Can You Really Make Someone Learn? - The Limits of Forced Education and the Science of Efficient Knowledge Sharing

• Target readers: Software engineers, team leaders, training managers
• Prerequisites: None
• Reading time: 22 minutes

Overview

“You can lead a horse to water, but you can’t make it drink.” This ancient proverb captures a fundamental truth about the limits of education.

Training new engineers, sharing best practices with team members, mandatory corporate training. We routinely invest time and energy in “teaching” and “making people learn.” But a question arises:

Is it truly possible to “make someone learn” who has no desire to learn?

If we try to force learning, isn’t that a form of “brainwashing”?

What are people who are “good at teaching” actually doing?

And isn’t there a more efficient approach?

This article explores the fundamental limits of “making people learn” based on scientific evidence from Self-Determination Theory, intrinsic motivation research, behavior change models, and the retrieval practice hypothesis. We then examine case studies from open source communities, marketing, healthcare, and other fields to propose a more efficient method of “pull-based knowledge sharing.”

Learning Is Inherently Voluntary

Three Psychological Needs Identified by Self-Determination Theory

Self-Determination Theory (SDT), proposed by Ryan & Deci, provides a powerful framework for understanding human motivation¹. According to this theory, effective learning requires the satisfaction of three basic psychological needs:

1. Autonomy: Acting with a sense of choice and volition
2. Competence: Feeling capable of exercising one’s abilities and improving skills
3. Relatedness: Feeling connected to others and having a sense of belonging

Research consistently shows¹:

The more autonomous the learner’s motivation, the better their academic performance, the longer they persist, the deeper they learn, the higher their satisfaction, and the more positive emotions they experience at school.

The key here is autonomy. This is the feeling of “choosing for oneself,” which is the opposite of being coerced.

The Overwhelming Power of Intrinsic Motivation

Cerasoli, Nicklin & Ford’s (2014) 40-year meta-analysis (183 studies, 212,468 data points) revealed the relationship between intrinsic motivation and performance²:

• Intrinsic motivation is a medium to strong predictor of performance (ρ = .21-.45)
• Intrinsic motivation predicts performance “quality,” while extrinsic incentives predict “quantity”

Furthermore, Deci, Koestner & Ryan’s (1999) meta-analysis of 128 studies found³:

• Extrinsic rewards significantly reduce intrinsic motivation (d = -0.28 to -0.40)
• Positive feedback enhances intrinsic motivation (d = 0.31 to 0.33)

In other words, “forced” learning is unlikely to lead to high-quality learning.

You Can’t Learn Without “Readiness” for Change

The Five Stages of Change

Learning is a change in behavior or thinking. The “Transtheoretical Model (TTM)” proposed by Prochaska & DiClemente describes behavior change in five stages⁴:

1. Precontemplation: Not recognizing the need for change
2. Contemplation: Beginning to consider change but not yet taking action
3. Preparation: Preparing to take action in the near future
4. Action: Actively changing behavior
5. Maintenance: Sustaining and establishing the change

Teaching People in Precontemplation Is Futile

Research shows that “stage-matched” interventions are more effective than mismatched ones⁴.

Stage	Learner’s State	Educational Effectiveness
Precontemplation	“I don’t need to learn this”	Almost none
Contemplation	“Maybe I should learn this”	Limited
Preparation	“I’m planning to learn”	Moderate
Action	“I’m actively learning”	High
Maintenance	“I’m continuing to learn”	High

In short, teaching someone who isn’t ready to learn (precontemplation) has almost no effect.

Is Forced Learning “Brainwashing”?

Let’s confront a fundamental question: Is forcing someone to learn against their will a form of “brainwashing”?

Similarities to Brainwashing

“Brainwashing” and “forced education” do share common elements:

Element	Brainwashing	Forced Education
Individual’s will	Ignored	Minimized to ignored
Purpose	Change beliefs/behavior	Change knowledge/behavior
Autonomy	Completely stripped	Significantly restricted
Psychological response	Resistance → submission (or rejection)	Psychological reactance (pushback)

From the perspective of Self-Determination Theory, learning without autonomy:

• May achieve surface-level compliance
• But deep internalization is unlikely
• Reverts when supervision ends

This resembles the effects of brainwashing. When removed from the coercive environment, the beliefs and behaviors that were supposedly instilled fade away.

