Blended online courses: students’ learning experiences and engaging instructional strategies
Bibliographic record
Abstract
The COVID-19 pandemic has accelerated the digital shift in higher education and forced university faculty to transform their courses into a blended or online modality to comply with current public health measures. Many instructors have implemented blended online courses, which combine synchronous and asynchronous online teaching and learning activities. The purpose of this study is to document university students’ learning experiences in blended online courses during the pandemic, and to identify instructional strategies to support student engagement in these courses. It adopts a mixed-methods research strategy in which data were collected through questionnaires from students who took a blended online course in the summer semester of 2020, in a variety of disciplines and academic cycles at four Quebec universities (n = 482). Following the analysis of student responses to open-ended questions, five recurring themes were identified: the enhancement of student-student interactions, the dynamism of synchronous and asynchronous sessions, the structured presentation of the course, the explanations and feedback from instructors, and the accessibility and involvement of instructors. For each theme, suggestions from student feedback are provided to facilitate student engagement in blended online courses.
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 | 0.001 | 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 | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".