Using a Study Planner with Predictive Analytics: Exploring the Effects on Academic Performance and Time Management: A Systematic Review

Abstract

This study examines the impact of a data driven study planner with predictive analytics on students' academic performance and time management to find out the effect of the innovation. The research aims to determine the effectiveness of task tracking and time management tools in improving the time management skills of students which improves academic success. The analysis of students' performance by using predictive analytics includes examining students' academic behaviour, interaction patterns and the advantages they get from the study planner. The study also identifies the advantages and the limitations of the planner and focuses on preventing the students from falling behind in their work by offering personalized insights and visualizations that align with the study patterns of each individual and provide the required motivational support. Additionally, the research explores the role of innovative testing methods to improve academic outcomes and provide suitable suggestions to enhance and develop study planners with new critical features.