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Enhancing English Grammar Skills of Grade 9 Students Through the Use of an English Grammar Application

Paper · 2024 · Joy Jopson Magbanua

Summary

This classroom action study asks whether a free mobile grammar app can help Philippine secondary students who struggle with English grammar. The author worked with 20 Grade 9 learners at Presbitero National High School in Pigcawayan, Cotabato. They were picked deliberately because their pre-assessment scores were low and they owned smartphones. For two weeks they practised with the British Council's LearnEnglish Grammar app and posted daily screenshots of their progress to a messenger group chat. The design was pre-experimental: one group, a test before and a test after, with no control group or random assignment. The group's mean score went from 18.30 to 26.30, and a paired-sample t-test was used to check whether the gain was significant. Recurring weak areas were building basic sentences, verb usage and recognising modals. The author takes this as evidence that cheap, phone-based practice is a practical supplement to traditional grammar teaching. She also notes that long-term retention and a fuller look at the app's features and limits still need study.

Key points

  • Participants were 20 Grade 9 ESL students chosen by purposive sampling for weak grammar and smartphone access. The intervention lasted two weeks.
  • The tool was the LearnEnglish Grammar app by the British Council. It offers 1000+ practice questions across ten activity types, including fill-in-the-blank and reordering, with levels, practice and test sections, progress tracking and multilingual in-app help.
  • Mean score rose from 18.30 on the pre-test to 26.30 on the post-test. Significance was tested with a paired-sample t-test, and descriptive statistics were also reported.
  • Learners slipped up most often when forming simple sentences, applying verbs correctly and spotting modal verbs.
  • The study has clear limits: a single group with no control, a small non-random sample, a short duration and no retention follow-up. The paper also mislabels which research question the t-test answers.

Interesting ideas

  • I1. Grouping learner mistakes into a small set of categories, such as sentence construction, verbs and modals, says more than a single total score.
  • I2. The study's main weakness is having only pre/post measurement with no control group, which means any gain might come from retesting or time rather than the intervention.
  • I3. The app deliberately goes beyond multiple choice and uses exercises like reordering scrambled words into a sentence, which test real structural knowledge rather than recognition.
  • I4. Daily screenshots sent to a group chat served as a lightweight, inspectable record of each learner's practice during the intervention.
  • I5. Participants were chosen on purpose from the weakest performers, which concentrates the intervention where gains are most visible.

For Mova

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

  • I1 (answer): School-course test results could be split by grammatical category, so we see which construction types the student models fail on instead of one accuracy number.
  • I2 (learn): Treat this as a warning case. Every reported training improvement should come with a baseline run or a negative control that did not get the intervention.
  • I3 (back): Word-reordering tasks could serve as a probe for generation, checking whether linearisation from the meaning graph rebuilds a grammatical word order.
  • I4 (learn): Saving a small snapshot after each training or self-play round, with scores and sample outputs, would give an explainable history of how a model reached its final state.
  • I5 (learn): A targeted evaluation slice built from sentences that the witness parsers disagree on would show whether repair rules help where the system is actually weak.

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

 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 Joy Jopson Magbanua. 2024. Enhancing English Grammar Skills of Grade 9 Students Through the Use of an English Grammar Application. ELT Worldwide: Journal of English Language Teaching 11.

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.26858/eltww.v11i2.66180

@article{magbanua2024enhancing,
  title = {{Enhancing English Grammar Skills of Grade 9 Students Through the Use of an English Grammar Application}},
  author = {Joy Jopson Magbanua},
  journal = {ELT Worldwide: Journal of English Language Teaching 11},
  year = {2024},
  doi = {10.26858/eltww.v11i2.66180},
  url = {https://doi.org/10.26858/eltww.v11i2.66180}
}

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