Support: The Keystone of Distance Education
Bibliographic record
Abstract
TÉLUQ University is the only French-language university in North America that is entirely dedicated to distance education. It has been in existence for 50 years and all courses are delivered asynchronously. As in most open or distance learning universities, the majority of students are adults who are returning to school and trying to balance their studies with their family or professional life. Students are attracted by the possibility of enrolling at any time and completing available courses at their own pace. However, as research in the field has demonstrated, the downside of such freedom is a higher dropout rate in distance learning than in traditional in-person courses. Thus, support seems to play a key role in improving student perseverance. But what type of support do students need? \n \nIn this paper, we highlight some of the ways in which we support distance students at our university. First, coordinators and professors support and guide students in their choice of programme courses and pathway. Second, follow-up is provided in each course by professors, tutors or supervisors who support the students in their learning. Finally, while the opportunity to communicate with other students is rare within the courses, the system called “Ensemble à distance” allows students to communicate in forums in asynchronous mode or in synchronous mode during virtual cafés. In addition, other special support mechanisms are available for certain categories of students, such as those with disabilities or those taking their first distance learning course. \n \nMoreover, during the COVID-19 pandemic, TÉLUQ University played a major role in supporting all teachers in Quebec (and beyond) by creating the J’enseigne à distance (I teach at a distance) training programme at the request of the Ministry of Education. This programme was created in four months and includes four microprograms (support, dissemination, adaptation and evaluation) for the different levels of education (preschool-primary/secondary/college-university). The modules were made available online as soon as each one was created and they were a great success, with more than 300,000 people consulting the training worldwide (connections from 191 countries). Although the majority (79%) of participants were in Canada, the reach of this training is a reminder of the extent of the need for assistance in the transition to distance learning. It is also interesting to note that among the students registered for a certificate, the microprogram on support was the most widely taken. In fact, as highlighted by the difficulties in interaction and the isolation experienced by distance education students during the lockdown, support remains the main challenge and the keystone of distance education.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.108 | 0.038 |
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".