AI and the Future of Learning: Expert Panel Report

Abstract

This report is based on the discussion that emerged from a convening of a panel of 22 experts in artificial intelligence (AI) and in learning. It introduces three layers that can frame the meaning of AI for educators. First, AI can be seen as “computational intelligence” and capability can be brought to bear on educational challenges as an additional resource to an educator’s abilities and strengths. Second, AI brings specific, exciting new capabilities to computing, including sensing, recognizing patterns, representing knowledge, making and acting on plans, and supporting naturalistic interactions with people. Third, AI can be used as a toolkit to enable us to imagine, study, and discuss futures for learning that don’t exist today. Experts voiced the opinion that the most impactful uses of AI in education have not yet been invented. The report enumerates important strengths and weaknesses of AI, as well as the respective opportunities and barriers to applying AI to learning. Through discussions among experts about these layers, we observed new design concepts for using AI in learning. The panel also made seven recommendations for future research priorities.

AI in learning

“…In their report, the research panel mentioned earlier (Roschelle et al, 2020) describes how deep learning algorithms perform feature extraction in an automated way, which allows researchers to extract discriminative features with minimal domain knowledge and human effort. They summarize that from the eyes, while the output is the classified objects.…”

“…The panelists (Roschelle et al, 2020) describe recent developments in the multimodality of data, which goes beyond observing what students type on a computer or how they answer questions. Newer research-based systems can listen to recordings or watch videos of classrooms, finding events that are significant for learning outcomes (e.g.…”

“…In many countries, school leaders are also seeking to understand how new AI capabilities could become a reality in education and what should be taken into account in future planning (Wong, 2018;Roschelle et al 2020). The following themes are in discussion:…”

“…In spite of their differences, the common visions have the following elements: AI means computational intelligence. Intelligent machines can examine data, make inferences, and then act by themselves (Roschelle et al, 2020). Many definitions also refer to machines as learning entities because they can adapt themselves to new tasks and make inferences based on interactions with other data-providing entities as well as with human beings.…”

“…In their report, the research panel mentioned earlier (Roschelle et al, 2020) describes how deep learning algorithms perform feature extraction in an automated way, which allows researchers to extract discriminative features with minimal domain knowledge and human effort. They summarize that These algorithms include a layered architecture of data representation, where the high-level features can be extracted from the last layers of the networks while the low-level features are extracted from the lower layers.…”