Investigating Students’ Perceptions of Motivating Factors of Online Class Discussions
Bibliographic record
Abstract
<p class="3">One of the goals of teacher education is to prepare our citizens to communicate in a variety of ways. In our present society, communication using digital media has become essential. Although online discussions are a common component of many online courses, engaging students in online discussions has been a challenge. This study queried 86 educators in a math/science teacher education graduate program to examine their perceptions on the factors that motivate them to participate in online discussions.</p><p class="3">The results revealed a pragmatic outlook on online education. In terms of intrinsic versus extrinsic motivation, the participants’ main motivation to participate in online class discussions was extrinsic (85.88%), specifically so that they could earn an acceptable participation grade. With regards to discussion grouping formats, they preferred small group discussions (81%) which could facilitate their ability to develop rapport with a small group of fellow classmates over whole class discussion (38.83%). With respect to discussion facilitation, they focused on the practical need to have the instructor to answer their questions about course assignments (67.06%) over online open discussion without a given topic (35.72%). Next, when asked about discussion question types based on Bloom’s taxonomy, their strongest preference reflected a desire for application (89.54%) questions which would facilitate their ability to use theories discussed in class in their daily work as educators. Through collaboration with twenty-first-century learners, online education can use data-driven decision making to help transform online discussion from being the least desirable component of online courses to a more relevant, instructional medium. </p>
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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 | 0.006 | 0.019 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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".