During the COVID-19 pandemic, what type of AI was utilized in online testing systems to monitor students' exam-taking?

The use of Mechanical AI in online testing systems during the COVID-19 pandemic was primarily focused on function and performance without the need for human-like reasoning or emotional interaction. Mechanical AI refers to algorithms and systems that can process data and perform specific tasks based on predefined rules. In the context of online testing, this type of AI was employed to monitor students through various means, such as analyzing video feeds to detect any suspicious behaviors, ensuring academic integrity by recognizing patterns in movements or comparing student actions against expected behaviors.

Mechanical AI works effectively in environments that require consistent, rule-based operations, making it ideal for the rigorous and structured demands of online examination settings. By employing this type of technology, institutions aimed to maintain the integrity of assessments while accommodating the challenges posed by remote learning during the pandemic. Other types of AI, such as Social AI, which focuses on interactions mimicking human social behaviors, or Emotional AI, which interprets human emotions, were less relevant in the strict context of monitoring test-takers’ compliance with exam rules and procedures.