Teaching Cognate Languages in Secondary Education: A Case Study on a Norwegian Language Summer School
Teaching Cognate Languages in Secondary Education: A Case Study on a Norwegian Language Summer School

Summary/Abstract: This paper examines the pedagogical potential of artificial intelligence (AI) in teaching cognate foreign languages, focusing on the acquisition of Norwegian by secondary-level learners (ages 11–16) who already possess a solid foundation in English (intermediate to upper-intermediate – B1/B2) and an elementary to intermediate level (A2–B1). Based on classroom insights from a 2021 Norwegian summer school, the paper explores how AI can enhance cognate-based language instruction, support cross-linguistic transfer, and deepen intercultural competence in both lower and upper secondary education.Cognate languages such as English, German, and Norwegian and other Germanic languages share numerous lexical, syntactic, and morphological similarities. From adidactic standpoint, these connections offer an almost ideal entry point into the acquisition of a third foreign language. AI tools can assist learners in making meaningful linguistic comparisons, promoting noticing, pattern recognition, and language awareness. It is recommendable, based on direct teaching experience, to use AI as a reflective learning support that helps learners uncover connections between related lexical items (cognates)and shared or divergent grammatical structures across the three languages.This paper is grounded in principles from plurilingual education, contrastive didactics,and task-based language teaching (TBLT). It aligns with CEFR descriptors related to language awareness, plurilingual competence, and intercultural communicative competence (ICC). It promotes guided AI use to support both receptive and productive skills, as well as critical cultural engagement. Classroom-recommended strategies include: using ChatGPT to generate contrastive dialogues or prompts in English,German, and Norwegian that highlight structural transfer points; employing Deep L or Reverso to conduct parallel translation tasks, helping students identify true and false cognates, word order patterns, and sentence structure rules; creating AI-assisted lexical comparison grids, where learners sort AI-suggested vocabulary into cognate and noncognate categories and assigning reflection tasks where students analyze how AI tools reflect cultural perspectives across the three linguistic contexts.The article also discusses how AI can support homework and autonomous learning,such as generating grammar explanation prompts in English and comparing them toAI-generated equivalents in German and Norwegian, or using conversational bots to practice oral skills with immediate lexical and syntactic feedback.

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