Plurilingual practices in Higher Education: An analysis of student perceptions from a South African University
Bibliographic record
Abstract
This study describes student perspectives on the teaching and learning of a newly introduced University language acquisition course. It identifies three basic components of teaching and learning, namely teaching approaches, teaching and learning resources, and assessment of learning. The study focuses on how students perceive these basic components of teaching and learning by investigating how 1st-year students at a university in South Africa perceive the teaching and learning of the Sesotho First Additional Language (FAL) course (a newly introduced course in the university). Hence the objectives of this study are to establish the views of 1st-year Sesotho FAL students regarding the teaching approaches used by the lecturers presenting the course; the teaching and learning resources used in the course; and the quality of assessments applied in the course. Guided by complex dynamic systems theory, the study employs a survey methodology. A questionnaire comprising both close-ended belief statements as well as open-ended statements for students to respond to was administered to 51 study participants purposefully selected. Quantitative data were analysed using IBM SPSS, while qualitative data were analysed by the researchers themselves. Results emerging from the data reveal that 1st-year students generally find their lecturers’ teaching approaches and assessment methods satisfactory; however, they perceive the teaching and learning resources used by their lecturers in teaching Sesotho as inadequate. This finding points to the need for further dialogue broadly on the quality of teaching and learning, quality of assessment criteria and the availability of teaching and learning resources provided for presenting newly introduced courses in higher education institutions (HEIs); and specifically on the level of preparation of lecturers in these courses tasked with the teaching and learning.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.005 | 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".