Assessment Methods


Towards artificial intelligence-based assessment systems

#artificialintelligence

In order to open this black box of learning, AI assessment systems need information about: (1) the curriculum, subject area and learning activities that each student is completing; (2) the details of the steps each student takes as they complete these activities; and (3) what counts as success within each of these activities and within each of the steps towards the completion of each activity. Specifically, it collects data about each step the student takes towards a task solution, the amount of hints or tips that the student requires to successfully complete each step and each task, and the difficulty level of each task the student completes. The AIAssess Student Model Component uses outputs from the Analytics Component to strengthen or weaken its judgement about every student's: Knowledge and understanding of each concept in a mathematics or science curriculum, by assessing each student's ability to complete a solution step, or entire task, correctly without any hints or tips. Potential for development in their knowledge and understanding of each concept in a mathematics or science curriculum, by assessing each student's ability to complete a solution step, or entire task, correctly with a particular level of hints or tips.