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Peer reviewed
Download full textFancsali, Stephen E.; Li, Hao; Sandbothe, Michael; Ritter, Steven – International Educational Data Mining Society, 2021
Recent work describes methods for systematic, data-driven improvement to instructional content and calls for diverse teams of learning engineers to implement and evaluate such improvements. Focusing on an approach called "design-loop adaptivity," we consider the problem of how developers might use data to target or prioritize particular…
Descriptors: Instructional Development, Instructional Improvement, Data Use, Educational Technology
Zhang, Mengxue; Wang, Zichao; Baraniuk, Richard; Lan, Andrew – International Educational Data Mining Society, 2021
Feedback on student answers and even during intermediate steps in their solutions to open-ended questions is an important element in math education. Such feedback can help students correct their errors and ultimately lead to improved learning outcomes. Most existing approaches for automated student solution analysis and feedback require manually…
Descriptors: Mathematics Instruction, Teaching Methods, Intelligent Tutoring Systems, Error Patterns
Direct linkShi, Genghu; Wang, Lijia; Zhang, Liang; Shubeck, Keith; Peng, Shun; Hu, Xiangen; Graesser, Arthur C. – Grantee Submission, 2021
Adult learners with low literacy skills compose a highly heterogeneous population in terms of demographic variables, educational backgrounds, knowledge and skills in reading, self-efficacy, motivation etc. They also face various difficulties in consistently attending offline literacy programs, such as unstable worktime, transportation…
Descriptors: Intelligent Tutoring Systems, Adult Literacy, Adult Students, Reading Comprehension
Scandura, Joseph M. – Technology, Instruction, Cognition and Learning, 2017
Adaptive learning has become a dominant theme in settings ranging from academic laboratories to commercial education. Despite tens of millions of dollars invested by governments, universities, the private sector and companies, however, progress has been both costly and limited. No established initiative has attempted to model the processes human…
Descriptors: Intelligent Tutoring Systems, Tutors, Tutorial Programs, Delivery Systems
Peiris, K. Dharini Amitha; Gallupe, R. Brent – Decision Sciences Journal of Innovative Education, 2018
Recommender-driven online learning systems (ROLS) are at the forefront of new computer-based learning. They incorporate machine learning to allow learning-by-doing, generating personalized recommendations in the process. This article describes the evaluations of a new type of online learning systems, ROLS. This evaluation was carried out in three…
Descriptors: Intelligent Tutoring Systems, Computer Science Education, Programming Languages, Conventional Instruction
Danial Hooshyar; Nour El Mawas; Yeongwook Yang – Knowledge Management & E-Learning, 2024
The use of learner modelling approaches is critical for providing adaptive support in educational computer games, with predictive learner modelling being among the key approaches. While adaptive supports have been shown to improve the effectiveness of educational games, improperly customized support can have negative effects on learning outcomes.…
Descriptors: Artificial Intelligence, Course Content, Tests, Scores
Rose E. Wang; Ana T. Ribeiro; Carly D. Robinson; Susanna Loeb; Dorottya Demszky – Annenberg Institute for School Reform at Brown University, 2024
Generative AI, particularly Language Models (LMs), has the potential to transform real-world domains with societal impact, particularly where access to experts is limited. For example, in education, training novice educators with expert guidance is important for effectiveness but expensive, creating significant barriers to improving education…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Tutors, Elementary School Students
Shakila Dada; Cathy Flores; Kirsty Bastable; Kerstin Tönsing; Alecia Samuels; Sourav Mukhopadhyay; Beatrice Isanda; Josephine Ohenewa Bampoe; Unati Stemela-Zali; Saira Banu Karim; Legini Moodley; Adele May; Refilwe Morwane; Katherine Smith; Rahab Mothapo; Mavis Mohuba; Maureen Casey; Zakiyya Laher; Nothando Mtungwa; Robyn Moore – International Journal of Language & Communication Disorders, 2024
Background: Over 8 million children with disabilities live in Africa and are candidates for augmentative and alternative communication (AAC), yet formal training for team members, such as speech-language therapists and special education teachers, is extremely limited. Only one university on the continent provides postgraduate degrees in AAC, and…
Descriptors: Intelligent Tutoring Systems, Augmentative and Alternative Communication, Curriculum Development, Technology Uses in Education
Sue-Jin Lee – CATESOL Journal, 2024
The emergence of AI writing assistants has raised concerns about their potential impact on language diversity, preservation, and education. This paper examines the capabilities and limitations of AI writing assistants in generating dialectic text in response to academic and professional writing prompts. The study uses a concordance tool to conduct…
Descriptors: Writing Assignments, Artificial Intelligence, Computer Software, Intelligent Tutoring Systems
Alaa Aladini; Rashed Mahmud; Abeer Ahmed Hammad Ali – Language Testing in Asia, 2024
In recent years, Intelligent Computer-Assisted Language Assessment (ICALA) has emerged as a transformative approach in language education, leveraging technology to enhance student assessment and learning processes. Despite its growing importance, there is a scarcity of research investigating the connections among needs satisfaction, teacher…
Descriptors: Intelligent Tutoring Systems, Second Language Learning, Evaluation Methods, English (Second Language)
Koji Osawa – RELC Journal: A Journal of Language Teaching and Research, 2024
With the recent rapid technological advance, second language (L2) educators have increasingly incorporated technologies into writing pedagogy. Two of the major technologies to promote L2 writing are e-portfolios and automated written corrective feedback (AWCF). Notably, feedback-rich portfolios facilitate L2 learners' self-regulation and writing…
Descriptors: Artificial Intelligence, Computer Software, Writing Instruction, Writing Evaluation
Almut Ketzer-Nöltge, Editor; Nicola Würffel, Editor – Peter Lang Publishing Group, 2024
For over four decades, textbooks have been enhanced with digital components, and today, it is almost impossible to find a textbook that does not contain any. Does this mean that textbooks have been fully digitalized and that we have reached a point where the integration of digital media into textbooks is the norm? Since there is no clear consensus…
Descriptors: Textbooks, Electronic Books, Computer Uses in Education, Educational History
Jaylin Lowe; Charlotte Z. Mann; Jiaying Wang; Adam Sales; Johann A. Gagnon-Bartsch – Grantee Submission, 2024
Recent methods have sought to improve precision in randomized controlled trials (RCTs) by utilizing data from large observational datasets for covariate adjustment. For example, consider an RCT aimed at evaluating a new algebra curriculum, in which a few dozen schools are randomly assigned to treatment (new curriculum) or control (standard…
Descriptors: Randomized Controlled Trials, Middle School Mathematics, Middle School Students, Middle Schools
Kole A. Norberg; Husni Almoubayyed; Logan De Ley; April Murphy; Kyle Weldon; Steve Ritter – Grantee Submission, 2024
Large language models (LLMs) offer an opportunity to make large-scale changes to educational content that would otherwise be too costly to implement. The work here highlights how LLMs (in particular GPT-4) can be prompted to revise educational math content ready for large scale deployment in real-world learning environments. We tested the ability…
Descriptors: Artificial Intelligence, Computer Software, Computational Linguistics, Educational Change
Loksa, Dastyni; Margulieux, Lauren; Becker, Brett A.; Craig, Michelle; Denny, Paul; Pettit, Raymond; Prather, James – ACM Transactions on Computing Education, 2022
Metacognition and self-regulation are important skills for successful learning and have been discussed and researched extensively in the general education literature for several decades. More recently, there has been growing interest in understanding how metacognitive and self-regulatory skills contribute to student success in the context of…
Descriptors: Metacognition, Programming, Computer Science Education, Learning Processes
