Arnon Hershkovitz

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Both gaming the system (taking advantage of the system’s feedback and help to succeed in the tutor without learning the material) and being off-task (engaging in behavior that does not involve the system or the learning task) have been previously shown to be associated with poorer learning. In this paper we investigate two hypotheses about the mechanisms(More)
This study illustrates the potential of applying Web usage mining the analysis of Web log files in educational research. It consists of two sub-studies and focuses on two types of analysis, both related to the whole learning process: investigating one learner's activity in order to learn about her or his learning process, and examining the activity of a(More)
Affect has been hypothesized to play a significant role in triggering engagement/disengagement during learning. In this paper, we study the interrelationships between students’ affect (boredom, confusion, frustration, engaged concentration) and their engaged and disengaged behaviors (off-task, on-task solitary, on-task conversation, gaming the system). We(More)
In recent years, student modeling has been extended from predicting future student performance on the skills being learned in a tutor to predicting a student’s preparation for future learning (PFL). These methods have predicted PFL from a combination of features of students’ behaviors related to meta-cognition. However, these models have achieved only(More)
In this paper, we study the relationship between goal orientation within a science inquiry learning environment for middle school students and carelessness, i.e., not demonstrating an inquiry skill despite knowing it. Carelessness is measured based on a machine-learned model. We find, surprisingly, that carelessness is higher for students with strong(More)
Work in recent years has shown that a student’s goals, attitudes, and beliefs towards learning impact their level of engagement during learning, and that engagement during learning plays a key role in learning outcomes. In this paper, we investigate the mechanisms through which a student’s goals, attitudes, and beliefs impact the student’s engaged and(More)
We present a new method for analyzing a student’s learning over time, for a specific skill: analysis of the graph of the student’s moment-by-moment learning over time. Moment-bymoment learning is calculated using a data-mined model which assesses the probability that a student learned a skill or concept at a specific time during learning (Baker, Goldstein,(More)
The purpose of this study is to identify and examine learning processes, based on data extracted from log files, which document the learners' action within an online learning environment. For this purpose, log files of four elementary school students, studied with a science Web-based module, were examined and analysed. A Learnogram graphical representation(More)