Concept maps can be a useful addition to a learning system, but they serve a different purpose from retrieval practice and spaced repetition. For someone building a serious long-term learning system, the most useful approach is not to choose between them, but to give each method a different job.
What Does the Research Say About Concept Mapping?
The evidence discussed here concerns concept maps, rather than traditional radial "mind maps" as such. Concept mapping and mind mapping are related techniques, but they are not identical.
A 2023 meta-analysis by Izci and Acıkgoz Akkoc examined 78 studies of concept mapping and academic achievement and reported a large overall effect, with Cohen's d = 1.08. However, the studies were highly heterogeneous, with I2 = 88.781%. The underlying studies also covered research published from 2005 through 2017. Therefore, the 1.08 effect size should not be interpreted as a universal estimate of how much concept mapping improves learning for an individual learner.
A newer 2025 meta-analysis by Wang and Wang focused specifically on STEM education and synthesized 37 studies. It found a more moderate overall positive effect of concept mapping on STEM achievement, with Hedges' g = 0.630 and a 95% confidence interval of 0.469 to 0.790. The analysis also found favorable results in conditions where students independently constructed their maps.
These findings support a general conclusion: concept mapping can improve learning, particularly by helping learners organize and connect knowledge. They do not justify saying that concept mapping produces a specific universal percentage improvement in comprehension or long-term retention.
Why Effect Sizes Do Not Translate Into a Personal Percentage Gain
It is tempting to ask, "How much does concept mapping improve comprehension?" and answer with a number such as 10%, 20%, or 25%.
That would create a false level of precision.
The research reports standardized effect sizes, not a universal percentage increase in comprehension or long-term retention. The studies also differ in their populations, subjects, comparison groups, mapping methods, outcome measures, and instructional settings.
For example, an effect size of d = 1.08 does not mean that an individual learner should expect an 108% improvement in learning. Effect sizes describe the difference between groups or conditions in standardized units; they are not direct percentage increases.
The more defensible conclusion is that concept mapping appears to provide a meaningful learning benefit in many circumstances, although the size of the benefit varies considerably across studies and settings.
Concept Maps and Mind Maps Are Not Exactly the Same
This distinction is important because the strongest research discussed here concerns concept mapping.
A traditional mind map is generally organized around a central topic with branches and sub-branches. It is useful for organizing information hierarchically and obtaining an overview of a subject.
A concept map focuses more explicitly on relationships among concepts. Connections can be labeled to indicate what relationship exists.
For example:
Delay → can cause → Oscillation
Or:
Emotion → can influence → Belief Formation
Concept maps can also contain cross-links between different parts of the map.
Because the cited research concerns concept mapping, it would be inappropriate to assume that every form of traditional radial mind mapping produces exactly the same effects.
For practical learning purposes, however, the important feature is whether the visual representation helps the learner understand and retrieve the structure and relationships within the knowledge. A concept map, a radial mind map, or another well-designed relational diagram can potentially serve that purpose, even though the research evidence for the different formats is not interchangeable.
The Distinctive Value of Mapping
I would regard mapping primarily as a knowledge-organization and relational-understanding technique.
Consider learning about systems thinking.
A paragraph might explain that feedback loops can be reinforcing or balancing, that delays can affect system behavior, and that feedback structures can produce unexpected outcomes.
A conceptual map can make some of those relationships explicit:
Feedback Loops
↓
Reinforcing Loops → amplify change
Balancing Loops → counteract change
Delays → can distort feedback → can contribute to oscillation
The learner is no longer dealing only with a sequence of statements. The learner is building a representation of how the ideas fit together.
That is where I think mapping is especially valuable for complicated subjects.
Active Construction Is More Useful Than Passive Viewing
There is an important difference between looking at a completed map and constructing or reconstructing a map.
A passive approach might look like this:
Read the material → look at a completed map → feel that you understand it.
That may provide a useful overview, but it does not require much retrieval from memory.
A more active approach is:
Read the material → close the source → construct a map from memory → compare it with the source → correct omissions or errors → explain the relationships → reconstruct the map later.
This process combines several useful learning activities, including retrieval, organization, elaboration, generation, and metacognitive checking.
It is therefore reasonable to expect active construction and later reconstruction to be more useful than simply looking at a finished diagram. The STEM meta-analysis also found favorable results for learner-constructed concept maps. However, I would not claim that research has established a precise additional benefit for this exact combination of mapping and retrieval practice.
Where RemNote and Anki Fit In
Concept maps and flashcards answer different questions.
Concept map:
"How does this knowledge fit together?"
Anki or RemNote:
"Can I retrieve this knowledge, and can I still retrieve it later?"
Application:
"Can I actually use this knowledge?"
