Before You Share: An Information Literacy Lab

Goals

Design Goals- Enable learners to slow down, investigate a claim, and justify a sharing decision using source-                     based evidence rather than surface cues. 

Learning Objectives- By the end of the experience, learners should be able to: 

• Identify the specific factual claim in a social media post.

• Inspect source documents for issuer, date, scope, and relevant details. 

• Classify information as accurate, misinformation, or disinformation based on available evidence. 

• Justify a classification with evidence and avoid attributing intent without proof. 

Design Process

Analysis- Targeted the gap between recognizing media-literacy terms and actually verifying realistic digital claims. 

Design- Mapped outcomes to modeled, coached, and independent tasks; made the reasoning process visible before assessment. 

Development- Created social-feed simulations, linked fictional sources, branching feedback, responsive screens, and a three-case independent assessment. 

Implementation- Published a working prototype on Netlify. A representative-learner pilot has not yet been conducted. 

Evaluation- Planned pre/post scenario comparison, human-scored evidence rubric, usability testing, and learner feedback; no learning-gain data are claimed.

Assessment & Feedback- The independent section scores three classifications. Written explanations are required        and receive case-specific keyword-based reflection cues. These cues do not measure reasoning quality; a human-scored rubric is recommended for a future evaluation study. The prototype does not claim demonstrated learning gains. 

Accessibility & Usability- The experience uses a responsive layout, readable contrast, descriptive interface labels, and browser-based interaction. Formal accessibility auditing and assistive-technology testing remain next steps; WCAG compliance has not been certified. 

AI Disclosure- Generative AI supported prototyping, code iteration, and visual development. Learning objectives, pedagogical structure, case framing, instructional judgments, and review were directed by the designer. The fictional examples are explicitly identified as simulations. 

Limitations & Next Iteration- All accounts, events, notices, and archive records in the exercises are fictional. The flood photograph is illustrative and its simulated archive is not the actual photograph’s provenance. External photos and fonts require an internet connection; licensing, attribution, local asset hosting, and accessibility testing should be finalized before wider distribution. Future iteration: baseline and post-assessment, a human-scored explanation rubric, and representative-learner pilot. 

Learning Experience 

I DO — Explicit Modeling. Three cases demonstrate accurate information, misinformation, and disinformation through visible source investigation and reasoning. 

WE DO — Coached Practice. Two new cases provide guided choices, explanatory feedback, and retry opportunities. 

YOU DO — Independent Application. Three unfamiliar cases require classification and a written explanation before feedback. Classification is scored; evidence prompts support self-review.

Authoring Tools- HTML5 • CSS3 • JavaScript • Netlify • AI-assisted visual and development prototyping (with human-directed instructional design, editing, and review).