1. What did you find out from the fun pre activity - learning style quiz? And how can you apply it to your student?

2. What is one take away from the sharing?

3. What is one strategy or resource that you have tried or keen to try this year?

1) What are some takeaways for you from this session?

2) What are some actions you would like to take moving forward?

However on the flip side I’m also mindful of fatigue, workload and time for myself?

So really then it’s about finding a good balance of effective use of data, efficient design of resources and lessons and at the same time meaningful learning happening for our students.

And of course still wanting to get our kids to still be engaged, and consistently wondering about what they are learning!

Tough!

From the many sharings, it is clear that understanding our learners is fundamental to making instruction effective and there are many ways to think about our learners. There were several frames presented - MI, Dunn & Dunn's learning preferences, interests, readiness and learning profiles.

Now what?

What do we focus on? I think it depends on what we value in our students as well as our instruction to determine what we want to find out from them.

Moving forward?

For my P2 EL class, related to my subject, I would want to find out more about their reading preferences, as well as their family backgrounds and the things they do with their families, to find out the extent of language exposure they have. Using the genres / content which they are exposed to, I could bring some of these in to make my lessons more engaging.

For my P6 class, I want to find out more about what modes of learning is benefitting their revision as they prepare for their PSLE. I would also want to find out more about their current family contexts to support them in managing their well-being. E.g. Videos / online SLS / hardcopy materials. Phone calls to parents and a quick survey could help me with this - and I will tailor my support accordingly.

While key takeaways can be all the strategies or tips to manage different profiles of students, I have to confess that when theory doesn't work, I had to figure out my ways to better engage and manage the students. Finding a balance to manage students of diverse behavioral profiles can be testing for any teacher for our class sizes.

Will look through all strategies thoroughly again before deciding on a few to best support my students in their final milestone towards PSLE.

Instructions:

• Please make one post per course/workshop attended.

• Use the reflection questions below to guide your sharing. Keep it concise and meaningful!

  
  

Reflection Questions for Padlet

🧭 Meta-reflection

1. On a scale of 1–5, how relevant was this session to your role? Explain your rating.

🔍 Understanding & Key Takeaways

1. What are 2–3 key takeaways from the session?

2. Was there a "lightbulb moment" during the workshop? Describe it.

🛠️ Application & Next Steps

1. What is one idea you can apply in your classroom / department work?

4; similar to another course I attended, the course touched on how it is important for humans to master the AI, not the other way around. The keynote address provided some practical suggestions on how I can engage AI to enhance my intelligence instead.

🔍 Understanding & Key Takeaways

1. What are 2–3 key takeaways from the session?

   • What is important for the students in the future is helping them to develop a better understanding of how they learn and think, which can be through the content areas. Developing a foundation of thinking capabilities will help them to learn better and also tap on AI to support their growth.

   • How do we master AI? By breaking down the skills / tasks that we want to learn and consider more intentionally how AI can be used to enhance specific processes

   • There are some forms of intelligence that AI cannot perform as it is trained with specific data.

2. Was there a "lightbulb moment" during the workshop? Describe it.

   • Teaching students to develop awareness of how they learn and valuing our forms of intelligence that AI cannot perform

🛠️ Application & Next Steps

1. What is one idea you can apply in your classroom / department work?

   • Supporting students to understand how they should work with AI

   • Utilising AI intelligently for ourselves

Key note by Prof. Rose Luckin

Title: Building Human Super Intelligence- Education in the age of AI

The key points are:

1. Technology is important as it analyses the environment and then achieves the goals

2. The development of technology has its history.

3. Types of AI - Narrow AI and General AI

4. 3 elements of AI - Data, processing power and algorithms

5. AI technology is moving very quickly and we need to keep up. It is uncomfortable but it is a reality.

6. AI can help us in personalised learning, marking feedback etc

7. We need to know that students can use AI in their assignments and hence integrity , data protection etc.

8. Human and Artificial Machine Intelligence are different. Tacit knowledge is absent eg. taste the food , smell the food, cuddle another person, feel the warmth of family members

9. There are 7 types of Intelligences:

a. Interdisciplinary intelligence

b. Social intelligence

c. Meta-cognitive intelligence

d.

e.

f.

g.