This is why I would not replace a retrieval-practice system with concept maps.
Anki and RemNote can be used to implement both retrieval practice and spaced repetition. The point is not that these tools perform completely separate functions. Rather, they are particularly well suited to maintaining access to specific pieces of knowledge through retrieval over time.
A Practical Learning System
For complex subjects, I would combine the methods rather than treating them as competitors.
1. Learn the material.
Read, listen to, or otherwise study the source material carefully.
2. Construct a conceptual map.
Identify the major concepts and, more importantly, the relationships among them. Include causal relationships, distinctions, mechanisms, processes, and important dependencies where appropriate.
3. Check the map against the source.
Look for missing concepts, incorrect relationships, and misunderstandings. Correct the map.
4. Create retrieval questions.
Turn important concepts and relationships into questions for Anki, RemNote, or another retrieval-practice system.
Good questions should not be limited to isolated definitions. Depending on the material, they can test:
- definitions
- distinctions
- causal relationships
- mechanisms
- examples
- boundary conditions
- applications
5. Use spaced retrieval.
Review the questions over time so that important knowledge remains accessible.
6. Periodically reconstruct the conceptual structure.
Instead of always reviewing the finished map, occasionally start with only the central concept and reconstruct the major branches and relationships from memory.
The "Blank Map Test"
I particularly like the idea of a blank map test.
Suppose the central concept is:
FEEDBACK LOOPS
Without looking at the original material, try to reconstruct the major concepts and relationships surrounding it.
Then compare your reconstruction with the original map.
This turns the map from a passive visual aid into a form of large-scale retrieval practice.
It also tests something that ordinary flashcards do not always test particularly well: whether you understand the overall structure of a subject.
Using AI to Create the Maps
There is an additional efficiency advantage if artificial intelligence is used to create the initial conceptual map.
For a large collection of educational articles, manually creating a conceptual map for every article could take substantial time. An AI system can perform much of the initial organizational work.
A useful workflow is:
Article
↓
AI identifies the conceptual structure
↓
AI creates a compact concept map
↓
Human checks the map for accuracy
↓
Map is placed below the article
The human review is important. The AI should not be allowed to introduce concepts that are absent from the article or distort the author's arguments.
I would also instruct the AI to create the minimum number of maps necessary. One map should be preferred when it can represent the material clearly. Multiple maps should be used only when an article contains genuinely distinct conceptual systems that would become confusing or excessively crowded in a single map.
The goal should not be to create an elaborate diagram. The goal should be to create a useful representation of the article's underlying knowledge structure.
From Articles to a Learning System
This approach becomes particularly powerful when used across an entire series of related articles.
Each article can contain:
Article
↓
Concept map
Important concepts from the map can then become:
Concept map
↓
Retrieval questions
↓
Anki/RemNote
↓
Spaced retrieval
Eventually, the maps from individual articles can also be integrated into a larger master conceptual map.
That master map can show how concepts from different articles relate to one another. It can also reveal gaps, redundancies, and connections that may not be obvious when the articles are considered separately.
What Each Method Is Best At
The simplest way to think about the system is:
Concept mapping: Organize and understand relationships.
Anki/RemNote: Practice retrieving specific knowledge and maintain access to that knowledge through spaced review.
Blank-map reconstruction: Retrieve and reconstruct the larger conceptual structure.
Application: Determine whether you can actually use what you learned.
These methods overlap, but they are not redundant. Each emphasizes a different aspect of learning.
The Bottom Line
I would not treat concept mapping as a replacement for retrieval practice or spaced repetition.
Instead, I would use it as a high-value complement to them.
The research supports the general conclusion that concept mapping can improve learning, although the size of the benefit varies considerably across studies and circumstances. The evidence does not justify assigning a universal percentage improvement to comprehension or long-term retention, nor does research on concept mapping automatically establish identical effects for every form of traditional mind mapping.
The most useful approach is therefore not:
Mind maps instead of Anki.
It is:
Conceptual organization + retrieval practice + spaced retrieval + application.
In simple terms:
Map: How does this knowledge fit together?
Retrieve: Can I recall the important pieces?
Reconstruct: Can I reproduce the larger structure?
Apply: Can I use what I know?
That combination provides a more complete learning system than relying on any one technique alone.
Sources
- Izci, E., & Acıkgoz Akkoc, E. (2023). The impact of concept maps on academic achievement: A meta-analysis. Heliyon, 10(1), e23290. DOI: 10.1016/j.heliyon.2023.e23290.
- Wang, X., & Wang, S. (2025). Concept mapping in STEM education: A meta-analysis of its impact on students' achievement. International Journal of STEM Education, 12, 50. DOI: 10.1186/s40594-025-00554-2.
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