forumguru.id The success of education cannot be measured simply by how much material a teacher delivers or how many questions students can answer correctly on a written test. True learning occurs when students understand what they are learning, can apply their knowledge in real situations, and are able to reflect on their learning experiences.
This is the esensial idea behind Deep Learning in education.
In the Indonesian education context, Pembelajaran Mendalam or Deep Learning is an approach designed to create learning experiences that are mindful, meaningful, and joyful. The learning experience is realized through three interconnected processes: understanding, applying, and reflecting.
Therefore, implementing Deep Learning in the classroom is not simply about using a particular teaching method. It requires careful planning, meaningful classroom experiences, authentic assessment, continuous reflection, and evidence that students are actually developing deeper understanding and greater independence.
This article explains the stages of Deep Learning implementation in the classroom and presents practical indicators that teachers and schools can use to determine whether Deep Learning is truly taking place.
What Is Deep Learning in the Classroom?
Deep Learning is an educational approach that encourages students to develop a deeper understanding of knowledge and connect that knowledge with real-life situations.
Students are encouraged not only to answer:
“What do I know?”
but also:
“Why does it matter?”
“How can I use it?”
“What evidence supports my understanding?”
“What can I do differently after learning this?”
The official Indonesian framework describes Deep Learning through three learning experiences:
- Understanding
- Applying
- Reflecting
These experiences are supported by four major elements:
- pedagogical practices;
- learning partnerships;
- learning environments; and
- digital utilization.
The three principles underlying the approach are:
- Mindful Learning — learning consciously and with awareness;
- Meaningful Learning — connecting learning with relevant contexts; and
- Joyful Learning — creating an engaging, positive, and motivating learning experience.
The Three Main Stages of Deep Learning Implementation
The implementation of Deep Learning in the classroom can be understood through three core stages:
UNDERSTAND → APPLY → REFLECT
These stages should not be interpreted as rigid steps that must always occur in exactly the same classroom sequence. Official guidance emphasizes that teachers can adapt learning activities according to the context, student needs, learning model, and classroom conditions.
Stage 1: Understanding
Building a Strong Foundation of Knowledge
The first stage is understanding.
At this stage, students actively construct knowledge rather than simply receiving information from the teacher.
The objective is to help students develop a strong understanding of essential concepts and connect them with different sources and contexts.
According to the official guidance, knowledge developed during this stage can include:
- essential knowledge;
- applicable knowledge; and
- values and character knowledge.
What Does Understanding Look Like?
A student demonstrates deeper understanding when they can:
- explain a concept using their own words;
- identify relationships between ideas;
- compare different examples;
- provide evidence or reasons;
- ask relevant questions;
- connect new knowledge with prior knowledge;
- identify patterns; and
- explain why a concept is important.
Simply memorizing a definition is not sufficient evidence of deep understanding.
For example, in a science lesson about climate change, students should not only memorize the definition of climate change. They should be able to explain possible causes, identify evidence, discuss consequences, and relate the issue to their local environment.
How Teachers Can Facilitate the Understanding Stage
Teachers can use various strategies, including:
Inquiry-Based Learning
Students investigate questions and construct explanations based on evidence.
Discussion
Students explain their ideas and listen to different perspectives.
Concept Mapping
Students visually organize relationships between concepts.
Observation
Students examine objects, phenomena, data, or situations.
Guided Investigation
Teachers provide appropriate scaffolding while allowing students to explore.
Prior Knowledge Activation
Teachers connect new concepts with what students already know.
The teacher’s role is therefore not simply to provide answers but to create conditions that allow students to construct meaningful understanding.
Stage 2: Applying
Turning Knowledge Into Action
The second stage is applying.
At this stage, students use the knowledge they have developed to solve problems, make decisions, create products, or respond to authentic situations.
The official Deep Learning framework describes application as the contextual use of knowledge and emphasizes activities such as problem-solving and decision-making. These activities may involve local, national, global, or professional contexts.
This stage is critical because students may understand a concept theoretically but still struggle to use it in a new situation.
Deep Learning therefore asks:
Can students transfer what they have learned to a different context?
Examples of Applying Knowledge
Suppose students have learned about waste management.
A conventional lesson might end after students answer questions about types of waste.
