Resources for

7 Things You Should Know About First Generation Learning Analytics


This brief describes the most pertinent aspects of learning analytics:

Learning Analytics (PDF)


Context, impact, and examples are among the categories detailed:

NMC Horizon Report > 2013 Higher Education Edition

New Media Consortium

A report summarizes learning analytics and showcases good examples:
> 2013 Horizon Report (PDF)

Whereas assessments look at the performance of learners or groups of learners, learning analytics takes this notion a step further. Learning analytics leverages a wide range of data about learners and their behaviors to help determine the optimal learning environment.

Excerpt from the New Media Consortium’s definition:

Learning analytics is education’s approach to “big data,” a science that was originally leveraged by businesses to analyze commercial activities, identify spending trends, and predict consumer behavior. Education is embarking on a similar pursuit into data science with the aim of improving student retention and providing a high quality, personalized experience for learners. Learning analytics research uses data analysis to inform decisions made on every tier of the educational system. This data can be leveraged to build better pedagogies and target at-risk learners.

There are several different categories of usage for analytics:

Identifying At-Risk Learners

Tracking learner performance on initial activities will give you a sense of which ones are at risk of failing the course or not being able to grasp the material. Identifying these individuals early in the process allows you to give special attention to the learners before it is too late.

Tracking Interaction

Gathering data on how long learners are interacting with readings or videos you posted will help you see how engaging the course content is and how well certain topics or lessons are being understood.

Pinpointing Effective Techniques

Learning analytics are often used by instructors to identify the success of their pedagogies. Integrating systems (e.g., polling) that capture data about how comfortable learners are with the material as it is being taught can help you make the necessary adjustments to better align your teaching methods to their learning styles.