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Learning by teaching
Learning by teaching
Learning by teaching
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In the field of pedagogy, learning by teaching is a method of teaching in which students are made to learn material and prepare lessons to teach it to the other students. There is a strong emphasis on acquisition of life skills along with the subject matter.

Background

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Student teaching vocabulary

The method of having students teach other students has been present since antiquity.[1] Most often this was due to lack of resources. For example, the Monitorial System was an education method that became popular on a global scale during the early 19th century. It was developed in parallel by Scotsman Andrew Bell who had worked in Madras and Joseph Lancaster who worked in London; each attempted to educate masses of poor children with scant resources by having older children teach younger children what they had already learned.[2]

Systematic research into intentionally improving education, by having students learn by teaching began in the middle of the 20th century.[3]

In the early 1980s, Jean-Pol Martin systematically developed the concept of having students teach other in the context of learning French as a foreign language, and he gave it a theoretical background in numerous publications, which was thus referred to in German as Lernen durch Lehren, shortened to LdL.[4] The method was originally resisted, as the German educational system generally emphasized discipline and rote learning.[5] However the method became widely used in Germany in secondary education, and in the 1990s it was further formalized and began to be used in universities as well.[4] By 2008 Martin had retired, and although he remained active Joachim Grzega took the lead in developing and promulgating LdL.[5][6]

LdL method

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Central to Martin’s entire theory, both for LdL and for the New Human Rights, are the following interacting concepts:[7] thinking (information processing and conceptualization) – control – antinomies – dialectical thinking – exploratory behavior – cognitive map – flow effect – top-down/bottom-up – centripetal/centrifugal forces – neuronal behavior – linearity/nonlinearity – homeostasis – integration/differentiation – centralization/decentralization – self-referentiality – coherence.

LdL, modeled on the structure of the brain by Martin[8]

After preparation by the teacher, students become responsible for their own learning and teaching. The new material is divided into small units and student groups of not more than three people are formed.[5]

Students are then encouraged to experiment to find ways to teach the material to the others. Along with ensuring that students learn the material, another goal of the method, is to teach students life skills like respect for other people, planning, problem solving, taking chances in public, and communication skills.[9][10][11][12] The teacher remains actively involved, stepping in to further explain or provide support if the teaching-students falter or the learning-students do not seem to understand the material.[5]

The method is distinct from tutoring in that LdL is done in class, supported by the teacher, and distinct from student teaching, which is a part of teacher education.[4]

Plastic platypus learning

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Plastic platypus learning in action

A related method is the plastic platypus learning or platypus learning technique. This technique is based on evidence that show that teaching an inanimate object improves understanding and knowledge retention of a subject.[13] [14][15] The advantage of this technique is that the learner does not need the presence of another person in order to teach the subject. The concept is similar to the software engineering technique of rubber duck debugging, in which a programmer can find bugs in their code without the help of others, simply by explaining what the code does, line by line, to an inanimate object such as a rubber duck.[16]

Feynman technique flowchart

A similar process is the Feynman technique, named after physicist Richard Feynman, in which a person attempts to write an explanation of some information in a way that a child could understand, developing original analogies where necessary. When the writer reaches an area which they are unable to comfortably explain, they go back and re-read or research the topic until they are able to do so.[17]

Flipped learning + teaching

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Traditional instructor teaching style classes can be mixed with or transformed to flipped teaching. Before and after each (traditional/flipped) lecture, anonymized evaluation items on the Likert scale can be recorded from the students for continuous monitoring/dashboarding. In planned flipped teaching lessons, the teacher hands out lesson teaching material one week before the lesson is scheduled for the students to prepare talks. Small student groups work on the lecture chapters instead of homework, and then give the lecture in front of their peers. The professional lecturer then discusses, complements, and provides feedback at the end of the group talks. Here, the professional lecturer acts as a coach to help students with preparation and live performance.[18]

