Predictive analytics software for higher education is being hailed as a bold development in education. The new technology can identify which students are at risk of failing, enabling teachers to extend assistance to them early on. However good these intentions may be, students are wary that the software will tag them as underachievers – way before they’ve had a chance to prove themselves.
The Hechinger Report covered students’ sentiments at the Edu Con 2.9 tech and education meet at the Philadelphia’s Science Leadership Academy. A panel of student representatives discussed the merits and disadvantages of the predictive education software. The high-tech program is being perceived negatively for the primary reason that students don’t want to be classified or judged based on an algorithm.
Students claim that predictive software will hamper them from achieving their full potential. They also voiced out possible breaches of privacy, claiming that digital dossiers can be kept and later used against them for a myriad of purposes. While these claims may sound unreasonable – or paranoid to some, the major point that the students wanted to make was that they didn’t trust software to compile contextual information about their academic performance, or their personal lives.
Moreover, students didn’t want to be relegated to a list of underperformer just because of bad grades for one semester. They maintained that the digital data would be inconclusive since it cannot factor in personal issues or challenges that students could be facing.
Predictive analytics was born out of the increasing volume digital data on students. It was created to make education more dynamic and become pivotal in making technology work for the benefit of students.
‘‘Predictive analytics gives richer educational opportunities to more students, guiding them on different paths depending on their capabilities and skills”
The Age explains that digital data is gathered and used to analyze a student’s learning patterns. By collating and sorting data such as attendance, courses taken, and more – the software will be able to predict his performance as well as improve learning opportunities. Proponents maintain that this kind of data is easier to gather and also faster to interpret.
‘‘Predictive analytics gives richer educational opportunities to more students, guiding them on different paths depending on their capabilities and skills,” Professor Simon Kaplan, director of Skills and Industry Transformation at NICTA, Australia’s information, communications and technology research centre was quoted in the report.
The ultimate aim of this predictive software is to have more students complete their courses and graduate. It will target students who are at risk of failing or dropping out so their teachers and instructors can devise an intervention to assist them. They could be made to do extra projects for additional credits or extend their term at the University.
This development is sure to make a bold impact on the lives of students and improve their chances of being gainfully employed in the near future.
However, it appears that predictive software is a paradigm shift in the field of education that students aren’t ready to accept. They still prefer to trust the judgment of teachers who interact with them on a regular and personal basis.
The 47-counts include “conspiracy, computer fraud and abuse, economic espionage, theft of trade secrets, wire fraud, access device fraud and aggravated identify theft.”