3. AI-Enhanced Class Design and Development

3. AI-Enhanced Class Design and Development#

Designing individual class sessions that align with course goals and engage participants with AI-enhanced learning experiences.

This module is about structuring the learning experience for clarity, engagement, and progression. It involves breaking down content into modules or units, designing individual class sessions with defined objectives, contents, and materials, creating learning strategies, selecting and preparing learning materials, and integrating discussion and reflection elements. AI can be used here to help design session elements, find relevant scientific literature, generate content from sources, and create learning activities and materials.

Pedagogical Note: When designing class sessions, instructors should intentionally incorporate productive friction and prompt literacy, two principles introduced in Module 0. Activities should require students to question, refine, and evaluate AI outputs rather than passively accept them.

Learning Objectives#

After completing this module, participants will be able to:

  • Break down content into structured modules.

  • Build session plans using prompt templates.

  • Generate literature-informed content, examples, activities.

  • Integrate multimodal AI-generated diagrams and artifacts.

  • Create an AI-powered class summary generator.

Class Design and Development

3.1 Break Down Content Into Modules or Units#

Purpose#

Translate course-level goals and outcomes into a usable modular structure that drives session planning, scaffolding, and pacing.

Prompt Template — Instructional + Role-Based

You are an instructional designer working inside the [Workspace/Project Name]. 
Break down the course [Course Title] into modules or class sessions. 
For each module, provide: 1) title, 2) description, 3) key concepts, 
4) materials, 5) applications, and 6) reflection.
Ground your proposal in the uploaded syllabus and course outcomes.

Additional Prompt Variant — Instructional

I am creating a modular course called [Course Title] for higher education students.
Propose a structure with a title and description for each module, progressing from foundations to application and reflection.

Exercise 1: Break Down Your Course Into Modules#

Goal: Structure your course into modules or sessions.

Steps:

  1. Paste your syllabus or course description into the Workspace.

  2. Use the module‑creation prompt.

  3. Review the proposed modules.

  4. Request alternative versions (basic, standard, advanced).

3.2 Design and Create a Class Session (Objectives, Contents, Materials)#

Purpose#

Develop structured, high‑quality class plans supported by AI: objectives, content, teaching strategies, timing, and required materials.

Pedagogical Note:
When planning AI-supported activities, instructors should consider how the task reinforces verification-first learning, ensuring students critically examine AI-generated information.

A. Direct Prompting on LLMs#

Task: Use the content generated by any LLM of your choice to create a presentation in a slide generator, e.g. Gamma.app or Power Point, by pasting the resultant text from the prompt.

Prompt Template — Instructional + Role-Based

You are an instructional designer working on the course [Course Title].
Design a 90-minute session for [Course Title] on the topic [Topic Name]. Include: 
- Session objectives 
- Sequence of activities with time estimates 
- Key content outline 
- Required materials  
- How AI will be used during the session 
- Optional multimodal artifacts (slides, diagrams, examples)

B. Prompting the AI Slide Generator#

Task: Accelerate production of professional-quality presentations and supporting visuals. Directly prompt the slides’ generator, e.g. Gamma.app, Canva, PowerPoint+Copilot, Scispace, Claude, check and refine the presentation produced.

Prompt Template — Slide Generator (Gamma, Canva, PPT+Copilot)

Generate a visually-engaging slide deck for a 90-minute class titled [Class Title].
Include objectives, diagrams, examples, teaching steps, risks, and interactive elements.

Prompt Template for Claude.ai

Generate a visually-engaging slide deck for a 90-minute class titled [Class Title].
Include objectives, diagrams, examples, teaching steps, risks, and interactive elements.
Create an interactive artifact.

Note 1: In Claude.ai you could have chosen Artifact -> New Artifact and selected one specific type, for example, Apps and websites to have an online presentation available for the students.

Note 2: In Copilot you can use menu Create -> Create a presentation.

C. Integrating Scientific Literature#

Task: Ground class content in peer‑reviewed research and provide academically reliable framing. Specific tools to be used:

Note 1: Other relevant tools for this task include Elicit (elicit.com), Scite (scite.ai), and Research Rabbit (researchrabitt.ai).

Note 2: There are various search engines focused on technical or scientific content, such as Semantic Scholar and the standard Google Scholar, which are useful but do not offer the AI prompt capabilities of the tools presented above.

C.1 SciSpace — Literature Review Mode

SciSpace works best with short, topic‑driven prompts and automatically generates summaries and many other information, including results, methods, limitations, objectives, datasets, and more.

Prompt — Topic Overview

For the topic on [Topic Name]: summarize the state of the literature, identify leading authors, and list the five most cited papers.

