Online Students, Where are they and When do they do Homework? Case Study from an Online MS in GIScience Program
Bibliographic record
Abstract
Online courses provide the flexibility of time and location for both students and educators. From an administration viewpoint, online courses do not require physical classrooms, hence they require less university resources; as such, online courses are often seen as cash cows. Unfortunately, in some cases online courses are still considered second-tier because of delayed interactions between students and faculty members in an asynchronous class. In order for an administration to properly allocate university resources to online faculty, it is essential to know where online students are from. Similarly, online faculty must know when their students conduct course activities in order to provide timely and quality responses. This study examined 97 online students attending an MS in GIScience program over where they are from, and when they do their course activities. Our findings concluded that around 90% of online students were not from the traditional catchment area, and around 70% were from out of state. We also found that an average of 72% of course activities were conducted during weeknights (40%) and weekends (32%).
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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".