Design of a specialized search engine for university students dedicated to education and environment

The aim of this study is to introduce a new specialized search engine that helps university students learn about environmental issues and improve their environmental literacy. Our search engine collects information from environmental documents and scientific articles from trusted sources. After intensive word processing, it provides a list of different contexts for the terms queried, depending on the chosen field, allowing students to refine their online search. In a single operation, students can find phrases and paragraphs using multiple related terms. This model aims to generate maximum output with semantic value using minimum user input, thanks to the new search mechanism on which it is based. The search engine is optimized for environmental education, allowing students to access environmental information in their preferred language. Our work is structured as follows: first, we motivate the need for a specialized environmental education search engine. Then, we discuss the context and construction of our specialized search engine for environmental education. Finally, we review the proposed solution and conclude with future work.