Phase 2: Analysis & Design

Focused on defining the learning strategy, aligning objectives, and designing an effective instructional approach.​

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Design Foundation:

​The module is grounded in adult learning principles and aligned with backward design methodology to ensure relevance, alignment, and practical application.

• Learner-centered and problem-oriented approach

• Focus on real classroom challenges

• Emphasis on immediate application and efficiency

• Designed for experienced adult learners with time constraints

Application of Andragogy (Knowles):

The design incorporates Knowles’ principles of adult learning:

• Need to Know - Highlights workload challenges and relevance of AI

• Self-Concept - Scenario-based decisions promoting autonomy

• Prior Experience - Activities connected to teachers’ real contexts

• Readiness to Learn - Focus on daily classroom tasks

• Problem-Centered Orientation - Solving real teaching challenges

• Internal Motivation - Emphasis on efficiency and professional growth

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​Learning Theories Applied: ​To support effective learning, the module integrates:

• Constructivism - Learning through active engagement and real-world scenarios

• Experiential Learning  -Learn → Reflect → Apply cycle

• Cognitive Load Theory - Simplified structure to reduce overload

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Instructional Design Principles:​​

• Clarity & Simplicity- Avoid overload of tools or theory

• Scaffolding - Awareness → guided practice → independent application

• Alignment -Activities directly support learning objectives

• Relevance - Real classroom application

• Immediate Application -Usable strategies post-training

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Backward Design Approach:​​

The module follows a backward design framework:

• Define Desired Results- Teachers apply AI effectively in classroom tasks

• Determine Evidence- Scenario-based tasks, prompt-building, output evaluation

• Plan Learning Experiences- Guided practice and real-world application

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Learning Goals & Objectives: ​

Learning Goal: Enable teachers to use AI strategically and ethically to improve classroom efficiency.

Learning Objectives: ​

• Apply the S.A.V.E. workflow to evaluate AI use in classroom scenarios.

• Construct structured prompts using the RGRO framework.

• Evaluate AI-generated outputs using an ethical checklist before classroom use.

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Assessment Strategy:

• Scenario-based decision-making tasks

• Prompt construction exercises

• AI output evaluation using ethical checklist

• Final applied classroom task

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Delivery Approach:

• Online, asynchronous module

• Self-paced learning

• Designed for varying digital confidence levels