Ontario Colleges in the Digital Age: Understanding the Student Experience, Perceptions and Attitudes of Online Learning at one Ontario College
Bibliographic record
Abstract
The global economy is undergoing drastic upheavals as Canada enters the 21st century. The key driver of this transformation is the emergence of the digital age. The digital age is impacting all facets of Canadian society, including postsecondary education. The integration of educational technologies into curriculum is spawning a new form of learning commonly referred to as online learning. Online learning has the potential to radically alter the manner in which knowledge is taught and learned in Canadian higher education. This mixed-methods study utilized both quantitative and qualitative data collection methods. The qualitative phase (n = 16) was developed and built upon the development and analysis of the quantitative phase (n = 279), which is based on Chickering and Gamson’s (1987) Seven Principles for Good Practice in Undergraduate Education, permitting the researcher to probe more deeply into the college students’ attitudes and perceptions of their online learning experience. The participating students represented most of the programs offered by this college. After the data analysis and interpretations of the findings, several themes emerged. The participants in the online questionnaire were satisfied with their online learning experiences at this one Ontario college. The participants cited the convenience, flexibility and the ability to control their learning as major benefits associated with online learning. Although the students who participated in the online questionnaire were satisfied with their online learning experiences, the quantitative and qualitative findings of this study provide compelling evidence that, as a matter of preference, students would chose a face-to-face / hybrid course over an online course. The participants in the semi-structured interviews repeatedly discussed how the interaction and physical contact between faculty and student, and between students enhanced the learning experiences, which contributed to their academic success. The socialization that occurred in the classroom was also a contributing factor for the preference for face-to-face / hybrid instruction. The results of this study may inform and guide college leadership and faculty about the complexities associated with implementing an online learning strategy at their college. Implications of the conclusions are presented and discussed on how they may impact Ontario’s colleges.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".