Application of Learning by Teaching (LdL) to Human-Robot Interaction

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The educational principle Lernen durch Lehren (LdL), or Learning by Teaching, has long been recognized for its ability to deepen the understanding of students through the act of teaching others. These same principles can be extended to human-robot interaction to enhance the learning process in artificial systems. In the context of human-robot interaction, the LdL approach provides a compelling model for designing robots that can learn, collaborate, and teach. One such relevant work done is developing a system where robots not only learn a skill from human experts but also teach that skill to novices.[19] The robot begins as a learner, observing and practicing a task under expert supervision. Through the teaching process, the robot is required to explain, demonstrate, and evaluate the skill, much like students in the LdL method. By teaching a novice, the robot gains feedback about its own understanding. This mirrors the LdL model, where teaching strengthens the learner's grasp of the material. The robot’s ability to switch between the roles of student, collaborator, and teacher enhances its capability to adapt, refine its task model, and assess its knowledge through teaching interactions. This dynamic role adaptation provides greater flexibility and leads to better long-term knowledge retention, which is also a core advantage of the LdL approach in human education. Some of the benefits of applying LdL approach to human-robot interaction include:

  • Enhanced Knowledge Evaluation: Teaching provides a new evaluation layer for the robot’s understanding. If the robot can teach effectively, it signifies a higher degree of task mastery, just as LdL assesses human understanding through peer teaching.
  • Improved Human-Robot Collaboration: By integrating LdL principles, robots can enhance collaboration with humans. When a robot teaches or learns from a human, the shared knowledge model becomes more aligned, leading to more efficient teamwork.
  • Promoting Lifelong Learning for Robots: Just as LdL fosters lifelong learning in humans by constantly engaging them in teaching roles, applying these principles to robots promotes continuous improvement in their learning models. The robot evolves not only by learning new skills but also by refining them through the act of teaching others.
    Learning by Teaching(LdL) for Human-Robot Interaction

See also

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References

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Further reading

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[edit]
Revisions and contributorsEdit on WikipediaRead on Wikipedia

Learning by teaching

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from Grokipedia
Learning by teaching, also known as the protégé effect, is an educational strategy where individuals deepen their own comprehension and retention of knowledge by actively explaining and instructing it to others, often leading to greater cognitive engagement and learning outcomes than solitary study methods. This approach leverages the act of teaching—such as preparing explanations, anticipating questions, and receiving feedback—to identify knowledge gaps, making it a cornerstone of collaborative and peer-based pedagogies. The concept has roots in antiquity, with empirical support emerging in the mid-20th century, and was formalized in the 1980s. It aligns with social constructivist theories like Vygotsky's , emphasizing bidirectional through interaction. Research, including meta-analyses and controlled studies, demonstrates benefits such as improved motivation, , and equity in diverse classrooms, though effectiveness varies with preparation and interaction quality. Recent applications as of 2025 extend to technology-enhanced scenarios, including AI-assisted and human-robot interaction, transforming passive learners into active builders.

Historical Development

Origins in Antiquity and Early Systems

The roots of learning by teaching can be traced to , where the , developed by in the 4th century BCE, employed dialectical questioning to encourage interlocutors to explain concepts to one another, fostering deeper understanding through peer-like dialogue. In his , further emphasized the interplay between teaching and learning, portraying the teacher-student relationship as a form of where instruction benefits both parties by reinforcing the teacher's and enabling the student's . During the medieval period, models within European craft guilds provided structured opportunities for novices to teach basic skills to their peers, as older apprentices assisted in instructing younger ones under the master's oversight, ensuring the transmission of trade knowledge in resource-limited workshops. In the late , the Monitorial System emerged as a formalized approach to peer instruction, pioneered by Andrew Bell in 1789 at the Military Male Orphan Asylum in Madras, , where he addressed teacher shortages by training older pupils as monitors to teach to younger ones, allowing a single master to oversee hundreds efficiently. Bell detailed this method in his 1797 publication An Experiment in Education, highlighting its for under-resourced colonial settings by drawing on local indigenous practices of mutual instruction. Joseph Lancaster independently adapted and popularized the system in early , opening a in 1798 that by the 1800s educated up to 1,000 poor children at a time through monitors who relayed lessons from the , emphasizing discipline, , and cost-effectiveness for mass education. Lancaster's version, outlined in his 1803 pamphlet Improvements in Education, focused on non-sectarian schooling and mechanical aids like sand trays for writing, enabling rapid expansion amid urban poverty. The Monitorial System spread widely across and the in the early 1800s, with over 275 schools established in the UK by 1816 alone, collectively serving thousands of students through peer-led classes that addressed teacher scarcity in industrializing societies. In the , it gained traction in northeastern cities like during the 1800s, where monitorial schools enrolled hundreds of pupils per institution, promoting orderly, large-scale instruction for immigrant and working-class children before graded systems supplanted it mid-century.