A Deep Learning lesson can continue by asking students to:
- observe waste produced at school;
- classify different types of waste;
- collect and analyze data;
- identify the main problems;
- discuss possible solutions;
- design a waste-reduction program;
- implement part of the program; and
- evaluate its effectiveness.
The students are no longer simply learning about waste management.
They are using knowledge to address a real problem.
Learning Activities That Support the Applying Stage
Teachers can use:
- Project-Based Learning;
- Problem-Based Learning;
- Inquiry-Based Learning;
- experiments;
- simulations;
- case studies;
- field observations;
- community projects;
- collaborative problem-solving;
- presentations;
- product development; and
- interdisciplinary projects.
The official guidance allows teachers to adapt existing learning models and strategies so that they support the experiences of understanding, applying, and reflecting.
Stage 3: Reflecting
Turning Experience Into Learning
The third stage is reflecting.
Reflection is more than asking students whether they enjoyed the lesson.
It involves students evaluating and interpreting the learning process and the results of their actions.
Students may consider:
- What did I learn?
- What did I understand better?
- What was difficult?
- What mistakes did I make?
- What strategy worked?
- What evidence changed my thinking?
- How can I improve?
- How can I apply this knowledge in the future?
The official Deep Learning framework describes reflection as a process in which students evaluate and give meaning to the learning process and outcomes.
Reflection Builds Independent Learners
One of the most important outcomes of reflection is the development of student autonomy and self-regulation.
Students gradually learn to recognize:
What they know.
What they do not know.
How they learn best.
What they need to improve.
How they can change their learning strategies.
This makes reflection an essential component of lifelong learning.
Reflection Methods Teachers Can Use
Teachers do not need complicated instruments.
Reflection can be conducted through:
- learning journals;
- reflection sheets;
- exit tickets;
- student portfolios;
- self-assessment;
- peer assessment;
- group discussions;
- presentations;
- learning logs; and
- short written responses.
For example:
Today I learned…
The most challenging part was…
I solved the problem by…
Next time I will…
Simple questions can provide valuable evidence of students’ learning processes.
The Role of Mindful, Meaningful, and Joyful Learning
The three principles of Deep Learning should be visible throughout classroom learning.
1. Mindful Learning
Students understand the purpose of learning and are consciously involved in the process.
Evidence may include students who:
- know the learning objectives;
- ask questions;
- monitor their progress;
- explain their learning strategies; and
- reflect on their experiences.
2. Meaningful Learning
Students understand the relevance of what they are learning.
Evidence may include students who:
- connect lessons with real life;
- use prior knowledge;
- apply concepts in authentic situations;
- solve contextual problems; and
- explain why the learning is important.
3. Joyful Learning
Students experience learning as engaging, positive, challenging, and motivating.
Evidence may include students who:
- participate actively;
- respond positively to challenges;
- show curiosity;
- collaborate with others;
- take initiative; and
- create or explore new ideas.
Importantly, joyful learning does not mean that every lesson must be a game or entertainment activity. The purpose is to create an environment in which students are emotionally engaged and motivated to learn.
Real Measures of Success in Deep Learning
This is one of the most important questions:
How can a teacher know whether Deep Learning has actually happened?
A noisy classroom, a sophisticated project, or a beautiful student product is not automatically evidence of Deep Learning.
Recent guidance from the Ministry of Primary and Secondary Education explicitly emphasizes that classroom success should not be judged only from the final product. Assessment should consider the learning process, collaboration, reflection, and student development.
Therefore, success should be measured through multiple sources of evidence.
1. Students Demonstrate Deeper Understanding
The first measure is the quality of student understanding.
Teachers can ask:
- Can students explain concepts in their own words?
- Can they connect different ideas?
- Can they identify cause-and-effect relationships?
- Can they provide evidence?
- Can they explain their reasoning?
- Can they apply concepts to unfamiliar examples?
Strong evidence of success:
Students can explain why and how, not merely what.
2. Students Can Apply Knowledge
A strong indicator of Deep Learning is the ability to transfer knowledge into new situations.
Teachers can observe whether students can:
- solve authentic problems;
- make decisions;
- design solutions;
- create products;
- conduct investigations;
- apply concepts in different contexts; or
- connect learning across subjects.
