This work presents the intelligent tutoring system, EvoLogic, developed to assist students in problems of natural production in propositional logic. EvoLogic has been modeled as a multiagent system composed of three autonomous agents: interface, pedagogical and specialist agents. It supports pedagogical strategies inspired by the theory of…

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…

Emotions play a crucial role in the learning process, yet there is a scarcity of studies examining emotion dynamics in problem-solving with fine-grained data and advanced tools. This study addresses this gap by investigating the emotional trajectories during self-regulated learning (SRL) phases (i.e., forethought, performance, and self-reflection)…

In interactive e-learning environments such as Intelligent Tutoring Systems, pedagogical decisions can be made at different levels of granularity. In this work, we focus on making decisions at "two levels": whole problems vs. single steps and explore three types of granularity: "problem-level only" ("Prob-Only"),…

Predicting student problem-solving strategies is a complex problem but one that can significantly impact automated instruction systems since they can adapt or personalize the system to suit the learner. While for small datasets, learning experts may be able to manually analyze data to infer student strategies, for large datasets, this approach is…

This research suggests a methodology to examine the effectiveness Artificial Intelligence (AI) on the cognitive abilities of college students so that future researchers can utilize this experimental project to focus on how AI-powered Intelligent Tutoring Systems (ITSs) affect learning outcomes. As AI continues to revolutionize all walks of life,…

This paper describes LOGAX, an interactive tutoring tool that gives hints and feedback to a student who stepwise constructs a Hilbert-style axiomatic proof in propositional logic. LOGAX generates proofs to calculate hints and feedback. We compare these generated proofs with expert proofs and student solutions, and conclude that the quality of the…

This paper develops a method for the construction and evaluation of cognitive models to support students in their problem-solving skills during robotics in school, aiming to build a basis for an implementation of a tutoring system in the future. Two Wizard-of-Oz studies were conducted, one in the classroom and one in the lab. Based on the…

This design-based study addresses the issue of how to digitally support students' problem-solving by providing heuristics, in the absence of the teacher. The problem is that, so far, digital tutoring systems lack the ability to diagnose students' needs in open problem situations. Our approach is based on students' ability to self-diagnose and find…

In this article, we leverage ideas from the theory of coevolutionary computation to analyze interactions of students with problems. We introduce the idea of "informatively" easy or hard concepts. Our approach is different from more traditional analyses of problem difficulty such as item analysis in the sense that we consider Pareto…

The present paper builds on the literature that emphasizes the importance of self-regulation for academic learning or self-regulated learning (SRL). SRL research has traditionally focused on count measures of SRL processing events, however, another important measure of SRL is being recognized: time-on-task. The current study captures the influence…

This paper demonstrates that a teachable agent (TA) can play a dual role in an online learning environment (OLE) for learning by teaching--the teachable agent working as a synthetic peer for students to learn by teaching and as an interactive tool for cognitive task analysis when authoring an OLE for learning by teaching. We have developed an OLE…

In this study, we developed a classification system of programming errors based on the historical data of 680,540 programming records collected on the Online Judge platform. The classification system described six types of programming errors (i.e., syntax, logical, type, writing, misunderstanding, and runtime errors) and their connections with…

Intelligent tutoring systems (ITSs) aim to deliver personalized learning support to each learner, aligning with the educational aspiration of many countries, including China. ITSs' personalized support is mainly achieved by providing individual prompts to learners when they encounter difficulties in problem-solving. The guiding principles and…