Educational Data Mining is an emerging discipline which seeks to develop methods to explore large amounts of data from educational settings, in order to understand students' behavior, interests and results in a better way. In recent years there have been various works related to this specialty and multiple data mining techniques derived from this…

This paper presents a systematic literature review of the state-of-the-art of research on learning dashboards in the fields of Learning Analytics and Educational Data Mining. Research on learning dashboards aims to identify what data is meaningful to different stakeholders and how data can be presented to support sense-making processes. Learning…

The number of e-learning platforms and blended learning environments is continuously increasing and has sparked a lot of research around improvements of educational processes. Here, the ability to accurately predict student performance plays a vital role. Previous studies commonly focused on the construction of predictors tailored to a formal…

This paper presents the dataset collected from student interactions with INQPRO, a computer-based scientific inquiry learning environment. The dataset contains records of 100 students and is divided into two portions. The first portion comprises (1) "raw log data", capturing the student's name, interfaces visited, the interface…

Student models for adaptive systems may not model collaborative learning optimally. Past research has either focused on modeling individual learning or for collaboration, has focused on group dynamics or group processes without predicting learning. In the current paper, we adjust the Additive Factors Model (AFM), a standard logistic regression…

Student models for adaptive systems may not model collaborative learning optimally. Past research has either focused on modeling individual learning or for collaboration, has focused on group dynamics or group processes without predicting learning. In the current paper, we adjust the Additive Factors Model (AFM), a standard logistic regression…

This study lies at an intersection between advancing educational data mining methods for detecting students' knowledge-in-action and the broader question of how conceptual and mathematical forms of knowing interact in exploring complex chemical systems. More specifically, it investigates students' inquiry actions in three computer-based models of…

The study presents a phenomenologically based research procedure, whose intent is to examine people's school experience and the meaning they ascribe to "school." Participants in this investigative endeavor are instructed to sketch an "ideal school," present their plan in a visual-schematic manner, and provide an oral and written description of…

Functional roles may explain the learning performance of groups. Detecting a functional role is critical for promoting group learning performance in computer-supported collaborative learning environments. However, it is not easy for teachers to identify the functional roles played by students in a web-based learning group, or the relationship…

Learning environments aim to deliver efficacious instruction, but rarely take into consideration the motivational factors involved in the learning process. However, motivational aspects like engagement play an important role in effective learning-engaged learners gain more. E-Learning systems could be improved by tracking students' disengagement…