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Learning from human tutoring

Paper · 2001 · Michelene T.H. Chi, Stephanie A. Siler, Heisawn Jeong et al.

Summary

Why is one-to-one tutoring so effective? Chi and colleagues compare three possible explanations. The first credits the tutor's pedagogical moves. The second credits the student's own knowledge construction. The third credits the joint interaction between the two. Study 1 analyzed naturally occurring tutoring dialogues about the human circulatory system and related learning outcomes to both tutor moves and student moves, including how they interacted. Study 2 tested the interactive account directly. Tutors were not allowed to give explanations or feedback and could only prompt students to reflect on the text, often with generic content-free questions.

Unexpectedly, students learned just as well under this restricted, prompt-only style as under the usual didactic style. The authors explain this through more frequent and deeper scaffolding episodes and through students taking charge of their learning, for example by reading more. However, poorer readers gained less from that reading. The work suggests that tutoring benefits come mainly from active student construction within interaction, not from tutor explanations alone. This matters for designing intelligent tutoring systems (ITS) and dialogue-based learning tools.

Key points

  • The paper opens with prior findings. Tutored students outperform classroom peers by roughly 0.4–2.3 standard deviations, Bloom's "2 sigma" effect.
  • A meta-analysis by Cohen et al. reports that tutors themselves improved in 33 of 38 reviewed studies, even though most tutors lack formal pedagogical training.
  • The paper contrasts three accounts: a tutor-centered T-hypothesis, a student-centered hypothesis and an interactive hypothesis. Its analysis builds on the "tutoring frame" of Graesser et al. and on a definition of scaffolding that excludes feedback.
  • In Study 2's prompting condition, tutors relied on prompts such as asking what a sentence means. An appendix lists 69 content-free prompts. Learning was not reduced in this condition.
  • Gains in the interactive condition came from deeper and more numerous scaffolding episodes and more student reading. Students' reading ability limited how much that reading helped.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

 Institutions

🎓University of PittsburghPittsburgh · United States68 works · 25,442 citations🎓Texas A&M UniversityCollege Station · United States32 works · 2,823 citations

 Fields, topics and concepts

📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Computer Science · 19,503 worksArtificial Intelligence · 18,805 worksPsychology · 1,673 worksExperimental and Cognitive Psychology · 950 worksDevelopmental and Educational Psychology · 533 works

Cite

Cite as Michelene T.H. Chi, Stephanie A. Siler, Heisawn Jeong, Takashi Yamauchi and Robert G. Hausmann. 2001. Learning from human tutoring. Cognitive Science 25(4).

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.1207/s15516709cog2504_1

@inproceedings{chi2001learning,
  title = {{Learning from human tutoring}},
  author = {Michelene T.H. Chi, Stephanie A. Siler, Heisawn Jeong, Takashi Yamauchi and Robert G. Hausmann},
  booktitle = {Cognitive Science 25(4)},
  year = {2001},
  doi = {10.1207/s15516709cog2504\_1},
  url = {https://doi.org/10.1207/s15516709cog2504_1}
}

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