C.2 Perplexity — Academic Mode

Perplexity Academic produces fully cited syntheses and is strong for deep, research‑grade output.

Prompt 1 — Literature Synthesis

Synthesize the peer-reviewed literature on [Topic Name]. Include citations and identify the most robust evidence.

Prompt 2 — Annotated Bibliography

Create an annotated bibliography of the 10 most relevant academic papers on [Topic Name]. Include summaries, strengths, limitations, and relevance for class design.

Prompt 3 — Research Gaps

Identify three major gaps in the literature on [Topic Name].

Prompt 4 — Teaching Application Extraction

From the best available research, extract practical teaching applications of [Topic Name], including activity examples and risks instructors should consider.

C.3 Consensus.app — Research Summaries

Consensus is a research engine that generates synthesized, evidence-based answers directly from peer-reviewed papers. It can also perform deep search, draft an outline, and create a table.

Prompt 1 — Summary

What does the research say about [Topic Name]?

Prompt 2 — Extract Conclusions

Summarize the strongest conclusions from peer-reviewed studies on [Topic Name].

Prompt 3 — Compare Outcomes

Compare learning outcomes reported in studies using [Topic Name].

Prompt 4 — Practical Implications

Using research findings, list the practical implications of [Topic Name].

C.4 Google Scholar Labs — Research Overview

Google Scholar Labs is ideal for fast, concise academic summaries and trend detection.

Prompt 1 — Quick Overview

Provide a concise overview of the academic literature on [Topic Name].

Prompt 2 — Key Papers Summary

List the foundational papers on [Topic Name] and explain the contribution of each in one sentence.

Prompt 3 — Trend Identification

Identify recent trends in [Topic Name] based on highly cited papers since 2020.

Prompt 4 — Rapid Instructor Summary

Summarize what instructors should know about [Topic Name], grounded in recent academic research.

Cross-Tool Prompt#

A universal prompt usable across tools:

Using current peer-reviewed research, explain how [Topic Name] can be integrated into a 90-minute higher education class session.
Include: summary, benefits, risks, best practices, and citation-backed recommendations.

Comparative Table of AI Literature Tools#

Tool

Type

Best For

Strengths

Limitations

Ideal Use in Module 3

SciSpace

AI literature analysis

Literature reviews & concept mapping

Visual concept maps, citation tracing, theme extraction

Needs short, topic-based queries

Building conceptual diagrams & evidence maps

Perplexity Academic

LLM + search

Deep research synthesis

Cited responses, robust summaries, strong reasoning

May over‑aggregate sources

Generating lecture content grounded in research

Consensus.app

Evidence summarizer

Quick synthesis of research findings

Direct conclusions from papers, comparisons, consistency analysis

Limited to indexed papers

Rapid evidence summaries for teaching decisions

Google Scholar Labs

Search + AI summaries

Rapid literature overview

Fast topic summaries, trend detection

Less detailed synthesis

Quick background reading & preparation

D. Generating Content from External Sources#

Task: Use a generative model like Perplexity, NotebookLM, or SciSpace, to analyze some pre-selected sources of reference and create content from them. As example, you can use the papers below as your source material if needed or some of the open access papers you saved from your previous searches.

Example contents (papers) for a [Course on Teaching with AI] and the topic of [AI for Assessment and Feedback]:

Paper_1: Artificial intelligence for assessment and feedback to enhance student success in higher education. (Open Access)
Paper_2: Feedback sources in essay writing: peer-generated or AI-generated feedback? (Open Access)

Step 1: Preferably upload this material in your AI Workspace, but you can also create a new Notebook in NotebookLM or Library in SciSpace and title it “AI for Assessment and Feedback”.
Step 2: Upload your sources of reference (see files above) into the LLM.
Step 3: Prompt the LLM.

Prompt Template - Instructional

Using the attached material, design a 90-minute session for the course [Course Name].
The topic is [Topic Name].
Include session objectives and sequence of activities with time estimates and main contents.

Note: After generating your content from your sources, you can use it to create the slides as explained previously.

Exercise 2: Design a Complete 90-Minute Class Session#

Goal: Produce a structured lesson plan using generative AI.

Steps:

  1. Select one module from Exercise 1.

  2. Use a session‑design prompt.

  3. Request two more variants (online, hybrid).

  4. Ask the model to create a slide deck outline.

3.3 Create Learning Activities#

Purpose#

Use AI to design active learning activities that promote practical engagement with generative AI tools.

Prompt Template — Instructional + Role-Based

You are a faculty developer facilitating a session on [Topic Name]. 
Suggest three learning activities that help participants understand this topic.
Include instructions, timing, and required tools.

Note 1: If you already know the learning activities you are going to use, you can always employ an LLM to check, improve, provide ideas and create specific activities for you.

