The learning analytics community has matured significantly over the past few years as a middle space where technology and pedagogy combine to support learning experiences. To continue to grow and connect these perspectives, research needs to move beyond the level of basic support actions. This means exploring the use of data to prove richer forms of actions, such as personalized feedback, or hybrid approaches where instructors interpret the outputs of algorithms and select an appropriate course of action. This paper proposes the following three contributions to connect data extracted from the learning experience with such personalized student support actions: 1) a student-instructor centred conceptual model connecting a representation of the student information with a basic set of rules created by instructors to deploy Personalized Learning Support Actions (PLSAs); 2) a software architecture based on this model with six categories of functional blocks to deploy the PLSAs; and 3) a description of the implementation of this architecture as an open-source platform to promote the adoption and exploration of this area. Notes for Practice• The report draws on research findings related to the effect of personalized feedback on student satisfaction and academic performance (Pardo, Jovanović, Dawson, Gašević, & Mirriahi, 2018).• The main contribution is the description of the design and implementation of an open source platform for researchers and practitioners to connect data with personalized learning support actions.• The area of learning analytics needs tools such as the one described in this document to serve as a vehicle to exchange insights among researchers and practitioners.• This is an example of the note for practice and research

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Case studies of teachers' experiences adopting a student-and teacher-centred learning analytics platform at three Australian universities

courses (MOOCs). Although there are a variety of types of videos used for educational purposes, lecture videos are the most widely adopted. Furthermore, with recent advances in video streaming technologies, learners' digital footprints when accessing videos can collection, measurement, and analysis of such data for the purposes of understanding how learners use videos can be referred to as video analytics. Coupled with more traditional data collection methods, such as interviews or surveys, and performance data to obtain a holistic view of how and why learners engage and learn with videos, video analytics can help inform course design and teaching practice. In this chapter, we provide an overview of videos integrated in the curriculum including an introduction to multimedia learning and discuss data mining approaches for investigating learner use, engagement with, and learning with videos, and provide suggestions for future directions.

Purpose -The purpose of this paper is to explore the relevance of three different types of styles measure for students' learning in a large introductory university course in psychology, using information technology to enhance teaching. The paper examines the relationship between styles, the usage of learning technology, and academic performance in this course. Design/methodology/approach -Styles are measured using approaches to learning, thinking styles, and cognitive styles. The usage of the online material is measured by considering both time spent on the resources and the amount of material viewed (pages and hits) as well as tools used. Findings -The findings are that the academic performance of students who used the online resources is significantly higher than those who either choose to not use the online materials at all or choose to use to the materials to a lesser extent. It is determined that the measure of approaches to learning (approaches and study skills inventory for students) is the stronger predictor for successful use of the material. Research limitations/implications -Using a reasonably sized sample in an ecologically valid context offered the opportunity to put styles into context and to consider the practical use of styles. This research is limited by the context and the particular sample. It is also difficult to completely exclude the fact that students using the extra material are generally more motivated and would have obtained better grades even without the resources. Originality/value -This paper offers further evidence for the relations between different measures of styles and evaluates the effects that styles might have on usage of online material and academic performance.