Assessing the dangers of AI applications in education

By Tony Bates. Most data collected about student learning is indirect, inauthentic, lacking demonstrable reliability or validity, and reflecting unrealistic retention timelines. And current examples of AIEd often rely on these poor proxies for learning, using data that is easily collectable rather than educationally meaningful. More...