Top Chinese university stops using AI to track students' attention after privacy backlash

The university, ranked sixth nationally in the 2026 ShanghaiRanking Best Chinese Universities Ranking, announced on Nov. 4 that it would discontinue calculating students' "head-up rates." The metric was designed to assess classroom engagement by measuring whether students were looking toward the lecturer or down at their phones, computers or desks.

The decision followed the circulation of screenshots showing live classroom footage alongside real-time statistics on attendance, late arrivals and students' attentiveness, sparking criticism online over facial recognition, personal data collection and the lack of student consent, according to the South China Morning Post.

Earlier this month students were informed that the university would use its upgraded smart classroom system to track attendance over a one-week period as part of routine teaching inspections. Some teachers reportedly warned that attendance records could affect students' grades or even prevent them from taking course examinations.

The university subsequently denied that attendance figures would be linked to grades or that the inspections had been ordered by higher authorities. It also said the system did not collect facial or other biometric data or conduct facial recognition during teaching activities without authorization. The university clarified that the screenshots circulating online had been taken during a system trial at one of its campuses in May, rather than during the latest attendance inspections.

Nanjing University in eastern China's Jiangsu Province. Photo courtesy of the university

It spent more than 30 million yuan (US$4.5 million) upgrading its smart classroom system, installing new equipment in more than 100 classrooms and several public areas. The platform combines classroom cameras with AI algorithms capable of counting students, recording attendance and measuring attentiveness through head-up rates.

Despite abandoning the attentiveness measure, the university defended the broader system, saying it was designed to improve teaching quality, support live-streamed lectures, facilitate interaction between campuses and allow students to review recorded lessons. It said the automated attendance calculations were intended to support teaching evaluations and future course improvements.

However, some students remained concerned that facial recognition technology could expose their biometric information to the university and private technology companies.

A Nanjing University faculty member said the monitoring was intended primarily to evaluate teachers' performance rather than scrutinize individual students. The faculty member also criticized students for frequently looking at electronic devices during lectures, saying the behavior undermined teaching and showed disrespect toward lecturers.

The controversy has highlighted wider concerns about the growing use of AI-powered monitoring systems in Chinese higher education.

Chinese financial publication Caixin reported that several universities had introduced smart classroom systems capable of automatically tracking attendance, measuring head-up rates and even calculating how many seats in the front rows were occupied.

In a commentary published on Nov. 4, Hubei-based news outlet Jimu News questioned whether such technology genuinely improved education, arguing that students should have a say in decisions about classroom surveillance. It warned that a lack of transparency in deploying these systems could fuel suspicion and misunderstanding.