Formalization in the 20th and 21st Centuries

The formalization of learning by teaching in the mid-20th century was initiated through research on peer tutoring in the United States. Early evidence came from Cloward (1967), who demonstrated that peer tutors in remedial reading programs showed superior progress compared to their tutees, attributing gains to the explanatory demands of teaching. Building on this, a seminal 1971 study by Gartner, Kohler, and Riessman examined programs where older students taught younger peers in school settings, revealing benefits such as enhanced retention and academic gains for tutors through active explanation and reinforcement of material. These experiments provided an empirical basis for structured student-led instruction, distinguishing it from earlier informal practices like the 19th-century monitorial system. In the 1980s, Jean-Pol Martin developed the Lernen durch Lehren (LdL) method—translated as "learning by teaching"—specifically for French language classes at the Catholic University of Eichstätt-Ingolstadt in . The approach centers on students independently preparing and delivering lessons to their peers, positioning the teacher primarily as a to guide preparation and ensure coherence. By the 1990s, LdL had proliferated across German schools, gaining official recognition and integration into curricula through initiatives by the Standing Conference of the Ministers of Education and Cultural Affairs (KMK), which promoted active, strategies. Following Martin's work, Joachim Grzega advanced LdL starting in the mid-2000s, extending its application to English language teaching and interdisciplinary contexts at the university level. In his influential 2005 publication "The Concept 'Learning by Teaching'," Grzega highlighted the method's emphasis on transferring teaching responsibilities to students, thereby cultivating independence, creativity, and essential competencies for knowledge-based societies. He also introduced variations like "Learning by Teaching and Doing Research" (LdL&F), incorporating research elements to broaden its scope beyond language instruction, with further refinements in subsequent works such as his 2008 collaboration on preparing students for knowledge societies. In the , LdL and analogous peer-teaching approaches achieved broader global adoption, with integration into European curricula—such as in during the 2000s—and alignment with constructivist reforms in the United States that prioritize .

Theoretical Foundations

Psychological Mechanisms

Learning by teaching enhances retention through retrieval practice, wherein the act of explaining material to others compels the teacher to actively recall information from memory, thereby strengthening neural pathways and consolidating long-term retention more effectively than passive review methods. This mechanism aligns with the observed in , where retrieval not only reinforces memory traces but also identifies weaknesses in understanding during the teaching process. Empirical evidence from controlled experiments demonstrates that students who teach material achieve higher test scores than those who study alone, as the retrieval demands of teaching simulate real-world application and reduce forgetting over time. Complementing retrieval, generative learning occurs as the teacher organizes and verbalizes concepts, which promotes deeper cognitive processing by revealing knowledge gaps and fostering integration of new information with prior knowledge. In this framework, teaching acts as a generative activity that encourages the creation of mental models through explanation, rather than mere repetition, leading to improved problem-solving and conceptual understanding. Fiorella and Mayer's (2013) model outlines this process in stages—preparation for teaching, the explanation itself, and subsequent reflection—which collectively enhance learning by prompting elaboration and self-correction without external prompts. Social facilitation further amplifies these effects through peer interactions, where the presence of an audience motivates effort and provides opportunities for elaboration, thereby reducing and enhancing comprehension via collaborative . This draws from Vygotsky's (ZPD), in which the tutor-learner dynamic allows the teacher to explanations within the learner's reach, while simultaneously refining their own understanding through reciprocal clarification and adjustment. Such interactions not only boost but also facilitate immediate error detection, making learning more efficient than solitary study. Finally, feedback integration during teaching sessions enables recursive refinement, as responses from the audience highlight misconceptions and reinforce accurate representations, resulting in measurable gains in comprehension. Studies on interactive show that this loop promotes metacognitive awareness and strategies. Overall, these mechanisms interplay to make learning by a robust pedagogical tool for deepening .

