Blended learning with international students: a multiliteracies approach
Bibliographic record
Abstract
While the use of information and communication technologies (ICTs) continues to transform learning, international migration and the increasing complexity of intercultural exchange and communication continue to do so as well. In this paper, we connect the dots and ask how ICTs can be used to enhance the learning experiences of international students. Using a case study of a new program for first-year international students at a Canadian university, we bring together insights from blended learning and multiliteracies approaches to show how multiple cultural references and multimedia can form the basis for the development of new potentials between learners, knowledge, and disciplinary practice. This involves an analysis of the innovative structure of a two-course sequence in Human Geography, followed by a discussion of student feedback on the model. Based on our results, we conclude that blended learning offers not only a sophisticated approach to multiliteracies in the context of an international student setting, but for teaching students in the social sciences and humanities more broadly.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".