10. We need to be careful with AI as we overly on it. We may become less smart as a result.

11. We cannot learn anything effortlessly. We need to put in effort in what we do.

12. We need to use our brains. We have to use AI to help us to become more intelligent.

13. High confidence in AI might lead to a decrease in the ability of using critical thinking

14. Numeracy, literacy

    AI literacy, learning mastery & knowledge mastery

Personal Reflection

It is good to have AI to help us in education. However, we must wise when we use AI. We want AI to motivate students, facilitate learning and promote critical thinking. Hence, we must decide on the fate of AI, not the other way round. We shall continue to strive for a balance between the use of AI and human intelligence.

AI is a tool that I can use to enhance my teaching and learning in class.

b)Understanding & Key Takeaways

-AI draws information from a lot of data to form algorithms.

-Need to be mindful of becoming over reliance to AI.

-Lightbulb moment : Integrity (from students) when using AI to complete assignment

c)Application & Next steps

Wait I ask ChatGPT first...

• AI is a support tool, not a substitute for teaching.

• The teacher’s role becomes even more critical in guiding critical thinking, creativity, and empathy—skills AI can’t teach.

  
  

  Preparing Students for the Future:

  • Early exposure to AI tools prepares students for future learning and careers.

  • Encourages curiosity about technology, helping them become not just users but potential future creators.

  • Students need to learn how to use AI responsibly and never be over-reliance on AI.

• Literacy and numeracy are interconnected and essential for learning.

• Numeracy is critical for success in math and science.

• Student engagement and a mindset of continuous learning are vital for effective teaching. Using AI at Work

  1. Lesson Planning
     Generate lesson ideas, activities, and differentiated tasks tailored to student needs and curriculum goals.

  2. Student Support
     Provide personalized feedback, reading support, or explanations of complex concepts.

  3. Data Analysis
     Analyze student performance data to identify learning gaps and inform instruction.

  4. Department Collaboration
     Draft meeting agendas, synthesize notes, and co-develop interdisciplinary resources.

AI is a support assistant but it is not a replacement of my own judgement or connection with others.

While AI brings about convenience, I must constantly remind myself it is ultimately just an assistant. It can make grading, lesson planning, idea generations or summarise content etc faster, but I should never over rely on that at the expense of quality thinking. I feel it when I look to AI for ideas. It really saves alot of time but I was also taken aback by how much I look to AI instead of thinking of ideas from scratch. Will that hinder creativity in time to come? Both as individuals or as a team. So AI is really just like a second opinion. While we marveled at how intelligent it is to be able to help us grade work according to the rubrics we input, I must still trust my professional judgement and have the final call and not to adopt AI's judgement wholesale. So perhaps moving forward, AI can help to grade low-level tasks or to provide first-draft fedback to students. but I should still mark the final product.

Disclaimer: This is written in my own words — it might not be as polished or impressive as something created with AI assistance, but it’s original and genuinely mine. :P

Meta-reflection:

1. Rating: 4.1415926535897932384626433832795028841

   Professor Luckin’s address speaks directly to my role as a teacher. Her vision for an “intelligence infrastructure”—where AI augments human cognition—aligns with my goals of fostering self‐regulated learning and evolving assessment practices to better recognise uniquely human skills. 🤖

Understanding & Key Takeaways

1. Distinguishing Human vs. Artificial Intelligence:

   • Prof. Luckin stressed that while AI handles pattern recognition and data processing at scale, human intelligence (HI) remains unmatched in creativity, empathy, ethical reasoning, and metacognitive reflection.

2. Evolving Assessment to Value Human Capacities:

   • Current systems often emphasise rote recall and standardisation. She argues for assessments that reward problem‐solving, critical thinking, and creativity—skills that machines cannot replicate. By shifting from “Can you recall facts?” to “Can you apply insight and judgment?”, we honor HI and avoid cognitive complacency.

