Course planTwo half-days · 90 min per session
IENET 2026 Academic open course
AI-Assisted Teaching & Research Open Course
From Generative AI to AI Agents: Foundations and Practice for Teaching & Research
Course formatLive online / optional in-person room
Teaching format2 instructors · 2 sessions each
For whomFaculty / researchers / graduate students / academic service staff
ParticipationFirst cohort free · 50–100 suggested
From AI foundations to your own workflow
Course overview
A public-interest, introductory AI course built around real university teaching and research tasks. Rather than stacking tools, it develops a five-step think, search, read, write and do pathway that turns one-off AI chats into repeatable workflows.
Your five-step learning pathway
- ThinkFrame the task
- SearchFind sources
- ReadRead critically
- WriteShape ideas
- DoAct and verify
Concepts & integrity
Understand AI concepts, limits and academic integrity
Prompt methods
Use task, context, constraints and output format
Research workflow
Move from topic framing to search, reading and verification
Teaching design
Build outcomes, lesson plans, cases and assessments
Agent workflows
Break down tasks, call tools, synthesize and review
Two half-days of guided learning
Four sessions. One connected workflow.
Half-day 1Foundations & research
- 01
Generative AI foundations
Concepts and limits, a tool map, four prompt elements and hands-on comparisons.
- 02
AI-assisted research, step by step
Topic framing, search, literature reading, paper structure, citation checks and research integrity.
Half-day 2Teaching & Agent workflows
- 03
AI-assisted teaching and course design
Learning outcomes, lesson plans, classroom cases, slide outlines, question banks and assessment.
- 04
AI Agents for academic workflows
Task decomposition, source reading, tool use, synthesis and human verification.
ⓘThe first half-day covers AI foundations and research; the second covers teaching and Agent workflows. Final dates will be announced on the website.
Ways to participate
Join online
Attend through the live-streaming or conference platform
Register onlineJoin in person
Attend at an on-site room for study and exchange
Register in personExample tools
DeepSeek
Kimi
Qwen
ChatGPT
Claude
Gemini
Metaso AI Search
Perplexity
Tools are compared by task; AI answers are not academic evidence and require source verification and human judgement
Core learning content
Generative AI & prompting
Concepts, limits, common pitfalls, integrity and four prompt elements
Research framing & search
Research questions, bilingual keywords, search strings and source lists
Literature & academic writing
Long-form reading, comparison matrices, research structure and citation checks
Learning design & lesson plans
Outcomes, syllabus, key concepts, classroom cases and activities
Resources & assessment
Slide outlines, handouts, question banks, assignments, rubrics and feedback
AI Agents & workflows
Task decomposition, source reading, tool calls, synthesis and human review
Who should attend
Hands-on practice
TaskOutput
Prompt iterationA complete prompt, before-and-after comparison and personal usage principles
Research breakdownKeywords, search strings, research questions and a literature reading card
Teaching planLearning outcomes, lesson plan, slide outline, question bank and assessment criteria
Agent task briefExecutable Agent instructions, results, a verification checklist and a personal workflow map
Resources and follow-up
- Course slides, four session handouts and operating guides
- AI tool list and prompt templates
- Research framing, search and literature review templates
- Paper comparison matrix and research structure templates
- Teaching plan, question bank and rubric templates
- Agent task brief and post-course feedback survey
Each session includes at least one reusable exercise, with follow-up Q&A for seven days after the course.
By the end of the course, you can
- Explain the core concepts, limits and common misconceptions of generative AI, large models and AI Agents
- Use the four prompt elements to improve a prompt and compare tool outputs
- Build a basic think, search, read, write and do workflow for teaching and research
- Produce editable research structures, teaching plans and Agent task briefs
- Apply source verification, research integrity and human judgement in AI-assisted work
Bring AI into your academic work
4 sessions · Two half-days · First cohort free
Open to university faculty, researchers, graduate students and academic service staff. Delivered mainly online, with an optional in-person venue.