Teacher Professionalism in Local & International Contexts

Overview & Intended Learning Outcomes

Teacher Professionalism in Local & International Contexts · 150 min · University Level · Social Constructivism

Intended Learning Outcomes

1

Analyze the key characteristics and tensions of teacher professionalism as defined in local (Hong Kong) and international (e.g., OECD, Western) policy frameworks.Cognitive: Analyze

2

Evaluate the role of context (cultural, political, economic) in shaping different models of teacher professionalism.Cognitive: Evaluate

3

Collaboratively construct a critical argument defending a specific model of professionalism for a contemporary educational challenge, using evidence from both local and international sources.Collaborative: Social Constructivism

4

Critically evaluate AI-generated analyses of teacher professionalism contexts, identifying cultural biases and limitations in the AI's output.AI Literacy: Analyze, Evaluate

5

Justify when and how to use or reject AI-generated suggestions for professional standards, demonstrating independent professional judgment.AI Literacy: Evaluate, Create

Lesson Structure Overview

Pre-Class

Flipped

Intro

15 min

Phase 1

30 min

Phase 2

40 min

Phase 3

35 min

Closure

15 min

Assessment

Post-class

Flipped Learning + Social Constructivism

Pre-Class Preparation

Pre-Reading Materials

Local Context: Hong Kong Education Bureau's "Teachers' Professional Conduct" guidelines
https://www.edb.gov.hk/en/teacher/conduct-and-ethics.html

International Context: Hargreaves, A. (2000). "Four ages of professionalism and professional learning." Teachers and Teaching: Theory and Practice, 6(2), 151–182. Focus on the "Post-modern" age.

Pre-Class AI Engagement Task

Tool: ChatGPT / Claude

Prompt to use:

Compare and contrast the concept of 'teacher professionalism' in Hong Kong and Finland. Give me 3 key differences.

Reflection Prompt: Post a 150-word response on the LMS discussion board answering:

"What limitations or biases did you observe in the AI's answer? Was it overly simplistic? Did it over-generalize? What important cultural aspects did it miss? Did you accept or reject its analysis? Why?"

How to Access ChatGPT / Claude▼

Purpose: Build initial awareness of AI limitations in cultural contextualization before class

Go to https://chat.openai.com or Claude at https://claude.ai
Create a free account if you don't have one
Type the prompt exactly as given above
Screenshot or copy the AI's response
Reflect on the response before class using the reflection prompt

Introduction

15 minutes · Hook + AI Critique + Pre-Test

15:00

Total: 15 minutes

1

Hook — Opening Scenario

5 min

▼

Scenario"A Hong Kong teacher is penalised for sharing a personal political view on social media, while a teacher in the Netherlands is praised for doing the same. Are they both 'professional'?"

Discussion prompts:

What factors make the same action "professional" in one context and "unprofessional" in another?
What does this tell us about the nature of professionalism?

2

AI-Generated Scenario Critique

5 min

▼

Show the class the original AI response from pre-class. Discussion questions:

How many of you found the AI's comparison of Hong Kong and Finland to be accurate?
What was its biggest blind spot?
How did the AI's response reflect a Western-centric view of professionalism?

Note: This models critical analysis of AI outputs — a key skill for this lesson.

3

Pre-Test with Mentimeter

5 min

▼

Mentimeter Setup Instructions (Instructor)▼

Purpose: Real-time misconception check before the lesson

Go to https://www.mentimeter.com and log in
Click "New Presentation" → Select "Quiz" type
Add Q1: "Is teacher professionalism the same in every country?" (Yes / No / It depends)
Add Q2: "Is professionalism primarily about individual autonomy or collective responsibility?" (Individual autonomy / Collective responsibility / Both equally)
Add Q3: "Which model best describes HK teacher professionalism?" (Civil Servant / Transformative Intellectual / Collaborative Professional / Unsure)
Click "Present" and share the voting code with students (displayed on screen)
Students vote on their devices at menti.com

Simulated Pre-Test Quiz — Try it yourself:

Q1: Is teacher professionalism the same everywhere?

