My View on Predictive Modeling and Machine Learning
When it comes to Predictive modeling data and Machine learning, there are numerous techniques that could be useful. The education system, businesses and companies have a type of system to some degree. Every work area must interpret the data to view their processes. Therefore, what is Predictive Modeling? In the educational field, it is a form of data. According to (Porter & Balu,2016) “Predictive modeling is an estimate individuals’ future outcomes or even their probabilities of future outcome. The outcome is done by building and test model using data on similar individuals whose outcome is already known. Commonly used in business and marketing research is gaining currency in many social policy domains as a way to identify individuals who may benefit from targeted intervention”. Predictive modeling, in the education system, as well as reading and interpreting data correctly, will provide help to the individual so they can improve and find the best outcome for the students. When it comes to businesses and companies, the use of data is to figure the outcome that will be best for their growth. At some point, these three-work fields have use predictive modeling to build up to where the individual, business, and company need to be.
Predictive Modeling in Education
The purpose of the educational field using predictive modeling is to help students that are at risk and not meeting the academic standards. Predictive Modeling helps and guides educators to see what steps they need to take into action to get a good outcome for the students. The article that I read called, “Predictive Modeling of K-12 Academic Outcomes A Prime for Researcher Working with Education Data”, mentioned that the school uses the
“ABC indicators for attendance, behavior, and course performance. An example that the article use was students who are at risk to not graduating high school” (Porter & Balu,2016). The education system uses data that can includes homework, test score, daily attendance, etc. The data is then categorized and is updating as the inputs are being entered. This is done by the use machine learning.
Machine learning in Education
Machine learning is a computer program that uses codes and determine or make a prediction of an outcome. Machine learning uses procedures to solve problems. When data is collected the machine learning is detecting data, labeling data, and clustering data. When the educator’s view data results and academic milestones are not reached, figuring out a solution is the next step. This is done by gathering data results, getting prepared, and start assisting the students who needs the help. An example of machine learning is the STARR testing in Texas. Students are tested and are measured on how well they learned the material for that school year in order to pass to the next grade level. The machine learning collects number data of who is high, average, low or at risk. Another example of machine learning is behavior and attendance. Did the student go all year long? Did the student miss half of the year? That also plays a key role on students learning. With machine learning, it can be predicted if the student is at risk by the data that is being input daily. Machine learning is utilized in many ways and is being operated in any field. The world is filled with data and is not going anywhere anytime soon. Data and technology are going to evolve even more. I would love to learn more about machine learning because there are many types software that are being use today and different types of programs that can be useful in any work field profession. A reference is provided below about Machine Learning in Educational Technology.
References
Porter, K. & Balu, R., (2016) PREDICTIVE MODELING OF K-12 ACADEMIC OUTCOMES: A Primer for Researchers Working with Education Data.
Nafea, Ibtehal Talal. “Machine Learning in Educational Technology.” IntechOpen, IntechOpen, 19 Sept. 2018, www.intechopen.com/books/machine-learning-advanced-techniques-and-emerging-applications/machine-learning-in-educational-technology.