Application of big data techniques to a problem 3

 

  Implications for Individuals and Society

You need to make sure to consider the broader implications for people and society as educational institutions are using predictive analytics to advance learning outcomes. The insightful results derived from data have had a positive impact on student support and have allowed for interventions to happen in real-time, thus, problems get mitigated early on, but at the same time, they bear negatives.

Local realities that exert a significant impact on a student's performance such as part-time jobs, family obligations, or health problems are sometimes outside the scope of the predictive models used. Students have expressed personal fears of academic surveillance and that the machines are watching them and are responsible for grading. Many students requested to be informed about the method these predictions were based on and the transparency and justice of risk scores were questioned. It is the rise of the need for explainable AI in education—tools that can predict and tell how they achieved their results in a way that can be understood by both teachers and students—that such resistance is drawing our attention to.

Even now, the bias of algorithms is one of the most steadfast problems at the societal level. Predictive models that are not being monitored or poorly designed may be harmful to non-traditional students, people with brain differences in learning, and those who differ from typical academic behavior patterns.

If these biases are not kept in check, teaching an equal opportunity society may become a mission impossible, societal success at large may become a dream for a few only the earth's wealth."Thus, people like students with disabilities, from low-income groups, and those who do not live in the typical neighborhoods may be further affected.