Konsep Pembelajaran Mendalam (Deep Learning)

Main ideas, concepts, and lessons

• Teachers as “lifelong learners”

  • The session frames Teacher Learning Day as a space for teachers to keep growing.
  • Reflection and sharing plans are presented as essential habits for improvement.

• Designing “grounded” deep learning (Deep Learning)

  • The core message is that deep learning shouldn’t be “theories above the clouds.”
  • Instead, it should be grounded in real classroom events and real student life.

• Two-day webinar theme

  • Day 1 (this session): designing meaningful deep learning teaching modules with AI, focusing on learning experiences, principles, and mapping them to graduate profile dimensions.
  • Day 2 (tomorrow): working with Mr. Rizki to design modules with AI.

• Main principles of deep learning

  • The principles are repeatedly stated as:
    • Mindful / Awareness
    • Meaningful / Meaning
    • Joyful / Joy
  • Key teaching challenge: keeping lessons fun while staying meaningful.
  • “Joy” is emphasized as coming from repeated aha moments—not from shallow entertainment or icebreakers alone.

• Graduate profile dimensions and how to verify them

  • The example lesson is used to show how multiple graduate profile dimensions can be “ticked” (evidenced) through learning activities.
  • The facilitator stresses that dimensions are reached through learning processes, not through superficial add-ons (e.g., prayer/songs as “stickers”).

• Learning experience cycle: Understanding → Applying → Reflecting

  • Deep learning is organized into a learning experience flow with three stages:
    1. Understanding
    2. Applying
    3. Reflecting
  • Reflection is not only “How do you feel?” but drawing conclusions and planning next actions (often described with the term mundeli).

• Scaffolding must match student diversity

  • Students with higher independence need less scaffolding and more autonomy.
  • Students who need more support get guidance tools (e.g., worksheet guidance for interviews/questions).
  • Teachers should use assessment to decide scaffolding levels.

• AI is a tool—pedagogical principles must lead

  • AI (mentioned: GPT, Gemini, etc.) can speed up design tasks, but teachers must:
    • ensure AI outputs are correct,
    • provide contextual judgment,
    • not let AI replace the teacher’s role in pedagogical grounding.

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Methodology / instruction list presented (detailed)

1) How to design deep learning using the learning experience flow

• Step A — Start with real initial assessment

  • Initial assessment can be informal and continuous (e.g., noticing what students talk about in everyday life).
  • Use student conversation/interests as a basis to set learning objectives.

• Step B — Build the learning experience in 3 stages

  1. Understanding

     • Connect the real context to the concept (e.g., experience-based discussions rather than definitions from a textbook).
     • Stimulate analysis and discussion (e.g., differences between evidence-based facts and opinions).
     • Allow exploration and expression based on student experience.
     • Build early awareness of diversity of thoughts/feelings → supports tolerance.

  2. Applying

     • Use real-life situations (not fictional worksheets that lead students to memorize definitions only for exams).
     • Apply new understanding to handle real information/filtering tasks.
     • Use mini-projects/case studies grounded in the students’ environment (e.g., “canteen detectives” investigating rumors).

  3. Reflecting

     • Guide students to summarize conclusions (mundeli), not just emotions.
     • Focus on behavioral follow-through:
       • “If we hear gossip again, what will we do?”
       • “How do we filter before believing/sharing?”
       • Respect differences of opinions and avoid impulsive conclusions.

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2) How to ensure the principles (Mindful–Meaningful–Joyful) appear in lessons

• Awareness (Mindful)

  • Evidence: students connect learning to real context; they recognize what/why it matters.

• Meaning (Meaningful)

  • Evidence: students can explain what the knowledge is used for and apply it to real challenges.

• Joy (Joyful)

  • Evidence: students experience aha moments repeatedly through challenge + thinking + problem-solving.
  • Caution: icebreakers alone don’t guarantee joy; joy must come from meaningful cognitive discovery.

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3) How to map graduate profile dimensions (what counts as evidence)

Treat dimensions as achieved through learning processes (Understanding–Applying–Reflecting), not as:

• routine habits (“prayer before class” as a mere formality),
• decorative content (citizenship/piety as stickers).

Use classroom evidence such as:

• observable behaviors,
• student outputs,
• discussion reasoning,
• project/product work,
• assessment instruments (when needed to measure achievement more precisely).

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4) How to design scaffolding and assessment

• Use assessment data to decide scaffolding level for each student group.

• Less independent students

  • Provide structured worksheets and clearer guidance (e.g., interview question templates).

• More independent students

  • Give bigger challenges (e.g., student-generated interview questions, independent investigation).

• Scaffolding should be adaptive to diversity of student conditions.

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5) How to use AI safely in module design

• AI can assist with:

  • speeding up project ideas,
  • designing scaffolding instruments,
  • accelerating compilation tasks.

• Teachers must:

  • verify correctness,
  • supply context so the AI does not produce inappropriate content,
  • remain the “pedagogical decision-maker.”

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Example used to ground deep learning (what the facilitator demonstrated)

Context

• A public elementary grade 5 class (teacher referred to as Mrs. IS) in an area described as near Merapi.
• Theme: distinguishing facts vs opinions using real experiences.

Initial assessment approach

• The teacher gathers assessment through student conversation and daily experiences, not only formal tests.

Learning experience events (Understanding stage focus)

• Instead of looking up definitions in a book, the teacher uses a previous day’s cooking/eating experience.

• Students’ statements are written in two columns:

  • Left: what was perceived as the same factual event (e.g., time, number of ice cubes, what food happened).

  • Right: statements tied to feelings/thought judgments that can differ (e.g., “soup is salty,” “fried chicken is delicious,” “not exciting,” etc.).

• Students reason about patterns:

  • Why the left column is shared/predictable,
  • Why the right column varies by individual perceptions.

Applying stage (how knowledge is used)

• Students handle real rumor/information in their environment (example described as “canteen detectives”).
• They investigate, collect data, separate factual data from opinions, and clarify rumors.

Reflecting stage

• Students conclude rules such as:
  • filter before sharing,
  • investigate truth before believing,
  • respect other opinions,
  • avoid impulsive judgment.

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Speakers / sources featured (as named in subtitles)

People (speakers)

• Host / moderator: Mrs. Alin (referred to as “I, Alin…” and as the session coordinator)

• Resource person: Mrs. Karunia Ningas Rezeki (called Mb[a]k Tias / Mrs. Tias)

• Committees mentioned for official session info:

  • Mrs. Erna
  • Mr. Huda
  • Mrs. Lukon
  • Mrs. Dina

• Other teachers/participants who spoke:

  • Mrs. Nina (Surabaya)
  • Mrs. Nur (Pasuruan; PAUD teacher)
  • Mrs. Dian Maharani
  • Mr. Paino (Serang, Banten)
  • Mrs. Dewi (asked a question; referenced in chat summary)

Planned/mentioned future speaker

• Mr. Rizki (tomorrow’s second-day presenter)

Sources / documents / institutions

• Indonesian Ministry of Education, Culture, Research, and Technology (Kemdikbud) curriculum/official documents
• Curriculum website mentioned: kurikulum.kemdikdasmen.go.id
• AI tools mentioned: GPT, Gemini