While artificial intelligence has long supported higher education research initiatives, it’s now expanding into areas that touch student data. Examples include face recognition in surveillance cameras ...

You have /3 articles left. Sign up for a free account or log in. The latest episode of The Key, Inside Higher Ed’s news and analysis podcast, features a discussion ...

Hackers gained access to an online coding repository belonging to the University of Sydney and stole files with personal information of staff and students. The ...

The Federal Trade Commission (FTC) is proposing that education technology provider Illuminate Education to delete unnecessary student data and improve its security to settle allegations related to an ...

The company failed to secure student health records, addresses, and other sensitive information for years Parents can take steps now to protect their children's data at school If your child attends ...

This series of Voices of Student Success focuses on the use of generative artificial intelligence in higher education and how technology can support student success goals. Central New Mexico Community ...

New York has reached a $1.7 million settlement with an educational technology company following a data breach that exposed the personal information of millions of students statewide, state officials ...

The hacker seemed focused on the Ivy League school’s admissions preferences. By Stephanie Saul The University of Pennsylvania has reported a massive data breach to the Federal Bureau of Investigation ...

Credit: Image generated by VentureBeat with FLUX-pro-1.1-ultra A quiet revolution is reshaping enterprise data engineering. Python developers are building production data pipelines in minutes using ...

Each school year, one important task on a principal’s plate is to review student-achievement data to identify trends and adjust goals. However, several common misinterpretations and misuse of such ...

Abstract: Data preprocessing is essential for enhancing the performance of machine learning models which involves key techniques like data cleaning, normalization, and feature selection to mitigate ...