Technological Tool for Formative Assessment in Higher Education: ZipGrade
Bibliographic record
Abstract
This descriptive study examines the effectiveness of ZipGrade, a digital assessment tool, in the context of formative evaluations within classroom settings, focusing on its deployment for multiple-choice question quizzes. This research contributes to the dialogue on the integration of information and communication technology to promote quality education and address the literature gap in providing immediate feedback to enhance the learning outcomes. Drawing on a sample of 63 fourth year B.Ed. students in Bahrain, the study combines quantitative and qualitative methodologies to assess student perceptions about the utility and effectiveness of ZipGrade. Data were collected through a semi-structured questionnaire following the administration of a series of formative tests across selected course segments. The findings reveal a predominantly positive reception of ZipGrade among students, highlighting its ease of use, immediate feedback provision, and potential to more effectively engage learners in the assessment process. Challenges such as the necessity for physical printing of answer sheets, a predisposition towards multiple-choice questions, and infrastructural and policy-related barriers were identified, suggesting areas for further development and support.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".