15-week digital literacy curriculum integrating GenAI tool usage with research ethics and critical thinking¶
Design · All designs
Evidence · 1 claim (1 mixed) · 2 studies (2 associational),q2· 0 of 2 report an effect size
Description¶
A lightning talk by Jiwoo Seo described a "15-week digital literacy curriculum" co-developed during their tenure as an AI Specialist Librarian at Chung-Ang University, "based on a survey of 2,076 students and 101 librarians". The curriculum addressed a critical gap by integrating GenAI tool usage with research ethics and critical thinking skills. It emerged from observing a trust gap in which students often over-trusted GenAI while faculty distrusted it, and it aims to empower users to act as critical reviewers rather than passive consumers.
Design Implications¶
Context¶
Requirements¶
- sustainable educational frameworks that adapt to rapid AI advancements, since single-session workshops are insufficient
Constraints¶
Target Learners¶
- university students and librarians
Learning Goals¶
- GenAI literacy, research ethics, and critical thinking for academic search
Claims¶
Related Designs¶
Examples¶
-
Key Sources¶
- Yifan Liu, Jaime Arguello, Orland Hoeber, Chang Liu, Soo Young Rieh, Luanne Sinnamon, et al. (2026). Report on CHIIR 2026 Workshop on Generative AI and Academic Search (GAI&AS). ACM SIGIR Forum. https://arxiv.org/abs/2606.08936
Page metadata
| Field | Value |
|---|---|
type |
design |
id |
15-week-genai-digital-literacy-curriculum |
title |
15-week digital literacy curriculum integrating GenAI tool usage with research ethics and critical thinking |
description |
A lightning talk by Jiwoo Seo described a "15-week digital literacy curriculum" co-developed during their tenure as an AI Specialist Librarian at Chung-Ang University, "based on a survey of 2,076 students and 101 libr... |
status |
review |
generated |
by process:settle-candidates on 2026-10-10 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — yifan-liu-2026 |
Frontmatter is the page's machine-readable record — see the Schema & Guide.