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Course Outline
AI in Education: Foundations and Practical Applications <\/p>
- Understanding AI and generative AI in plain language – recognizing its capabilities and limitations in the classroom. <\/li>
- Common educator use cases: lesson planning, resource creation, differentiation, assessment support, and communication. <\/li>
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Establishing realistic expectations: viewing AI as a co-pilot rather than a substitute for professional judgment or institutional policy.
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Getting Started with AI Tools in School Environments <\/p>
- Choosing suitable tools: web-based assistants and integrated AI features within common platforms. <\/li>
- Essential safety setup: managing accounts, adhering to school guidelines, and identifying information that must remain confidential. <\/li>
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Quick wins for educators: summarizing content, rephrasing, generating examples, and improving clarity and tone.
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Prompting Skills for Teachers <\/p>
- Crafting effective requests: defining role, task, context, constraints, format, and providing examples. <\/li>
- Core prompt patterns: brainstorming, drafting, critiquing, refining, comparing options, and generating variations. <\/li>
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Practice: building a reusable prompt library tailored to your subject, grade levels, and frequent tasks.
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Lesson and Resource Design with AI <\/p>
- Drafting lesson outlines that align with learning intentions, success criteria, and curriculum outcomes. <\/li>
- Developing classroom-ready materials: explanations, worked examples, worksheets, slide outlines, and discussion prompts. <\/li>
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Differentiation strategies: adjusting reading levels, adding scaffolds, providing extension activities, and suggesting multi-modal options.
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Assessment and Feedback Support <\/p>
- Generating question banks, formative checks, and rubric descriptors aligned with standards and task requirements. <\/li>
- Drafting feedback comments and conference prompts while maintaining the teacher’s voice and professional responsibility. <\/li>
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Practice: creating an assessment support pack for a current unit, including questions, rubric language, and feedback stems.
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Quality Assurance: Accuracy, Bias, and Learner Fit <\/p>
- Identifying common issues: hallucinations, missing context, uneven depth, and inappropriate reading levels. <\/li>
- Simple verification methods: cross-checking facts, requesting sources, and validating against trusted references. <\/li>
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Editing for inclusivity and accessibility: conducting bias checks, using culturally responsive language, and making adjustments for diverse learners.
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Responsible Classroom Use and Implementation Planning <\/p>
- Privacy and safety: managing student data, addressing sensitive topics, and ensuring appropriate prompts and outputs. <\/li>
- Academic integrity: guidelines for acceptable use, attribution expectations, and AI literacy activities for students. <\/li>
- Action plan: designing one AI-supported lesson or workflow, defining boundaries and routines, and planning communication with stakeholders. <\/li> <\/ul>
Requirements
- Familiarity with using computers, web browsers, and standard educational tools (such as Google Workspace or Microsoft 365). <\/li>
- Experience in designing lessons and creating learning resources for primary or secondary school students. <\/li>
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No prior programming knowledge is necessary.
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Audience <\/p>
- Primary School teachers from any subject discipline. <\/li>
- High School teachers from any subject discipline. <\/li>
- Curriculum coordinators, learning support staff, and instructional coaches involved in classroom delivery. <\/li> <\/ul>
14 Hours
Testimonials (2)
The interactive style, the exercises
Tamas Tutuntzisz
Course - Introduction to Prompt Engineering
A great repository of resources for future use, instructor's style (full of good sense of humor, great level of detail)
