Web based content and hybrid teaching: Student perceptions of the effectiveness of using web based content and hyper-linked teaching units in teaching hybrid business and marketing post secondary classes
Bibliographic record
Abstract
This exploratory, descriptive action research study is based on a survey of a \nsample of convenience consisting of 172 college and university marketing students, and 5 \nprofessors who were experienced in teaching in an internet based environment. The \nstudents that were surveyed were studying e-commerce and international business in 3^^ \nand 4*'' year classes at a leading imiversity in Ontario and e-commerce in 5^ semester \nclasses at a leading college. These classes were taught using a hybrid teaching style with \nthe contribution of a large website that contained pertinent text and audio material. \nHybrid teaching employs web based course materials (some in the form of Learning \nObjects) to deliver curriculimi material both during the attended lectures and also for \nstudents accessing the course web page outside of class hours. The survey was in the \nform on an online questionnaire. The research questions explored in this study were: \n1. What factors influence the students' ability to access and learn from web based course \ncontent? \n2. How likely are the students to use selected elements of internet based curriculum for \nlearning academic content? \n3. What is the preferred physical environment to facilitate learning in a hybrid \nenvironment? \n4. How effective are selected teaching/learning strategies in a hybrid environment? \nThe findings of this study suggest that students are very interested in being part of \nthe learning process by contributing to a course web site. Specifically, students are \ninterested in audio content being one of the formats of online course material, and have \nan interest in being part of the creation of small audio clips to be used in class.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".