3. Light Bulb Moment

   Realising that AI can serve not merely as a “grader” but as a “thinking coach” was transformative. For example, an AI prompt that asks a student to revisit their hypothesis after reviewing data shifts feedback from summative to formative. It reframes AI’s role: not to replace human judgment, but to amplify students’ capacity for reflection and deeper understanding.

Application & Next Steps

1. Enjoy June Holidays first! 🤣🤣🤣

2. Explore AI chatbots and integrate Ai-prompted reflection. 🤔

The points are here:

1. it is a good way to integrate EL, Math, Computer Applications & Art

2. Math - Pythagoras theorem in a form a comic. Book integrator was used to present the sharing.

3. Students use programming skills to create animation in Pythagoras theorem.

4. Students had to source pictures and creating a story using Story Boarding.

5. In this way, it will make meaning for Normal Technical Students.

6. Use padlet to check on the students’ ideas about Pythagoras theorem. Teachers could pick out those with misconceptions.

7. Students could use Geogrbra App to draw diagrams of different shapes.

8. Reflection was done to ask feedback from students whether they like direct instructions or use digital method to teach Zpythagoras theorem.

9. To find out whether the students learn, use exit tickets and reflection to check.

10. This lesson approach uses 21 CC skills in many ways.

11. EL teachers taught Pythagoras theorem from the EL perspective through research. Using EL reading Comprehension skills where chunking strategy was taught. They had to paraphrase the research article and interpret the meaning of certain words. Students were taught inference skills based on how debunking technique was used.

12. The Art teacher taught the students how to use Pythagoras Theorem to include the properties of certain triangles in their drawings.

Personal Reflection

It is very interesting to see how EL, Math, Art and Computer Applications can come together to motivate students to learn well. The 21st CC skills that are used will help students to apply it in other subjects eg. Science.

Over reliance on AI generated answers may discourage deeper thinking, problem solving or exploration of multiple solutions, stifling students' creativity.

AI should be leveraged thoughtfully in the classroom to nurture active learning, where AI complements, not dominates, the cognitive process.

What's next...

Learning to evaluate AI resources, to design AI enhanced learning tasks that encourage deep engagement and to explore assessment strategies that measure understanding rather than AI assisted performance.

My Takeaways from West Grove Primary’s Use of Sam AI

1. Personalized Learning
   Sam AI adapts to each student’s learning pace and needs, helping them master science concepts more effectively.

2. Engaging, Inquiry-Based Lessons
   It supports interactive learning by guiding students through questions, simulations, and real-time feedback.

3. Teacher Empowerment
   Teachers get insights into student progress and can adjust lessons or groupings accordingly.

4. Seamless Integration
   It works well with platforms like SLS, making it easy to embed AI tools into existing lesson plans.

💡 How I Can Use This in My Teaching or Department Work

• Try AI Tools for Differentiation: Use AI platforms to assign tasks based on students’ readiness levels.

• Enhance Science Inquiry: Incorporate AI-driven simulations or questioning tools to deepen scientific thinking.

  
  

🧭 Meta‐reflection
Rate: 4. I face the same challenges: designing inquiry‐rich lessons, integrating EdTech meaningfully, and providing timely, individualised feedback. The exemplars and AI companion directly address these needs.

🔍 Understanding & Key Takeaways

1. Seamless Inquiry + EdTech + Authenticity

• Each exemplar (Water Cycle, Energy, Life Cycle) showed how to combine hands-on labs, digital simulations, and real‐world fieldwork (hydroponics, insect farms) in a cohesive unit. Some are shared via sgLDc which you can look up (West Grove Primary School).

  2. AI for Personalized Feedback & Teacher Insight

  • “Sam tutor” can deliver instant, scaffolded feedback that meets both lower- and higher-ability learners’ needs—clarifying concepts or offering challenging questions on demand.

