We could define predictive psychology as a new branch of psychology that focuses on the use of data and statistical techniques to predict future results, which manages to combine psychometric processes with new artificial intelligence and machine learning technologies to obtain reliable projections about skills, potential and future performance of a person in various areas of his or her life.
According to expert Isaías Sharon, PhD in education and new technologies and CEO of HPI International, this concept is related to “the ability to predict the behavior, skills and potential that a person has for their learning and development goals”. In the context of higher education, it refers to the application of these techniques to predict student academic performance, student retention and student completion.
Predictive psychology in higher education can be used by educational institutions to identify students who may be struggling academically or to identify students who are at a higher risk of dropping out. Through the collection and analysis of data from different sources, such as students’ previous grades, their demographic profiles, and their interactions with the educational environment, predictive models can be developed to help institutions make informed decisions about how to support their students.
In addition, predictive psychology can also be used by students themselves to assess their own academic performance and to identify areas in which they need to improve. By analyzing their academic history and study patterns, students can use predictive results to identify areas where they need to spend more time and effort.
Overall, predictive psychology in higher education can be a valuable tool for improving the quality of education and helping students achieve their academic goals. By using statistical techniques and data analysis to predict students’ academic performance and retention, educational institutions and students themselves can make informed decisions and tailor their study approaches to improve outcomes.