Relation to Broader Learning Theories

Learning by teaching aligns closely with constructivist learning theories, particularly Jean Piaget's cognitive constructivism, which emphasizes that individuals actively construct by integrating new experiences into preexisting cognitive schemas through processes like assimilation and accommodation. In this framework, the act of teaching compels learners to reorganize and verbalize their understanding, thereby strengthening schema development and revealing inconsistencies in their . This approach also resonates with John Dewey's 1938 theory of , where education occurs through hands-on, collaborative activities that involve peer roles to negotiate meaning and apply concepts in social contexts, fostering reflective growth beyond isolated study. As a form of , learning by teaching diverges from passive methods like lectures by engaging students in generative activities such as explaining concepts to peers, which promotes and retention. Freeman et al.'s 2014 meta-analysis of 225 studies across STEM fields found that active learning approaches, including peer teaching and discussion-based explanations, yield substantial gains: student examination scores improve by 0.47 standard deviations (equivalent to a 6% increase), and failure rates are 55% higher under traditional lecturing compared to active learning, with effects consistent across class sizes and disciplines. These outcomes underscore how learning by teaching enhances conceptual mastery by shifting from reception to production of knowledge. The Feynman Technique, developed by physicist in the 1960s, directly embodies learning by teaching principles by instructing learners to explain material in simple terms as if to a , thereby simplifying ideas and exposing gaps in comprehension that require further study. This self-directed method parallels broader learning by teaching practices, where articulation to an audience—real or imagined—forces refinement of understanding without relying on rote . Learning by teaching further connects to Albert Bandura's , which posits that individuals acquire knowledge through observation, modeling, and within social environments, extending these mechanisms to reciprocal exchanges where the teacher learns from the learner's feedback. In this vein, the theory supports bidirectional modeling, as tutors demonstrate expertise while adapting to tutees' queries, enhancing mutual and behavioral reinforcement. This reciprocity is exemplified in strategies like reciprocal teaching, pioneered by Palincsar and Brown in 1984, where participants alternate roles in generating summaries, questions, clarifications, and predictions to build comprehension collaboratively.

Implementation Strategies

Core LdL Method in Classrooms

The core LdL method in classrooms follows a structured, student-centered approach where learners actively and present content to peers, fostering through the act of teaching. Developed by Jean-Pol Martin in the , this method delegates traditional teaching responsibilities to students while the instructor serves as a . The process is divided into distinct phases, emphasizing in small groups to build both subject knowledge and communication skills. In the preparation phase, students in groups of 2-3 select or are assigned specific topics from the and prepare teaching materials during class time, typically over about 2 lessons, using teacher-provided resources, textbooks, and authentic sources. They develop materials such as slides, diagrams, or interactive demonstrations to explain key concepts. This work encourages students to organize information clearly and anticipate potential questions, aligning with psychological mechanisms like the , where active retrieval strengthens memory. Groups collaborate to divide tasks and ensure comprehensive coverage. The delivery phase involves student groups presenting their prepared material to classmates in class sessions, using varied methods such as presentations followed by a question-and-answer segment and related exercises. Rotation among group members ensures every participant teaches at least once, promoting equal engagement and . These sessions are integrated into regular class time, with the class organized to cover the full syllabus efficiently. The teacher's role is primarily facilitative: providing initial resources, guiding topic selection, and monitoring sessions for factual accuracy, intervening only if misconceptions arise. Post-session allows the teacher to clarify errors collectively and reinforce learning. This hands-off approach empowers students while maintaining educational oversight. Assessment in LdL focuses on process and growth rather than punitive grading. Students use self-evaluation rubrics to reflect on their teaching clarity, content depth, and strategies, while group feedback forms capture peer insights on learning gains and effectiveness. Teachers may contribute formative feedback based on criteria like interaction and use, along with evaluations of quality and learning progress. The method is suitable for students across various ages and school levels, particularly in lower and settings, and applicable to a range of subjects including languages and sciences. For instance, in German high school French classes, LdL has been applied to build through student-led sessions on thematic units, where learners and teach word families or contextual usage to peers.

