Utilization of Quizizz-Assisted Instructional Materials for Mathematics 8
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study focused on the utilization of Quizizz-Assisted Instructional Materials for Mathematics for the Grade 8 students at San Jose National High School, City Schools Division Office of Antipolo, School Year 2022 – 2023. The topics that were developed into Quizizz-Assisted Instructional Materials based on the school quarterly test result for two consecutive years’ school year 2020 – 2020 and 2021 – 2022 were the topics under the second quarter on which gained least mean percentage score. The evaluation of Math experts and Math teacher respondents on the developed instructional materials in terms of content, organization and presentation, ease of use, usefulness, impact was interpreted as very highly acceptable, with a grand weighted mean of 3.89 and 3.92, respectively which also showed no significant difference. Meanwhile, the level of performance of the control group and the experimental group based on the pretest revealed that the performance of the control and experimental groups has mean scores of 7.87 and 7.67, respectively, and standard deviations of 2.97 and 3.10, with both interpreted as Not Proficient, On the other hand, the posttest performance of two groups of students, the control group has the mean score of 16.83 and standard deviation of 5.14 with verbal interpretations of Nearly Proficient, while the experimental group has the mean score of 23.20 and standard deviation of 4.73 with verbal interpretation of Proficient. Also, there was a significant difference between the pretest and posttest mean scores of the experimental groups. Comments and suggestions were given by the respondents to further improve the instructional material.
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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 it