Evaluating Pre-Service Teaching Practice for Online and Distance Education Students in Pakistan
Bibliographic record
Abstract
In addition to conventional modes, teacher education programs in Pakistan are also offered through online and distance education. Teaching practice is a significant component of pre-service teacher education programs. Assessing the quality of teaching practice for pre-service student teachers is important, as these modules train the prospective teachers for their professional teaching careers. Virtual University of Pakistan (VU), an online university, offers pre-service teacher education programs. This research is an investigation into the learning opportunities and practices of VU student teachers in their teaching practice modules. Students enrolled in different teacher education programs served as the population of this study. Those in the fall 2018 semester who were enrolled in teaching practice modules were selected as a sample. Data sources included lesson plans prepared, lessons delivered, administrative and co-curricular duties performed by the students, as well as evaluation reports by supervisors, cooperating teachers, and school principals. There were improvements in the student teachers’ lesson plan formation and their overall learning. Data obtained through personal visits by VU faculty was used to verify and assess actual classroom teaching. Lack of regular attendance and punctuality by student teachers was observed as a result. Internal review of the VU system as it relates to the teaching practice modules was conducted to address any shortcomings in the course(s), its procedures, and its controls. Recommendations for improving the system, such as grading the modules, peer-assessment, and orientation workshops for student teachers are provided, as well as suggestions for developments in the teaching practice modules themselves.
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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 | 0.013 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 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".