Pedagogical design of intelligent models for teaching foreign languages

• Group assignment #1: create an online terminology glossary AI in language learning in Russian and English
• Group assignment #2: Compare and contrast various intellectual language learning models, analyze Russian and foreign experiences, create a presentation
• Round table discussion #3: Neurolinguodidactics in Language Education: investigate the multidisciplinary character of neurolinguodidactics, with an emphasis on its pedagogical, psychological, and linguistic and neurolinguodidactic principles
• Group Case #4: Work out an Ethical Code for the Use of AI in Foreign Language Education Based on UNESCO Documents: AI and Education: Guidance for Policymakers (2021)
• Group Case Study: Analyze the effectiveness of AI in language learning: Choose a published study that examines AI's impact on language acquisition, summarize the findings and reflect on how these insights could apply to your teaching practice.
• MIDTERM TEST on theoretical issues and terms
• Individual Assignment #5: create an adaptive lesson plan/polymodal activity with the help of AI tools for various levels of language proficiency (CEFR). Comment on the pros and contras of the plan creation with the help of AI
• Group case #6: create a voice agent bot for boosting interaction and debate skills in foreign languages on Google Colab
• Group Case Study #7: Analyze a dataset of student performance on our Moodle using an analytics tool and discuss findings in small groups
• Group Research Project Using Research Rabbit #8: Use categories to group different aspects of your research project. Create collections for individual topics or papers, add key papers, search for titles, DOIs, keywords, and use network visualization feature to see how different papers are connected through citation and collaboration
• Group Case Study #9 Utilizing Intelligent books in language learning: Choose an intelligent textbook, explore its AI capabilities and didactic potential, create a lesson plan with the help of Teachguin.ai that incorporates its didactic potential
• Group Case Study #10: Developing a Metacognitive Scaffolding Model for a Tutor Bot: Review theoretical sources on the topic; based on the proposed algorithm, develop a metacognitive scaffolding model for a tutor bot designed for a specific language course and target group
• Final Group Project Pedagogical Design of Intelligent Models for Teaching Foreign Languages: Choose one of the intellectual learning models discussed in the course and design an AI-Enhanced Instructional Model for a specific language course and target group featuring adaptiveness, polymodality and metacognitive scaffolding, immediate feedback

Requirements for completing the course:

English language proficiency level not lower than B2, completion of the following disciplines – History of foreign language teaching methods, Methodology of teaching foreign languages at a university, Pedagogy.

Topic 1. Typology of AI-based tech solutions used in foreign language education for: 1. Teaching in language class; 2. Organization and control of didactic process; 3. Language courses management and analytics

Topic 2. Types of intelligent learning models in language instruction: immersive metaverses, intelligent conversation systems, intelligent research environment, digital tutors, intelligent learning systems and intelligent assessment systems

Topic 3. Basic principles of pedagogical design of intelligent learning models: psychological, pedagogical, linguistic, and neurolinguodidactic principles of developing intelligent learning models; adaptiveness, polymodality and metacognitive scaffolding, immediate feedback as the main neurolinguodidactic principles of pedagogical design of intellectual learning models

Topic 4. The ethical and legal implications of implementing AI in the classroom. An overview of national and international regulations regarding the use of AI in education. Responsibility and ethics in AI usage. Risks of information leakage and how AI gathers and analyzes student data. Creation of guidelines for the moral use of AI

Topic 5. The Pedagogical design of polymodal AI-supported materials for adaptive learning: activities, lesson plans, syllabus. Strategies for integrating AI-generated materials into coherent syllabi. Balancing traditional pedagogical approaches with innovative AI solutions. Syntx AI; Jarvis AI; ChatGPT 4/Midjourney; MidJourney 6v.1 Bot @midjorobot: analysis of functionalities and didactic potential. The practical use of AI tools for polymodal materials (Kandisky, Stability AI https://stability.ai/, Synthesia, Kapwing https://www.kapwing.com/). Analysis of Russian educational practices: Kandisky and Teachguin.ai. Hands-on workshop introducing Teachquin.ai (RF)

Topic 6. The pedagogical design of intelligent dialogue models and digital tutors for personalized learning: theoretical foundations of intelligent dialogue systems, analysis of various chatbot frameworks. Comparative analysis of chatbot frameworks based on functionality and user experience. Dialogue agents based on AI for developing interaction skills. Review of foreign educational models utilizing AI dialogue systems LJ Dataset Speech; Stellar AI; Speechling; @AI English Tutor. Examination of Russian initiatives in digital tutoring and chatbot use SpeakMate (RF). Hands-on workshop introducing Google Colab

Topic 7. The pedagogical design of intelligent assessment systems: current, midterm, final assessment, reflection, and feedback. Implementation of peer-assessment and self-assessment based on AI (Essay Grader; AcademicGPT; OpenEssayist). Tools of Learning Analytics such as Tableau, Google Data Studio. Analysis of Russian (HSE) and foreign experience (IBM, Pearson). Predictive analytics tools for education, such as Civitas Learning. Hands-on workshop introducing AI tools on assessment and feedback

Topic 8. The Pedagogical design of Intelligent Research Environments for Language Learning: Enhancing Creativity and Analytical Thinking through AI Tools: Perplexity, Research Rabbit; YouNote; YouNote; Consensus; Elicit. Hands-on workshop on Research Rabbit that can assist in curating research materials and enhance collaboration and creativity

Topic 9. Specific features of Intelligent Textbooks incorporating AI (iTell models from AI-ALOE): personalized learning paths; interactive content; instant activity creation; real time feedback; integration with other tools: Pearson MyLab; McGraw-Hill; Houghton Mifflin Harcourt's Journeys; Cengage MindTap offer quizzes, interactive exercises that adapt to student performance; track student progress and engagement; provide instant feedback

Topic 10. Pedagogical design of intelligent learning systems (Carnegie Learning). Designing metacognitive scaffolding strategy for intelligent learning systems. Use of Corpus Data for language learning English Corpora; Flexible Language Acquisition; Kontext; Linggle; Michigan Corpus)

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