Variations Including Flipped and Inanimate Teaching

In flipped learning models, students engage with instructional content, such as pre-recorded videos, outside of class time, allowing in-class sessions to focus on interactive, student-led activities like discussions and peer teaching. This approach, pioneered by chemistry teachers Jonathan Bergmann and Aaron Sams, reverses traditional lecture formats by dedicating classroom time to application and collaboration, where students can explain concepts to one another to reinforce understanding. Integrating learning by teaching into flipped classrooms enhances retention through post-video student-led explanations, as learners articulate and clarify material during group interactions. Inanimate teaching variations adapt the method for individual practice by having learners explain concepts to non-responsive objects or imaginary audiences, promoting self-clarification without peer involvement. A notable example is "plastic platypus learning," where students teach to a toy to simplify and communicate ideas, drawing from broader self-explanation strategies in educational settings. Similarly, , originating from programming in the late 1990s, involves programmers verbalizing code line-by-line to an inanimate to identify errors, a technique that fosters deeper comprehension through articulated reasoning. The Feynman technique extends this by encouraging learners to pretend-teach complex topics to a or empty room, simplifying explanations to reveal knowledge gaps, as inspired by physicist Richard Feynman's emphasis on clear articulation for mastery. Solo or virtual adaptations of learning by teaching allow preparation of lessons for recorded delivery or forums, yielding benefits comparable to live interactions through enhanced self-explanation. Research demonstrates that explaining material to a fictitious or remote , without real-time feedback, still improves retention by prompting retrieval and of , as shown in experiments where students outperformed restudying groups on comprehension tests. For instance, 2021 studies found that non-interactive teaching to absent audiences boosted learning outcomes in science topics, attributing gains to the cognitive effort of generating explanations. Hybrid examples combine these variations in settings, such as seminars where students first teach concepts to AI chatbots or before peer sessions, refining explanations through simulated dialogue. In one , learners explained programming problems to a listening , which improved problem-solving by mimicking attentive feedback and encouraging precise articulation, bridging solo practice with collaborative preparation.

Research and Effectiveness

Key Empirical Studies

One of the earliest comprehensive investigations into the benefits of learning by teaching came from a by Cohen, Kulik, and Kulik (1982), which reviewed 65 independent evaluations of school tutoring programs involving over 1,000 participants across elementary and secondary levels. The analysis revealed that students serving as tutors achieved an average gain of 0.40 standard deviations in academic performance compared to non-tutoring peers, with similar positive effects on attitudes toward the subject but negligible impacts on . In the development of the LdL (Lernen durch Lehren) approach during the 1980s, Jean-Pol Martin conducted classroom experiments with hundreds of students in German schools, where groups prepared and delivered lessons on topics, leading to observed improvements in content mastery and retention through active explanation and peer interaction. A related empirical study by Annis (1983) involved 130 college undergraduates randomly assigned to five conditions: reading, studying, preparing to teach, teaching without interaction, or teaching with interaction. Results from pre- and post-tests showed that participants in the teaching conditions outperformed those in reading or studying alone on both content and cognitive measures, with the interactive teaching group demonstrating the strongest gains in comprehension and . Qualitative research by Grzega (2005) examined LdL implementation in classes with university students, analyzing classroom observations and student reflections to highlight increased engagement, , and collaborative skills, as students took ownership of lesson design and delivery, fostering deeper linguistic understanding over traditional lectures. More recent work by Fiorella and Mayer (2013) conducted two experiments with 134 undergraduates studying scientific texts, comparing studying alone, expecting to teach, and actually . Findings indicated that the teaching expectancy condition improved immediate and delayed retention by approximately 16% over studying alone, while actual teaching yielded an additional 9% benefit, attributed to enhanced cognitive processing during preparation. A 2025 study by Firat and colleagues, published in Educational Psychology Review, examined non-interactive teaching across multiple experiments with university students, finding that it fosters conceptual when combined with drawing activities, with effect sizes around 0.40-0.50 standard deviations in retention and transfer compared to studying alone, particularly in science learning contexts. Across these studies, common methodologies include randomized controlled designs with pre- and post-tests assessing knowledge retention and application, alongside control groups contrasting study with activities; sample sizes typically range from 50 to over 1,000 participants, spanning K-12 and higher education contexts.

