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      <title>Learning Analytics by Martin Sueldo</title>
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      <pubDate>2023-05-30 01:10:18 UTC</pubDate>
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         <title>Learning analytics is defined as &quot;the measurement, collection, analysis, and reporting of data about learners and their context, for purposes of understanding and optimizing learning and the environments in which it occurs.&quot; Beyond the academic definition of it, we know that learning analytics have three main components: data, analysis, and action. It uses different techniques to gather, store, and report data in different purviews such as administration, programming, and pedagogy. Learning analytics display the national trend in the US of evidence-based learning and digital learning content delivery.</title>
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         <pubDate>2023-05-30 01:33:56 UTC</pubDate>
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         <title>Learning analytics allows one to measure the success (and deficiencies) of one&#39;s teaching methods. It gives you the opportunity to see things that you may not otherwise be aware of in the learning process. It can be used for exams, for student feedback, and many times, it allows you to tailor the content and delivery to be more effective in what is taught. Learning analytics are in the same line with the flipped classroom, because it allows you to plan and foresee discrepancies that otherwise may be missed. </title>
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         <pubDate>2023-05-30 01:46:29 UTC</pubDate>
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         <title>As a faculty in the humanities, I can see myself using learning analytics in the design of exams, and also as a source to provide better methods for student feedback. It would also give valuable information in identifying variables and discrepancies among different demographics; in this way, I could reach a better perspective on the achievement gap and thus try to come up with different tools for different student populations. As a professor in the humanities, it also encourages one to see what kind of information and sources students feel the most comfortable with.</title>
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         <pubDate>2023-05-30 01:53:09 UTC</pubDate>
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