Evaluation of an ODL Contemporary Novel Program for Sudanese EFL University Students During the Wartime: A Case Study of Khartoum University
Bibliographic record
Abstract
This study critically evaluates an Open and Distance Learning (ODL) program that aimed to continuously support English as a Foreign Language (EFL) students at the University of Khartoum during Sudan's war in 2023. The conflict severely disrupted education across Sudan and displaced millions. In this challenging context, the ODL “Contemporary Novel Appreciation” course aimed to enable students to progress academically while coping with instability and hardship. The analytical-descriptive research methodology was utilized. The gathered data was analyzed using the SPSS software, and subsequently, the numbers and percentages were stated. The conclusions of this study are: the majority of students found that the program design effectively catered to their learning requirements and fostered pertinent abilities. Most students considered the course content and readings to be pertinent to their experiences, enhancing their comprehension and offering solace amongst the battle. In terms of delivery methods and technological concerns, the majority of students had a neutral position about the appropriateness of online delivery during conflicts and whether these issues impeded or facilitated their participation in continuing education. The key recommendations conclude enhancing technology infrastructure and support to mitigate the challenges that impede the participation of 60% of students. Suggesting alternative study resources such as pre-recorded lectures and textbooks in case of connectivity issues. Providing a hybrid approach that combines both online and face-to-face interactions to accommodate the diverse needs and preferences of students. Ensuring that faculty members receive comprehensive training to proficiently conduct online discussions and provide assistance to a wide range of learners who have been displaced from their usual learning environments.
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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 | 0.003 | 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 | 0.001 |
| 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".