AI-Based Assessments Systems in Education

Course Description

How AI-based tools might improve student assessment in elementary and secondary education will be covered in this course. The All-Party Parliamentary Group on Artificial Intelligence (APPG AI) in the UK looked more closely at various types of AI-based assessment systems in education in the wake of the controversy surrounding the statistical model that was used to standardise students’ A-level (secondary school/high school) results in England during lockdown 2020 (instead of physical exam results). In addition, the UK government later acknowledged that the statistical models used to determine students’ final A-level marks during the covid-lockdown period contained algorithmic and mathematical problems. The future path and the lessons learnt will be discussed in this course.

The exploration of the advantages and disadvantages of employing algorithms to evaluate student performance continues in this course. We specifically challenge the contribution that AI technologies could or should make to a more equitable evaluation of students’ performance across all educational levels. We also explore how AI-based technologies may or should be used safely or ethically for both students and teachers, and how to make sure that algorithm-based tools and statistical models offer objective, accurate, and transparent outcomes, using expert knowledge and real-world experiences. Further, we investigate the potential effects of algorithm-based assessment systems related to teacher evaluations and how they can affect students’ behaviour, drive, and trust.

The expert contributions in this course come from the United Kingdom, the United States and Australia. They are leading academic professors from renowned universities, experts from the big tech industry, interest organisations and think tanks.