AI for Assessments and Academic Integrity
- Description
- Curriculum
- Notice
This 8 Lesson interactive course explores how educators can use AI tools to design effective assessments, streamline grading, and deliver personalized feedback—all while maintaining academic integrity and ethical standards. Participants will learn practical strategies for generating assessment content, using AI for rubric-based evaluation, and addressing common concerns like algorithmic bias and student misuse. The course also supports school teams in developing shared policies and reflective practices to ensure AI enhances learning rather than undermines it.
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1
Lesson 1.1: Assessment Design with AIOverview of how AI can support formative, summative, and alternative assessments.
Prompting strategies for generating multiple-choice, open-ended, scenario-based, and standards-aligned questions.
Activity: Use ChatGPT or Claude to generate a quiz based on a provided topic and rubric.
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2
Lesson 1.2: Differentiating Assessment with AI
Prompting for different reading levels, scaffolds, and cognitive demands (e.g., Bloom’s Taxonomy).
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3
Lesson 2.1: Automating the Rubric
Prompting AI to apply rubrics to short responses or essays.
Demo: AI-generated feedback with tone, content, and structure analysis.
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4
Lesson 2.2: Feedback that Feeds Forward
Creating personalized, strengths-based, and next-step feedback using AI.
Activity: Enter sample student work + rubric; refine AI-generated feedback for tone and clarity.
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5
Lesson 3.1: Addressing Bias and Reliability
Understanding bias in AI-generated assessments and grading.
Why AI-detection tools aren’t reliable for catching misconduct.
Reflection Prompt: When might AI unintentionally disadvantage learners?
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6
Lesson 3.2: Rethinking Integrity in the Age of AI
Encouraging transparency: student-AI conversations as part of submission.
Accountability strategies: oral defense, version tracking, process portfolios.
Group Discussion: How do we balance innovation with trust?
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7
Lesson 4.1: Developing Shared Guidelines
Key considerations for school or district assessment policies involving AI.
Sample policy language: disclosures, acceptable use, teacher roles.
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8
Lesson 4.2: Building Assessment Literacy in the AI Era
What teachers and students must know about AI-assisted assessments.
Professional development planning and student-facing mini-lessons.
Team Task: Draft a policy statement or classroom practice guide.
Course Notice: Who This Course Is For — and What It Is Not
This course is designed for:
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Educators and school leaders who are actively assessing student work and want to integrate AI to support and streamline their practices.
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Teachers interested in creating equitable assessments and feedback with the help of AI tools.
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Teams developing school policies or norms around the ethical use of AI in learning and evaluation.
This course is not designed to:
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Teach technical AI development or how to build grading algorithms.
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Focus exclusively on detecting AI misuse by students (though this will be discussed).
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Replace the educator’s professional judgment or decision-making in assessment.
Learning Outcomes
Participants will:
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Learn how to generate diverse, standards-aligned assessments using AI tools.
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Practice using AI for rubric-based grading and tailored student feedback.
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Understand the risks of bias, over-reliance, and the limits of AI detection tools.
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Explore ethical strategies for upholding academic integrity in an AI-enabled classroom.
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Begin crafting school- or team-based guidelines for responsible AI use in assessment.
What’s Included
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Demonstrations of AI-generated quizzes, rubrics, and essay evaluations.
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Prompting frameworks for differentiated assessment creation.
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Templates for grading and feedback automation using AI.
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Case studies and examples of academic integrity challenges.
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Sample policy language and accountability strategies for schools.
Educators, Teachers and Teams
