventions, 2024
The purpose of this study was to evaluate the effectiveness of training plus Practice-Based Coaching (PBC), delivered via text message, on teacher use of targeted Pyramid Model (PM) practices. A multiple baseline design across behaviors was replicated across three early childhood teachers. Following training on self-selected target practices, the…
Descriptors: Coaching (Performance), Training, Telecommunications, Handheld Devices
Hyeongdon Moon; Richard Lee Davis; Seyed Parsa Neshaei; Pierre Dillenbourg – International Educational Data Mining Society, 2025
Knowledge tracing models have enabled a range of intelligent tutoring systems to provide feedback to students. However, existing methods for knowledge tracing in learning sciences are predominantly reliant on statistical data and instructor-defined knowledge components, making it challenging to integrate AI-generated educational content with…
Descriptors: Artificial Intelligence, Natural Language Processing, Automation, Information Management
Lixiang Yan; Lele Sha; Linxuan Zhao; Yuheng Li; Roberto Martinez-Maldonado; Guanliang Chen; Xinyu Li; Yueqiao Jin; Dragan Gaševic – British Journal of Educational Technology, 2024
Educational technology innovations leveraging large language models (LLMs) have shown the potential to automate the laborious process of generating and analysing textual content. While various innovations have been developed to automate a range of educational tasks (eg, question generation, feedback provision, and essay grading), there are…
Descriptors: Educational Technology, Artificial Intelligence, Natural Language Processing, Educational Innovation
Chapman, Jared R.; Kohler, Tanner B.; Gedeborg, Sam – Journal of Educational Computing Research, 2023
Research on gamification's effects in educational environments has been a growing domain in recent years. As research has demonstrated the power of gamified systems to effectively motivate learners in educational settings, it has also become clear that not all individuals are motivated in the same way, or to the same extent, by the same gamified…
Descriptors: Educational Technology, Gamification, Student Motivation, Student Attitudes
Maria Fahlgren; Mats Brunström – International Journal of Mathematical Education in Science and Technology, 2025
This paper provides some insights into the use of example-generating tasks in the design of a technology-rich learning environment to enhance students' mathematical thinking. The paper reports on an early stage of a design-based research project concerning the design of tasks and associated feedback utilising the affordances provided by a combined…
Descriptors: Mathematics Instruction, Educational Technology, Technology Uses in Education, Computer Software
Medeiros Machado, Guilherme; Bonnin, Geoffray; Castagnos, Sylvain; Hoareau, Lara; Thomas, Aude; Tazouti, Youssef – Journal of Computer Assisted Learning, 2023
Background: Early literacy and numeracy skills are developed during early childhood. Among the many factors that influence the development of such skills, the literature shows that the executive functions, especially the response inhibition (RI)--that is the capability to block out or to tune out what can be considered irrelevant information or…
Descriptors: Executive Function, Responses, Inhibition, Child Behavior
Kimble Teresa Parkman-Colbert – ProQuest LLC, 2023
Microlearning is a relatively new educational technology that allows students to learn through short, direct segments using various modalities. The nursing profession has used microlearning to provide continuing medical education (CME). The problem addressed through this study was that instructional designers who create microlearning for medical…
Descriptors: Instructional Design, Nursing Education, Cognitive Style, Professional Continuing Education
Radosavljevic, Vitomir; Radosavljevic, Slavica; Jelic, Gordana – Interactive Learning Environments, 2022
This paper introduces the smart classroom learning model based on the concept of ambient intelligence. By analyzing a smart classroom, the ambient intelligence system detects a student and determines their level of fatigue based on the data about their previous daily academic activities. This information is then used to assign the student the…
Descriptors: Virtual Classrooms, Educational Technology, Technology Uses in Education, Artificial Intelligence
Zhai, Xuesong; Xu, Jiaqi; Chen, Nian-Shing; Shen, Jun; Li, Yan; Wang, Yonggu; Chu, Xiaoyan; Zhu, Yumeng – Journal of Educational Computing Research, 2023
Affective computing (AC) has been regarded as a relevant approach to identifying online learners' mental states and predicting their learning performance. Previous research mainly used one single-source data set, typically learners' facial expression, to compute learners' affection. However, a single facial expression may represent different…
Descriptors: Affective Behavior, Nonverbal Communication, Video Technology, Online Courses
Brandon J. Yik; David G. Schreurs; Jeffrey R. Raker – Journal of Chemical Education, 2023
Acid-base chemistry, and in particular the Lewis acid-base model, is foundational to understanding mechanistic ideas. This is due to the similarity in language chemists use to describe Lewis acid-base reactions and nucleophile-electrophile interactions. The development of artificial intelligence and machine learning technologies has led to the…
Descriptors: Educational Technology, Formative Evaluation, Molecular Structure, Models
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
Forbes-Lorman, Robin; Korb, Michele; Moser, Amy; Franzen, Margaret A.; Harris, Michelle A. – Journal of College Science Teaching, 2022
Physical and life science disciplines emphasize how basic structural units influence function, yet it is challenging for students to understand structure-function relationships, particularly at molecular scales. Undergraduates in our biology capstone course struggled to connect mutations in a gene encoding a key protein in a cell development…
Descriptors: Formative Evaluation, Science Education, Undergraduate Students, Summative Evaluation
Sahin, Ferhan; Sahin, Yusuf Levent – Social Psychology of Education: An International Journal, 2022
The vital role of motivation becomes even more evident when considering the digital transformation of learning and teaching environments, especially with the effect of the pandemic. Basic psychological needs and emotions, which have not been comprehensively examined together despite their important roles in motivating, draw attention. Accordingly,…
Descriptors: COVID-19, Pandemics, Educational Technology, Technology Uses in Education

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