Development and Evaluation of an Innovative Web-Based Training, Learning, and Sharing Platform for Social Workers (Hong Kong Jockey Club SMART Family-Link Project): Mixed Methods Evaluation Study
Bibliographic record
Abstract
BACKGROUND: Information and communication technology (ICT) use may enhance social work practice and continuous professional development. Under the Hong Kong Jockey Club SMART Family-Link Project, we developed an innovative web-based training, learning, and sharing platform (i-TLS) to support not only ICT and other learning needs of Hong Kong social workers but also their practice. OBJECTIVE: We developed i-TLS with 3 major components (i-Training, i-Learning, and i-Sharing) and assessed its acceptability and impact on facilitating ICT use in family services. METHODS: We described the i-TLS development based on a 4-phase model and evaluated i-TLS using the platform database, Google Analytics, a self-administered survey, and individual phone interviews 1 year after launching. RESULTS: i-TLS was launched in 12 nongovernmental organizations on July 1, 2019. The COVID-19 outbreak in December 2019 limited face-to-face services, which galvanized digital transformation in social work practice. By July 31, 2020, 313 social workers had registered with i-TLS. Approximately 79.6% (249/313) of users accessed i-TLS at least once in the past 28 days, averaging 3.2 (SD 1.35) platform visits per day and viewing 4.8 (SD 1.42) pages per visit. i-Training provided 41 mini-modules on applying ICT to family services, with 730 enrollments. Approximately 70% (511/730) of users completed the mini-modules and obtained digital mini-certificates. i-Learning provided 112 items of learning resources centered on ICT use in family services, with nearly 4000 page views. i-Sharing had 25 discussion threads with 59 posts. Approximately 53.7% (168/313) of users completed the 1-year evaluation survey, including 7.1% (12/168) who were phone interviewed. The mean i-TLS satisfaction score (out of 10) increased from light (4.99, SD 1.54) to occasional (6.15, SD 1.34) and frequent (6.31, SD 2.29) users. Frequent users showed higher scores (out of 10) than light users for an increase in knowledge (5.84, SD 1.34 vs 4.09, SD 1.74; P<.001), self-efficacy (5.23, SD 1.92 vs 3.96, SD 1.77; P=.02), and knowledge application (6.46, SD 1.33 vs 1.91, SD 1.40; P<.001). Interviewees reported increased ICT use in services and considered i-TLS an acceptable and supportive tool for learning and practice, especially during the pandemic. CONCLUSIONS: i-TLS is acceptable to social workers and enhances their learning and use of ICT in family services. This was achieved through access to self-directed and collaborative learning and sharing of experiences within their practice. Further research on enhancing web-based platforms is needed to expand participation and capacity building among social workers and other health and social care professionals.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.036 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".