Reading comprehension is essential for both knowledge acquisition and memory reinforcement. Automated modeling of the comprehension process provides insights into the efficacy of specific texts as learning tools. This paper introduces an improved version of the Automated Model of Comprehension, version 3.0 (AMoC v3.0). AMoC v3.0 is based on two…

Over the past decade, low graduation and retention rates have plagued higher education institutions. To help students graduate on time and achieve optimal learning outcomes, many institutions provide advising services supported by educational technologies. Accurate grade prediction is an integral part of these services such as degree planning…

Computational models of learning can be powerful tools to test educational technologies, automate the authoring of instructional software, and advance theories of learning. These mechanistic models of learning, which instantiate computational theories of the learning process, are capable of making predictions about learners' performance in…

Reading comprehension is key to knowledge acquisition and to reinforcing memory for previous information. While reading, a mental representation is constructed in the reader's mind. The mental model comprises the words in the text, the relations between the words, and inferences linking to concepts in prior knowledge. The automated model of…

The purpose of this paper is to provide a coherent framework to present the relationship between individual differences and web-based learning. Two individual difference factors have been identified for investigation within the present paper: Cognitive style and prior knowledge. The importance of individual differences is reviewed and previous…

Recent years have seen a growing interest in block-based programming environments for computer science education. While these environments hold significant potential for novice programmers, they lack the adaptive support necessary to accommodate students exhibiting a wide range of initial capabilities and dispositions toward computing. A promising…

Intelligent behavior of adaptive educational systems is based on student models. Most research in student modeling focuses on student learning (acquisition of skills). We focus on prior knowledge, which gets much less attention in modeling and yet can be highly varied and have important consequences for the use of educational systems. We describe…

Language skills are the ultimate 21st century social skill, linked to creativity, problem solving, and the ability to effectively communicate. Knowledge of teachers' beliefs is central to understanding teachers' decision-making in the classroom. In an interconnected and globalized world, foreign language is a global competency, and multilingualism…

Within the context of complex cognitive processing and educational interventions, Woolfolk (2016) makes reference to problem solving acquisition, problem solving retention, and problem solving transfer. In each of the aforementioned types of problem solving activities, problem identification and problem representation (reflecting procedural…

In this paper, we propose a computational approach to model the Zone of Proximal Development (ZPD) using predicted probabilities of correctness and engaging students in reflective dialogue. To that end, we employ a predictive model that uses a linear function of a variety of parameters, including difficulty and student knowledge and we analyze the…

In this paper, we propose a computational approach to modeling the Zone of Proximal Development of students who learn using a natural language tutoring system for physics. We employ a student model that predicts students' performance based on their prior knowledge and their activity when using a dialogue tutor to practice with conceptual,…

While Educational Data Mining research has traditionally emphasized the practical aspects of learner modeling, such as predictive modeling, estimating students knowledge, and informing adaptive instruction, in the current study, we argue that Educational Data Mining can also be used to test and improve our fundamental theories of human learning.…

This research targets children's informal strategies and knowledge of fractions by examining their ability to create, interpret, and connect representations in doing and communicating mathematics when solving fractions tasks. Our research group followed a constant comparative method to analyze clinical interviews of children in grades 2-6 solving…

Research in Educational Data Mining could benefit from greater efforts to ensure that models yield reliable, valid, and interpretable parameter estimates. These efforts have especially been lacking for individualized student-parameter models. We collected two datasets from a sizable student population with excellent "depth" -- that is,…

This report shares the findings and lessons learned from an investigation into the economics of disaggregated models for assessing and accrediting informal learners undertaking post secondary education. It presents some key economic and governance challenges for universities to consider in implementing OER assessment and accreditation policies. It…