AI Literacy for Higher Education: Hands-On Training at Fahutan IPB University
Published: October 1, 2025
Learning never stops, including for lecturers. The Department of Forest Management, Faculty of Forestry and Environment (Fahutan) at IPB University ran an AI training session led by Dr Budi Kuncahyo.
The workshop was fully interactive. Lecturers practiced real prompts and workflows for research, teaching, and community service-moving from theory to application in a single sitting.
Why this matters for educators
AI is now part of day-to-day academic work. The standout value: faster evidence gathering, clearer feedback, and repeatable workflows that reduce busywork while keeping academic standards intact.
Practical uses highlighted
- Research: literature mapping, summarizing papers, drafting methods sections, and basic code generation for data analysis.
- Teaching and assessment: lesson outlines, rubric creation, question banks, and feedback templates with citation checks.
- Community service: rapid needs assessments, proposal drafting, and translating materials for local stakeholders.
- Field and lab work: data cleaning, spreadsheet automation, and quick documentation for protocols and safety notes.
- Administration: schedule planning, email drafting, and standard operating procedures.
- Integrity and ethics: bias checks, source verification, privacy safeguards, and clear student guidance.
Inside the session
- Prompt patterns for research, teaching prep, and peer feedback.
- Hands-on data tasks: cleaning tables, generating code comments, and structuring outputs.
- Fact-checking and citations with transparent source tracking.
- Ethical use: bias, academic integrity, and fair use of training data.
- Privacy: redacting sensitive data and using institution-approved tools.
Quick-start plan for your faculty
- Pick one high-friction workflow (e.g., rubric drafting or literature summaries) and improve it with AI.
- Create a one-page policy: what's allowed, what needs citation, and what stays off-limits.
- Build a shared prompt library with 10 tried-and-tested templates.
- Run a 60-90 minute clinic per department; collect before/after time-on-task data.
- Review outputs for accuracy and bias; add source verification steps.
- Publish the playbook internally; iterate every semester.
Resources
One session can reset how a faculty works. Start small, measure gains, share what works, and keep improving with each cohort.
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