Khan Academy is a widely used online learning platform that integrates embedded learning analytics to support both teaching and assessment. The platform tracks student activity, including time spent on tasks, number of attempts, and mastery of specific skills. These data points are compiled into visual dashboards accessible to teachers, who can then monitor class progress, identify struggling learners, and assign targeted practice. For students, real-time feedback and adaptive recommendations foster a more personalized learning experience (Khan Academy, 2023).

The effects of this system are significant. Learning analytics in Khan Academy has been shown to improve student motivation and engagement, as learners can track their own progress and earn badges or mastery points (Papamitsiou & Economides, 2014). Teachers also benefit from having actionable insights that allow them to shift from traditional assessment models to more formative, data-driven practices. However, challenges exist: analytics may risk reducing learning to quantifiable outcomes and raise concerns around student data privacy and interpretation biases (Ferguson, 2012).

Overall, Khan Academy illustrates how embedded analytics can bridge teaching and assessment by providing immediate, personalized insights. When used thoughtfully, it enhances both self-regulated learning and instructional design, but it must be balanced with qualitative evaluations of student understanding.

References

Ferguson, R. (2012). Learning analytics: Drivers, developments and challenges. International Journal of Technology Enhanced Learning, 4(5/6), 304–317. https://doi.org/10.1504/IJTEL.2012.051816

Khan Academy. (2023). Teacher tools: Progress and reporting. Retrieved from https://www.khanacademy.org

Papamitsiou, Z., & Economides, A. A. (2014). Learning analytics and educational data mining in practice: A systematic literature review of empirical evidence. Educational Technology & Society, 17(4), 49–64.