{"id":8938,"date":"2017-09-18T18:00:34","date_gmt":"2017-09-18T15:00:34","guid":{"rendered":"https:\/\/www.talentlms.com\/blog\/?p=8938"},"modified":"2024-11-11T17:14:05","modified_gmt":"2024-11-11T15:14:05","slug":"gather-analyze-learning-insights","status":"publish","type":"post","link":"https:\/\/www.talentlms.com\/blog\/gather-analyze-learning-insights\/","title":{"rendered":"Looking Within: How To Gather And Analyze Actionable Learning Insights"},"content":{"rendered":"

Mark Twain notoriously advised, \u201cFirst get your facts; then you can distort them at your leisure.\u201d Today, we have access to more facts to distort than ever before. In fact, more data has been created<\/strong><\/a> (and collected) in the last two years than in the entire history of the human race!<\/p>\n

<\/p>\n

Being able to collect learning data holds significant promise for better learning experiences and ROI on training investments.<\/strong> Training managers and instructional designers also have more concrete information to work with than ever before. But there\u2019s a catch \u2013 too often, data is poorly interpreted. And poorly interpreted data has no actionable value.<\/p>\n

Learning insights are often referred to by other names, like learning analytics, or learning metrics.<\/strong> With the right goals and techniques in mind, you can gather all of the above and, most importantly, translate training insights into action that improves training for your learners and organization.<\/p>\n

Why Gather Learning Insights?<\/h2>\n

The two big promises of learning insights are to help you make solid decisions, based on relevant data, and to demonstrate the value of your training.<\/strong> Improving this value using data-driven decisions then becomes a virtuous cycle.<\/p>\n

Sounds great, right? Let\u2019s take a closer look at these two core benefits.<\/p>\n

1. Data-driven decision making<\/h3>\n

eLearning is a developing science, and this means there are both exciting opportunities for innovation, and some tricky, unknown challenges. For what we don\u2019t yet know, it becomes somewhat necessary to rely on assumptions – even when they\u2019re rooted in best practice – to design and deliver online training.<\/p>\n

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eLearning is a developing science, and this means there are both exciting opportunities for innovation, and some tricky, unknown challenges.<\/a><\/div>\n

Click To Tweet<\/a><\/p>\n

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Hard facts can bridge the gap between assumption and informed decision,<\/strong> and help you design courses that are better suited to your audience, learning outcomes, and organizational needs.<\/p>\n

The majority of decisions made using learning insights will directly affect learners and course design in the following ways.<\/p>\n

Impact on learners:<\/strong> By using metrics that focus on individual performance and its relation to learning goals<\/strong><\/a>, learning resources, and the study habits of learners, you can improve:<\/p>\n

\u25cf Learner retention<\/strong><\/a>
\n\u25cf Completion rates
\n\u25cf Learner engagement<\/strong><\/a>, and
\n\u25cf Facilitation quality<\/p>\n

Impact on course design:<\/strong> Using metrics that focus on the social activity of learners, the development of knowledge and skill from easier to more difficult learning outcomes, the flow of the curriculum, and the feedback loops built into the course for assessment and communication, you can improve:<\/p>\n

\u25cf Course design to better suit the audience\u2019s preferences
\n\u25cf Personalization and adaptability
\n\u25cf Timing of course components in relation to learners\u2019 habits<\/p>\n

Learning insights can also be used to create models that predict the success or failure of learners on a course \u2013 but more on that later.<\/p>\n

2. Improved ROI<\/h3>\n

Training is an investment, and learning insights are the proof of the success of that investment.<\/strong> While the changes in learner behavior that training aims to achieve can be pretty hard to measure, online learning insights can prove the effectiveness of your training in other ways.<\/p>\n

For example, by comparing insights about course completion and assessment results, learning insights can demonstrate that a new course had an improved ROI over a previous iteration.<\/strong><\/p>\n

\"\"<\/p>\n

Data, Analytics Or Insights?<\/h2>\n

Now, before we get into the practical steps on how to gather effective learning insights, let\u2019s make sure we\u2019ve got the lingo down.<\/p>\n

Data includes the raw figures, responses and statistics gathered from a Learning Management System\u2019s (LMS) reporting and the metrics we set.<\/strong> Metrics are the questions or standards of measurement we use to gather data, like assessment completion rates. Unfortunately, data is an overwhelming jumble of nonsense by itself.<\/p>\n

That\u2019s why analytics are so important \u2013 they make sense of your data by finding trends and patterns. Analytics are a huge step towards getting value from your data, but they\u2019re not actionable by themselves.<\/p>\n

Insights are where you access the value of analytics. The insights gained through analytics should relate more directly to decision-making and improvement.<\/p>\n

Here\u2019s a simple learning insights example.<\/strong><\/p>\n

Let\u2019s say that you have a list of the number of times learners signed into a course, how they signed in, and what they did when they signed in. This is your data. By analyzing this data, you find that in the past month, there were 400 sign-ins, half of which were using a mobile phone, and 40 of which were to access the course assessments. The key insight from this analysis is that only 10% of learners sign on using a mobile device to complete assessments.<\/p>\n

