Abstract:

Artificial Intelligence (AI) has significantly transformed various aspects of life by enabling the creation of human-like digital content. Despite some resistance, such as bans in some colleges and universities, the Austrian Federal Ministry of Education is advocating for AI's integration into the education system from an early age. To support this, a web application is being developed to help integrate AI into language and (social) media education in a positive manner by analyzing literary data and identifying trends.

This Austrian educational initiative intends to demystify AI for non-technical audiences, particularly making it easily accessible for language teachers and their students. The project involves developing a web application that uses AI for text analysis, including a Named Entity Recognition (NER) model and scraping algorithms for content collection. The application aims to facilitate the analysis of extensive literary data, enabling the extraction of trends and topics, thereby enhancing AI’s role in education and addressing its challenges.

The approach outlined in the abstracts was managed through a project-based learning initiative at a vocational high school, spanning an entire academic year. Students were engaged in the hands-on development of a web application aimed at making AI more accessible and understandable for their peers and language teachers, while delving deeper into the technology of topic modeling, web scraping to gather news articles as well as literature data, data storage and providing API frameworks which were part of one of two thesis projects strongly interconnected with each other. The other project focused on collecting and formatting text data, implementing a Named Entity Recognition (NER) model and performing topic recognition based on automatized prompt engineering, providing an interactive web app which allows for exploration of news media and literature.

The students involved in the projects gained practical experience in AI and web development, learning to collect, format, and store text data for analysis. They implemented a adapted language models, compared data stores and API frameworks and developed scraping algorithms. The resulting web application serves as an educational tool for analyzing literary and news media data, applying AI to identify trends and topics with a Shiny framework frontend. In addition to students learning outcomes, the project reached its goal to develop a web app that enables the analysis of historical text data, facilitating the integration of AI into language education and making AI (beyond generative AI) more approachable for non-technical users in education.

In conclusion, this project is a valiant educational initiative by the Austrian Ministry of Education to integrate Artificial Intelligence (AI) into language teaching. Executed by vocational high school students through project-based learning, it resulted in the creation of a web application that leverages AI for the analysis of literary texts. The application, which includes features like Named Entity Recognition (NER), automatized topic modeling and an interactive shiny frontend, aims to clarify the complexities of AI for non-technical users without delving too deeply under the surface and enhance its accessibility as well as positive perception among educators.

Keywords:

Artificial intelligence, natural language processing, interactive web application, project-based learning, software development, educational technology, literary data analysis.