From the course: Instructional Design: Needs Analysis
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Understanding data-analysis techniques
From the course: Instructional Design: Needs Analysis
Understanding data-analysis techniques
I want to let you in on a secret. I'm not exactly a statistics wizard. Truth is, most of us instructional designers aren't. Now if you are really good at math and statistics, then consider yourself lucky. You'll have a huge advantage when it comes to data analysis. However, no matter what your skill level, there are techniques that you will find useful when it comes to analyzing your data. You might even have fun. Analyzing data can be like being detective making a case. You might have a theory or two, but you need to find concrete evidence to support it. It's up to you to search for clues and then put all the pieces of the puzzles together. Let's go back to the interviewing skills example that we've used throughout this course. One of our research questions was, what are the causes of turnover? Our theory was that high turnover rates among new employees is a result of poor hiring decisions. How could we test that theory and prove that a poor hiring decision was a cause of turnover?…
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Contents
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Introduction to data analysis3m 25s
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Understanding data-analysis techniques3m 22s
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Evaluating performance gaps5m 19s
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Identifying participant needs3m 34s
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Determining whether training will solve the problem5m 28s
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Defining learning outcomes4m 43s
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