---
title: "The Comparative Effects of Digitally vs. Print Enhanced Modalities — Hassanzadeh 2026"
description: "English prepositions are hard for EFL learners. 30 references."
authors: ["Mohammad Hassanzadeh", "Mohaddeseh Moazzeni"]
year: 2026
venue: "Issues in Language Teaching 15"
source: "https://ilt.atu.ac.ir/article_21039_6c366534a48f3e57554bedb024240e1a.pdf"
doi: "10.22054/ilt.2026.90927.967"
licence: "CC BY (journal licence per DOAJ; Issues in Language Teaching)"
licence_url: "https://creativecommons.org/licenses/by/4.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/hassanzadeh-2026-comparative-effects-digitally-vs-print/"
---
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# The Comparative Effects of Digitally vs. Print Enhanced Modalities on the Incidental Acquisition of English Prepositions through Extensive Reading

**Authors:** Mohammad Hassanzadeh and Mohaddeseh Moazzeni · **Year:** 2026 · **Venue:** Issues in Language Teaching 15 · **Licence:** [CC BY (journal licence per DOAJ; Issues in Language Teaching)](https://creativecommons.org/licenses/by/4.0/)

**Links:** [Publisher's page](https://doi.org/10.22054/ilt.2026.90927.967) · [PDF](https://ilt.atu.ac.ir/article_21039_6c366534a48f3e57554bedb024240e1a.pdf) · [DOI 10.22054/ilt.2026.90927.967](https://doi.org/10.22054/ilt.2026.90927.967) · [OpenAlex](https://openalex.org/W7214221513)

**Citations:** 0 citations (OpenAlex, 2026-10-14)

## Summary
English prepositions are hard for EFL learners. They are short, unstressed and easy to miss in running text, and their meanings shift with context. The authors asked whether the physical medium of extensive reading changes how well learners pick up simple prepositions incidentally. Sixty-six Iranian adolescent learners (female, from one language institute) were split into three groups: digitally enhanced extensive reading (DEER), print-enhanced extensive reading (PEER) and a control group. For nine weeks, twice a week, the experimental groups spent the final half hour of class reading two Oxford Bookworms graded readers. Target prepositions were typographically highlighted, and learners retold four pages aloud each session. Both conditions had the same audio support and the same highlighting. The digital text appeared on a single teacher-controlled screen, so medium was the only difference. An immediate and a delayed post-test showed that PEER beat the control group both times. DEER did not differ significantly from either group. The study suggests digital texts are not a neutral swap for print when the goal is noticing subtle grammatical forms.

## Key points
- Design: three groups (DEER, PEER, control) with 66 learners in total, all from one Iranian institute (ILI).
- Schedule: nine weeks, two sessions per week, 30 minutes each, reading two Oxford Bookworms graded readers with oral summaries of four pages per session.
- Results: PEER significantly outperformed control on both the immediate and delayed post-tests, while DEER showed no significant gains against either group.
- Errors clustered on prepositions with no direct Persian counterpart, which the authors link to L1 transfer and the Interpretability Hypothesis.
- Limitations:
  - There was no pretest; the institute's placement tests were used to argue the groups were comparable.
  - The delay before the second post-test was only two weeks.
  - The sample was small and female-only.

## Interesting ideas
- Hold everything equal except one factor: same texts, same audio and same highlighting, so that only the medium differs. That way a null or positive result can be attributed to that single factor.
- Small, low-salience function words are the first thing lost under shallow processing, so they deserve a dedicated check rather than being averaged into an overall score.
- Testing twice, once right after and once later, separates momentary gains from durable ones.
- A control group with no intervention anchors the comparison, and the digital arm's failure to beat it was the informative finding.
- Difficulty concentrated on items whose source-language mapping is one-to-many, which predicts where errors will appear.

## For Mova

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

- **I1** (learn): When comparing parser or teacher-tier variants, run ablations that change exactly one component and keep data, features and rule sets identical, so gains are traceable.
- **I2** (tree): Report attachment accuracy for prepositions (case/obl/nmod arcs) as a separate metric, so weaknesses on function words are not hidden inside overall LAS.
- **I3** (learn): Re-run evaluation of self-induced repair rules after subsequent training rounds to catch "forgetting" or regressions on previously fixed preposition cases.
- **I4** (learn): Always pair a new silver-data or repair method with a no-change baseline as a negative control, and treat "no difference from baseline" as a real result.
- **I5** (back): In translation through the meta-world, mark prepositions whose Ukrainian equivalent maps onto several English ones and resolve them from frame roles rather than lexical lookup.

*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: [Linguistics & languages](https://md.research.elamur.ai/free/en/shelves/linguistics/)

## Cite

Cite as: Mohammad Hassanzadeh and Mohaddeseh Moazzeni. 2026. The Comparative Effects of Digitally vs. Print Enhanced Modalities on the Incidental Acquisition of English Prepositions through Extensive Reading. Issues in Language Teaching 15.

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

```bibtex
@inproceedings{hassanzadeh2026comparative,
  title = {{The Comparative Effects of Digitally vs. Print Enhanced Modalities on the Incidental Acquisition of English Prepositions through Extensive Reading}},
  author = {Mohammad Hassanzadeh and Mohaddeseh Moazzeni},
  booktitle = {Issues in Language Teaching 15},
  year = {2026},
  doi = {10.22054/ilt.2026.90927.967},
  url = {https://doi.org/10.22054/ilt.2026.90927.967}
}
```

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## References

30 references, 0 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

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