Important Differences

However, there are crucial differences between brainwashing and forced education:

Brainwashing typically:

• Uses extreme methods like isolation, sleep deprivation, and fear
• Attempts to destroy critical thinking
• Does not permit exit

Forced education:

• Is usually not that extreme
• Generally permits critical thinking
• Allows exit options (resignation, transfer, etc.)

“Inputting Information” vs “Learning”

Research suggests a more fundamental distinction:

	Inputting Information	Learning
Possible through coercion?	Somewhat	Difficult
Persistence	Short-term	Long-term
Application ability	Low	High
Internalization	Does not occur	Occurs

You can force “information input.” You can make people answer test questions. But whether that becomes internalized as “learning” is up to the individual.

Thus, forced education is less like “brainwashing lite” and more like “ineffective information transmission.”

The Truth About “Great Teachers” - What Are They Actually Doing?

So what are people who are “good at teaching” actually doing?

Surprising Research: “Great Teachers” Don’t Teach

Research revealed a surprising fact: Teachers considered “great at teaching” aren’t actually “teaching”⁵.

What they do:

Effective Teacher Behaviors	Ineffective Teacher Behaviors
Listen	Talk incessantly
Ask what students want to do	Give detailed instructions
Explain the rationale for tasks	Ask controlling questions
Pick up on student questions	Give answers before students finish
Provide encouraging feedback	Criticize
Treat failures as exploration opportunities	Punish failures

Research has identified teacher behaviors that demotivate students⁵:

Students were demotivated by these teacher behaviors: talking incessantly, giving detailed instructions, asking controlling questions, setting deadlines, criticizing, and giving answers before students finish.

“Great Teachers” Are Really “Environment Facilitators”

What people called “great teachers” are actually doing:

1. Supporting autonomy: Offering choices and letting students set their own goals
2. Building competence: Providing appropriate challenges and constructive feedback
3. Fostering relatedness: Building trust and providing a safe space for failure
4. Removing demotivators: Avoiding criticism, control, and pressure

This is precisely “creating a learning environment,” which is fundamentally different from “teaching.”

“Great teachers” don’t teach. They draw out the desire to learn and create an environment for learning.

But It Still Costs Resources

Creating a “learning environment” requires:

Cost Factor	Content
Time	Listening, questioning, providing feedback, building relationships
Skills	Autonomy support techniques, appropriate difficulty calibration, trust-building ability
Patience	Respecting the other person’s pace and waiting
Energy	Customized responses for each individual

And importantly: Even after investing all these resources, whether someone learns is still up to them.

The Learning Benefits of “Teaching” Can Be Achieved Through “Output”

Let’s reconsider the value of “teaching.”

The Truth About the Protégé Effect

Psychology research has confirmed the “Protégé Effect” - people put more effort into learning when they’re learning to teach others⁶.

This seems to demonstrate the value of “teaching.” However, recent research reveals a deeper truth.

The Retrieval Practice Hypothesis: You Don’t Need to Teach

Koh et al.’s research compared “teaching” groups with “testing” groups⁷:

There was no significant difference in learning outcomes between the teaching group and the test-taking group (d = 0.10)

Researchers propose the “Retrieval Practice Hypothesis”⁷:

The learning benefits of “teaching” actually come from “retrieval practice (the effort of recalling information),” and you don’t need to actually teach someone.

The Generation Effect: Output Alone Is Sufficient

Furthermore, a meta-analysis of the “Generation Effect” found⁸:

“Generating” information yourself (writing, explaining, summarizing) improves memory by approximately half a standard deviation (effect size d = 0.40).

This also doesn’t require another person. The same effect can be achieved through:

• Writing blog posts
• Summarizing
• Self-explaining
• Taking notes
• Writing and publishing code

“Teaching” vs “Output” Comparison

Method	Learning Benefit for Self	Requires Others	Efficiency
Teaching someone	Yes	Required	Low
Writing a blog	Yes	Not required	High
Writing summaries/explanations	Yes	Not required	High
Testing/reviewing	Yes	Not required	High

The only guaranteed benefit of “teaching” (learning for yourself) can actually be achieved without others.

The Most Efficient Model: Output + Dialogue with Responders

Integrating the research so far, the most efficient knowledge-sharing model emerges.