  • The real-time dashboard synthesizes student queries, engagement levels, and off-task alerts, allowing me to intervene precisely where needed instead of chasing each individual in a busy classroom.

Lightbulb Moment
Seeing how Sam’s dashboard aggregates hundreds of real-time data points into clear, actionable alerts—so I can deliver micro-interventions on the spot rather than waiting for end-of-lesson scores—was transformative.

🛠️ Application & Next Steps

• Enjoy the June Holidays first! 😙😙😙

• Explore "Sam the Science Tutor", comparing it with similar Ai tools such as EdCafe, Mizou.

In summary, the role of an educator does not diminish with the push into the AI world. I used the word 'push' because the modern-world current caused me to involuntarily moved into the shift of paradigm. I still have to use my professional judgment to determine what is best for my students.

Teachers can include some of the elements in language lessons, weekly classroom discussions and even during TTLT where open discussions are highly encouraged.

I cannot teach anybody anything. I can only make them think - Socrates

Applying DI and using SLS are the areas that I would like to do more of in my teaching.

b)Understanding & Key Takeaways

-Sharing involved many examples of the digital tools used to track learning progress

Key Takeaways:

• The library is a gateway to lifelong learning

• Student ownership of the library (e.g. peer recommendations) increases engagement.

• Library programming can be integrated with school-wide goals like SEL (Social Emotional Learning) and digital citizenship.

Application in Your School

1. Reimagine the Library Space

   • student art displays.

   • Use student feedback to redesign the layout or book displays.

2. Launch Library Programmes

   • Book Talks: Students present their favorite books.

   • Reading Challenges: Themed reading months or genre bingo.

   • Author Visits / Virtual Meetups: Connect with writers or illustrators.

3. Collaborate Across Subjects

   • Work with teachers to integrate library resources into lessons

     
     

Understanding & Key Takeaways

1) Purposeful tech integration using TPACK – Technology is most effective when aligned with pedagogy and content. Using tech should support learning outcomes, not replace pedagogy.

2) Platform layering with clear objectives –

• SLS for differentiated tasks and consolidation.

• NearPod for flipped learning and readiness checks.

• Padlet for collaborative learning, peer feedback, and self-reflection.

Was there a "lightbulb moment" during the workshop? Describe it.
My lightbulb moment was when I saw how uploading of videos on Padlet can be transformed into a gallery walk and the use of Praise–Question–Polish (PQP) for students to provide peer feedback thereafter.

Application and Next Steps

Science presentation via video with peer assessment. Students become both creators and critics, owning their learning journey while learning from peers.

I would rate this session a 3. The session is a collective approach on how Maths, PE and Science and CL teachers used SLS and Classpoint to conduct their lessons. The sharing of SLS features was more heavy-going than AI.

Understanding & Key Takeaways

1) Layered lesson design enhances engagement – A structured flow using game story, video, guided discussion, and assessment keeps students engaged and builds deeper understanding for the topic on adaptation.

2) Feedback is not the end, but a bridge – The example where students corrected their responses on SLS after receiving targeted feedback shows how learning deepens through reflection and revision.

Was there a "lightbulb moment" during the workshop? Describe it.
Seeing how SLS ITT can be used not just for collecting responses but also for student self-correction. When students act on teacher feedback immediately (as shown in the diagrams), they internalise learning better. It transforms assessment into a dynamic and learner-led process.

Application and Next Step
SLS ITT for Science open-ended responses.

Students to use teacher's feedback and self-assessment to improve in their learning

b)Understanding & Key Takeaways

-Presenter shared how it was done and challenges faced

-Success criteria must be clear

-Feedback / self-assessment can be by component/parts, not to do everything at one go

1. On a scale of 1–5, how relevant was this session to your role? Explain your rating.

5 - definitely relevant as a character educator

🔍 Understanding & Key Takeaways

1. What are 2–3 key takeaways from the session?

   • Character is not about the rules / the consequences. It is about your foundational values that guides you to make a decision, that might not follow rules / consequences.

