A longstanding goal of learner modeling and educational data mining is to improve the domain model of knowledge that is used to make inferences about learning and performance. In this report we present a tool for finding domain models that is built into an existing modeling framework, logistic knowledge tracing (LKT). LKT allows the flexible…

Knowledge tracing is the task of modeling each student's mastery of knowledge concepts (KCs) as (s)he engages with a sequence of learning activities. Each student's knowledge is modeled by estimating the performance of the student on the learning activities. It is an important research area for providing a personalized learning platform to…

Instruction in many STEM domains heavily relies on visual representations, such as graphs, figures, and diagrams. However, students who lack representational competencies do not benefit from these visual representations. Therefore, students must learn not only content knowledge but also representational competencies. Further, as learning…

Knowledge tracing (KT) models are a popular approach for predicting students' future performance at practice problems using their prior attempts. Though many innovations have been made in KT, most models including the state-of-the-art Deep KT (DKT) mainly leverage each student's response either as correct or incorrect, ignoring its content. In…

One of the essential problems, in educational data mining, is to predict students' performance on future learning materials, such as problems, assignments, and quizzes. Pioneer algorithms for predicting student performance mostly rely on two sources of information: students' past performance, and learning materials' domain knowledge model. The…

This paper elaborates on the teacher change process described in the Interconnected Model of Teacher Professional Growth by providing empirical evidence from a study that investigated the knowledge construction process of three mathematics teachers in Melbourne, Australia. Through a research design that aimed to facilitate teacher reflection…

Statistical terms are used in everyday language and, at times, used in non-statistical ways. It is often assumed students understand statistical terms because of their common use; however, research into their understanding of specific statistical terms is scant. This report focuses on 58 Year 3 students' responses to the basic question, "What…

The study used activity systems analysis to characterize the processes, dynamics, and tensions in the social practices developed by a class of academic low-achievers in a knowledge-building environment augmented by analytics-supported reflective assessment. A class of 37 Grade 9 low-achievers and an experienced teacher participated this study.…

This article demonstrates how an adaptive instructional design for a physics module can be realized in a standard learning management system. We implemented a didactic design with physics-specific online exercises that were accompanied by either detailed or non-detailed instructions, depending on the results of the previous task (or a prior…

Learning curves have proven to be a useful tool for understanding how a student learns a given skill as they progress through a curriculum. A learning curve for a given Knowledge Component (KC) is a plot of some measure of competence as a function of the number of opportunities the student has had to apply that KC. Consider the case where each…

Using Korthagen's (2010) three-level teacher learning model, I conducted a qualitative study addressing a central question: What factors contribute to preservice teacher development of knowledge about teaching during field experiences? Data were collected through interviews, supplemented by observation videos and document analysis. The findings…

We show that student learning can be accurately modeled using a mixture of learning curves, each of which specifies error probability as a function of time. This approach generalizes Knowledge Tracing [7], which can be viewed as a mixture model in which the learning curves are step functions. We show that this generality yields order-of-magnitude…

This paper presents a study carried out in a nursery and primary school in order to ascertain the level of self-assessment undertaken by teachers with respect to their educational processes using the "ACADI" instrument, "School-based self-assessment of diversity awareness from an inclusive approach." The objective was to…

Over the last couple of decades, there have been a large variety of approaches towards modeling student knowledge within intelligent tutoring systems. With the booming development of deep learning and large-scale artificial neural networks, there have been empirical successes in a number of machine learning and data mining applications, including…

Additive Factors Model (AFM) and Performance Factors Analysis (PFA) are two popular models of student learning that employ logistic regression to estimate parameters and predict performance. This is in contrast to Bayesian Knowledge Tracing (BKT) which uses a Hidden Markov Model formalism. While all three models tend to make similar predictions,…