Problems with the Traditional “Teaching” Model

Try to teach everyone
    ↓
Spend time on precontemplation people (no effect)
    ↓
Cost of assessing readiness
    ↓
Tends to become coercive (counterproductive)

The Efficient “Output + Response” Model

Create output (blog, presentation, code publication, etc.)
    ↓
Gain learning benefits for yourself (retrieval practice, generation effect)
    ↓
People who respond/ask questions = people ready to learn (self-selection)
    ↓
Communicate only with them

Why This Model Is Efficient

Aspect	Traditional “Teaching”	Output + Response
Target selection	Must assess yourself	Naturally filtered
Others’ readiness	Unclear	Confirmed when they respond
Your own learning	Through teaching	At the point of output
Coercion	Tends to occur	They come voluntarily
Scalability	1-to-1 or small groups	1-to-many possible

Win-Win for Both Parties

For you (the creator):

• Gain learning benefits at the point of output
• Don’t waste time on uninterested people
• Questions deepen your understanding further
• One output reaches many people

For others (receivers):

• Learn at their own timing (autonomy)
• Not coerced
• Learn deeply because they’re interested
• Have an environment to ask questions (relatedness)

Responders = Ready People

This is the key insight.

People who respond to or question your output already:

• Are ready for change (preparation stage or beyond)
• Are interested (have intrinsic motivation)
• Came on their own (have autonomy)

This means you don’t need to assess their readiness. By responding, they’ve demonstrated they’re “ready to learn.”

Research on Mandatory Training

For reference, let’s examine research on traditional mandatory approaches.

Voluntary vs. Mandatory Participation Comparison

Jong’s (2025) research compared training effects between voluntary and mandatory participation⁹:

For soft skills (communication, leadership, etc.):

• Voluntary participants showed significantly higher transfer of learning (practical application)
• Mandatory participants felt lack of autonomy and decreased learning motivation

For hard skills (technical skills):

• Mandatory participation can be effective in some cases
• However, this is at the level of acquiring minimal knowledge in a “no choice” situation

Problems with Mandatory Training

Research has identified factors that impede mandatory training effectiveness¹⁰:

• Pushback against lack of control: Dissatisfaction from not choosing for oneself
• Lack of interest: No inherent interest to begin with
• Perceived irrelevance: Feeling it’s unrelated to one’s work

Mandatory training is traditionally unpopular, perceived as ineffective, and seen as reducing learning motivation.¹⁰

Applying This to Engineering Workplaces

Traditional vs. Efficient Approaches

New Employee Training:

Traditional	Efficient
“This is essential knowledge” and teach	Prepare and publish documentation/tutorials
Same training for everyone	Respond carefully to those who ask questions
Frustration: “I taught them but they can’t do it”	Learn yourself through output

Sharing Best Practices with Teams:

Traditional	Efficient
“Mandatory attendance” study sessions	Write blog posts, internal wiki, ADRs
“Why aren’t you writing tests?” interrogation	Lead by example and demonstrate results
Mandatory rules	Answer questions from interested people

Practical Examples

Output formats:

• Technical blog posts
• Internal wiki/documentation
• ADRs (Architecture Decision Records)
• Code comments/READMEs
• Study session materials (voluntary attendance)
• OSS/sample code publication

Responding to engagement:

• Carefully answer Slack/chat questions
• Deep discussions in 1-on-1s
• Pair programming (with volunteers)
• Dialogue through code reviews

Cost-Effective Resource Allocation

Their State	How to Identify	Recommended Approach
Precontemplation	No response, no interest	Just publish your output
Contemplation	“Like” level response	Provide additional information
Preparation	Asking questions	Answer carefully, introduce resources
Action	Active discussion	Deep dialogue, pair work
Maintenance	Creating their own output	Collaboration

Key point: Don’t pursue people with no response (precontemplation)

Validation Across Various Fields

The “output + dialogue with responders” model described so far is actually a pattern that has already succeeded in various fields. Let’s look at some examples.

Open Source Communities: A Success Story of Coercion-Free Knowledge Sharing

Open source software (OSS) communities are a large-scale success story of the “output + response” model.

Research shows that OSS contributors are overwhelmingly intrinsically motivated¹¹:

• “Because it’s fun” is the strongest motivation (enjoyment-based intrinsic motivation)
• Learning opportunities and intellectual stimulation are primary motivators over monetary rewards
• No coercion at all; completely voluntary

The OSS knowledge-sharing model:

Publish code (output)
    ↓
Issues, pull requests, and questions come in (response)
    ↓
Dialogue with responders (= interested people)
    ↓
Both parties learn and the project grows

Why it works: No one is coerced. Only interested people respond and contribute voluntarily. This is exactly the model described in this article.