Benefits, Limitations, and Criticisms

Learning by teaching offers several evidence-based benefits, particularly in enhancing retention and comprehension. Students who engage in teaching others without relying on notes demonstrate significantly better understanding and long-term retention compared to those who simply restudy material or perform unrelated tasks, as the act of teaching prompts retrieval practice that strengthens memory encoding. This approach also fosters skill development in communication and , as peer tutors must articulate concepts clearly and guide discussions, leading to improved interpersonal abilities and confidence in explanatory roles. Additionally, assuming active teaching roles boosts and engagement, transforming passive learners into proactive participants who feel a greater of ownership over their learning process. Despite these advantages, learning by teaching has notable limitations that can hinder its practical application. Preparation for teaching activities is often time-intensive for educators, straining instructional planning. Without close supervision, there is a of misinformation propagation, as novice tutors may inadvertently reinforce errors or misconceptions among peers, particularly in unstructured settings. Criticisms of learning by teaching often center on equity issues, where advanced or high-status students tend to benefit more by dominating interactions, while lower-achieving or marginalized peers receive fewer opportunities to learn, exacerbating achievement gaps. This disparity is highlighted in early reviews of peer tutoring, which noted that without intervention, able students reinforce their advantages, disadvantaging strugglers in heterogeneous groups. Cultural biases in group dynamics further compound these concerns, as differing norms around participation and authority can silence students from collectivist or minority backgrounds, leading to unequal contributions and outcomes. To address these challenges, mitigation strategies include comprehensive teacher training to facilitate balanced grouping and monitor dynamics, ensuring equitable participation through structured roles and status interventions. Hybrid models, blending teaching activities with traditional elements, can also reduce preparation load by distributing responsibilities and providing scalable support in large classes.

Modern Applications

In Traditional Education

In K-12 settings, learning by teaching manifests through structured peer instruction programs that encourage students to explain concepts to classmates, fostering active engagement and retention. In , the Lernen durch Lehren (LdL) method, pioneered by Jean-Pol Martin in the 1980s, has been widely adopted in secondary schools since the 1990s, particularly for preparing students for the examinations in subjects such as . This approach involves students researching and presenting historical topics to peers, which teachers report enhances comprehension and critical analysis of complex events. A notable example comes from U.S. middle schools, where the National Science Teachers Association (NSTA) has promoted peer-led laboratory activities since the early 2010s as part of initiatives. In these programs, students take turns leading experiments in science classes, such as demonstrating chemical reactions or ecological simulations, which builds confidence and deepens understanding of scientific processes through explanation and peer questioning. Teachers observe that such peer labs improve collaborative skills and reduce misconceptions compared to traditional demonstrations. In higher education, learning by teaching is often implemented via peer-led team learning (PLTL) workshops, where undergraduate students facilitate sessions on advanced topics for their peers. PLTL has been applied in introductory and other STEM courses, with peer leaders guiding discussions on topics like cellular processes and ; studies show this leads to higher retention rates compared to lecture-only formats. Subject-specific applications highlight the versatility of learning by teaching across disciplines. In , Martin's LdL model for French instruction requires high school students to prepare and deliver lessons on and vocabulary to classmates, promoting fluency and cultural insight through role reversal. In , university students explaining proofs to peers—such as geometric theorems or algebraic derivations—strengthens , with empirical studies indicating improved proof-writing skills via peer critiques and revisions. Interdisciplinary uses include project-based , where students collaborate across fields to create educational materials for community groups. Practical outcomes underscore the method's impact in traditional classrooms. Teachers frequently report that students achieve deeper conceptual understanding when teaching material, as the process of articulating ideas reveals and resolves knowledge gaps. A 2023 pilot study on formats, including peer teaching, found that most participants preferred interactive methods over traditional lectures for maintaining engagement and retention.

