JSBJ2270 Using Generative AI in Research (3 op)

Avaa opintojakson esite Sisussa
Opinnon taso:
Jatko-opinnot
Arviointiasteikko:
0-5
Suorituskieli:
englanti
Vastuuorganisaatio:
Jyväskylän yliopiston kauppakorkeakoulu
Opetussuunnitelmakaudet:
2025-2026, 2026-2027, 2027-2028

Kuvaus

Instruction and examination: The course is structured as a two-day intensive workshop with additional pre- and post-course assignments. Each day runs  from 9:15 to 17:00 and includes:
  • Interactive lectures on key topics
  • Guided hands-on exercises using various AI platforms (e.g., Claude, GPT-4,
  • and Gemini)
  • Small group discussions and collaborative problem-solving
  • Practical demonstrations of research-specific AI applications

The course will cover practical applications of AI such as:

  • Visualization of regression results
  • Full analysis of datasets
  • Grounded theory analysis using interview data
  • Coding of large numbers of survey responses
  • Improving academic writing
  • Ideating discussions sections
  • Writing feedback to students
  • Grading exams and assignments
  • Automating work with coding agent Cline and using GitHub Copilot

Practical activities will include:

  • Setting up and using Ollama to run open-source LLMs locally (such as Gemma, Llama, and DeepSeek)
  • Creating effective research-oriented prompts for different AI models
  • Accessing and utilizing API endpoints with provided API keys to complete practical research tasks
  • Testing special-purpose AI tools (e.g. Deep Research)
  • Comparative analysis of different AI models for specific research tasks
  • Guided programming exercises in Python (no prior programming experience required)
A course dinner will be arranged between the two workshop days to facilitate networking and informal discussion.

Osaamistavoitteet

Learning goal and objectives: This course aims to provide doctoral students with hands-on experience and practical skills in leveraging Large Language Models (LLMs) for various aspects of academic research. The course is designed to accommodate both beginners and those with some AI experience. By the end of the course, students will be able to:
  • Understand the fundamental principles, capabilities, and limitations of generative AI and LLMs
  • Apply appropriate AI tools ethically and effectively across different research phases
  • Develop critical skills in prompt engineering for research-specific tasks
  • Implement AI-assisted workflows for literature reviews and academic writing
  • Utilize AI tools for both quantitative and qualitative data analysis
  • Evaluate the ethical and legal implications of AI use in academic contexts
  • Set up and use local LLM installations for research privacy and customization
  • Creatively and critically evaluate when and how AI tools can enhance specific research processes

Lisätietoja

KATAJA course. 

Completion method: participation in teaching and independent assignment

Assessment will be based on:
  • Pre-course assignment: Reflective essay (1000-1500 words) based on provided readings about AI in academic research (20%)
  • Active participation during the workshop (40%)
  • Post-course assignment: Critical reflection on potential applications of AI in the student's field or a small practical experiment with an AI tool of choice, documented with screenshots and analysis (40%)

Accepted participants will receive a reading package containing articles, book chapters, and videos on using AI that should be completed before the course.

Suoritustavat

Tapa 1

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Osallistuminen opetukseen (3 op)

Tyyppi:
Osallistuminen opetukseen
Arviointiasteikko:
0-5
Suorituskieli:
englanti

Opetus