For example, a student who learns mathematical percentages and can use them to analyze household spending demonstrates stronger application than a student who can only solve textbook exercises.
3. Students Ask Better Questions
The quality of students’ questions is another important indicator.
Compare:
“What is the definition?”
with:
“Why does this happen?”
“What evidence supports this conclusion?”
“What would happen if this variable changed?”
“How could we solve this problem?”
The second group of questions indicates a movement toward deeper thinking.
4. Students Become More Independent
Deep Learning should gradually reduce students’ dependence on constant teacher direction.
A student who initially asks:
“What should I do next?”
may eventually ask:
“I think this strategy will work. Can I test it?”
That shift represents growing learning autonomy.
The 2026 guidance for school-model implementation includes learning autonomy as an indicator, with higher levels characterized by students independently planning, selecting, and adjusting learning strategies according to their needs and goals.
5. Students Can Reflect on Their Learning
A student who can clearly explain:
- what they learned;
- what they found difficult;
- how they solved a problem;
- what strategy they used;
- what they would change; and
- what they need to learn next
is demonstrating an important characteristic of Deep Learning.
Reflection should therefore be observed as evidence of learning, not treated merely as an additional classroom activity.
6. Students Are Able to Collaborate
Deep Learning often involves interaction with teachers, classmates, learning resources, communities, and the surrounding environment.
Teachers can observe whether students:
- listen to others;
- contribute ideas;
- share responsibilities;
- provide constructive feedback;
- resolve disagreements;
- communicate effectively; and
- work toward a common goal.
The quality of collaboration matters more than simply placing students into groups.
Group work is not automatically collaborative learning.
7. Students Show Greater Engagement
Engagement can be seen through:
- participation;
- curiosity;
- persistence;
- willingness to face challenges;
- initiative;
- active discussion; and
- willingness to revise ideas.
Official school-model guidance describes the higher levels of joyful learning as students becoming interested and inspired, responding to challenges, experiencing moments of learning success, and taking opportunities to initiate and create.
8. Students Produce Authentic Evidence of Learning
The final product can be useful evidence, but it should not be the only evidence.
Authentic evidence may include:
- projects;
- presentations;
- portfolios;
- experiments;
- prototypes;
- reports;
- performances;
- problem solutions;
- student explanations; and
- reflection records.
The important question is:
Does the evidence demonstrate understanding, application, and reflection?
9. Assessment Shows Progress, Not Just Scores
Deep Learning requires assessment to be integrated into the learning process.
The current planning guidance emphasizes that assessment is not merely an end-of-learning activity. Formative assessment is used during learning to provide meaningful feedback and improve understanding, while summative assessment evaluates overall achievement. Authentic assessment can collect evidence through products, performance, discussion, and reflection.
Therefore, teachers should compare:
Where students started
with
Where students are now.
Student growth can sometimes be more meaningful than a single final score.
10. Learning Outcomes Improve
Ultimately, the success of Deep Learning should be reflected in improved learning outcomes.
The official evaluation framework states that, in general, the success indicator for Deep Learning is improving the quality of education as reflected in student learning outcomes. Evaluation is organized into document evaluation, implementation evaluation, and impact evaluation.
However, learning outcomes should not be interpreted only as test scores.
They can include:
- conceptual understanding;
- application;
- critical thinking;
- creativity;
- collaboration;
- communication;
- learning autonomy;
- reflection; and
- other targeted competencies.
A Practical Deep Learning Success Measurement Table
Teachers can use the following simple framework to monitor implementation:
| Understanding | Students explain concepts in their own words and connect ideas |
| Application | Students use knowledge to solve authentic problems |
| Reflection | Students evaluate their learning and identify improvements |
| Mindful Learning | Students understand learning goals and monitor their progress |
| Meaningful Learning | Students connect learning with real-life situations |
| Joyful Learning | Students are engaged, motivated, and willing to face challenges |
| Critical Thinking | Students analyze evidence and provide reasons |
| Creativity | Students develop original ideas or solutions |
| Collaboration | Students contribute, communicate, and work effectively |
| Autonomy | Students increasingly manage their own learning |
| Assessment | Evidence comes from multiple authentic sources |
| Learning Outcomes | Students demonstrate measurable progress |
A Simple Four-Level Rubric for Classroom Monitoring
Schools can also develop a simple four-level observation rubric.
