Multimodal Interaction in a Foreign Language Class at Higher Education Institutions of Ukraine
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
Multimodality is implemented to the modern learning environment in line with trends towards multidisciplinarity. In the current study, multimodal interaction is based on the mutual integration of understanding of multimodality in philological and pedagogical perspectives. The purpose of the article was to analyze and compare the results of learning a foreign language (German) for professional purposes (German for Economists) with an emphasis on multimodal interaction and without it (in a way of traditional language learning with a predominance of classical methods of classroom and extracurricular activities). There were universal scientific and specific methods used: a controlled-type educational experiment; Likert-scale type questionnaire; reliability test: Cronbach’s alpha using IBM SPSS Statistics 28.0.0.0; qualitative-quantitative interpretation and contrastive-comparative analysis of the obtained experimental data; statistical-mathematical interpretation of empirical data; comparative analysis; the functional analysis. Respondents of empirical intelligence were students of the Faculty of Management and Marketing, specialty 073 “Management”. Averagely in the experimental group, almost all the assessing criteria of the effectiveness of multimodal interaction outreached 4 points. These data were also confirmed by the results of self-reflection-questionnaire. The novelty of the research is in the principle of theoretical substantiation and practical application of the content of multimodal interaction as an umbrella term that integrates the most fundamental concepts of modern pedagogy in general and, in particular, methods of teaching a foreign language.
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.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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