Note 2: Some LLMs offer features and artifacts that can be directly used to create learning activities. For example, Claude.ai allows you to create (interactive) artifacts (e.g., apps and websites, documents and templates, games, creative projects, quiz or survey) that can be used as learning activities by the students.

Exercise 3: Generate Learning Activities#

Goal: Create AI-supported activity plans that promote active learning.

Steps:

  1. Choose a class topic.

  2. Use the activity-generation prompt.

  3. Request variations for different complexity levels.

3.4 Select and Prepare Learning Materials#

Purpose#

Identify, generate, transform, and validate materials needed for class delivery.

Task 1: Search for and generate new learning materials#

Prompt Template

Suggest a list of materials for a class on [Class Topic]: 
Include 1 reading, 1 hands-on tool, 1 AI-generated example, 
and 1 multimodal artifact.

Task 2: Select and validate content and sources#

From all the materials generated in the previous steps, identify and validate those that can be used as part of your teaching component.

Note: The GenAI models should be used as assistants to support you in the process of planning, designing, and creating your course, but you must ensure everything is accurate and ready to be presented in class. The scientific content retrieved and analyzed in Section 3.2C may be particularly relevant to become part of the content for your course.

Exercise 4: Generate and Validate Learning Materials#

Goal: Use AI to produce readings, examples, tools, and teaching aids.

Steps:

  1. Run the materials prompt.

  2. Request multiple formats (summary, table, example, visual).

  3. Validate outputs manually for accuracy.

3.5 Integrate Discussion and Reflection Elements#

Purpose#

Use AI to generate reflective questions and discussion points that deepen understanding.

Prompt Template — Few Shot

Examples of reflective questions:
1. What are the potential benefits and risks of using AI-generated feedback?
2. How would you explain the role of AI to your students?

Generate 3 reflection questions that promote critical thinking about [Course Topic].

Exercise 5: Generate Discussion and Reflection Questions#

Goal: Create a reusable prompt that generates discussion and reflection questions for your class sessions.

Steps:

  1. Copy the reflection prompt template provided above.

  2. Replace [Course Topic] with a topic from your course (for example: regression analysis, climate change mitigation, ethical AI, market segmentation, etc.).

  3. Run the prompt in your preferred AI tool and generate three reflection questions.

  4. Ask the AI to generate two additional discussion prompts designed for small group discussion.

  5. Review the questions and revise them so that they:

    • encourage critical thinking

    • connect to real-world situations

    • cannot be answered with a simple factual response.

3.6 Create an AI-Powered Class Summary Generator#

Purpose#

Automate class closing reflections using AI-generated summaries.

Prompt Template — Instructional

Write a 1-paragraph summary of key takeaways from today's class using the notes or transcript provided.
Include the main concepts, examples, tools used, and next steps for students.

Meta-Prompting

Write a prompt I can give to an LLM at the end of each class to generate a 1-paragraph summary of key takeaways based on notes or transcripts from a session on [Course Topic].

Exercise 6: Create a Class Summary Generator#

Goal: Build a reusable summary generator prompt.

Steps:

  1. Copy the summary prompt.

  2. Run it on an example transcript or your own notes.

  3. Ask for three versions: bullet list, student-friendly, expert-level.

3.7 Updates to Your AI Workspace and Personalized Assistant#

This section summarizes the main updates to your AI Workspace (Project) and Course Personalized Assistant (PA) to ensure both tools evolve consistently as you progress in this program.

A. Updates to Your AI Workspace (Project)#

  1. Upload New Files to the Workspace Knowledge Base: all materials (e.g., modules, class sessions, slides) generated or selected in this module.

  2. Update Workspace Instructions: modify the Project’s instruction block to reflect new responsibilities.

Add under Capabilities:

- Structured session plan generation  
- Learning material creation  
- Multimodal artifact generation  
- Literature-grounded content synthesis

Add under Behaviors:

- Validate accuracy of AI-generated materials  
- Flag inconsistencies or missing content

B. Updates to Your Course Personalized Assistant (PA)#

  1. Upload New Files to the PA Knowledge Base: all content and learning materials generated or selected in this module.

  2. Update PA Instructions:

Add under Capabilities:

- Explain class concepts at multiple difficulty levels  
- Generate practice questions based on session materials

Add under Safety & Boundaries:

- Avoid generating full solutions for graded assignments

Note: Have a look at Section 2.7C for instructions on workflow adjustments going forward each module.

3.8 Reflection#

  • Which class-design tasks benefited most from AI?

  • Where did human oversight become essential?

  • How could multimodal AI tools enrich the learning experience?

  • What tasks should remain strictly human-led?