SOME FEATURES OF THE NATIONAL LANGUAGE AS A FOREIGN LANGUAGE PROFICIENCY ASSESSMENT SYSTEMS
Bibliographic record
Abstract
This article analyses and compares assessment systems for the national language as a foreign language, using the TOEFL (Test of English as a Foreign Language), the HSK (Chinese Proficiency Test), and the TORFL (Test of Russian as a Foreign Language) as examples. The identification of similarities and differences in assessing abilities, skills, and requirements for the level of language proficiency determines the specifics of national education systems and differences in approaches to educational assessment systems.In the modern world, foreign language skills are becoming increasingly important due to various factors, such as the increasing processes of globalization and integration, the strengthening of trade, economic and political relations and academic exchanges, the development of tourism and business, the elimination of borders between countries through the forming interplanetary Internet network. Foreign language skills are an essential requirement of employers, and the growing competition in the labour market motivates applicants to learn foreign languages. The analysis and improvement of existing knowledge assessment systems are current research directions.In the XX century, researchers started to use the testing form of assessment in the educational process. Compared with the traditional forms, researchers have identified the test as a universal form of assessment that effectively evaluates the level of national language proficiency without the subjective attitude of the examiner towards the student.The article describes and compares three testing systems for assessing national language proficiency for foreign citizens.The TOEFL is an international examination used to assess the English proficiency of non-native speakers. The TOEFL has changed in structure and content parts since its development in 1964. To the present day, the TOEFL is one of the most popular foreign language exams required for admission to educational institutions in various countries such as the United States, Canada, and the European Union. The HSK is a test used to evaluate the Chinese language proficiency of foreign citizens from 1990. The HSK is equivalent to the TOEFL. However, the test has structural differences due to the specific of Chinese hieroglyphics. In the beginning, the HSK consisted of eleven levels. Then, the number of levels reduced to six in 2010. The HSK is going to be reformed in 2022. According to the statement, the new test will have nine proficiency levels.The TORFL is an international test of Russian language as a foreign language developed in 1995. The TORFL has not undergone any significant reform. The government announced new changes in the organization and structure of the exam for foreign citizens on 7 June 2021. This article compares the currently relevant testing systems.The study uses empirical and theoretical methods such as analysis, synthesis, comparison, and deductive method.The obtained results can help assess the quality of knowledge of students in learning foreign languages.
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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".