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Predictive Analytics Hold Great Promise for Improving Student Performance

Software analytics can identify struggling students and get them help faster, proponents claim. The increase in digital data is spurring the trend, as well as “consistent marking systems” across different classrooms.

The amount and type of data institutions gather about their students is quickly proliferating. In the past, this data may have been limited to student completion rates. In contrast, some instructors are now collecting data after individual units and using those metrics to drive classroom instruction. Experts caution, though, that privacy may be an issue, particularly in a rapidly-evolving field. Many advise creating an institutional strategy prior to collecting or analyzing data in order to ensure that the information is used ethically and in accordance with privacy laws. For example, Cengage Learning is developing an e-textbook with student usage analytics, a move that some consider contentious. On the other hand, many ‘traditional’ analytics, such as tracking student performance in a single course or degree path, are relatively uncontroversal.

There is still much more to explore: data may help create solutions to problems that have yet to be identified.

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About the Author: Jaclyn Neel is a visiting Assistant Professor in Ancient History at York University in Toronto, Ontario.

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