Intelligent tutoring system (ITS) provides learners with step-by-step problem-solving support through scaffolding. Most ITSs have been developed in the USA and incorporate American instructional strategies. How do non-American students perceive and use ITS with different native problem-solving strategies? The present study compares Stoich Tutor,…

Bayesian Knowledge Tracing (BKT) is a well-established model for formative assessment, with optimization typically using expectation maximization, conjugate gradient descent, or brute force search. However, one of the flaws of existing optimization techniques for BKT models is convergence to undesirable local minima that negatively impact…

Solving a math word problem (MWP) requires understanding the mathematical components of the problem and an ability to decode the text. For some students, lower reading comprehension skills may make engagement with the mathematical content more difficult. Readability formulas (e.g., Flesch Reading Ease) are frequently used to assess reading…

Large Language Models (LLMs) hold promise as dynamic instructional aids. Yet, it remains unclear whether LLMs can replicate the adaptivity of intelligent tutoring systems (ITS)--where student knowledge and pedagogical strategies are explicitly modeled. We propose a prompt variation framework to assess LLM-generated instructional moves' adaptivity…

Think-aloud protocols are a standard method to study self-regulated learning (SRL) during learning by problem-solving. Advances in automated transcription and large language models (LLMs) have automated the transcription and labeling of SRL in these protocols, reducing manual effort. However, while effective in many emerging applications, previous…

Students' effort and emotions are important contributors to math learning. In a recent study evaluating the efficacy of MathSpring, a scalable web-based intelligent tutoring system that provides students with personalized math problems and affective support, system usage data were collected for 804 U.S. 10-12-year-olds. To understand the patterns…

This article presents a meta-analysis of the existing literature using Stata 18.0, focusing on the effects of ITSs on learning attitudes, knowledge acquisition, learner motivation, performance, problem-solving skills, test scores, and educational outcomes across different countries and educational levels (k = 30, g = 0.86). The findings suggest…

Purpose: The purpose of this study is to develop an intelligent tutoring system (ITS) for programming learning based on information tutoring feedback (ITF) to provide real-time guidance and feedback to self-directed learners during programming problem-solving and to improve learners' computational thinking. Design/methodology/approach: By…

Math anxiety has been found to negatively correlate with math achievement, affecting students' choices to take fewer math classes and avoid math educational opportunities. Educational technology tools can ameliorate some of the negative effects of math anxiety. We examined students' math anxiety, effort in an educational technology platform, and…

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…

Artificial Intelligence (AI) integration in andragogical education offers significant enhancements to the learning experience for adult learners. By utilizing AI-powered platforms, instructors can provide personalized learning paths that adapt to the unique needs, interests, and goals of each individual. These systems can analyze performance data…