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E-Learning Case Study

This case study showcases a Canvas-based professional learning module for K–12 educators. The module applies adult learning theory (andragogy), Universal Design for Learning (UDL), and experiential learning principles to support autonomy, accessibility, and authentic classroom application.

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The sections below outline the key design decisions and instructional strategies used throughout the module.

Testing AI Feedback & Assessment Tools

Module Overview

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This Canvas-based professional learning module supports K–12 educators in exploring, evaluating, and applying AI-supported feedback and assessment tools. Through guided exploration, hands-on practice, and structured reflection, participants develop confidence in selecting appropriate tools, interpreting AI-generated feedback, and making informed instructional decisions aligned to classroom goals.

1

Adult Learning Theory

Andragogy 

This module is designed for adult learners by emphasizing relevance, autonomy, and authentic classroom application. Teachers engage with real instructional tasks and make decisions aligned to their own teaching contexts.

2

Universal Design for Learning

UDL

The module incorporates flexible pathways for engagement, representation, and expression. Learners choose how they explore content, access information, and demonstrate understanding in ways that best support their learning needs.

3

Experiential Learning

Learning Through Practice & Reflection

Teachers learn through guided practice, reflection, and application. Hands-on experiences with AI feedback tools support meaningful reflection and transfer to real classroom practice.

Adult Learning Theory

Andragogy
Real Student Work
1. Relevance & Authentic Application

Learning activities are grounded in authentic classroom feedback and assessment contexts.

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  • Tools are explored using real student work

  • Activities emphasize feedback and assessment decisions, not tool features

  • Learners analyze how AI feedback informs instructional judgment

2. Choice & Learner Autonomy

Learners are provided with meaningful choices aligned to their instructional context.

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  • Learners choose which AI tools to explore

  • Educators determine the focus and depth of exploration

  • Reflection tasks support personalized classroom connections

3. Self-Directed, Applicable Learning

The module supports flexible pacing and immediate transfer to practice.

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  • Learners progress at their own pace

  • Guided practice mirrors real instructional tasks

  • Reflection focuses on applying feedback to current teaching contexts

1. Multiple Means of Engagement

Learners are provided with meaningful choices that increase relevance and ownership of learning.

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  • A choice board allows teachers to select which AI tools to explore

  • Tool selection aligns with individual instructional contexts

  • Activities emphasize authentic classroom application

2. Multiple Means of Representation

Content is presented in multiple formats to support access and understanding.​

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  • Tool concepts are introduced through videos and text-based resources

  • Text-based alternatives support accessibility

  • Clear, structured instructions support understanding and navigation

3. Multiple Means of Action & Expression

Learners are offered flexible options to demonstrate understanding and apply learning.

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  • Participants create a one-page summative artifact

  • Learners choose the format and mode of expression (e.g., one-pager, infographic, slide, planning document, or essay)

  • Tasks focus on instructional application, not tool features

Universal Design

UDL
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Choice Board Supports UDL

Experiential Learning

Learning Through Practice & Reflection
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Assignments Emphasize Guided Practice & Reflection
1. Experience 

Learners build understanding through direct, hands-on engagement with tasks.

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  • Guided practice activities provide structured interaction

  • Scaffolding supports progression from exploration to independent application

  • Activities use authentic classroom tasks to ground learning in practice

2. Reflect

Reflection supports sense-making and a deeper understanding of the experience.

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  • Learners reflect after exploring tools through the choice board

  • Reflection tasks in the AI Feedback Tool Trial Log prompt analysis of tool use and feedback quality

  • Prompts encourage consideration of instructional decisions and ethical use

3. Apply

Learners transfer insights from experience and reflection to future practice.

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  • The summative artifact requires applying learning to a specific classroom task

  • Teachers explain how AI-supported feedback would be used within their instructional context

  • Tasks emphasize professional judgment rather than tool features

Try the Module

​Explore the e-learning module from a participant’s perspective using test login credentials. This demo allows you to experience the guided practice, reflection activities, and summative task firsthand.

Test Login
Username: wguteststudentmw2@gmail.com
Password: wgudegree2026
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