In Technology and Human-Robot Interaction

In technology and human-robot interaction, learning by teaching has been integrated through teachable agents, where students instruct software-based entities to reinforce their own understanding. A seminal example is Betty's Brain, developed in the 2000s at , which employs a learning-by-teaching in science education. Students construct concept maps to teach the virtual agent Betty about topics like river ecosystems, receiving feedback on inaccuracies to promote and . Empirical studies with Betty's Brain have demonstrated significant pre-post learning gains in science concepts, particularly among engaged students who iteratively refine their teaching. Human-robot interaction (HRI) extends this approach by positioning physical robots as tutees, fostering deeper engagement through embodied interactions. Studies have shown that children teaching humanoid robots exhibit increased engagement, as the robots' responses encourage explanatory behaviors. Similarly, collaborative HRI scenarios have enhanced knowledge retention through consistent feedback. Research from the 2021 ACM/IEEE International Conference on Human-Robot Interaction highlights how empathetic robot responses—such as acknowledging confusion or enthusiasm—further boost retention by building and motivating sustained teaching efforts. Online platforms have adapted learning by teaching for remote and collaborative environments, especially following the 2020 pandemic. Post-pandemic adaptations include Discord-based teaching circles, where learners form virtual groups to tutor each other on subjects like , leveraging voice and text channels for real-time feedback and explanation. Virtual reality (VR) simulations enable inanimate teaching by allowing users to instruct digital avatars or objects, improving conceptual clarity through immersive feedback loops. Emerging trends point toward advanced AI tutors enabling personalized learning through interactive dialogues where users refine explanations based on AI queries. However, these integrations raise ethical considerations, including biases in robot learning models that could perpetuate inequalities if training data reflects societal stereotypes, necessitating transparent algorithms and diverse datasets in HRI design.

