Many studies have shown that visual representations can enhance student understanding of STEM concepts. However, prior research suggests that visual representations alone are not necessarily effective across a broad range of students. To address this problem, we created a novel, scaffolded form of diagrammatic self-explanation in which students…

This dissertation presents various machine learning applications for predicting different cognitive states of students while they are using a vocabulary tutoring system, DSCoVAR. We conduct four studies, each of which includes a comprehensive analysis of behavioral and linguistic data and provides data-driven evidence for designing personalized…

This article presents a new conceptualization of 'shadow curriculum', one component of the worldwide phenomenon of shadow education, i.e. learning outside of school. Traditional conceptions of curriculum are not applicable to shadow education, and so this article begins by exploring how shadow education practices qualify as a new focus of…

Prior research has shown that, under certain conditions, Human-Agent (H-A) alignment exists to a stronger degree than that found in Human-Human (H-H) communication. In an H-H Second Language (L2) setting, evidence of alignment has been linked to learning and teaching strategy. We present a novel analysis of H-A and H-H L2 learner dialogues using…

In this paper we show how we can utilize human-guided machine learning techniques coupled with a learning science practitioner interface (DataShop) to identify potential improvements to existing educational technology. Specifically, we provide an interface for the classification of underlying Knowledge Components (KCs) to better model student…

In this paper we review the contribution of our original work titled "Simulating Instructional Roles Through Pedagogical Agents" published in the "International Journal of Artificial Intelligence and Education" (Baylor and Kim in "Computers and Human Behavior," 25(2), 450-457, 2005). Our original work operationalized…

Today's technology-enabled learning environments are becoming quite different from those of a few years ago, with the increased processing power as well as a wider range of educational tools. This situation produces more data, which can be fed back into the learning process. Open learner models have already been investigated as tools to promote…

The aim of this article is to propose a method for development of concept map in web-based environment for identifying concepts a student is deficient in after learning using traditional methods. Direct Hashing and Pruning algorithm was used to construct concept map. Redundancies within the concept map were removed to generate a learning sequence.…

Data collected from online learning and tutoring systems for individual students showed strong autocorrelation or dependence because of content connection, knowledge-based dependency, or persistence of learning behavior. When the response data show little dependence or negative autocorrelations for individual students, it is suspected that…

Bayesian Knowledge Tracing (BKT) is a commonly used approach for student modeling, and Long Short Term Memory (LSTM) is a versatile model that can be applied to a wide range of tasks, such as language translation. In this work, we directly compared three models: BKT, its variant Intervention-BKT (IBKT), and LSTM, on two types of student modeling…

The future of education is human expertise and artificial intelligence working in conjunction, a revolution that will change the education as we know it. The Intelligent Tutoring System is a key component of this future. A quantitative measurement of efficacies of practice to heterogeneous learners is the cornerstone of building an effective…

Online planning of good teaching sequences has the potential to provide a truly personalized teaching experience with a huge impact on the motivation and learning of students. In this work we compare two main approaches to achieve such a goal, POMDPs that can find an optimal long-term path, and Multi-armed bandits that optimize policies locally…

We explore the effectiveness of a simple algorithm for adaptively deciding whether to further decompose a step in a line of reasoning during tutorial dialogue. We compare two versions of a tutorial dialogue system, Rimac: one that always decomposes a step to its simplest sub-steps and one that adaptively decides to decompose a step based on a…

This paper deals with a problem of digital competence acquisition and certification. In order to overcome the problem of still inadequate number of digitally competent students and the tools that merely focus on skills acquisition, this paper proposes the CRISS platform which is a unique cloud-based digital learning solution, based on the most…

Classroom experiments that evaluate the effectiveness of educational technologies do not typically examine the effects of classroom contextual variables (e.g., out-of-software help-giving and external distractions). Yet these variables may influence students' instructional outcomes. In this paper, we introduce the Spatial Classroom Log Explorer…