TIME SAVINGS CALCULATION IN TEST CREATION USING ARTIFICIAL INTELLIGENCE

Abstract

Distance learning has been evolving for many decades, but it garnered significant attention with the onset of the COVID- 19 pandemic when quarantine restrictions were implemented worldwide. As a result, the integration of this type of learning into traditional face-to-face education was expedited. Distance learning, with its flexibility, allowed for the continuation of the curriculum and learning almost on a self-paced schedule. However, while listing the advantages of distance learning, it also has negative impacts on health, such as deteriorating eyesight, posture, and psychological aspects. Distance learning offers numerous advantages over traditional classroom attendance, as materials can be studied anywhere, and if something is not understood, it can be reviewed again. Additionally, lectures and assignments can be downloaded to devices, allowing learning without the need for light or the internet. During distance learning, testing in the form of quizzes becomes increasingly common and relevant. The time savings calculation in test creation using artificial intelligence is an important aspect of our study. By leveraging AI algorithms, we aim to streamline the test creation process, reducing the time and effort required from instructors. This involves developing a mathematical model to quantify the amount of time saved when utilizing AI compared to traditional manual test creation methods. The results of this calculation will provide valuable insights into the efficiency gains offered by AI in educational settings, ultimately contributing to the advancement of technology-enhanced learning methodologies. This study developed a mathematical model to calculate time savings in test creation using artificial intelligence compared to manual test creation by instructors. The research showed that this approach can achieve time savings of more than 60%. The study also presents the implementation of test creation using both proposed methods (with and without AI) in a system developed using the Laravel framework. The results obtained confirm the feasibility and effectiveness of using AI in test development.