Proceedings Abstracts of the Twenty-Fifth International Joint Conference on Artificial Intelligence

Questimator: Generating Knowledge Assessments for Arbitrary Topics / 3726
Qi Guo, Chinmay Kulkarni, Aniket Kittur, Jeffrey P. Bigham, Emma Brunskill

Formative assessments allow learners to quickly identify knowledge gaps. In traditional educational settings, expert instructors can create assessments, but in informal learning environment, it is difficult for novice learners to self assess because they don't know what they don't know. This paper introduces Questimator, an automated system that generates multiple-choice assessment questions for any topic contained within Wikipedia. Given a topic, Questimator traverses the Wikipedia graph to find and rank related topics, and uses article text to form questions, answers and distractor options. In a study with 833 participants from Mechanical Turk, we found that participants' scores on Questimator-generated quizzes correlated well with their scores on existing online quizzes on topics ranging from philosophy to economics. Also Questimator generates questions with comparable discriminatory power as existing online quizzes. Our results suggest Questimator may be useful for assessing learning in topics for which there is not an existing quiz.