Optimize Student Learning through Personalized Instruction and Need-aware Gaming (PING)

Ying Tang
Rowan University

Need: Continuing efforts to increase the quality of student education has led to an increasing need for automated systems that can personalize a student’s learning experience. However, instructors and educational institutions cannot often implement fully personalized lesson plans due to time and resource constraints, especially with increased sizes of modern classrooms and online learning. This project addresses the need for an automated personalized learning system through a modular framework for an educational game system. By attaching our modular framework to a pre-existing educational game, we create an automated game system that can address the need of personalized education without instructor intervention, ultimately improving the efficiency of student education and lessening the workload on instructors. Additionally, attaching the system over top of an educational game serves to both improve a student’s learning experience and increase their engagement with the subject matter presented.

Guiding Question: The system was developed and tested with the following research questions in mind:
1. Does the system improve a student’s learning experience and classroom performance?
2. Can the system provide personalized learning assistance that is accurate to a student’s needs and helpful to them in their learning?

Outcomes: Throughout testing of a game integrated with our modular framework, we will measure the game’s impact on students’ learning experiences in a real classroom setting. To do so, we will compare student performance both in terms of content tests and opinion surveys to verify that the game improves a student’s learning experience. We will also provide a full write-up of our game system, allowing other researchers to integrate our personalized educational framework in their own games or subjects.

Broader Impacts: Upon completion and final testing of the modular framework, we hope to achieve more widespread adoption of our personalized educational system. Using an augmented game in conjunction with lesson plans or project work, we will provide personalized lessons without the need for instructor intervention. Widespread adoption would free up instructor resources and increase the effectiveness of student learning.


Ryan Hare