Student-Centered Online Assessment in Foreign Language Classes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In 2020 educational institutions in many countries had to implement online learning due to quarantine restrictions caused by the coronavirus pandemic. The research aims to study the peculiarities of the distance learning technologies used by Ukrainian foreign language teachers for formative and summative assessment and their impact on students. At the end of 2020, a survey about online resources used for creating different types of tasks for foreign language classes in Ukraine was conducted by the authors of the study, and the main characteristics of the most popular online resources were analyzed. According to the survey, to create assessment tasks the majority of Ukrainian teachers use the following platforms: Kahoot, Google Forms, Quizlet, Classtime, Quizizz, Socrative, Quizalize, Gimkit, Blooket, Liveworksheets, and Wizerme. Some of these resources provide a strong element of competition that makes them perfect for formative assessment, while the others better suit summative assessment as they have a clear interface without distracting elements. When designing online tasks for the assessment, teachers should also take into consideration the possibilities online resources provide to reduce their students’ anxiety and stress caused by performing test tasks.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it