   • Holistic way of looking at character: intellectual virtues, moral virtues, civic virtues, performance virtues

   • Framework to consider how we can promote human flourishing in the digital world; values undergird how we operate that promotes human fluorishing.

   • Students need to be given autonomy to work out their character within themselves. Conditioning doesn't work.

   • Literacy through narratives, reasoning through moral dilemmas, exemplars, journals (some ways in which we teach character education)

2. Was there a "lightbulb moment" during the workshop? Describe it.

   • There needs to be some space for students to come to their own realisations on what they value for their character. Some autonomy and space to deliberate - I guess will need to frame this in an age-appropriate way.

🛠️ Application & Next Steps

1. What is one idea you can apply in your classroom / department work?

   • Considering how I can enrich opportunities for students to deliberate and consider what is right in different situations

Rating: 5 / 5
This session zeroed in on AI’s impact on education—precisely where my leadership focus lies. From adaptive feedback loops to safeguarding students’ meta‑cognition, every discussion thread mapped directly onto our Science and EdTech strategic plans.

Understanding & Key Takeaways

1. The “perfect storm” of AI – exponential data, processing power, and smarter algorithms explains the post‑2022 ChatGPT leap and the pace of change we must keep up with.

2. Opportunity–risk duality – AI can personalise learning and automate formative feedback, yet over‑reliance and embedded biases threaten students’ reasoning if left unchecked.

3. Human meta‑intelligence matters – our tacit knowledge, senses, and meta‑contextual thinking are where humans outpace machines; cultivating these is the key to thriving alongside potential super‑intelligence.

   
   

Lightbulb moment:
Realising that true synergy appears only when AI‑generated analytics prompt deliberate student reflection—turning raw “data to insight” into a Fitbit‑for‑the‑mind that strengthens, rather than supplants, critical thinking.

Application & Next Steps

I will pilot a POEW‑aligned “Learning Analytics Dashboard”:

• Teachers set tasks → students attempt → AI analyses attempts → dashboard visualises patterns and auto‑prompts students to reflect on misconceptions and strategy choices.

• This marries AI insights with our Wonderment focus, nudging students to question why their data looks the way it does and plan next steps.

Rating: 5 / 5
The session laser‑focused on integrating AI to stimulate—not replace—critical thinking. That aligns perfectly with our Science department’s push to deepen students’ reasoning while harnessing AI dashboards and Wonderment tasks. Every framework (4D AI strategy, logic‑model planning, evidence‑based impact) feeds directly into our tech‑infused pedagogy plans.

Understanding & Key Takeaways

1. Critical thinking re‑defined – intelligent discrimination: knowing when to question, what evidence to seek, and how to construct arguments; tacit, meta‑cognitive, and meta‑contextual facets remain uniquely human.

2. AI as “friction” for thought – well‑designed prompts, challenge bots, structured debates, and collaborative problem‑solving can push students to test AI outputs, marshal counter‑evidence, and refine their own questions.

3. Theory‑of‑Change mindset – map users → resources → activities → outputs → outcomes → impact, test assumptions, and track data (qual + quant) to prove AI is stimulating rather than supplanting student reasoning.

Lightbulb moment:
Realising I can intentionally insert “productive struggle” by raising the friction level in a chatbot—forcing students to interrogate AI evidence, spot bias, and defend a position they don’t initially agree with. That turns AI from answer‑machine into thinking‑partner.

Application & Next Steps

I’ll prototype a “Challenge‑Bot” Logic Model:

• Activity: Students feed their scientific claims into the bot; it returns a counter‑argument laced with subtle flaws or unsupported assertions.

• Output: Students annotate the bot’s reasoning, flagging opinion vs. evidence, then rewrite a stronger argument.

• Outcome: Improved evidence‑based reasoning and metacognitive awareness, tracked via rubric and dashboard analytics.
  This slots neatly into POEW’s Explain phase, reinforcing critical‑thinking muscles across the department.