AYes, good teaching is universal

BNo, it is shaped by cultural, political, and economic context

COnly in Western countries

Correct! Professionalism is context-specific. This is a central theme of today's lesson.

Not quite. Professionalism varies significantly by cultural and political context.

Q2: Is professionalism about individual autonomy or collective responsibility?

APurely individual autonomy

BPurely collective responsibility

CBoth — it varies by context and model

DNeither

Right! Different professional models emphasise different aspects. We'll explore both today.

Not quite. Both dimensions matter — their balance depends on context and the model of professionalism.

Phase 1 · Co-construction & AI Critique

Local–International Tension

30:00

Total: 30 minutes

1

Interactive Lecture — Two Models

10 min

▼

High Stakes Accountability Model
Hong Kong / Singapore

Centralized curriculum
Teacher as implementer
Education Bureau oversight
Performance metrics

High Trust, High Autonomy Model
Finland / Scotland

Teacher as professional expert
School-based curriculum
Collaborative culture
Trust-based accountability

Hong Kong

Centralized Control
Civil Servant Role
EDB Guidelines
Accountability Metrics

Both

Quality Teaching
Student Welfare
Ethical Conduct
Prof. Learning

Finland

Autonomy
Research-based Practice
Teacher Union Power
Collaborative Networks

Key Question: Where does your own context sit on this spectrum?

2

Group AI-Enabled Activity

20 min

▼

In groups of 4-5, return to the pre-class AI response.

Task Steps

Review the AI's comparison of HK and Finnish professionalism
Accept or reject the AI's claims, citing class readings (Hargreaves & EDB guidelines)
Write a new, improved analysis explaining where the AI's cultural bias was strongest
Document your decision: "We rejected the AI's point about Finnish autonomy because..." or "We accepted the AI's point about HK centralization because..."

Instructor Circulation Prompts:"Does the AI ignore the role of the teacher union in Finland?"
"Does it oversimplify the role of the Education Bureau in Hong Kong?"
"Does the AI assume 'autonomy = better'? Where does that assumption come from?"

Challenge Task

Prompt: Ask the AI: 'What are the weaknesses of your own answer?' Then evaluate whether it correctly identifies its own biases.

What are the limitations and potential biases in your previous comparison of teacher professionalism in Hong Kong and Finland?

Phase 2 · Social Constructivism & Peer Critique

The Professional Spectrum

40:00

Total: 40 minutes

1

Group Digital Storyboard Task

35 min

▼

Group A: Teacher as Civil Servant

Focus: Loyalty, rule-following, institutional compliance
Context: Hong Kong
Crisis: Declining student mental health
Task: Argue this is the MOST appropriate model

Group B: Teacher as Transformative Intellectual

Focus: Critical thinking, autonomy, change-making
Context: Western/International
Crisis: Rise of AI in the classroom
Task: Argue this is the MOST appropriate model

Group C: Teacher as Collaborative Professional

Focus: Networks, shared expertise, community
Context: Finland model
Crisis: Post-pandemic learning recovery
Task: Argue this is the MOST appropriate model

Padlet Setup Instructions▼

Purpose: Visual co-construction of group arguments for gallery walk

Go to https://padlet.com and click "Sign up free"
Click "Make a Padlet" → choose "Wall" layout for storyboard
Title your Padlet: "[Group X] – [Model Name] – Teacher Professionalism"
Add at least 4 posts: (1) Model overview, (2) Key evidence from readings, (3) How it addresses the crisis, (4) Limitations of the model
Add images, arrows, or colour coding to make it visually clear
Click "Share" → copy the link and post it in the LMS for gallery walk

Peer Assessment Rubric

Criteria	Excellent (A)	Satisfactory (C)	Unsatisfactory (F)
Clarity of argument	Clear, compelling, well-structured	Present but lacks focus	Unclear or missing
Use of evidence from readings	Both Hargreaves & EDB cited accurately	One source used	No readings cited
Identification of contextual limitations	Sophisticated analysis of model's limits	Brief mention	Not addressed

2

Gallery Walk & Calibration

5 min

▼

Groups view one another's Padlets and leave one "Critical Friend" feedback comment.

