While Learning Analytics is a core topic, the spreadsheet data from job descriptions highlights a need for more detailed, practical subtopics. Suggested additions include:
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Data Wrangling and Cleaning: Topics on cleaning and manipulating raw data using statistical software.
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Predictive and Inference Modeling: Specific discussions on the application of algorithms, such as regression and classification, within a learning engineering context.
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Experimental Design and Validation: This could include topics on conducting A/B testing of learning conditions and validating models to ensure accuracy.
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Data Visualization and Reporting: The ability to "create graphs, charts, or other visualizations" and "deliver oral or written presentations" of data analysis results is a key task in learning engineering job roles.