Applying the context, input, process, product evaluation model for evaluation, research, and redesign of an online master’s program
Bibliographic record
Abstract
<p>This study aimed to evaluate and redesign an online master’s degree program consisting of 12 courses from the informatics field using a context, input, process, product (CIPP) evaluation model. Research conducted during the redesign of the online program followed a mixed methodology in which data was collected through a CIPP survey, focus-group interview, and open-ended questionnaire. An initial CIPP survey sent to students, which had a response rate of approximately 60%, indicated that the Fuzzy Logic course did not fully meet the needs of students. Based on these findings, the program managers decided to improve this course, and a focus group was organized with the students of the Fuzzy Logic course in order to obtain more information to help in redesigning the course. Accordingly, the course was redesigned to include more examples and visuals, including videos; student-instructor interaction was increased through face-to-face meetings; and extra meetings were arranged before exams so that additional examples could be presented for problem-solving to satisfy students about assessment procedures. Lastly, the modifications to the Fuzzy Logic course were implemented, and the students in the course were sent an open-ended form asking them what they thought about the modifications. The results indicated that most students were pleased with the new version of the course.</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 | 0.049 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".