When studying for exams, sometimes, students are expected to prepare by solving examples. Similarly, whenever a student does not feel confident about a particular subject, making practice by solving relevant examples is suggested. However, in such cases, finding the right set of questions may not be so easy. That is, identifying relevant questions may end up being overwhelming due to the abundance and complexity of resources. Moreover, in most cases, students may have limited time to study. As a consequence, they may not have enough time to scan all the resources to select relevant questions. Given this problem, we proposed a system named “Que-Base”, for which the details are discussed next.
Que-Base is a web-based application that uses natural language processing (NLP) to help students find relevant study material. Specifically, given a particular question, Que-Base identifies questions that are similar to the provided one. It scans both online resources and course textbooks to bring relevant questions. The ultimate goal of the system is to analyze questions from plenty of resources in a short amount of time and, eventually, facilitate the process of studying.
- Abdullah Ercüment Çiçek (supervisor)
- Fazlı Can (jury member)
- Özcan Öztürk (jury member)
More detailed information can be found on reports of the project in the following link: Que-Base