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…

When students learn skills to solve problems by teaching others, they often need to receive scaffolding to benefit from learning by teaching. To facilitate learning by teaching (aka tutor learning), two types of scaffolding have been commonly studied--the scaffolding on how to teach (to induce appropriate teaching activities) and the one on how to…

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…

Artificial Intelligence (AI) permeates every aspect of our daily lives and is no longer a subject reserved for a select few in higher education but is essential knowledge that our youth need for the future. Much is unknown about the level of AI knowledge that is age and developmentally appropriate for high school, let alone about how to teach AI…

Collaborative Problem-Solving Skills (CPS) have become increasingly important. Research into the development of CPS is still scarce, but there are several approaches that may be useful for its development. Specifically, providing feedback in collaborative contexts is key. In this paper, we study and develop a feedback system that uses Automated…

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"),…

Intelligent tutoring systems (ITS) have been shown to be highly effective at promoting learning as compared to other computer-based instructional approaches. However, many ITS rely heavily on expert design and hand-crafted rules. This makes them difficult to build and transfer across domains and limits their potential efficacy. In this paper, we…

Research has shown assistance can provide many benefits to novices lacking the mental models needed for problem solving in a new domain. However, varying approaches to assistance, such as subgoals and next-step hints, have been implemented with mixed results. Next-Step hints are common in data-driven tutors due to their straightforward generation…

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…

When students are first learning to program, they not only have to learn to write programs, but also how to trace them. Code tracing involves stepping through a program step-by-step, which helps to predict the output of the program and identify bugs. Students routinely struggle with this activity, as evidenced by prior work and our own experiences…

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…

Jim Greer and his colleagues argued that student modelling is essential to provide adaptive instruction in tutoring systems and showed that effective modelling is possible, despite being enormously challenging. Student modelling plays a prominent role in many intelligent tutoring systems (ITSs) that address problem-solving domains. However,…

The aim of this paper is to survey recent research publications that use Soft Computing methods to answer education-related problems based on the analysis of educational data 'mined' mainly from interactive/e-learning systems. Such systems are known to generate and store large volumes of data that can be exploited to assess the learner, the system…

Learning involves a substantial amount of cognitive, social and emotional states. Therefore, recognizing and understanding these states in the context of learning is key in designing informed interventions and addressing the needs of the individual student to provide personalized education. In this paper, we explore the automatic detection of…

This research is focused on how to support students' acquisition of program construction skills through worked examples. Although examples have been consistently proven to be valuable for student's learning, the learning technology for computer science education lacks program construction examples with interactive elements that could engage…