2025/2026
Генеративный искусственный интеллект в образовании
Статус:
Маго-лего
Кто читает:
Департамент образовательных программ
Где читается:
Институт образования
Когда читается:
2 модуль
Охват аудитории:
для всех кампусов НИУ ВШЭ
Язык:
английский
Кредиты:
3
Контактные часы:
28
Course Syllabus
Abstract
This course provides a comprehensive introduction to the applications of generative artificial intelligence (Gen-AI) in education. Designed for students interested in how Gen-AI can enhance teaching and learning practices, it emphasizes both research perspectives and practical applications, including ethical considerations. Throughout the course, students will develop research competencies relevant to the study of Gen-AI in education. They will examine distinctions between Gen-AI and other types of AI, explore the scientific landscape of Gen-AI research, and learn to identify knowledge gaps. The course includes practice in formulating research questions and introduces key methodological approaches for investigating this technology. Students will engage with both quantitative and qualitative research tools, such as key metrics, measurement models, interview guides, and reflective diaries. Theoretical frameworks relevant to Gen-AI in education will also be explored, allowing students to connect theory with methodology. The course incorporates best practices for using Gen-AI in educational contexts, including hands-on experience with prompt design and the use of various Gen-AI tools for academic tasks. By the end of the course, students are expected to acquire the skills needed to conduct independent research and to develop a framework for their own research project in the field of Gen-AI in education.
Learning Objectives
- Introduce the distinctions between AI and Gen-AI, with a focus on their applications and implications in educational settings
- Develop students' research competencies, including identifying gaps in Gen-AI research, formulating research questions, and selecting suitable qualitative and quantitative methods
- Foster the integration of theory and methodology, enabling students to apply educational theories when designing and conducting research on Gen-AI
- Enhance practical and ethical awareness, through hands-on work with Gen-AI tools (e.g., prompt design, tool comparison) and critical reflection on the ethical dimensions of Gen-AI use in education
Expected Learning Outcomes
- IL1. Differentiate between artificial intelligence (AI) and generative artificial intelligence (Gen-AI)
- IL2. Identify and evaluate Gen-AI tools applicable to the study process and academic tasks in educational contexts
- IL3. Describe and analyse current research trends in the field of Gen-AI in education and identify knowledge gaps
- IL4. Formulate research questions based on a critical analysis of existing gaps in Gen-AI in education literature
- IL5. Choose relevant theoretical frameworks to investigate Gen-AI in education and justify their use in a chosen research context
- IL6. Design and conduct qualitative research using methods such as interviews, reflective diaries, and AI-generated log analysis
- IL7. Apply quantitative research methods, including surveys and regression analysis, to investigate the impact and use of Gen-AI in education
- IL8. Demonstrate the use of prompt engineering techniques and evaluate prompts potential as educational tools
- IL9. Analyse the use of Gen-AI in educational product development and propose appropriate applications for learning contexts
- IL10. Address ethical considerations related to the use of Gen-AI in educational research and practice in planned research framework
Course Contents
- Understanding differences and similarities between AI and Gen-AI
- Overview of Gen-AI tools
- Mapping Gen-AI in education via digital tools
- What is studied in the field of Gen-AI in education
- Gen-AI and the cognitive perspective: the encoding-storage paradigm in collaborative learning
- Gen-AI and the constructivist perspective: sociocultural theory, scaffolding, and over-scaffolding in group work
- Qualitative methods for studying Gen-AI in education: interviews, reflections, and AI interaction logs
- Quantitative methods for studying Gen-AI in education: surveys, measurement models; mediation, moderation, regression analysis
- Understanding prompting in educational contexts: research overview
- Developing effective Gen-AI prompts: strategies and practice
- Exploring Gen-AI-based products in EdTech
- Designing educational products using Gen-AI: group work and presentation
- Understanding Gen-AI ethics through real-world case studies
- Gen-AI and ethics: group discussions and creating a set of regulations
Assessment Elements
- Getting around Gen-AI conceptually and practically
- Mapping scientific landscape & Gap identification
- Theoretical framework application
- Data collection protocol outline
- Prompt engineering portfolio & analysis
- Designing EdTech product
- Designing ethical protocol
- Final assignment
- Participation
Interim Assessment
- 2025/2026 2nd module0.1 * Data collection protocol outline + 0.1 * Designing EdTech product + 0.1 * Designing ethical protocol + 0.2 * Final assignment + 0.1 * Getting around Gen-AI conceptually and practically + 0.1 * Mapping scientific landscape & Gap identification + 0.1 * Participation + 0.1 * Prompt engineering portfolio & analysis + 0.1 * Theoretical framework application
Bibliography
Recommended Core Bibliography
- A guided tour of artificial intelligence research. Vol. 1: Knowledge representation, reasoning and learning, , 2020
- Generative artificial intelligence : what everyone needs to know®, Kaplan, J., 2024
- Great philosophical objections to artificial intelligence : the history and legacy of the AI wars, , 2021
- Haenlein, M., & Kaplan, A. (2019). A Brief History of Artificial Intelligence: On the Past, Present, and Future of Artificial Intelligence. California Management Review, 61(4), 5–14. https://doi.org/10.1177/0008125619864925
Recommended Additional Bibliography
- A guided tour of artificial intelligence research. Vol. 2: AI algorithms, , 2020