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Large Language Models and Intelligent Tutoring Systems: Conflicting Paradigms and Possible Solutions

Punya Mishra; Danielle S. McNamara; Gregory Goodwin; Diego Zapata-Rivera – Grantee Submission, 2025
The advent of Large Language Models (LLMs) has fundamentally disrupted our thinking about educational technology. Their ability to engage in natural dialogue, provide contextually relevant responses, and adapt to learner needs has led many to envision them as powerful tools for personalized learning. This emergence raises important questions about…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Technology Uses in Education, Educational Technology
Michelle Banawan; Reese Butterfuss; Karen S. Taylor; Katerina Christhilf; Claire Hsu; Connor O'Loughlin; Laura K. Allen; Rod D. Roscoe; Danielle S. McNamara – Grantee Submission, 2023
Writing is essential for success in academics and everyday tasks, but the development of writing skills depends on consistent access to high-quality instruction, extended practice, and personalized feedback. To address these demands and meet students' needs, educators and researchers have turned to technology-based writing tools. Ideally, these…
Descriptors: Intelligent Tutoring Systems, Writing (Composition), Technology Uses in Education, Feedback (Response)
Janice D. Gobert; Haiying Li; Rachel Dickler; Christine Lott – Grantee Submission, 2024
An intelligent tutoring system (ITS, henceforth) is currently defined as a computer system that delivers personalized instruction to students by using computational techniques to evaluate the learner in a variety of ways, including (but not limited to) their prior knowledge, competency/skill levels, motivation, and affective states. ITSs are…
Descriptors: Artificial Intelligence, Scaffolding (Teaching Technique), Computer Science Education, Teaching Methods
Renu Balyan; Tracy Arner; Tong Li; Ellen Orcutt; Reese Butterfuss; Panayiota Kendeou; Danielle McNamara – Grantee Submission, 2022
Speech technology (automated speech recognition -- ASR and text-to-speech) offers great promise in the field of automated literacy and reading tutors for children. Students in third and fourth grades struggle with generating longer strings of text on a QWERTY keyboard because they still "hunt and peck" for AQ1 the letters and symbols…
Descriptors: Assistive Technology, Technology Integration, Intelligent Tutoring Systems, Automation

Amy Adair – Grantee Submission, 2024
Developing models, using mathematics, and constructing explanations are three practices essential for science inquiry learning according to education reform efforts, such as the Next Generation Science Standards (NGSS Lead States, 2013). However, students struggle with these intersecting practices, especially when developing and interpreting…
Descriptors: Artificial Intelligence, Computer Software, Technology Integration, Scaffolding (Teaching Technique)
Mitten, Carolyn; Collier, Zachary K.; Leite, Walter L. – Grantee Submission, 2021
Adoption of online resources to support instruction and student performance has amplified with technological advances and increased standards for mathematics education. Because teachers play a critical role in the adoption of technology, analysis of data pertaining to how and why teachers utilize online resources is needed to optimize the design…
Descriptors: Teaching Methods, Educational Resources, Mathematics Instruction, Teacher Role
Kenneth Holstein; Bruce M. McLaren; Vincent Aleven – Grantee Submission, 2017
Intelligent tutoring systems (ITSs) are commonly designed to enhance student learning. However, they are not typically designed to meet the needs of teachers who use them in their classrooms. ITSs generate a wealth of analytics about student learning and behavior, opening a rich design space for real-time teacher support tools such as dashboards.…
Descriptors: Intelligent Tutoring Systems, Technology Integration, Educational Technology, Middle School Teachers
Snow, Erica L.; Jacovina, Matthew E.; Jackson, G. Tanner; McNamara, Danielle S. – Grantee Submission, 2016
This chapter provides an overview of the Interactive Strategy Tutor for Active Reading and Thinking-2 (iSTART-2). iSTART-2 is a game-based tutoring system designed to improve students' reading comprehension skills. It does so by providing them with instruction on how to self-explain using comprehension strategies. In this chapter, we first discuss…
Descriptors: Reading Comprehension, Reading Strategies, Reading Instruction, Educational Games