Level 1 — Emerging
Students mainly follow teacher instructions, demonstrate limited understanding, and depend heavily on guidance.
Level 2 — Developing
Students participate and demonstrate basic understanding but still require substantial guidance.
Level 3 — Advanced
Students demonstrate deeper understanding, apply knowledge independently in several situations, collaborate effectively, and reflect on their learning.
Level 4 — Excellent
Students consistently demonstrate deep understanding, independently apply knowledge in new contexts, initiate solutions, reflect critically, collaborate effectively, and regulate their own learning.
This four-level approach is consistent with the school-model guidance, which uses developmental levels such as Pra Berkembang, Berkembang, Maju, and Unggul for indicators including joyful learning, learning autonomy, and reflection.
What Should Teachers Observe During a Deep Learning Lesson?
Teachers can use a simple observation checklist:
Before Learning
- Is the learning objective clear?
- Does the lesson connect with students’ prior knowledge?
- Is the learning context relevant?
- Is the planned activity aligned with the intended competency?
During Learning
- Are students actively thinking?
- Are they asking questions?
- Are they discussing and collaborating?
- Are they investigating or solving problems?
- Are they applying knowledge?
- Does the teacher provide appropriate scaffolding?
- Is the learning environment safe and supportive?
After Learning
- Can students explain what they learned?
- Can they apply the knowledge?
- Can they identify difficulties?
- Can they reflect on their strategies?
- Can they identify what they need to improve?
Deep Learning Is Not Measured by Classroom Noise
A classroom can be very active but still produce shallow learning.
Students may be talking, moving around, using technology, and producing attractive projects without developing deep understanding.
Conversely, a quiet classroom can contain very deep learning if students are thinking carefully, analyzing information, solving problems, and reflecting.
Therefore:
Activity is not the same as learning.
And:
A beautiful product is not necessarily evidence of deep understanding.
The real question is what students understand, apply, think about, and learn from the process.
This point has also been emphasized by the Ministry’s recent discussion of Deep Learning implementation, which notes that a busy classroom does not automatically indicate Deep Learning and that assessment should consider the broader learning process.
The Role of Teachers in Measuring Deep Learning
Teachers are not merely evaluators at the end of a lesson.
They are observers of learning throughout the process.
Teachers should collect evidence through:
- questioning;
- observation;
- student work;
- discussions;
- performance;
- projects;
- formative assessments;
- self-assessment;
- peer assessment; and
- reflection.
This creates a more complete picture of student development.
The Role of School Leaders
Successful Deep Learning implementation requires support beyond perseorangan classrooms.
School leaders can monitor:
- teacher readiness;
- quality of lesson planning;
- classroom implementation;
- assessment practices;
- teacher collaboration;
- learning environments;
- learning partnerships;
- digital utilization; and
- student learning outcomes.
Recent guidance for Deep Learning school models identifies three broad areas of excellence: student learning, school leadership, and teaching quality. Teaching quality includes effective learning, authentic and equitable assessment, and continuous professional development.
A Practical Cycle for Continuous Improvement
Deep Learning should be treated as a continuous improvement process:
PLAN → IMPLEMENT → ASSESS → REFLECT → IMPROVE
PLAN
Design learning objectives, experiences, activities, and assessment.
IMPLEMENT
Provide meaningful, mindful, and joyful learning experiences.
ASSESS
Collect evidence of understanding, application, reflection, collaboration, and other intended competencies.
REFLECT
Teachers and students examine what worked and what did not.
IMPROVE
Revise learning strategies and plans for the next learning cycle.
This cycle ensures that Deep Learning does not become a one-time classroom activity but develops into a sustainable school culture.
Conclusion
The implementation of Deep Learning in the classroom is fundamentally a process of creating deeper and more meaningful learning experiences.
The three central experiences are:
Understanding → Applying → Reflecting
Students first build meaningful understanding, then use their knowledge in relevant contexts, and finally reflect on both the process and the results.
However, the real success of Deep Learning cannot be determined simply by asking whether teachers have used projects, group work, technology, or innovative activities.
The more important question is:
What changed in the students?
