The investigation of the relationship between online games and acquisition of Turkish vocabulary
Open accessAbstract
This study examines the relationship between online games and Turkish vocabulary acquisition.It adopted the sequential explanatory design of the mixed methods research.The quantitative data were collected through cluster sampling technique from 225 students studying in two secondary schools.The qualitative data were collected through the criterion sampling technique of the purposeful sampling methods from 20 participants.While vocabulary knowledge assessment form was used to collect quantitative data, a semi-structured interview form was used for the qualitative data.According to quantitative findings, whilst there was a significant difference between the scores in vocabulary knowledge test and the duration of the game, experience in playing the game, and time spent in watching broadcasts, there was not a significant difference between vocabulary scores and following League of Legends on media or social media.The experience of the participants in playing games, the weekly hours of playing games, and weekly hours spent watching broadcasts significantly predicts the scores in the vocabulary test.Whereas the qualitative findings revealed the relation of watching broadcasts and playing League of Legends to learn words of foreign origin with its reasons, there was not a significant relationship between following social media and acquisition expressions of foreign origin.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The measurement tool had a high level of reliability (KR-20 = 0.98).
“The reliability of the measurement tool, which includes 82 English words identified as frequently used within the context of the game, was examined using the KR-20 coefficient, and the test was found to have a high level of reliability (KR-20 = 0.98).”
From Incidental vocabulary learning from digital games: the predictive role of game playing time, foreign language motivation, and anxiety (2026) · cites this paper as Simşek and Direkci (2019)
Cites
Digital Games in Language Learning and Teaching
(2012) · doi:10.1057/9781137005267 · Cited by 248 · see citing works
3D Role-Playing Games as Language Learning Tools
Rankin, Y., Gold, R., & Gooch, B. (2006) · The Eurographics Association · doi:10.2312/eged.20061005 · Cited by 131 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Akbulut, S., Şimşek, B., Direkci, B., Koparan, B., Gülmez, M., Şimşek, E. E., & Kayır, G. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1798613
“We used the Vocabulary Knowledge Assessment Form developed by Sim¸sek and Direkci (2019) to assess learners’ vocabulary levels acquired through digital game play.”
Self-citation
- Authors
- Akdeniz University, T., Şimşek, B., Direkci, B., & Akdeniz University, T.
- Affiliations
- Akdeniz University (TR)
- ORCID
- Şimşek, Bilal
- Venue
- International Journal of Instruction
- Publisher
- Modestum Ltd
- Published
- 2019-07-03
- Volume
- 12
- Issue
- 3
- Pages
- 69-88
- ISSN
- 1308-1470 (ISSN-L)
- 1694-609X
- OpenAlex
- W2950643331
- Cited by
- 8
- References
- 2
- Citations by year
- 2026: 1 · 2024: 1 · 2023: 2 · 2022: 2 · 2021: 2
- FWCI
- 1.82
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- International Journal of Instruction (publishedVersion)
- Topics
- Social Sciences › Psychology › Developmental and Educational Psychology › Second Language Acquisition and Learning
- Social Sciences › Psychology › Developmental and Educational Psychology › Educational Games and Gamification
- Social Sciences › Sociology and Political Science › Digital Games and Media
- Keywords
- online games, vocabulary knowledge, League of Legends, match duration, game experience, social media, foreign words, high school students, English as a foreign language
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review