The big picture? Video and the representation of interaction

Researchers who use video to record interactions usually need to translate the video data into another medium at some stage in order to facilitate its analysis and dissemination. This article considers some methodological issues that arise in this process by examining transcripts, diagrams and pictures as examples of different techniques for representing interaction. These examples are used to identify some general principles for the representation of data where video is the source material. The article presents an outline of guided interaction and this is used as a case for illustrating these principles in the context of young children, technology and adults in pre-school settings. Although the article focuses on a specific study and solution, the principles are applicable in all cases where video is used as a source of data for the representation of interaction, whether or not it is technologically mediated

A Framework to Support Interdisciplinary Engagement with Learning Analytics

Learning analytics can provide an excellent opportunity for instructors to get an in-depth understanding of students’ learning experiences in a course. However, certain technological challenges, namely limited availability of learning analytics data because of learning management system restrictions, can make accessing this data seem impossible at some institutions. Furthermore, even in cases where instructors have access to a range of student data, there may not be organized efforts to support students across various courses and university experiences. In the current chapter, the authors discuss the issue of learning analytics access and ways to leverage learning analytics data between instructors, and in some cases administrators, to create interdisciplinary opportunities for comprehensive student support. The authors consider the implications of these interactions for students, instructors, and administrators. Additionally, the authors focus on some of the technological infrastructure issues involved with accessing learning analytics and discuss the opportunities available for faculty and staff to take a multi-pronged approach to addressing overall student success.https://scholarworks.wm.edu/educationbookchapters/1045/thumbnail.jp

Succession and firm growth: results from a non-parametric matching approach

Succession, Family firms, Employment growth, Matching, Austria, C14, L25, L26,