Corporate Compliance Training: An Example of Forced Education’s Limits

In contrast, the mandatory compliance training conducted at many companies clearly demonstrates the “limits of forced education” discussed in this article.

Research revealed a harsh reality¹²:

“Bad training is indistinguishable from no training at all”

• No direct evidence has been found for the effectiveness of mandatory training
• Some studies found training had “no effect on knowledge” and “increased discriminatory behavior”
• Tens of millions of dollars invested annually with unclear effectiveness

Problem	Correspondence to This Article’s Theory
Mandatory participation	Loss of autonomy → Deep learning doesn’t occur
Uninteresting content	Approach to precontemplation people → No effect
Formal attendance	Inputting information ≠ Learning

Implication: Providing information to people who are ready to learn is more effective than “implementing” training.

Inbound Marketing: The Victory of “Attraction”

The same pattern is confirmed in the marketing world.

Outbound (push-based): Ads, cold calls, one-way emails Inbound (pull-based): Attracting with blogs, SEO, valuable content

Research findings¹³:

• Inbound has approximately 60% lower lead acquisition costs ($135 vs $346/lead)
• Enables long-term relationship building with customers
• Accumulates sustainable assets (content)

This is exactly the “output + response” model:

Marketing	Education Equivalent
Publish content	Output
Interested people come	Responders = ready
Build relationships with them	Dialogue, deep learning

Attracting interested people (pull) is more effective than pushing on uninterested people - this applies to education as well.

Health Behavior Change: The Importance of Stage-Matching

The importance of “change stages” described in this article is also confirmed in healthcare and public health.

What research shows¹⁴:

• Stage-matched interventions are effective
• Intervention for people who aren’t ready is a waste of time and resources
• “Providing information to ready people” is better than “teaching”

Patient State	Effective Approach
Precontemplation (“I don’t need to change”)	Just provide information, don’t push
Contemplation (“Thinking about it”)	Organize pros and cons of change
Preparation (“I’m going to change”)	Plan specific methods together
Action (“I’m changing”)	Support and feedback

Even when doctors and nurses “instruct,” if patients aren’t ready, behavior doesn’t change. Waiting is also an important strategy.

A Common Pattern Across Four Fields

When we line up these phenomena, a common pattern emerges:

Field	Inefficient Approach	Efficient Approach
Education	Forced teaching	Provide environment for ready learners
OSS	—	Output + dialogue with responders
Corporate Training	Mandatory attendance for all	Deep support for interested people
Marketing	Push-based advertising	Attract with content
Healthcare	Uniform instruction	Stage-matched intervention

We might call this “Pull-Based Knowledge Sharing.”

Push-based: Force on others → Resistance, ignoring, formal compliance Pull-based: Publish value and attract → Voluntary participation, deep learning

Research shows that pull-based is overwhelmingly more efficient.

Conclusion: You Can’t “Make Someone Learn,” But There Are Efficient Methods

What psychology research consistently shows:

1. Learning Is Inherently Voluntary

• Autonomy is one of the basic psychological needs for learning
• Intrinsic motivation determines learning “quality”
• Coercion strips autonomy and inhibits deep learning

2. “Great Teachers” Don’t Teach

• What they do is “create a learning environment”
• But even then, whether someone learns is up to them
• Even with investment, results are probabilistic

3. The Learning Benefits of “Teaching” Can Be Achieved Through “Output”

• Retrieval practice hypothesis: The effort of recalling strengthens learning
• Generation effect: Writing/explaining alone improves memory
• Others are not needed

4. The Most Efficient Approach Is “Output + Dialogue with Responders”

• Gain your own learning benefits through output
• Responders = people ready to learn
• Natural filtering for efficiency

Practical Recommendations

1. Make Output a Habit

• Publish blogs, documentation, code
• Write not to “teach” but to “learn for yourself”
• Prioritize consistency over perfection

2. Value People Who Respond

• Answer questions carefully
• Invest time in people who show interest
• Create opportunities for deep dialogue

3. Don’t Obsess Over Non-Responders

• Don’t try to change precontemplation people
• Publish your output and wait
• Let them come when they’re ready

4. Reduce Mandatory “Education”

• Keep required training to a minimum
• Make information public and accessible
• Offer choices, not mandates

Summary

Can you “make someone learn”?

Based on psychology research, the answer is: Truly, no.

However, there are efficient methods of knowledge sharing.

