Learning analytics is a research topic that is gaining increasing popularity in recent time. It analyzes the learning data available in order to make aware or improvise the process itself and/or the outcome such as student performance. In this survey paper, we look at the recent research work that has been conducted around learning analytics, framework and integrated models, and application of ...

We examine correlations between dialogue behaviors and learning in tutoring, using two corpora of spoken tutoring dialogues: a human-human corpus and a human-computer corpus. To formalize the notion of dialogue behavior, we manually annotate our data using a tagset of student and tutor dialogue acts relative to the tutoring domain. A unigram analysis of our annotated data shows that student lea...

The primary measure used to determine relative effectiveness of in-class activities has been student performance on pre/posttests. However, in today's active-learning classrooms, learning is a social activity, requiring students to interact and learn from their peers. To develop effective active-learning exercises that engage students, it is important to gain a more holistic view of the student...

Abstract The research focused on the student (learning) outcomes captured upon completion of mathematics teaching is end goal presage-process–product research. Student learning are generally agreed as representing ultimate purpose and final criterion which any assessment ‘good’ based. Traditionally, seen changes in students’ understanding mathematics, here measured a school-based or external ev...

Abstract This chapter provides an overview of different conceptualizations student engagement with mathematical ideas in studies that occur mathematics classrooms and teaching experiment environments, the types quality learning activities result desired outcomes. Over last three decades, curriculum initiatives have called for development behaviors dispositions (i.e., competencies, processes, pr...

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We describe an approach to student modelling where the student can delve into the student model. We describe how this can support learning on several levels. It serves as a basis for planning learning goals, improving communication between the teaching system and the learner, and as an aid to reflection about learning. There is a growing group of researchers working with accessible and understa...

This paper describes an application of established machine learning principles to student modelling. Unlike previous machine learning based approaches to student modelling, the new approach is based on attributevalue machine learning. In contrast to many previous approaches it is not necessary for the lesson author to identify all forms of error that may be detected. Rather, the lesson author n...