Integrating Natural Language Processing into Research-Based Teaching and Learning for Developing a Swahili Corpus

Natural language processing is a machine-learning technique that encompasses multiple topics and tasks related to data and information management, ultimately enhancing the value of the teaching and learning process. Research-based teaching and learning is a constructive approach in which students learn through research, and instructors support the process by teaching in a way that does not present topics as closed but instead opens them up for students to explore and research. This technique motivates students to learn collaboratively and communicate effectively. This study aimed to employ a new research-based teaching approach in the NLP domain for third-year students who opt for advanced topics in computer science courses, thereby enhancing their learning experience. Initially, the course only provided a basic foundation in research. For the last two academic years (2021/2022 and 2023/2024), the module was dedicated to the current university effort to develop the Swahili Language corpus. In the new approach, teams of students are provided with topics, basic guidelines, and other aids to help work with different areas of research in the Swahili Language structures. Student teams then deployed various libraries, tools, methods, and algorithms to solve the task of Swahili text summarisation using big data, which is an ideal problem for addressing NLP in learning. Incorporating these research-focused teaching and learning methods has empowered students to become critical thinkers, influential researchers, and lifelong learners. The outcome is a coherent and readable summary of research reports, ranging from 3000 to 5000 words, based on the designed template and algorithms. The adoption of a new teaching method suits the specific subject matter by establishing a baseline that serves as a blueprint for the comprehensive development of the Swahili language corpus