You can see how the decision to make assessments more mobile-friendly could flow from this data.<\/p>\n

Golden Rules for Gathering and Using Learning Insights<\/h2>\n

Many organizations struggle to make truly data-driven decisions. This is because they\u2019re not using actionable learning metrics. Here are our four golden rules for making that sure you get all the value you can from your learning data.<\/p>\n

1. Know why you\u2019re collecting data<\/h3>\n

How do you get the insights you want? Start with knowing why you want those insights.<\/p>\n

We\u2019ve previously recommended that you try the SMART goals system to plan your analytics; so here’s a quick refresher<\/strong><\/a>. In most training contexts, learning insights can serve one or many of the following.<\/strong><\/p>\n

\u25cf Prediction:<\/strong> Identifying learners at risk of dropout or course failure, as well as predicting the overall success of a type of design or delivery.
\n\u25cf Personalization:<\/strong> Giving learners customized learning pathways, and\/or assessments.
\n\u25cf Intervention:<\/strong> Providing instructors and facilitators with information about learner performance for improved support.
\n\u25cf Information visualization and communication:<\/strong> Dashboards that visually display an overview of learning data (per learner or course).<\/p>\n

Not all of these will be equally important to every organization. So understand which insights are most useful to different stakeholders, and then tailor your metrics and training insights to those needs.<\/p>\n

2. Evaluate learning success using tried and tested models<\/h3>\n

The standard post-training evaluation model is the Kirkpatrick model<\/strong><\/a>. This model is organized around four levels that translate into data collection.<\/p>\n

According to this model, there are four categories of data that should be collected as a minimum:<\/strong><\/p>\n

1. Learner reaction:<\/strong> What learners thought about the training. Use surveys, course and facilitator ratings, and course completion statistics.<\/p>\n

2. Learning:<\/strong> Changes in knowledge or skill. Measure learner performance through assessments results and course pass rates.<\/p>\n

3. Behavior:<\/strong> The extent of behavior and skill improvement in the application. Measure and compare performance in assessments, and use manager surveys pre- and post-training.<\/p>\n

4. Results:<\/strong> The effects on the business or environment resulting from the learner\u2019s performance. Measure changes in efficiency through reduced work hours, faster turnaround, less rework, etc.<\/p>\n

Start with these metrics, and then make them more specific to your needs<\/a> with custom LMS metrics<\/a> and reporting tweaks.<\/strong> For example, if you\u2019re using a new quiz assessment, and your metrics show that many learners are leaving it incomplete, a secondary metric can be used to measure how long each learner spent on the assessment. Maybe the activity was too time-consuming?<\/p>\n

3. Emphasize action upfront<\/h3>\n

If you can\u2019t identify what action to take next using your learning insights, the chances are you didn\u2019t have a clear goal in mind when you started measuring or analyzing your data.<\/p>\n

Make sure your intended insights are actionable by phrasing them as questions<\/strong>. Where can the course content improve? How and when can we spot struggling learners? Is the course material appropriate to learners\u2019 knowledge and skill levels? Is this training increasing organizational performance? Or, how is the online course reducing operating costs and increasing revenue?<\/p>\n

4. Beware the vanity metric<\/h3>\n

Finally, be wary of only seeing what you want to see.<\/strong> To avoid this, steer clear of what is known as \u201cvanity metrics\u201d, i.e. metrics that show off what\u2019s working, such as high course completion rates, and hide what isn\u2019t working, like, low course pass rates.<\/p>\n

Remember that data is only helpful if you\u2019re asking the right questions, and you\u2019re prepared to take a hard look at the results.<\/p>\n

Using Your LMS to Support Learning Insights<\/h2>\n

If you\u2019re using a quality LMS, it\u2019s likely already set up to automatically track and record all the data you need<\/strong> to get powerful learning insights from your online training.<\/p>\n

If your LMS offers custom metrics to get the exact information you need to gather actionable insights, and easy-to-use\u00a0<\/strong>reporting features and tools<\/strong><\/a> like surveys and reporting dashboards, you can take even better steps toward improving the learning experience and ROI of your training.<\/p>\n","protected":false},"excerpt":{"rendered":"

Mark Twain notoriously advised, \u201cFirst get your facts; then you can distort them at your leisure.\u201d Today, we have access to more facts to distort than ever before. In fact, more data has been created (and collected) in the last two years than in the entire history of the human race!<\/p>\n","protected":false},"author":9,"featured_media":8946,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[255],"tags":[],"class_list":["post-8938","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ld-workplace-trends"],"acf":[],"yoast_head":"\nHow To Gather And Analyze Actionable Learning Insights<\/title>\n<meta name=\"description\" content=\"Why do you absolutely need to gather learning insights and what can they show you about your training program, your learners and even your business?\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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