Systematic Review Of Collaborative Learning Activities For Promoting AI Literacy

TL;DR

This systematic review evaluates how collaborative learning activities enhance AI literacy, analyzing nine studies from 2015 to 2023 using the ICAP framework, and finds CL effective across diverse settings and groups.

Contribution

It provides a comprehensive analysis of CL's effectiveness in improving AI literacy through a systematic review and theoretical framework application.

Findings

CL effectively increases AI literacy across various activities and settings.

Most studies involved classroom environments, with some expanding to broader participation.

All ICAP modes were represented in instructional activities.

Abstract

Improving artificial intelligence (AI) literacy has become an important consideration for academia and industry with the widespread adoption of AI technologies. Collaborative learning (CL) approaches have proven effective for information literacy, and in this study, we investigate the effectiveness of CL in improving AI knowledge and skills. We systematically collected data to create a corpus of nine studies from 2015-2023. We used the Interactive-Constructive-Active-Passive (ICAP) framework to theoretically analyze the CL outcomes for AI literacy reported in each. Findings suggest that CL effectively increases AI literacy across a range of activities, settings, and groups of learners. While most studies occurred in classroom settings, some aimed to broaden participation by involving educators and families or using AI agents to support teamwork. Additionally, we found that instructional activities included all the ICAP modes. We draw implications for future research and teaching.