AI for Educators: Innovative Tools Revolutionizing Education（教育工作者的人工智能：革新教育的创新工具）

Overzicht

Who is this course for?— Educators and researchers seeking to reduce time spent on routine tasks— University instructors looking to diversify classes with digital toolsWhat does the course include?Core Module:

— How neural networks work:

from machine learning to text generation— Avoiding pitfalls:

why AI makes mistakes and how to spot them— Ethical dilemmas:

copyright issues and academic integrity— Prompt engineering workshop:

learning to communicate with neural networksSpecialized module for university educators & researchers:

— Automating routine tasks:

grading assignments, generating tests, designing courses— Replicable examples of AI integration in the classroomThe course features interviews with practitioners sharing real-world experiences of implementing AI technologies in education.What will you learn?Effective AI collaboration:

— Distinguish reliable results from erroneous conclusions— Apply specialized platforms for research and text analysisAutomate routine work:

— Delegate standard (and non-standard) tasks to AI— Structure information and extract dataCreate innovatively:

— Generate personalized assignments— Make the mundane exciting through interactive formatsMaster key tools:

— Generative AI Assistants:

DeepSeek, Perplexity, Qwen, Mistral, YandexGPT, GigaChat, Neuro, LLM Arena.ru— Academic Research Tools:

Scite.ai, Undermine, Litmaps, Research Rabbit— AI-Powered Education Platforms:

Twee, Brisk Teaching, Magic SchoolYou’ll master neural networks not as a trend, but as a practical tool—with full awareness of their capabilities, pitfalls, and ethical boundaries.The course is taught online and includes recorded lectures, tests, and additional materials.Upon completing the course, participants will:

Know:

The fundamental principles of how neural networks operateThe capabilities and key application areas of AI technologies in educationThe limitations and potential risks of using AIThe main categories and examples of modern AI tools for educationPrinciples of effective interaction with AI systems (including the basics of prompt design)Ethical dilemmas and legal aspects related to AI use in academiaBe able to:

Critically evaluate AI-generated results:

distinguish reliable information from erroneous conclusionsFormulate effective prompts to solve various educational tasks using generative assistantsApply specialized AI tools for research activities (literature search, source analysis, visualization of connections)Use AI to automate routine tasks (structuring information, data extraction, test generation, grading standard assignments, course element design)Generate personalized learning materials and assignments with AICreate interactive and creative learning/working formats using AIAssess the feasibility and effectiveness of specific AI tools for solving given educational or research tasksPossess:

Skills in effective interaction with generative conversational assistants for tasks such as:

automated grading, test and assignment generation, course design, and research optimizationProficiency in using research tools for analyzing scientific literature and supporting academic researchCompetence in working with AI-powered educational platforms to optimize teaching practicesMethods for integrating AI tools into the educational process, considering their capabilities, limitations, and ethical normsAn approach to using neural networks as a practical tool while being aware of their boundaries

Lesprogramma

• Module 1. Course Introduction
What Is This Course About?
Introduction. Reasons for Techno-Optimism
Introduction. Regional Polarity of Opinions
• Module 2. Psychological Aspects of Interacting with AI
Psychological Aspects of Interacting with AI
• Module 3. AI Fundamentals
Fundamentals of Artificial Intelligence and Machine Learning
Knowledge, Knowledge Bases, Knowledge Graphs
• Module 4. Generative AI: Large Language Models (LLMs)
How AI Understands and Generates Text
Basics of Prompting for Text-Based AI Assistants
• Module 5. Ethics and Legal Aspects of AI Development and Use
Legal Regulation of AI
Ethics and Policies for AI Use
• Module 7. Using AI in Research. Part 1
Using AI in Research Activities Without Violating Ethical Requirements
Approaches to Boosting Research Productivity
• Module 8. Using AI in Research. Part 2
Conducting Literature Reviews Using AI Assistants
AI Assistants for Analyzing Scientific Texts and Data
• Module 9. How Neural Networks Support Educators
Preparing for Class and Designing Materials
Examples of Using AI in Class That You Can Replicate
• Final Exam

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Gegeven door

Anna N. Sytnik , Tatyana A. Gavrilova, Sergey Yu. Sevryukov, and Aleksandra K. Bordunos

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Vakgebieden

Artificial Intelligence