Enhancing Misinformation Identification And Correction With The Contextual Cognitive Reinforcement Algorithm (CCRA)

Abstract

As misinformation becomes more widespread due to the increased usage of technology, this work proposes a new game-based learning framework with the CCRA to increase students’ resistance to fake news. In contrast to the adaptation’s approaches, CCRA uses contextualize analysis, reinforcement learning, and behavioural knowledge to operate over realistic misinformation scenarios. The algorithm adapts game features according to how a player processes information and responds; contains contextual cues correlated with players’ actions in the game. The impact of CCRA is analysed in the quasi-experimental research conducted with 240 8th and 9th-grade students. Users are split into three groups, Control group playing non-adaptive misinformation game, a second group playing basic adaptive game and a third group playing adaptive game powered by CCRA. It puts importance to feedback loop, dynamic scenario adaptation and real time correction plans. The learning outcomes are evaluated with the use of pre- and post-football game tests that look for increases in discernment accuracy, usage of cognitive strategies and behavioural changes. Experimental results show that playing the game with CCRA yields a substantially better result in comparison to other models, reaching the rate of 94% in the ability to recognize misinformation against 78% of the non-adaptive games and 86% of the basic adaptive games.   As such, these results shed light on the capability of contextual reinforcement and behavioural feedback in the MIS information game. This study offers a rich idea for educators to help students to develop critical thinking and understand the primary and complex uses of technology through an approach that focuses on the real-world context of learning.