Prompt template: "Your model works well in [context X], but what about [context Y]?"

Phase 3 · AI Literacy & Independent Judgment

AI as a Professional Partner

35:00

Total: 35 minutes

Scenario"You are a newly qualified teacher asked by your principal to draft a new 'Professional Code of Conduct' for the school's AI policy."

1

AI-Enabled Task — 3 Steps

25 min

▼

Step 1 — AI Generation

Use this prompt to generate an AI-drafted code of conduct:

Write a professional code of conduct for teachers regarding their use of AI in the classroom. Include 5 rules.

Example AI Output:

AI-Generated Response

1. Teachers must declare any AI-generated content to students.
2. AI tools must not replace teacher judgment in grading.
3. Teachers should use AI to enhance, not replace, lesson planning.
4. All AI use must comply with school data privacy policies.
5. Teachers should undergo regular AI literacy training.

Step 2 — Critical Interrogation

Groups must:

Identify at least one bias in the AI's code (Does it assume all teachers have equal tech access? Does it focus too much on surveillance and not enough on pedagogy?)
Modify the AI's response: Rewrite two rules to make them more culturally appropriate for a Hong Kong school context
Justify rejection: Explain clearly why the AI's original rule was insufficient or problematic

Critique Prompts:"Does the AI's code assume all schools have the same tech infrastructure?"
"Is the focus on 'declaring AI use' more surveillance-oriented than pedagogy-oriented?"
"Does the code account for Hong Kong's specific EDB guidelines or cultural context?"
"What power dynamics has the AI missed? (e.g., teacher-admin, teacher-student)"

Step 3 — Final Product

Each group submits a revised, critically-examined "AI + Human" code of conduct to the LMS.

Deliverable Checklist:

Original AI-generated code (screenshot or copy)
At least 2 rewritten/modified rules
Written justification for each change (citing readings where possible)
At least 1 identified AI bias with explanation
Submit to LMS before end of class

2

Class Synthesis — Debrief

10 min

▼

Discussion Questions:"What patterns did you see in the AI's advice across all groups?"
"When should you trust an AI suggestion versus your own professional judgment?"
"How do you decide which AI outputs to accept, modify, or reject?"
"What did the AI consistently fail to account for?"

Closure · Consolidating Understanding

Synthesis & Closure

15:00

Total: 15 minutes

1

Post-Test — Compare with Pre-Test Results

5 min

▼

Same Mentimeter questions as pre-test — compare results to show learning growth. Discuss visible misconceptions that shifted.

Mentimeter — Compare Pre/Post Results▼

Show change in results; discuss visible misconceptions that shifted. Display both the opening results and the closing results side-by-side if possible.

Post-Test — Same Questions, Revisited:

Q1: Is teacher professionalism the same everywhere? (After learning)

AYes, good teaching is universal

BNo, it is shaped by cultural, political, and economic context

COnly in Western countries

Correct! You've internalized a key lesson theme — professionalism is always context-specific.

Revisit today's Venn diagram. Context shapes professionalism fundamentally.

Q2: Is professionalism about individual autonomy or collective responsibility? (After learning)

APurely individual autonomy

BPurely collective responsibility

CBoth — it varies by context and model

DNeither

Well done! Both dimensions co-exist — their balance is shaped by context and professional model.

Revisit Phase 1 and 2. The HK and Finland models both illuminate different aspects of this question.

2

Peer-Teaching Summary

5 min

▼

2-3 randomly selected groups share one key insight.

Prompt: "What is the single most important thing you learned today about how 'professionalism' is NOT universal?"

