{"id":155,"date":"2023-03-01T15:01:52","date_gmt":"2023-03-01T20:01:52","guid":{"rendered":"https:\/\/carleton.ca\/learninganalytics\/?page_id=155"},"modified":"2023-04-27T16:26:50","modified_gmt":"2023-04-27T20:26:50","slug":"designing-courses-for-learning-analytics","status":"publish","type":"page","link":"https:\/\/carleton.ca\/learninganalytics\/designing-courses-for-learning-analytics\/","title":{"rendered":"Designing Courses for Learning Analytics"},"content":{"rendered":"

It is important to consider that analytics data collected by educational technology is the product of two factors: the design of the course and its evaluation structure<\/strong> as well as the performance of the learners<\/strong>. Therefore, t<\/span>o maximize the benefits of using Learner Data, instructors are advised to intentionally evaluate their course design with the goal of collecting learning analytics in mind.
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Incorporating Learning Analytics into Course Design<\/h2>\n

These are overall design practices you should consider when designing your course with the intention of obtaining Learning Analytics.<\/p>\n\n\n\n\n\n\n
Recommendation<\/td>\nExample<\/td>\nResources<\/td>\n<\/tr>\n<\/thead>\n
Template course structures<\/a><\/td>\n\n
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  • Use the same timeline, evaluation structure (i.e., due dates, and weightings), and content locations in each course.<\/li>\n<\/ul>\n<\/td>\n
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Include\u00a0 “Checkpoints”<\/a><\/td>\n\n
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  • Include a syllabus quiz at the beginning of the course.<\/li>\n
  • Use checklists to give students an idea of what they are meant to be doing and when.<\/li>\n
  • Collect data throughout the term, not just at one point.<\/li>\n<\/ul>\n<\/td>\n
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