Using mobile technology to enhance undergraduate student digital information literacy skills: A Canadian case study
Bibliographic record
Abstract
Learning essential information literacy skills through the use of mobile phones is an innovative m-learning pilot project that was collaboratively undertaken in a Canadian university college over the course of two academic terms by faculty and the library staff. The research pilot project involved ninety one undergraduate students in five different classes majoring in psychology, social work, education or social development studies in an attempt to determine the effectiveness of using mobile technology to enhance students’ information literacy skills and learning experiences. Pre and post-test measures, and survey questionnaires generated quantitative and qualitative data that was analyzed to determine the degree of changes in frequency of mobile device information literacy access and fluency in digital literacy skills. The article highlights the Mobile Information Literacy innovation and includes the development and design of the mobile lessons, interactive exercises, and its applications. The study’s main results and conclusions are also discussed. Additionally, the successes and challenges of the pilot to support anytime, anywhere student mobile information literacy eLearning training that engages mobile learners and enhances their learning experience are identified and critically reflected upon to improve the innovation for stage two of the project.
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 | 0.000 | 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".