Rating: 4 / 5
Watching the open‑classroom lesson at MGS gave me concrete, live examples of how Pear Deck plus Gen AI can scaffold deep‑learning communication. While not a full workshop, the observation aligned strongly with our plans to embed AI‑mediated feedback and student‑designed prompts in Science lessons.

Understanding & Key Takeaways

1. Prompt‑creation loop – Students designed, tested and iterated their own prompts in Pear Deck, receiving colour‑coded AI feedback (green / yellow / red) that made quality visible at a glance.

2. AI as formative checker – The AI analysed written responses for structure, clarity and evidence, functioning as a real‑time “check‑for‑understanding” without derailing lesson flow.

3. Self‑directed refinement – Re‑reading, editing and group‑sharing cycles pushed learners from individual prompts to collaborative improvements, modelling metacognitive practice.

   
   

Lightbulb moment:
The traffic‑light feedback system instantly flagged prompt strength, freeing the teacher to roam and coach higher‑order thinking. That simple visual cue sparked richer peer conversation than a traditional rubric ever could.

Application & Next Steps

I’ll pilot a “Prompt Studio” segment in upcoming Science lessons:

• Design (1 min): Students draft a question or hypothesis prompt

• AI Feedback: Gen AI rates it G‑Y‑R and explains why.

• Revise & Share: Students edit, then merge top prompts into a group “Gold Question” for the class Wonderment board.
  This mirrors POEW’s Predict and Wonder phases while training students to craft precise, evidence‑seeking questions.

🧭 Meta-reflection

1. On a scale of 1–5, how relevant was this session to your role? Explain your rating.

   3

🔍 Understanding & Key Takeaways

1. What are 2–3 key takeaways from the session?

   • The Gap Year initiative is a deliberate shift toward a more self-directed, personalised form of professional learning that respects adult learning principles.

   • Creating “white space” and embedding flexibility into professional development structures allows teachers to reflect, reignite passion, and explore areas of deep interest.

   • The success of such an initiative hinges on trust, clarity, structured flexibility, and celebration of learning.

     
     

Lightbulb moment:
One powerful moment was the realisation that professional development does not always need to be top-down or workshop-based. The idea of journaling and celebrating individual growth at the end of the year resonated with me—it reframed PD as a narrative of ownership, not just attendance.

🛠️ Application & Next Steps

1. What is one idea you can apply in your classroom / department work?

I am thinking about how we can provide more white space in our PD, that we can tie in with reflection journal for our teachers to enhance / level up their practice in a more intentional manner.

On a scale of 1–5, how relevant was this session to your role?
Rating: 5
This session was highly relevant to my role as a classroom practitioner and school leader. It provided both a conceptual foundation and practical approaches to fostering metacognition in the English Language classroom. The strategies shared deepened my understanding of how to help students become more self-aware, intentional, and independent in their language learning, aligning well with our school's goals for cultivating lifelong learners.

🔍 Understanding & Key Takeaways

2–3 key takeaways:

1. Metacognition involves not just “thinking about thinking,” but also monitoring, evaluating, and regulating one’s learning processes to achieve goals more effectively.

2. Effective metacognitive instruction includes structured pre-, during-, and post-task reflection—e.g., planning for learning, monitoring strategies, and evaluating progress.

3. Teachers play a critical role by modelling metacognitive strategies, embedding metacognitive prompts in lessons, and scaffolding reflection to build learner agency.

Lightbulb moment:
One insight that stood out was how metacognitive development is a prerequisite for successful transfer of learning across contexts. The idea of productive struggle—allowing space for learners to plan, evaluate, and adjust—challenged me to reconsider how much I scaffold and when to let go.

🛠️ Application & Next Steps

One idea I can apply in my classroom / department work:
I plan to integrate metacognitive prompts more intentionally in my lessons, especially during reading and writing tasks. For example, prompting students to reflect on the strategies they use before tackling comprehension texts, or having them evaluate how a specific feedback loop (e.g., from the SLS Language Checker) impacted their writing revision. At the department level, we can explore professional learning sessions where we co-design metacognitive routines that fit our students' profiles.