The Data Mining Method in Healthcare and Education

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Table of Contents

Answer to the Classmate (Taylor)
Answer to the Classmate (Jen)
References

Although the data mining method was developed primarily in commercial environments, it is widely used in various fields such as healthcare and educational systems. An example of the former is using the algorithms for analyzing high-risk groups for specific illnesses to identify and help people in need (Obermeyer Powers, Vogeli, & Mullainathan, 2019). The algorithm analyses data based on the money spent by people on health care. The latter example presents data mining in the educational system and represents the use of machine learning for student dropout prediction (Hedge & Prageeth, 2018). It can help the organization retain the students from the high-risk group from the respective academic program.

Both examples aim to improve the efficiency of whether health or educational system. However, as the latest research demonstrates, these algorithms have certain biases, such as racial bias. If bias is recorded in data, models& can also be biased (Hu & Rahgwala, 2020, p. 431). Thus, I would use data mining in both cases; however, before that, I would discover a way to improve the algorithms used for it.

Answer to the Classmate (Taylor)

In his discussion, Tailor addressed two cases of data mining: the example of Target, whose manager discovered a clients pregnancy, and the TikTok suggestions of chosen for you items. In both cases, as Taylor says, the system had recognized the possible clients needs before they did so that they felt someone is watching their every step. Taylor stated that if he were a business owner, he would use these strategies for his success. Although I agree there is a benefit in using it, I would first consider clients sense of privacy. The actions based on the data mining results should not make the customers uncomfortable, as the result of it may be the opposite of what is expected.

The internet opens many possibilities for its users, from education and marketing to friendship and relationships. Primarily, I use it to communicate with my friends and family while being distant from them. It allows to maintain a connection with the people and be aware that someone needs help, as well as to inform them you are in trouble. Besides, I intensively use online resources for education, as often, the variety of books and articles available online is wider than provided in the local libraries.

I think, in the latter case, as in some others, the use of online sources would be more effective if before the knowledgeable person gives the reference. For example, if I need to find information related to some subject in my education, I would first ask my teachers for the bibliography. Easy access to a large body of information can sometimes confuse those unfamiliar with the subject in terms of data and knowledge (Bourgeouis, Mortati, Wang, & Smith, 2019). Without advice, I would spend excessive time looking the sources that may not be relevant.

Answer to the Classmate (Jen)

In the post, Jen discusses that it is important to look at reviews of services, products, etc., on specific websites or social media. This opinion is close to my point of view expressed above. I think the freedom of the internet can lead us to engage with the wrong people or get access to illegitimate products and services. Thus, in view, along with access to the world base of information, we need to nurture our consciousness about what is right and wrong. It will help us to avoid improper actions in communication, marketing, and education in any field.

References

Bourgeouis, D., Mortati, J., Wang, S., & Smith, J. (2019). Information systems for business and beyond. Pressbooks. Web.

Hedge, V., & Prageeth, P. P. (2018). Higher education student dropout prediction and analysis through educational data mining. IEEE 2018 2nd International Conference on Inventive Systems and Control (ICISC), 694699.

Hu, Q., & Rangwala, H. (2020). Towards fair educational data mining: A case study on detecting at-risk students. In Proceedings of the 13th International conference on Educational Data Mining (EDM 2020), 431-437.

Obermeyer, Z., Powers, B., Vogeli, C., & Mullainathan, S. (2019). Dissecting racial bias in an algorithm used to manage the health of populations. Science, 366(6464), 447453.

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The Data Mining Method in Healthcare and Education

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