3

AI Reflection Discussion

5 min

▼

Whole-class discussion: "How did AI support your learning today? Where did it hold you back?"

Self-Rating Scale — Your Critical AI Engagement

How critically did you engage with AI today? Click a rating:

1 = Blindly trusted the AI · 3 = Accepted and rejected in equal measure · 5 = Constantly and rigorously challenged AI

Assessment

Formative (during class) & Summative (post-class essay)

Formative Assessment (During Class)

Two Methods:

1. Instructor Observation: Notes on collaboration quality (Social Constructivism — are they building on each other's ideas?) and Critical AI engagement (Are they blindly accepting AI or actively critiquing it?)

2. AI-Supported Formative Check: After Phase 3, students submit their revised AI code of conduct + brief justification document. Instructor scans for common patterns in student critique.

Summative Assessment (Post-Class — 1 week deadline)

Critical Essay & AI Audit

Task: "Critically analyse how the concept of 'teacher professionalism' is negotiated in a local (Hong Kong) vs. international context. You MUST use an AI tool (e.g., ChatGPT) to generate a first draft. Then provide an 'AI Audit' page documenting:

What did you ask the AI?
What specific content from the AI did you use (quote it)?
What did you modify or reject from the AI, and why? (Provide reasoning based on class readings)
Where did human judgment take precedence over the AI's suggestion, and why was that essential for this topic?"

Grading: 25% of module grade, includes 'Critical AI Engagement' criterion

Assessment Rubric

Criteria (Bloom's Level)	Excellent (A)	Satisfactory (C)	Unsatisfactory (F)
Analysis of Contextual Factors (C5)	Nuanced comparison of HK & international models, with clear cultural/political analysis	Identifies key differences but lacks depth on cultural context	Superficial comparison or factual errors
Evidence & Argumentation (C6)	Compelling, well-supported argument using both EDB & Hargreaves. Demonstrates independent synthesis	Argument is present but relies heavily on AI's initial structure	Shows poor use of evidence or relies uncritically on AI
Critical AI Engagement (C5)	SUPERB: Clearly identifies AI biases, explains why specific AI content was rejected, provides strong rationale for human judgment	ADEQUATE: Reports what was used/modified but has weak reasoning	MISSING/POOR: No AI Audit, or blindly copies AI output without critique

AI-Supported Feedback Process

Students submit essay + AI Audit to AI-powered feedback tool (Turnitin Draft Coach)
Tool generates feedback on argument structure and evidence integration
Instructor reviews AI-generated feedback AND student's AI Audit
Instructor adds personalized human comment highlighting what the AI feedback missed
Students have 24 hours to respond to both AI and instructor feedback

Constructive Alignment Matrix

How ILOs, teaching activities, assessment, pedagogy, and AI integration connect

Learning Outcome	Teaching Activity	Assessment Method	Pedagogy Link	AI Integration
ILO 1: Analyze key characteristics	Pre-class readings; Lecture on HK vs. Finland	Pre-test & Post-test; Summative essay analysis	Social Constructivism: Knowledge built comparing established frameworks	Pre-class AI Task: Students use AI to explore differences
ILO 2: Evaluate role of context	Group AI-Enabled Activity (local vs. international)	Formative: Group observation; Summative: AI Audit justification	Social Constructivism: Contextual understanding co-constructed through group critique	Phase 1 Activity: Students critically evaluate AI's contextual analysis
ILO 3: Collaboratively construct argument	Group digital storyboard (Padlet) & Gallery Walk	Summative: Peer assessment rubric; Final essay	Social Constructivism: Groups build shared argument (collective knowledge)	Phase 1: Groups build on the AI's flawed starting point
ILO 4: Critically evaluate AI-generated analysis	Pre-class task; Phase 1 & 3 AI critique activities	Summative: AI Audit page in final essay	Social Constructivism: Critiquing AI is a social learning process	Primary AI Literacy Outcome: Central to all activities
ILO 5: Justify use/rejection of AI	Phase 3: AI as Professional Partner task	Summative: AI Audit justification; Instructor feedback on rationale	Social Constructivism: Justifying decisions is professional dialogue	Core AI Task: Students document rejection/modification rationale