Successful Deep Learning can be seen when students:
- understand concepts more deeply;
- connect knowledge with real life;
- apply knowledge to new situations;
- ask better questions;
- think critically;
- collaborate effectively;
- become more independent;
- reflect on their learning;
- respond positively to challenges; and
- demonstrate measurable learning progress.
Therefore, the real measure of Deep Learning is not how busy the classroom looks, but how deeply students understand, how effectively they apply knowledge, and how consciously they reflect and grow as learners.
When these changes become visible and measurable, Deep Learning is no longer just a concept. It becomes a genuine transformation of classroom learning.
Frequently Asked Questions (FAQ)
1. What are the stages of Deep Learning in the classroom?
The three main learning experiences are understanding, applying, and reflecting. These experiences are supported by mindful, meaningful, and joyful learning principles.
2. What does the understanding stage mean?
The understanding stage is when students actively construct knowledge and develop deeper conceptual understanding from different sources, experiences, and contexts.
3. What happens during the applying stage?
Students use the knowledge they have learned to solve problems, make decisions, conduct investigations, create products, or respond to authentic situations.
4. Why is reflection important in Deep Learning?
Reflection helps students evaluate their learning process, recognize strengths and challenges, improve their strategies, and develop greater learning autonomy.
5. How can teachers measure the success of Deep Learning?
Teachers can measure success through multiple sources of evidence, including conceptual understanding, application, critical thinking, collaboration, reflection, student autonomy, engagement, authentic performance, and learning outcomes.
6. Is a high test score proof that Deep Learning has occurred?
Not necessarily. A test score can provide important evidence of learning, but Deep Learning requires broader evidence, including application, reasoning, authentic performance, collaboration, and reflection.
7. Is project-based learning required for Deep Learning?
No. Project-Based Learning can support Deep Learning, but teachers can also use inquiry, problem-based learning, experiments, discussion, contextual learning, simulations, and other appropriate strategies.
8. Does Deep Learning require digital technology?
No. Digital technology can support learning, but it is only one element of the learning framework. Meaningful learning can also occur through direct observation, discussion, experimentation, collaboration, and real-world activities.
9. What are the three principles of Deep Learning?
The three principles are Mindful Learning, Meaningful Learning, and Joyful Learning, which in the Indonesian framework are expressed as berkesadaran, bermakna, dan menggembirakan.
10. What is the strongest evidence that Deep Learning has succeeded?
The strongest evidence is a combination of student learning progress and observable changes in how students understand, apply, think, collaborate, reflect, and manage their own learning.
References
- Ministry of Primary and Secondary Education of the Republic of Indonesia. Deep Learning – Sistem Informasi Kurikulum Nasional. The official framework explains the principles, learning experiences, and four elements of the Deep Learning framework.
- Ministry of Primary and Secondary Education of the Republic of Indonesia. Panduan Mata Pelajaran Bahasa Indonesia. The guide explains the three learning experiences of understanding, applying, and reflecting and the types of knowledge developed through Deep Learning.
- Ministry of Primary and Secondary Education of the Republic of Indonesia. Naskah Akademik Pembelajaran Mendalam. The document explains contextual application, problem-solving, decision-making, and the role of multidisciplinary learning.
- Ministry of Primary and Secondary Education of the Republic of Indonesia. Perencanaan Pembelajaran dan Asesmen. The guidance explains formative and summative assessment, authentic assessment, and the use of multiple forms of evidence such as products, performance, discussion, and reflection.
- Ministry of Primary and Secondary Education of the Republic of Indonesia. Panduan Penyelenggaraan Sekolah Model Implementasi Pembelajaran Mendalam dan Koding dan Kecerdasan Artifisial, 2026. The guide provides developmental indicators for joyful learning, learning autonomy, and reflection.
- Ministry of Primary and Secondary Education of the Republic of Indonesia. Indikator Keberhasilan Implementasi Pembelajaran Mendalam. The framework describes document evaluation, implementation evaluation, and impact evaluation, with improved student learning outcomes as the general indicator of success.
- Ministry of Primary and Secondary Education of the Republic of Indonesia. Apa Itu Pelatihan Pembelajaran Mendalam? The official training guidance explains understanding, applying, and reflecting as core learning experiences.
