This paper presents a tool for creating student models in logistic regression. Creating student models has typically been done by expert selection of the appropriate terms, beginning with models as simple as IRT or AFM but more recently with highly complex models like BestLR. While alternative methods exist to select the appropriate predictors for…

This paper presents a tool for creating student models in logistic regression. Creating student models has typically been done by expert selection of the appropriate terms, beginning with models as simple as IRT or AFM but more recently with highly complex models like BestLR. While alternative methods exist to select the appropriate predictors for…

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…

Automated Essay Scoring (AES) tools aim to improve the efficiency and consistency of essay scoring by using machine learning algorithms. In the existing research work on this topic, most researchers agree that human-automated score agreement remains the benchmark for assessing the accuracy of machine-generated scores. To measure the performance of…

Automatic short answer grading is an important research direction in the exploration of how to use artificial intelligence (AI)-based tools to improve education. Current state-of-the-art approaches use neural language models to create vectorized representations of students responses, followed by classifiers to predict the score. However, these…

This paper introduces web viewers for educational VR contents. Recently, many types of VR goggles have been released as commercial products and many entertainment applications for them have been created. However, educational VR contents have been created so far are not so many because the creation of VR contents is time consuming task. We need to…

The automatic code generation is the process of generating source code snippets from a program, i.e., code for generating code. Its importance lies in facilitating software development, particularly important is helping in the implementation of software designs such as engineering diagrams, in such a case, automatic code generation copes with the…

Randomized A/B tests within online learning platforms enable us to draw unbiased causal estimators. However, precise estimates of treatment effects can be challenging due to minimal participation, resulting in underpowered A/B tests. Recent advancements indicate that leveraging auxiliary information from detailed logs and employing design-based…

Automated scoring of student responses to open-ended questions, including short-answer questions, has great potential to scale to a large number of responses. Recent approaches for automated scoring rely on supervised learning, i.e., training classifiers or fine-tuning language models on a small number of responses with human-provided score…

This paper discusses the "Just Keep Solving" apps that are designed based on deliberate practice model for developing mathematical skills. Features of deliberate practice include well-defined goals involving areas of weakness as determined by a knowledgeable other such as a teacher. The integration of game design features provides a…

Recent research seeks to develop more comprehensive learner models for adaptive learning software. For example, models of reading comprehension built using data from students' use of adaptive instructional software for mathematics have recently been developed. These models aim to deliver experiences that consider factors related to learning beyond…

In studies that generate course recommendations based on similarity, the typical enrollment data used for model training consists only of one record per student-course pair. In this study, we explore and quantify the additional signal present in course transaction data, which includes a more granular account of student administrative interactions…

Text summarization is an effective reading comprehension strategy. However, summary evaluation is complex and must account for various factors including the summary and the reference text. This study examines a corpus of approximately 3,000 summaries based on 87 reference texts, with each summary being manually scored on a 4-point Likert scale.…

Automatically identifying struggling students learning to program can assist teachers in providing timely and focused help. This work presents a new deep-learning language model for predicting "bug-fix-time", the expected duration between when a software bug occurs and the time it will be fixed by the student. Such information can guide…

What can eye movements reveal about reading, a complex skill ubiquitous in everyday life? Research suggests that gaze can reflect short-term comprehension for facts, but it is unknown whether it can measure long-term, deep comprehension. We tracked gaze while 147 participants read long, connected, informative texts and completed assessments of…