Factors enabling and hindering an eLearning programme for nurses and midwives in Afghanistan
Bibliographic record
Abstract
Afghanistan faces an acute shortage of trained healthcare providers. To build capacity of nurses and midwives, in 2014 a private hospital in Afghanistan initiated an eLearning programme to enhance their knowledge and skills. The study was conducted to identify facilitating and hindering factors for the successful implementation of eLearning. Data collection took place between June and September 2016, when seven Maternal and Child Health (MNCH) related eLearning sessions were conducted. The participants were nurses and midwives working in MNCH wards at the research sites in Bamyan, Faizabad and Kandahar, along with the programme planners and facilitators. Data was collected through pre/post and delayed post-tests, observations and questionnaires, semi-structured interviews and documents analysis. The results highlight four major factors as important for the successful implementation of eLearning, namely: curriculum, context, technology and individual. The needs assessment ensured relevance of the sessions to the needs of the participants. However, pedagogy was lecture-based with limited focus on skills development. Poor connectivity and language of instruction posed challenges. eLearning has shown the potential for developing knowledge and skills of nurses and midwives. Clear communication between teams involved in planning and implementation of the programme, technology infrastructure, design of online pedagogy and facilitator readiness are critical for the success of eLearning in low and middle income countries. Keywords: Health care providers/system, eLearning Programme, Nurses, Midwives, Maternal and child careHow to cite this article:Naseem, A., Ali, K.Q., Juma, A., Sajwani, A., Khan, B.A., Sayani, A. & Abidi, S.S.R. 2020. Factors enabling and hindering an eLearning programme for nurses and midwives in Afghanistan. Scholarship of Teaching and Learning in the South. 4(2): 80-99. https://doi.org/10.36615/sotls.v4i2.106.This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
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 | 0.010 | 0.008 |
| 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 | 0.003 |
| 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".