A New Age of LMS Analytics: Success Drivers for the Broad-Based Adoption of LMS-Based Academic Analytics

Over the past two weeks, we've been highlighting aspects of Moodlerooms President, Lou Pugliese's, whitepaper, A New Age of Learning Management Analytics. Today, we're providing the closing remarks of the paper, which brings all of the aspects of learning management analytics full-circle and gives a small snapshot of institutions' e-Learning potential and what it will take to reach such potential.

You can read Lou's closing remarks, Success Drivers for the Broad-Based Adoption of LMS-Based Academic Analytics in their entirety below or by scrolling to page 13 of the whitepaper, here. As always, if you have any comments or would like to share insight on the current state of LMS, please share it in the comments below or feel free to contact us directly at feedback@moodlerooms.com.

Success Drivers for the Broad-Based Adoption of LMS-Based Academic Analytics

With over 12 years of history of institutions developing rich competency in e-learning, a treasure trove of critical institutional performance information is now available in ways that will profoundly change the dynamics of teaching and learning online. In order to accomplish data-rich, evidence-based e-learning environments, higher education must increasingly choose
flexible technology platforms with strong data discovery, visualization, collection and maintenance practices. More importantly, institutions must develop the necessary internal
leadership where administrators are committed to evidence-based decision making, an environment where all hierarchical levels of the organization have basic skills in data analysis.

As higher education continues to develop competency in implementing a progressive approach to these maturity models, information and instructional technology leaders will increasingly need to develop a culture of evidence to adequately support the institutional data enterprise. Institutions must develop the technical and social environment where individualized data shaping from multiple sources can be collaboratively shared for broad-based institutional change.

Clearly robust data sets, more predictive analytics capabilities and new methods for extracting and organizing data will allow institutions to capture and expose information to a greater number of stakeholders — enabling informed academic and programmatic decision making a better time to value. With increasing regulatory pressure and public demand for evidence-based learning
outcomes, student persistence and retention, learning management systems are now at the gravitational center of leveraging data for top down institutional and program improvement.

Moreover, competency in later stages of the analytics maturity models will ultimately enable the
transformation of online learning as it is defined today. Ultimately, critical data that informs instruction and continuous program improvement will be the catalyst for more adaptive, personalized learning environments that will form the basis for categorical change in LMS systems themselves.