Work in progress: Use of mobile technology to deliver training in blended learning and independent study formats
Bibliographic record
Abstract
As citizens of countries and employees become comfortable using mobile technology, there is an opportunity for the workplace to deliver training using mobile technology. Using mobile learning allows employees to learn just in time, in their own context, and for continuing professional development. This paper will present information and results on a collaborative mobile learning research project between education and industry. The paper will present results on two delivery formats that were used for the training. One format used blended learning where the training was delivered using a combination of classroom instruction and independent study. The second format used only independent study where participants completed the training lessons at their own convenient time when they were mobile. The training lessons were delivered through a mobile learning application (app) that was downloaded on participants' mobile devices. Upon completion of the training, participants completed a questionnaire to obtain their feedback on their experience with the mobile deliver formats. This research project has implications for how training is delivered in the workplace using mobile technology. It will inform the workplace on best practices to deliver training in the workplace using mobile technology.
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 | 0.001 |
| 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) | 0.000 | 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".