Create output
    ↓
You learn (retrieval practice, generation effect)
    ↓
Dialogue with responders (= ready people)
    ↓
Both parties learn deeply

This model:

• Guarantees your own learning (obtained at point of output)
• Naturally assesses others’ readiness (known by response)
• Is not coercive (only voluntary participants)
• Is scalable (one output reaches many)

You can lead a horse to water. But whether it drinks is up to the horse.

That’s why it’s more efficient to publish information about the watering hole (output) and wait for thirsty horses to come on their own (response).

And drinking water yourself (learning) is something you can control. Every time you create output, you yourself are the one most certainly learning.

Related Articles

Check out other articles related to this topic:

• It’s More Cost-Effective to Change Yourself Than to Change Others - Evidence from Psychology Research - A companion piece to this article. Why attempts to change others often backfire
• Evidence-Based Effective Learning Methods - Research on improving your own learning efficiency

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Note:

The research cited in this article has been verified through:

• Academic databases (PubMed, Google Scholar, PsycNET, etc.)
• Official journal website verification
• Cross-verification through multiple independent sources

References

References corresponding to citation numbers in the main text, listed in numerical order.

Additional References (not numbered in main text)

• Stages of Change Theory - StatPearls, NCBI Bookshelf (2023). [Reliability: High]

• The Testing Effect: How Retrieval Practice Strengthens Learning - Structural Learning. [Reliability: Medium]

• The Generation Effect: Why Creating Information Beats Reading It - Structural Learning. [Reliability: Medium]

1. Applying Self-Determination Theory to Education: Regulations Types, Psychological Needs, and Autonomy Supporting Behaviors - Guay, F. (2022). Canadian Journal of School Psychology. [Reliability: High] ↩︎ ↩︎²

2. Intrinsic Motivation and Extrinsic Incentives Jointly Predict Performance: A 40-Year Meta-Analysis - Cerasoli, C. P., Nicklin, J. M., & Ford, M. T. (2014). Psychological Bulletin. [Reliability: High] ↩︎

3. Extrinsic Rewards and Intrinsic Motivation in Education: Reconsidered Once Again - Deci, E. L., Koestner, R., & Ryan, R. M. (1999/2001). Review of Educational Research. [Reliability: High] ↩︎

4. Applying the transtheoretical model to adolescent academic performance using a person-centered approach - ScienceDirect (2019). Learning and Individual Differences. [Reliability: High] ↩︎ ↩︎²

5. The Effect of the Teacher’s Teaching Style on Students’ Motivation - NYU Steinhardt. and Teachers’ authentic strategies to support student motivation - Frontiers in Education (2023). [Reliability: Medium-High] ↩︎ ↩︎²

6. Teachable Agents and the Protégé Effect: Increasing the Effort Towards Learning - Chase, C. C., Chin, D. B., Oppezzo, M. A., & Schwartz, D. L. (2009). Journal of Science Education and Technology. [Reliability: High] ↩︎

7. The Retrieval Practice Hypothesis in Research on Learning by Teaching: Current Status and Challenges - Frontiers in Psychology (2022). [Reliability: High] ↩︎ ↩︎²

8. The generation effect: A meta-analytic review - Bertsch, S., Pesta, B. J., Wiscott, R., & McDaniel, M. A. (2007). Memory & Cognition. [Reliability: High] ↩︎

9. The Effects of Voluntary and Mandatory Training Participation on the Dynamics of Transfer of Training for Different Training Types - Jong, J. (2025). International Journal of Training and Development. [Reliability: High] ↩︎

10. Evidence Brief: The Effectiveness Of Mandatory Computer-Based Trainings - NCBI Bookshelf (2016). [Reliability: High] ↩︎ ↩︎²

11. Working for Free? Motivations for Participating in Open-Source Projects - Lakhani, K. R., & Wolf, R. G. (2005). International Journal of Electronic Commerce. and Why Hackers Do What They Do: Understanding Motivation and Effort in Free/Open Source Software Projects - MIT Sloan Working Paper. [Reliability: High] ↩︎

12. Evidence Brief: The Effectiveness Of Mandatory Computer-Based Trainings - NCBI Bookshelf (2016). [Reliability: High] ↩︎

13. Inbound Marketing vs Outbound Marketing - HubSpot. and State of Inbound reports showing conversion rate comparisons. [Reliability: Medium] ↩︎

14. Stages of Change Theory - StatPearls, NCBI Bookshelf. [Reliability: High] ↩︎