A Study on the Motivation Levels and Problems in the Language Learning for the Higher Education Learners
Bibliographic record
Abstract
Language builds social and economic connections within countries as the most effective communication tool. It has the potential to introduce new opportunities and helps the speakers become world citizens. Although second language teaching focuses more on early education in many countries, it is still crucial for university students to acquire a foreign language. Second language acquisition enables institutional cooperation not just on a domestic but also on an international scale, thus contributing significantly to universal and contemporary growth. This research aims to determine university students' motivations for learning a foreign language, identify the problems during the process, and offer solutions. For this purpose, the opinions of the German Language and Literature department students studying at a state university on language learning were evaluated by taking the "Motivation Scale in Language Learning" and semi-structured interview forms. This study relies on a mixed research method combining the quantitative and the qualitative. The findings point out that students have a good motivation to learn a language, and the motivations are the same regardless of age, gender, grade level, previous educational background, and parents' educational background. According to the findings, students' motivations are living abroad, cultural growth, curiosity, interest, love, and new technologies. On the other hand, the lack of sufficient incentives, linguistic challenge, feelings of inadequacy, and prejudices affect their motivation negatively.
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 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 | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".