The Evolution of Online Education at a Small Northern Ontario University: Theory and Practice
Bibliographic record
Abstract
One of the major influences on university education in Ontario is the growing use of Internet technologies. These new technologies have led faculty and learning experts at universities to talk about online and technology-enhanced learning with a fervor not often found on most campuses. Among other things, these discussions have challenged well known understandings of what has historically been called distance education. In this paper, we examine a cross-section of publications on distance and online education and reflect on our professional experiences in relation to the evolution of a teaching and learning centre in our small university in Northern Ontario. In addition to supporting the teaching and learning needs of an on-campus community, our Centre oversees the development and delivery of online courses for students at a distance from the physical campus. Within the context of this Centre, we represent the Academic Director and a faculty member completing doctoral studies on technology-enabled learning in the United Kingdom. As a conclusion, we propose that the geographical distance and possible isolation of Northern Ontario can be considerably reduced through online education and that it is no longer appropriate to speak about distance education. As Wenger (2004) suggests, many remote and rural communities as well as individual learners in these communities can access information and even inspiration from on line educational experiences. To achieve this, faculty continue to require resources including pedagogical supports, mentorship, and even inspiration to capitalize on the potential and opportunity of online models and strategies. Resume Une des influences majeures sur l’enseignement universitaire en Ontario est l’utilisation croissante des technologies en ligne. Ces nouvelles technologies ont amene les enseignants et les experts en apprentissage dans les universites a discuter de l’apprentissage en ligne et de l’apprentissage ameliore par la technologie avec une ferveur rarement rencontree sur d'autres campus. Ces discussions ont notamment remis en question certains preceptes bien etablis sur ce qu’on a, historiquement, defini comme etant de l’apprentissage a distance. Dans cette etude, nous faisons une analyse transversale de publications portant sur l’education a distance et l’apprentissage en ligne et proposons une reflexion sur nos experiences professionnelles en lien avec l’evolution d’un centre d’enseignement et d’apprentissage dans notre petite universite situee dans le nord de l’Ontario. En plus de soutenir la communaute se trouvant sur le campus au plan de ses besoins relatifs a l’enseignement et l’apprentissage, notre Centre supervise le developpement et la dispensation des cours en ligne pour les etudiants qui sont eloignes du campus physique. Dans le contexte de ce Centre, nous representons le Directeur universitaire (Academic Director) et un membre du personnel enseignant faisant des etudes doctorales sur l’apprentissage habilite par les technologies au Royaume-Uni. En terminant, nous proposons que la distance ainsi que le possible isolement geographique du nord de l’Ontario puissent etre considerablement reduits par l’education en ligne et qu’il ne soit plus approprie de parler d’education a distance. Comme le suggere Wenger (2004), de nombreuses communautes eloignees et rurales, de meme que des etudiants individuels dans ces communautes peuvent puiser des informations et meme de l’inspiration a partir d’experiences d’apprentissage en ligne. Pour ce faire, les corps enseignants ont toujours besoin de ressources, incluant le soutien pedagogique, le mentorat, et meme de l’inspiration pour profiter au maximum des opportunites et du potentiel offerts par les modeles et les strategies d’enseignement en ligne.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.015 | 0.018 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".