yuriyajp/class-feedback-nlp-database-japanese

A dataset derived from students' feedback answers on class projects' levels of difficulty.

Enhancing English Learning Experience through Student Feedback

Overview: Here you can see how I've collected data feedback from 120 students who participated in my English class. The goal was to compare their experiences of the class and its 4 seasonal projects and use NLP technologies to visualize the findings.

Data Collection:

I had the privilege of teaching these 120 students over the course of one year, from 2022 to 2023, in a public high school. Our curriculum featured four major projects, and each student had the opportunity to share their thoughts on these projects. We delved into various aspects like project simplicity, implementation, usefulness, and recommendations for future improvements. To ensure an efficient data collection process, students answered in Japanese, using an online Google form, and the responses were seamlessly stored in an Excel file.

Goals:

The primary objective of this project is to create a feedback-driven learning environment. By accumulating and analyzing this rich feedback, I aim to tailor future projects to meet students' preferences and requirements. Each project's responses have unveiled key challenges, allowing us to refine recommendations for an even better learning experience. My hope is that this endeavor will inspire educators to listen more closely to their students, fostering a culture of continuous improvement and constructive feedback.

Key Tools:

• Nagisa Library: Used for Japanese text tokenization.
• Pandas
• Unidic Japanese Dictionary: Sourced from the Amazon Web Services Open Data Sponsorship Program.
• Jupyter Notebook: