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The Use of Mobile Assisted Language Learning To Improve English Grammar for Senior High School Students

Paper · 2024 · Redyta Zalfa Maharani, Putu Dian Danayanti Degeng and Khairil Azwar Razali

Summary

The paper asks how Indonesian EFL senior high school students perceive the Duolingo mobile app as a tool for improving English grammar. It is framed within Mobile Assisted Language Learning (MALL) and gamification. Grammar is described as hard to learn because of its rules, exceptions and inconsistencies in sentence structure, tense and word order. At Widyagama Senior High School in Malang, the authors purposively sampled 53 students whose classes had used Duolingo for one semester. All of them completed a 14-item, six-point Likert questionnaire on four aspects: knowledge, understanding, motivation and effectiveness. Ten of them also took part in a six-question structured interview. Reported agreement was high: the abstract states that over 93% responded positively, and the conclusion gives 83–95% per aspect. Interviewees described the app as engaging and useful in daily life. The authors recommend wider use of MALL in English teaching. The evidence rests entirely on self-reported perceptions, with no pre/post grammar test and no control group. The study therefore shows that students accept the app, not that their grammar measurably improved.

Key points

  • Participants: 53 students (38 from class X, 15 from class XI B) at Widyagama Senior High School, Malang, selected by purposive sampling after one semester of Duolingo-based lessons.
  • Instruments: a Google Form questionnaire with 14 six-point Likert items adapted from Amaliah, Devi (2020), plus six structured interview questions for 10 students (5 per class).
  • Questionnaire items are grouped into four perception aspects: knowledge, understanding, motivation and effectiveness.
  • Item-level results:
    • Motivation: 97% felt motivated and 92% felt excited about memorizing grammar.
    • Effectiveness: 95% felt their grammar improved and 91% felt their grammar knowledge improved.
  • Aspect summaries in the conclusion: knowledge 83%, understanding 92%, motivation 95%, effectiveness 93%. The methodology is labelled qualitative-descriptive, though the paper also calls it dual-method.

Interesting ideas

  • I1. The evaluation is split into four separate facets (knowledge, understanding, motivation, effectiveness), each probed by both survey items and interview questions, so one weak area cannot hide behind a single average.
  • I2. Grammar difficulty is broken into concrete trouble areas (sentence structure, verb tenses, word order) so that improvement can be located rather than asserted globally.
  • I3. A broad closed-scale survey is paired with follow-up interviews of a small subset to explain what the numbers mean.
  • I4. The paper treats self-reported improvement as evidence of effectiveness without any objective test, which shows why outcome claims need an independent check.
  • I5. The cited view that Duolingo teaches grammar in order from the most basic to the hardest levels suggests ordering material by difficulty.

For Mova

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

  • I1 (answer): Score the school-course readers separately on distinct facets, such as recall of facts versus inference versus multi-step reasoning, instead of reporting one accuracy figure.
  • I2 (tree): Report parser and tagger errors bucketed by these categories (e.g. tense/aspect morphology, constituent order) to see which construction types need repair rules.
  • I3 (learn): Accompany every aggregate silver-data or training metric with a small hand-inspected sample that explains why the scores moved.
  • I4 (learn): Never accept an LLM teacher's or a model's own confidence as proof of quality; always pair it with held-out tests and negative controls.
  • I5 (learn): Build a curriculum of training and test texts graded by syntactic complexity, so failures can be traced to the first level where the pipeline breaks.

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

🎓International Islamic University MalaysiaKuala Lumpur · Malaysia3 works · 4 citations

Also on the byline: University of Brawijaya.

 Fields, topics and concepts

📚 Shelves 4The field of science this work belongs to (OpenAlex fields).Computer Science · 16,667 worksArts and Humanities · 16,039 worksLanguage and Linguistics · 15,891 worksInformation Systems · 1,437 works

🧭 Topics 1Research subjects and languages the work is about.English · 2,263 works

Cite

Cite as Redyta Zalfa Maharani, Putu Dian Danayanti Degeng and Khairil Azwar Razali. 2024. The Use of Mobile Assisted Language Learning To Improve English Grammar for Senior High School Students. Journal of Languages and Language Teaching 12.

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.33394/jollt.v12i3.11041

@article{maharani2024use,
  title = {{The Use of Mobile Assisted Language Learning To Improve English Grammar for Senior High School Students}},
  author = {Redyta Zalfa Maharani, Putu Dian Danayanti Degeng and Khairil Azwar Razali},
  journal = {Journal of Languages and Language Teaching 12},
  year = {2024},
  doi = {10.33394/jollt.v12i3.11041},
  url = {https://doi.org/10.33394/jollt.v12i3.11041}
}

References

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