🤖 AI Summary
This study addresses the insufficient AI literacy among language-oriented professionals in translation and specialized communication by designing and implementing the first systematic AI curriculum tailored for non-technical language service practitioners. The course covers foundational concepts including vector embeddings, tokenization, neural network basics, and the Transformer architecture, aiming to cultivate computational thinking, algorithmic awareness, algorithmic agency, and digital resilience. Implemented within a master’s program at TH Köln (Cologne University of Applied Sciences), the curriculum demonstrated pedagogical efficacy, with findings indicating that advanced instructional scaffolding—such as direct instructor support—is essential to further enhance learning outcomes. This work thus offers an innovative paradigm for integrating AI literacy into language service education.
📝 Abstract
This paper presents a technical curriculum on language-oriented artificial intelligence (AI) in the language and translation (L&T) industry. The curriculum aims to foster domain-specific technical AI literacy among stakeholders in the fields of translation and specialised communication by exposing them to the conceptual and technical/algorithmic foundations of modern language-oriented AI in an accessible way. The core curriculum focuses on 1) vector embeddings, 2) the technical foundations of neural networks, 3) tokenization and 4) transformer neural networks. It is intended to help users develop computational thinking as well as algorithmic awareness and algorithmic agency, ultimately contributing to their digital resilience in AI-driven work environments. The didactic suitability of the curriculum was tested in an AI-focused MA course at the Institute of Translation and Multilingual Communication at TH Koeln. Results suggest the didactic effectiveness of the curriculum, but participant feedback indicates that it should be embedded into higher-level didactic scaffolding - e.g., in the form of lecturer support - in order to enable optimal learning conditions.