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Guido Makransky; Ban M. Shiwalia; Tue Herlau; Steven Blurton – Educational Psychology Review, 2025
Generative artificial intelligence (GenAI) has emerged as a transformative tool in education, offering scalable individualized learning. However, there is a lack of theoretically informed and methodologically rigorous research on how GenAI can effectively augment learning. This manuscript addresses this gap by investigating the potential of a…
Descriptors: Artificial Intelligence, Technology Uses in Education, Learning Processes, College Students
Conrad Borchers; Paulo F. Carvalho; Meng Xia; Pinyang Liu; Kenneth R. Koedinger; Vincent Aleven – Grantee Submission, 2023
In numerous studies, intelligent tutoring systems (ITSs) have proven effective in helping students learn mathematics. Prior work posits that their effectiveness derives from efficiently providing eventually-correct practice opportunities. Yet, there is little empirical evidence on how learning processes with ITSs compare to other forms of…
Descriptors: Problem Solving, Intelligent Tutoring Systems, Mathematics Education, Learning Processes
Xiao-Rong Guo; Si-Yang Liu; Shao-Ying Gong; Yang Cao; Jing Wang; Yan Fang – Education and Information Technologies, 2024
To enhance the effectiveness of educational games, researchers have advocated adding learning supports in educational games, but this may come at the cost of disrupting the learning experience. Embedding virtual companions to provide learning supports may be an effective solution that naturally integrates learning supports into the game. However,…
Descriptors: Educational Games, Mathematics Education, Middle School Students, Psychological Patterns
Conrad Borchers; Alex Houk; Vincent Aleven; Kenneth R. Koedinger – Grantee Submission, 2025
Active learning promises improved educational outcomes yet depends on students' sustained motivation to engage in practice. Goal setting can enhance learner engagement. However, past evidence of the effectiveness of setting goals tends to be limited to non-digital learning settings and does not scale well as it requires active teacher or parent…
Descriptors: Learner Engagement, Educational Benefits, Goal Orientation, Rewards
Meng Xia; Robin Schmucker; Conrad Borchers; Vincent Aleven – Grantee Submission, 2025
Mastery learning improves learning proficiency and efficiency. However, the overpractice of skills--students spending time on skills they have already mastered--remains a fundamental challenge for tutoring systems. Previous research has reduced overpractice through the development of better problem selection algorithms and the authoring of focused…
Descriptors: Mastery Learning, Skill Development, Intelligent Tutoring Systems, Technology Uses in Education
Joel B. Jalon Jr.; Goodwin A. Chua; Myrla de Luna Torres – International Journal of Education in Mathematics, Science and Technology, 2024
ChatGPT is largely acknowledged for its substantial capacity to enhance the teaching and learning process despite some concerns. Based on the available literature, no study compares groups of students using ChatGPT and those who did not, more so in programming. Therefore, the main goal of this study was to examine how ChatGPT affects SHS students'…
Descriptors: Artificial Intelligence, Computer Software, Synchronous Communication, Learning Processes
Munshi, Anabil; Biswas, Gautam; Baker, Ryan; Ocumpaugh, Jaclyn; Hutt, Stephen; Paquette, Luc – Journal of Computer Assisted Learning, 2023
Background: Providing adaptive scaffolds to help learners develop effective self-regulated learning (SRL) behaviours has been an important goal for intelligent learning environments. Adaptive scaffolding is especially important in open-ended learning environments (OELE), where novice learners often face difficulties in completing their learning…
Descriptors: Scaffolding (Teaching Technique), Metacognition, Independent Study, Intelligent Tutoring Systems
Ni, Aohua; Cheung, Alan – Education and Information Technologies, 2023
Previous studies have demonstrated the effectiveness of intelligent tutoring systems (ITS) in facilitating English learning. However, no empirical research has been conducted on secondary students' intention to use ITSs in the language domain. This study proposes an extended technology acceptance model (TAM) to predict secondary students'…
Descriptors: Intelligent Tutoring Systems, English (Second Language), Second Language Learning, Second Language Instruction
Burkhard, Michael; Seufert, Sabine; Cetto, Matthias; Handschuh, Siegfried – International Association for Development of the Information Society, 2022
Educational chatbots promise many benefits for teaching and learning. Although chatbot use cases in this research field are rapidly growing, most studies focus on individual users rather than on collaborative group settings. To address this issue, this paper investigates how chatbot-mediated learning can be designed to foster middle school…
Descriptors: Artificial Intelligence, Teaching Methods, Learning Processes, Web Based Instruction
Gresse Von Wangenheim, Christiane; Da Cruz Alves, Nathalia; Rauber, Marcelo F.; Hauck, Jean C. R.; Yeter, Ibrahim H. – Informatics in Education, 2022
Although Machine Learning (ML) is used already in our daily lives, few are familiar with the technology. This poses new challenges for students to understand ML, its potential, and limitations as well as to empower them to become creators of intelligent solutions. To effectively guide the learning of ML, this article proposes a scoring rubric for…
Descriptors: Performance Based Assessment, Artificial Intelligence, Learning Processes, Scoring Rubrics
Nguyen, Huy; Wang, Yeyu; Stamper, John; McLaren, Bruce M. – International Educational Data Mining Society, 2019
Knowledge components (KCs) define the underlying skill model of intelligent educational software, and they are critical to understanding and improving the efficacy of learning technology. In this research, we show how learning curve analysis is used to fit a KC model--one that was created after use of the learning technology--which can then be…
Descriptors: Middle School Students, Knowledge Representation, Models, Computer Games
Prihar, Ethan; Heffernan, Neil – International Educational Data Mining Society, 2021
Similar content has tremendous utility in classroom and online learning environments. For example, similar content can be used to combat cheating, track students' learning over time, and model students' latent knowledge. These different use cases for similar content all rely on different notions of similarity, which make it difficult to determine…
Descriptors: Computer Software, Middle School Teachers, Mathematics Teachers, College Students
Timms, Michael; DeVelle, Sacha; Lay, Dulce – Australian Journal of Education, 2016
It is well known that learners using intelligent learning environments make different use of the feedback provided by the intelligent learning environment and exhibit different patterns of behaviour. Traditional approaches to measuring such behaviour have focused on observational methods, think-aloud protocols, ratings and log data. More recently,…
Descriptors: Feedback (Response), Learning Processes, Intelligent Tutoring Systems, Models
Jordan, Pamela; Albacete, Patricia; Katz, Sandra – Grantee Submission, 2016
We explore the effectiveness of a simple algorithm for adaptively deciding whether to further decompose a step in a line of reasoning during tutorial dialogue. We compare two versions of a tutorial dialogue system, Rimac: one that always decomposes a step to its simplest sub-steps and one that adaptively decides to decompose a step based on a…
Descriptors: Algorithms, Decision Making, Intelligent Tutoring Systems, Scaffolding (Teaching Technique)
Fang, Ying; Nye, Benjamin; Pavlik, Philip; Xu, Yonghong Jade; Graesser, Arthur; Hu, Xiangen – International Educational Data Mining Society, 2017
Student persistence in online learning environments has typically been studied at the macro-level (e.g., completion of an online course, number of academic terms completed, etc.). The current examines student persistence in an adaptive learning environment, ALEKS (Assessment and LEarning in Knowledge Spaces). Specifically, the study explores the…
Descriptors: Learning Processes, Academic Persistence, Correlation, Academic Achievement
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