AI and Academic Administrative Integrity

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Evidence-based report quiz

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ANGELIE UNTALAN

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AI and Academic Administrative Integrity


AI and Academic Administrative IntegrityVersión en línea Evidence-based report quiz por ANGELIE UNTALAN 1 What is the primary purpose of using LeapSpace in the report on AI and academic integrity? a To create fictional data for scenarios b To store private student data c To replace researchers with automation d To assist in evidence gathering and analysis for the report 2 Which facet is essential for maintaining integrity when employing AI in administration? a Benevolent AI ownership b Transparency about AI methods and data sources c Assuming AI is always correct d Using AI to hide decision reasons 3 What is a key risk to academic integrity from AI tools in administration? a Data privacy and potential bias in outputs b No need for human oversight c Low computing costs d Always accurate recommendations 4 Which practice supports reproducibility in an AI-assisted report? a Omitting model versions b Using random results for flexibility c Relying on one-off expert opinions d Documenting data sources and model configurations 5 What should be included to avoid plagiarism when using AI-generated content? a Deleting AI prompts after use b Proper citation and disclosure of AI contributions c Using confidential data without consent d Claiming all output as human work 6 In evaluating AI outputs for integrity, which approach is recommended? a Cross-check results with independent sources b Ignore inconsistencies c Only rely on AI certainty scores d Accept outputs as final 7 Which governance measure boosts ethical use of AI in administration? a Banning all AI tools b Establishing an AI ethics and compliance framework c Relying on informal guidelines d Leaving decisions solely to vendors 8 What role does human oversight play in AI-assisted administrative decisions? a Critical review and adjudication in ambiguous cases b Ignoring AI warnings to expedite processes c Automatic adoption of all AI outputs d Complete replacement of human staff 9 Which data practice supports integrity when using AI for reports? a Use de-identified, consented data where possible b Share raw data publicly c Store data without access controls d Use data without consent to speed up work 10 What is a sign of a robust evidence-based AI report? a Only listing favorable outcomes b Balanced discussion of AI benefits, limitations, and uncertainties c Ignoring limitations to appear decisive d Overstated AI capabilities Feedback 1 LeapSpace is used to aid evidence collection and analysis, not to replace researchers or fabricate data. 2 Transparency ensures stakeholders understand how AI decisions are made and what data underpin them. 3 AI can propagate bias and mishandle sensitive data if not properly controlled. 4 Reproducibility requires clear documentation of sources, methods, and configurations. 5 Citing AI contributions maintains academic honesty and proper attribution. 6 Independent verification helps ensure accuracy and reduces error propagation. 7 A formal framework provides consistent standards and accountability. 8 Humans should review and interpret AI results, especially in edge cases. 9 De-identification and consent protect privacy and uphold ethics. 10 A robust report acknowledges both strengths and limitations of AI.

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AI and Academic Administrative Integrity

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AI and Academic Administrative IntegrityVersión en línea

por ANGELIE UNTALAN

What is the primary purpose of using LeapSpace in the report on AI and academic integrity?

Which facet is essential for maintaining integrity when employing AI in administration?

What is a key risk to academic integrity from AI tools in administration?

Which practice supports reproducibility in an AI-assisted report?

What should be included to avoid plagiarism when using AI-generated content?

In evaluating AI outputs for integrity, which approach is recommended?

Which governance measure boosts ethical use of AI in administration?

What role does human oversight play in AI-assisted administrative decisions?

Which data practice supports integrity when using AI for reports?

What is a sign of a robust evidence-based AI report?

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