As part of our work on learning analytics interoperability and data sharing, we are creating a number of studies and releasing them as early-stage public drafts for comment. The documents will subsequently be revised to take account of comments, and ultimately released as a finished document. Each draft has its own information page, indicating status and links to: an online-commentable version, a downloadable pdf, a discussion thread on our Open Forum for Learning Analytics Interoperability Google Group. If you refer to a draft, please use the URL of the information page (link in each title, below), since that page will be updated to point to the latest version.
Audio and Video Playback – opened for comment 2014-10-13
This working document considers a number of APIs for web based audio and video playback from the perspective of asking “which events may be of interest for learning analytics?”. Its purpose is to identify that set of events and attributes which may be considered to be commonplace, and therefore a candidate for cross-platform data stores, analysis-time mapping, implementing APIs on black-box players, improving interoperability, and potentially standardisation.
The document summarises existing learning analytics use of playback data, compares events from four players, and advances a possible common model for player events of use for learning analytics.
Assessment and Allied Activities – initial publication 2014-12-15
This working document considers the kind of events that are likely to occur in mainstream assessment processes, and allied activity such as questionnaire responses. It does so from the perspective of asking: “which events are of interest for learning analytics?” Its purpose is to identify that set of events and attributes which may be considered to be commonplace, and therefore a candidate for cross-platform data stores, analysis-time mapping, improving interoperability, and standardisation.
Standards and Specifications Quick Reference Guide – opened for comment 2014-11-19
This document presents a list of standards and specifications, including research work, which may be relevant to people building learning analytics systems. A brief summary of the capabilities of each is presented, along with notes on adoption to-date.
The aim of the author in writing this guide is to raise awareness of existing technical specifications, and to support a process of due diligence through exploration of prior art when designing Learning Analytics systems. The guide is intended to reduce the incidence of unintentional invention or deviation from what already exists.
Sharing learning analytics data between organisations may sometimes be a highly desirable action, both for furthering research and as part of an expertise or technology based service. This document describes a number of examples to show how this can be the case, to illustrate similarities and differences, and to tentatively identify some of the possible causes of success or failure of sharing data for learning analytics.