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The Effects of Online Peer Tutoring on First-Year Undergraduate Students’ English Grammar Achievement

Paper · 2019 · Somchai Watcharapunyawong

Summary

This classroom study from Thepsatri Rajabhat University in Thailand asks whether peer tutoring delivered online can raise first-year English majors' grammar scores. The motivation was weak results in the earlier course English Structure 1, where more than half the students failed. In a quasi-experimental pre/post design, 53 students taking English Structure 2 were placed by pre-test level into ten small groups. Over 12 weeks, they used Facebook to teach each other five grammar points from the syllabus: sentences with "if" conditions, reporting what others said, structures for having someone else do something, linking expressions between ideas, and the subjunctive. For each topic, the teacher reviewed the tutors' materials before broadcasting, and an in-class discussion followed to check understanding. Achievement was measured with a 50-item multiple-choice test given before and after. Satisfaction was measured with a Likert questionnaire and semi-structured interviews. Paired t-tests showed significant gains at the .01 level, and satisfaction was rated very high. The author credits responsibility, preparation and collaboration for the improvement. The study is a practical case for peer-led, platform-based grammar teaching, but it has only one group and no control group.

Key points

  • Sample: 53 first-year English major students in English Structure 2, Semester 2/2017, split by pre-test level into ten groups of 5–6.
  • The 12-week cycle repeated for each of the five grammar points:
    • tutors present their materials to the teacher;
    • tutors take turns broadcasting lessons on Facebook;
    • the class holds an in-person discussion.
  • Instruments:
    • a 50-item multiple-choice pre/post test, checked by three language experts;
    • a Likert satisfaction questionnaire (reliability 0.84);
    • a semi-structured interview.
  • Reported gains (mean scores, pre → post):
    • conditional clause: 1.96 → 4.85 (t = −8.085);
    • indirect speech: 2.00 → 6.17 (t = −12.956);
    • causative form: 2.08 → 4.25 (t = −5.910).
    • All gains were described as significant at the .01 level.
  • The author names three factors behind the effect (knowledge management, knowledge transfer, knowledge discussion) and five success keys (responsibility, preparation, collaboration, cooperation, interaction).

Interesting ideas

  • I1. Vet before teaching: a tutor's materials are checked by the teacher before they reach peers, so errors are caught before they spread.
  • I2. Group by measured level: a diagnostic pre-test, not convenience, decides how learners are grouped.
  • I3. Score per phenomenon: the pre/post comparison is broken down by grammar point rather than reported as one total, which shows where gains are weak.
  • I4. Choose meaning-heavy targets: the syllabus focuses on constructions that change interpretation, such as conditionals, indirect speech, causatives and subjunctive.
  • I5. Recurring verification loop: a weekly group discussion re-checks what was learned for correctness and clarity, separately from the teaching step.

For Mova

How these ideas could serve Mova, our small open language model — its files, stages and tests:

  • I1 (learn): Before silver annotations from one witness parser are used to train others, an LLM teacher tier could audit a sample, so wrong labels do not propagate.
  • I2 (learn): Training sentences could be bucketed by how badly current parsers disagree on them, and repair or self-play effort aimed at each difficulty band separately.
  • I3 (answer): School-course test results could be reported per construction type, so a regression in one area is not hidden by the overall average.
  • I4 (frames): These constructions could form a dedicated test set for frame building, checking who caused what in causatives and keeping reported or hypothetical content apart from asserted facts.
  • I5 (learn): Each self-induced repair rule could be re-evaluated on a fixed schedule against held-out data and negative controls, rather than trusted once it has been accepted.

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

Also on the byline: Thepsatri Rajabhat University.

📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Computer Science · 9,086 worksArts and Humanities · 9,296 worksLanguage and Linguistics · 9,206 worksSocial Sciences · 744 worksInformation Systems · 523 worksEducation · 112 works

🧭 Topics 1Research subjects and languages the work is about.English · 1,373 works

Cite

Cite as Somchai Watcharapunyawong. 2019. The Effects of Online Peer Tutoring on First-Year Undergraduate Students’ English Grammar Achievement. IJIE (Indonesian Journal of Informatics Education) 2.

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.20961/ijie.v2i2.24382

@article{watcharapunyawong2019effects,
  title = {{The Effects of Online Peer Tutoring on First-Year Undergraduate Students’ English Grammar Achievement}},
  author = {Somchai Watcharapunyawong},
  journal = {IJIE (Indonesian Journal of Informatics Education) 2},
  year = {2019},
  doi = {10.20961/ijie.v2i2.24382},
  url = {https://doi.org/10.20961/ijie.v2i2.24382}
}

References

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