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Record W4412744152 · doi:10.54855/ijli.25431

Students’ Perceptions of Kahoot!, Gamification, and the Role of Instructor in Online French as a Foreign Language Classes in Jamaica

2025· article· en· W4412744152 on OpenAlexaff
Oneil Nathaniel Madden, Rashad Higgs, Sheldon P. Gordon

Bibliographic record

VenueInternational Journal of Language Instruction · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology-Enhanced Education Studies
Canadian institutionsDiscovery Centre
Fundersnot available
KeywordsPerceptionForeign languagePsychologyMathematics education

Abstract

fetched live from OpenAlex

Gamification is a pedagogical tool that has brought much value to teaching and learning, including foreign languages (FLs), and serves to keep students engaged and motivated. Tools such as Kahoot! have gained much traction in FL contexts, with many studies focusing on their relation to learner enthusiasm and participation. However, the available data focuses primarily on the role of the teacher. The authors sought to gain students’ perspectives of Kahoot! in online French classes and the role of the instructor in the process. Sixteen undergraduate students at the University of Technology, Jamaica responded to a questionnaire. The study used a mixed-methods research design. Qualitative content analysis was employed to analyze the qualitative data, while descriptive statistics were used to analyze the quantitative data. Major findings reveal that Kahoot! is beneficial to FL learning, as it helps to improve students’ vocabulary, grammar, pronunciation, and cultural competence. Kahoot! also aids in the application, retention, and reinforcement of knowledge. However, technical and internet connectivity issues can impact the game’s flow. The teacher is responsible for preparing and facilitating the game strategically, as well as reviewing the answers with the students in a manner that promotes metacognition.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.221
Threshold uncertainty score0.592

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.353
Teacher spread0.347 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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