Augmented reality knowledge vault for educational institutions using the Fisher–Yates shuffle algorithm

Abstract

This study evaluates the effectiveness of an Augmented Reality (AR) Knowledge Vault enhanced with the integration of Fisher – Yates Shuffle Algorithm for improving learning outcomes among undergraduate students in Educational Institutions. Fifty-five students were purposively selected and randomly assigned to experimental and control groups with 25 students in each group, yielding a final analysed sample of 50 participants. The experimental group used the AR Knowledge Vault with Fisher – Yates Shuffle Algorithm, while the control group relied on a marker-based tools system. Learning performance was assessed across three parameters: engagement, retention and motivation levels. Results showed that students in the AR Knowledge Vault with Fisher – Yates Shuffle Algorithm group achieved remarkably higher engagement and retention level (Mean Value = 74.76 and 71.34) compared to the control group (Mean Value = 59.75 and 58.21 respectively). Motivation level also increased from 6.05 to 7.58 with the AR Knowledge Vault enhanced with Fisher – Yates Shuffle Algorithm. These gains highlight the impact of interactive, varied and algorithmically structured content enabled by the Fisher – Yates Shuffle Algorithm. The system was developed using ASP.NET with C#, Bootstrap, jQuery, and SQL Server. Overall, the findings suggest that AR Knowledge Vault enhanced with algorithmic content variation can meaningfully improve learning experiences and academic outcomes.