Resources & Technology

Platforms

LMS: Moodle or Blackboard — discussion board, AI Audit submission, file sharing
Padlet: padlet.com — visual co-construction for gallery walk
Mentimeter: mentimeter.com — real-time polling & pre/post-test

AI Tools

ChatGPT: chat.openai.com — pre-class task & in-class AI interaction
Claude: claude.ai — alternative to ChatGPT
Turnitin Draft Coach: Initial AI-powered feedback on essays
AI Literacy Resources: Campus library shared document on "Identifying Bias in AI Language Models"

Physical Materials

Printed copies of EDB "Teachers' Professional Conduct" excerpt
Printed rubric for Peer Assessment

Technology Checklist

LMS discussion board set up for pre-class reflection posts
Mentimeter presentation created with pre/post-test questions
AI Audit submission folder created on LMS
Shared AI Literacy resource document linked on LMS
Student devices available or BYOD confirmed

Differentiation & Inclusivity

Multiple Entry Points (Social Constructivism-tailored)

Visual learners: Padlet storyboards for visual argument construction
Auditory learners: Structured discussion and peer-teaching summary
Kinesthetic/reading learners: AI chatbot interaction for hands-on exploration

Scaffolding for Struggling Groups

If your group is struggling with AI critique, try these scaffold prompts:

Ask the AI: "What are the weaknesses of your own answer?" Ask the AI: "What cultural biases might be present in your analysis?" Ask the AI: "What would a Hong Kong educator say is missing from your answer?"

For Struggling Learners

Use the AI tool to generate simplified explanations of Hargreaves' "four ages" of professionalism in bullet points.

For Advanced Learners

Challenge: "Prompt the AI to create a new model of professionalism that combines the best of East and West, then critique that AI-generated hybrid for feasibility."

Accessibility

All AI interactions via text-based chat (text-to-speech enabled)
Mentimeter and Padlet have screen-reader compatibility
Captioned video links for any pre-class materials
5-minute "How to prompt effectively" mini-workshop at start of class for students new to AI

!

Instructor's 5-Minute AI Prompting Workshop

5 min

▼

Key principles for effective AI prompting:

Be specific: Include context, constraints, and format in your prompt
Iterate: If the first answer is poor, refine your prompt and try again
Be critical: AI responses reflect training data biases — always question them
Compare: Ask the same question to two different AI tools and compare
Cite: Never use AI output directly — always paraphrase, cite, and critique

Reflection & Improvement

Success Indicators

Group Collaboration Efficacy: Were all members active? Did groups build on each other's ideas? Measured via instructor observation & Padlet "comment" feature.

Post-Class Survey (AI-specific, anonymous): "Did the AI tools enhance or distract from your learning? Did you feel you maintained independent thinking, or did you rely too much on AI? Rate 1–5."

Instructor Reflection Questions

Where did students struggle most with AI criticality — Phase 1 (cultural bias) or Phase 3 (professional code)?
Did the AI feedback tool on the essay help or hinder deeper analysis?
What patterns emerged in students' AI Audit documents?

Data on AI Engagement

Review the "AI Audits" from summative assessment. Count instances where students rejected AI suggestions vs. accepted them. This reveals whether the lesson fostered independent judgment or passive consumption.

Modification Strategies

If students blindly accept AI: "In the next iteration, provide groups with a deliberately flawed AI analysis. Make the task entirely about 'Identify and fix the AI's 3 critical errors.'"

If students find theory too complex: "Replace academic readings (Hargreaves) with a shorter AI-generated summary of the 'Four Ages of Professionalism' and ask students to evaluate the summary itself for accuracy."