Learning Analytics: Predictive & Prescriptive Complexity

By Andrew Downes | Apr 10, 2019

The highest complexity of learning analytics is predictive and prescriptive analytics. This means using data to either predict what might happen, or to prescribe learning activities. And, out of the 5,713 reports we reviewed as part of our Learning Analytics Research Study, we only found a fraction of reports that we classed as “Predictive and Prescriptive.” In this post, we’ll explain how these reports are being used and suggest other ways you can try predictive or prescriptive analytics in your organization.

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Learning Analytics: Advanced Evaluation Complexity

By Andrew Downes | Mar 26, 2019

Advanced Evaluation is less common than Data Evaluation, which means there’s no well-worn path leading the way. Organizations venturing into this level of complexity are often doing so in ways that are different from others. We see this in our Learning Analytics Research Study data, where there isn’t one analysis type that has significantly more report views than the rest. That's why we’ve divided the Advanced Evaluation complexity into five analysis types, which we’ll explore in this post along with examples of what organizations are doing in terms of this complexity.

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Learning Analytics: Data Evaluation Complexity

By Andrew Downes | Mar 12, 2019

Last week, we saw that Data Evaluation is by far and away the most common complexity level of Learning Analytics we observed in our research study. Within this complexity, we found 16 types of analysis represented, which we’ve bundled into three headings and will explore in this blog post.

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Learning Analytics: Complexities & Analysis Types

By Andrew Downes | Mar 05, 2019

The last few posts in our Learning Analytics Research series have looked at the three categories of learning analytics (i.e. learner, program, and experience) and their respective dimensions. Now, we’ll focus several posts on exploring the four levels of complexity—starting with a quick overview of each level.

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Learning Analytics Dimensions: Learning Experience Analysis

By Andrew Downes | Feb 20, 2019

As we completed our Learning Analytics Research Study, we found many reports that fell into the Learning Experience category. Not only were there more reports, but they also were more varied—leading us to create nearly double the amount of dimensions under this category than compared to the Learner and Learning Program categories. And, in this post, we'll explore these learning experience dimensions in practice.

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Learning Analytics Dimensions: Learning Program Analysis

By Andrew Downes | Feb 12, 2019

Welcome to our fifth installment exploring results from our Learning Analytics Research Study and what they mean in practice. This week, we’re diving into the dimensions under the Learning Program categories. (We’ll pick up the Learning Experience category next week.)

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Learning Analytics Dimensions: Learner Analysis

By Andrew Downes | Feb 05, 2019

Welcome to our fourth installment exploring results from our Learning Analytics Research Study and what they mean in practice. This week, we’re diving into the dimensions under the Learner categories. (We’ll pick up the Learning Program and Learning Experience categories in our next posts.)

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Learning Analytics Categories [UPDATED]

By Andrew Downes | Jan 29, 2019

We’ve introduced our Learning Analytics Research Study and explained how learning categories are split into dimensions. And now it’s time to explore results from our study, starting with an overview of these categories, including two new categories we discovered.

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Learning Analytics Analytics

By Andrew Downes | Jan 21, 2019

In our last blog post, we introduced our latest series that focuses on findings from our Learning Analytics Research Study—during which we collected and analyzed data to see how real organizations are implementing learning analytics. We're kicking things off by sharing insights from overall Watershed report usage and how certain times of the year can affect both learning data and reports of different types and categorizations.

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Corporate Learning Analytics in Practice [Introduction]

By Andrew Downes | Jan 08, 2019

During the summer of 2018, we conducted a Learning Analytics Research Study to research how our clients are actually implementing these analytics. This research aimed to place organizations on the learning analytics triangle as a measure of maturity, and to paint a picture of what this actually looks like in 2018.* In this blog series, we’ll explore the results from our study and how real people are doing real learning analytics.

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