References

  1. https://aaalab.stanford.edu/assets/papers/2009/Protege_Effect_Teachable_Agents.pdf
  2. https://webs.uab.cat/grai/wp-content/uploads/sites/353/2016/11/Learning-by-teaching.-D.-Duran-2016.pdf
  3. https://www.cmjpublishers.com/wp-content/uploads/2025/02/learning-by-teaching-a-pathway-to-educational-justice.pdf
  4. https://www.researchgate.net/publication/386044974_The_Socratic_Method_A_Timeless_Approach_to_Critical_Thinking_and_Personal_Growth
  5. https://digitalcommons.assumption.edu/philosophy-faculty/29/
  6. https://www.researchgate.net/publication/248933632_Diffusing_Useful_Knowledge_The_Monitorial_System_of_Education_in_Madras_London_and_Bengal_1789-1840
  7. https://books.google.com/books/about/An_Experiment_in_Education_Made_at_the_M.html?id=cZtbAAAAQAAJ
  8. https://files.eric.ed.gov/fulltext/EJ1064144.pdf
  9. https://www.clarelibrary.ie/eolas/coclare/history/strangers_gaze/strangers_lancaster.htm
  10. https://educationalopportunity.org.uk/history-of-the-educational-opportunity-foundation/
  11. https://www.academia.edu/81696850/Undermining_the_Common_School_Ideal_Intermediate_Schools_and_Ungraded_Classes_in_Boston_1838_1900
  12. https://www.tandfonline.com/doi/abs/10.1080/00220973.1967.11034294
  13. https://eric.ed.gov/?id=ED056157
  14. https://www.ldl.de/Material/f_/ldlintheoryandpractice.pdf
  15. http://www.joachim-grzega.de/ldl-engl.pdf
  16. https://www.tandfonline.com/doi/abs/10.1080/02607470802212157
  17. https://www.verlagdrkovac.de/978-3-8300-4096-5.htm
  18. https://www.researchgate.net/publication/324539123_The_learning_benefits_of_teaching_A_retrieval_practice_hypothesis
  19. https://pmc.ncbi.nlm.nih.gov/articles/PMC9130926/
  20. https://www.bps.org.uk/research-digest/learning-teaching-others-extremely-effective
  21. https://www.sciencedirect.com/science/article/pii/S0361476X13000209
  22. https://www.cambridge.org/core/books/learning-as-a-generative-activity/learning-by-teaching/9E4FB72F26465C47A4113F4B9B404732
  23. https://files.eric.ed.gov/fulltext/EJ1081990.pdf
  24. https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2019.03087/full
  25. https://visible-learning.org/hattie-ranking-influences-effect-sizes-learning-achievement/
  26. https://www.simplypsychology.org/constructivism.html
  27. https://www.simplypsychology.org/piaget.html
  28. https://www.pnas.org/doi/10.1073/pnas.1319030111
  29. https://nesslabs.com/feynman-technique
  30. https://www.simplypsychology.org/bandura.html
  31. https://www.tandfonline.com/doi/abs/10.1207/s1532690xci0102_1
  32. https://jeanpol.files.wordpress.com/2018/04/jpm_learning-by-teaching_2018_v3.pdf
  33. https://www.rcboe.org/cms/lib/ga01903614/centricity/domain/15451/flip_your_classroom.pdf
  34. https://readyct.org/2013/11/flipping-expectations-student-led-learning-flipped-classroom/
  35. https://www.youtube.com/watch?v=uk7plrzRRSU
  36. https://fs.blog/feynman-technique/
  37. https://link.springer.com/article/10.1007/s10648-021-09643-4
  38. https://www.[researchgate](/page/ResearchGate).net/publication/355896075_Learning-by-Teaching_Without_Audience_Presence_or_Interaction_When_and_Why_Does_it_Work
  39. https://arxiv.org/abs/2301.06511
  40. https://eric.ed.gov/?id=ED228964
  41. https://link.springer.com/article/10.1007/s10648-025-10060-0
  42. https://onlinelibrary.wiley.com/doi/abs/10.1002/acp.3410
  43. https://www.facultyfocus.com/articles/faculty-development/using-collaborative-learning-to-elevate-students-educational-experiences/
  44. https://www.engageli.com/blog/active-learning-statistics-2025
  45. https://link.springer.com/article/10.1007/s13384-023-00657-1
  46. https://www.mdpi.com/2673-8392/5/1/25
  47. https://complexinstruction.stanford.edu/about/Equity-in-Cooperative-Learning-Classrooms
  48. https://reflectionsonculture.com/cultural-bias-in-education/
  49. https://pce.sandiego.edu/strategies-for-promoting-equity-in-the-classroom-faqs/
  50. https://pmc.ncbi.nlm.nih.gov/articles/PMC11241882/
  51. http://www.joachim-grzega.de/GrzegaSchoener-LdL.pdf
  52. https://www.nsta.org/blog/cooperative-learning-lab
  53. https://files.eric.ed.gov/fulltext/EJ851877.pdf
  54. http://www.joachim-grzega.de/ldl%2Bbge.pdf
  55. https://pubs.nctm.org/abstract/journals/mtlt/117/2/article-p121.xml
  56. https://encompass.eku.edu/jote/vol7/iss2/8/
  57. https://link.springer.com/article/10.1007/s40593-015-0057-9
  58. https://dl.acm.org/doi/proceedings/10.1145/3434073
  59. https://www.uptale.io/en/how-virtual-reality-simulations-enhances-learning-and-teaching/
  60. https://www.americanscientist.org/article/trust-and-bias-in-robots
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