Attendance rate is an important indicator of students' study motivation, behavior and Psychological status; however, the heterogeneous nature of student attendance rates due to the course registration difference or the online/offline difference in a blended learning environment makes it challenging to compare attendance rates. In this paper, we…

A student's ability to regulate their thoughts, emotions and behaviors in the face of temptation is linked to their task specific motivational goals and dispositions. Behavioral tasks are designed to strain a targeted resource to differentiate individuals through measures of their performance. In this paper, we explore how student behavior on…

We propose a new model for learning that relates video watching behavior and engagement to quiz performance. In our model, a learner's knowledge gain from watching a lecture video is treated as proportional to their latent engagement level, and the learner's engagement is in turn dictated by a set of behavioral features we propose that quantify…

Behavioral records collected through course assessments, peer assignments, and programming assignments in Massive Open Online Courses (MOOCs) provide multiple views about a student's study style. Study behavior is correlated with whether or not the student can get a certificate or drop out from a course. It is of predominant importance to identify…

Peer grading is widely used in MOOCs and in standard university settings. The quality of grades obtained via peer grading is essential for the educational process. In this work, we study the factors that influence errors in peer grading. We analyze 288 assignments with 25,633 submissions and 113,169 reviews conducted with CrowdGrader, a web based…

Identifying at-risk students at an early stage is a challenging task for colleges and universities. In this paper, we use students' oncampus network traffic volume to construct several useful features in predicting their first semester GPA. In particular, we build proxies for their attendance, class engagement, and out-of-class study hours based…

In this paper, we investigate the relationship between students' learning gains and their compliance with prompts fostering self-regulated learning (SRL) during interaction with MetaTutor, a hypermedia-based intelligent tutoring systems (ITS). When possible, we evaluate compliance from student explicit answers on whether they want to follow the…

Effective mining of data from online submission systems offers the potential to improve educational outcomes by identifying student habits and behaviours and their relationship with levels of achievement. In particular, it may assist in identifying students at risk of performing poorly, allowing for early intervention. In this paper we investigate…

Student login data is a key resource for gaining insight into their learning experience. However, the scale and the complexity of this data necessitate a thorough exploration to identify potential actionable insights, thus rendering it less valuable compared to student achievement data. To compensate for the underestimation of login data…

This paper reports on an analyis of data from a novel "Peer Instruction" application, named DALITE. The Peer Instruction paradigm is well suited to take advantage of peer-input in web-based learning environments. DALITE implements an asynchronous instantiation of peer instruction: after submitting their answer to a multiple-choice…

The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…