How can you identify areas where learners struggle with learning analytics?

1 Define your learning objectives and metrics

The first step to identify areas where learners struggle is to define your learning objectives and the metrics that measure them. Learning objectives are the specific and measurable outcomes that you want your learners to achieve after completing your course. Metrics are the indicators that show how well your learners are progressing towards those objectives. For example, if your learning objective is to improve learners' problem-solving skills, some metrics could be the number of attempts, errors, hints, and feedback they use in a scenario-based activity.

3 Analyze learner data and identify patterns

The third step is to analyze learner data and identify patterns that indicate areas where learners struggle. You can use different methods and techniques to analyze learner data, such as descriptive, diagnostic, predictive, and prescriptive analytics. Descriptive analytics summarize what happened in your course, such as how many learners completed it, what scores they achieved, and what activities they completed. Diagnostic analytics explain why something happened, such as why some learners dropped out, why some learners scored low, and why some learners skipped some activities. Predictive analytics forecast what will happen in the future, such as how likely learners are to complete the course, how well they will perform, and what challenges they will face. Prescriptive analytics suggest what actions you can take to improve the situation, such as how to motivate learners, how to provide feedback, and how to adapt the course content.

4 Validate your findings and test your solutions

The fourth step is to validate your findings and test your solutions. You can use different methods and tools to validate your findings and test your solutions, such as experiments, A/B testing, and user testing. Experiments are controlled studies that compare the effects of different variables on learner outcomes. A/B testing is a type of experiment that compares two versions of a course element, such as a headline, a layout, or a feedback message, and measures which one performs better. User testing is a method that involves observing and interviewing learners as they use your course, and collecting their feedback and suggestions.

5 Monitor and evaluate your results and iterate

The final step is to monitor and evaluate your results and iterate. You can use different tools and methods to monitor and evaluate your results, such as dashboards, reports, and analytics platforms. You can use the same metrics that you defined in the first step to measure the impact of your solutions on learner outcomes. You can also collect and analyze learner feedback and satisfaction to assess the quality of your course. You can then use the insights and learnings from your results to iterate and improve your course design and delivery.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?