Interactive Manual

Unit 2.4 — Online Safety and Responsible AI Use — closes Quarter 2 with the most immediately personal content in the suite. Unlike spreadsheet functions or document formatting, the threats and tools covered here affect students' lives right now: their accounts are either secured or they are not; the AI tools they use are either employed with integrity or they are not. The interactive tools are designed to convert awareness into concrete action.

This unit has more facilitator discussion anchors than any other Quarter 2 unit because the content invites it — phishing targeting in vulnerable communities, data as a community resource, and AI as an economic equalizer are all topics that connect directly to the Heritage-as-Capital framework running through the curriculum.

The Six Pairs — Answer Key

Scenario Guide

Scenario 6 — Most discussion-worthy

Scenario 6 (Brianna, no written AI policy) is the most nuanced in the set. Students often argue that absence of a policy means absence of a rule. The teaching point: academic integrity is about the purpose of the assignment, not only about written prohibitions. An essay exists to develop and demonstrate analytical capability — submitting AI output misrepresents that capability regardless of policy. This scenario generates productive classroom discussion about integrity vs. compliance.

Answer Key — All 10 Statements

Statements 1 (HTTPS) and 7 (phishing design) are the most commonly missed — both correct popular misconceptions that feel like common sense. Statement 10 (AI integrity without policy) is the highest-discussion item. Below 7/10 on this exit ticket: revisit Topics 1, 2, and 5 before the quiz.

Scoring Logic

Score interpretation

Total maximum: 10. Score 80%+ (8–10): Strong. Score 55–79% (6–7): Moderate. Below 55% (0–5): Needs Work. The priority action hierarchy: missing professional email → no self-Google → high post volume → many platforms → always LinkedIn. The audit is self-reported and unverified — its value is in prompting honest reflection, not producing a certified score.

Question Bank Coverage

Grading Scale

Highest error-rate questions

The HTTPS misconception question (false: HTTPS does not mean a site is safe) and the phishing visual design question (false: professional design is not a reliability indicator) are the most missed. Both correct commonly held but wrong beliefs. Students who score below 70% should return to Topics 1 and 5 and re-read the annotated phishing email in the Study Guide.

Recommended Learning Sequence

• 1Study Guide Topics 1–2 (~25 min). Phishing anatomy (annotated email), smishing/vishing, password security, 2FA. Students should be able to identify five phishing red flags before moving on.
• 2Threat Spotter (5–8 min). After completing: run the discussion — which attack type is most likely to succeed on someone in their community and why.
• 3Study Guide Topics 3–4 (~20 min). SIFT framework, misinformation vs. disinformation, data privacy. Apply SIFT to a live example as a class — choose a current financial or health claim in the news.
• 4Study Guide Topics 5–6 (~20 min). AI capabilities/hallucination, responsible AI use. Demonstrate a live AI hallucination using an available AI tool: ask it for a financial statistic with a source, then attempt to verify the source independently. The demonstration is more effective than any description.
• 5Safe or Risk? (10–15 min). Pause at Scenario 4 (AI statistics) for the honest-reflection question. Pause at Scenario 6 (AI integrity) for the integrity vs. compliance discussion.
• 6Security Audit (8–10 min). Run as anonymous aggregate first. Then have students complete it individually and identify their one priority action to take this week.
• 7True or False (8–10 min). Exit ticket. Below 7/10: re-read Topics 1, 2, and 5 before the quiz.
• 8Unit Quiz independently. 70% minimum passing score.

Heritage-as-Capital Discussion Anchors

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  Introduction — Scam Targeting as a Community Wealth Problem"Financial fraud is not an abstract internet problem — it is a community wealth problem." Ask: do you know someone who has been targeted by a phone or email scam? What made them vulnerable? What would have helped them recognize the attack?
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  Topic 4 — Data as Community Resource"Tech companies collect data from communities across Birmingham-Bessemer and profit from it — but the community sees none of that value." Ask: what would it mean for a community to collectively understand and assert its data rights? What decisions could be made differently?
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  Topic 6 — AI as Equalizer"A student in Birmingham-Bessemer with strong AI literacy has access to tools that cost thousands of dollars per hour a decade ago." Ask: what professional task could you accomplish better or faster with AI literacy that you could not do easily without it? What does it mean to use that capability with integrity?

NAF / AOBF Alignment