Estimating the Effectiveness and Feasibility of a Game-based Project for Early Foreign Language Learning
Bibliographic record
Abstract
This paper outlines the rationale for and the purpose of designing and implementing a project aiming to make very young EFL learners develop their language skills through their involvement in interactive psychomotor activities. The project, which is a part of a broader longitudinal project having introduced EFL in the first primary school grade, was implemented in two 2nd grade Greek classrooms with a total of 44 seven year old children. Multisensory teaching was followed through the use of a combination of activities: classroom creative activities included memory and word games, drawings, constructions, role-play games, pantomime as well as songs. In the gym, children participated in physical activities such as races, chases and hopscotch as well as dance and music activities, with the aim to improve their oral communicative skills and creativity. In order to examine the effectiveness and feasibility of the project, an evaluation study was conducted by using a pre- and post- language test and journals kept by the teachers. It was evident that the project had a positive effect on developing very young learners’ language skills, and on enhancing their motivation to participate in psychomotor activities.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".