STUDENTS’ ACADEMIC PERFORMANCE AND THEIR PERCEPTION ON THE USE OF GOOGLE APPLICATIONS IN SOCIAL STUDIES
Bibliographic record
Abstract
The aim of this study is to determine the effect on students’ academic performance and their perception on the use of Google Applications in Social Studies. It sought to answer the following questions: (1) the level of students’ satisfaction in learning Social Studies using Google Applications such as Google Classroom, Google Meet and Google Forms; (2) the mean level of the students’ academic performance in learning Social Studies in terms of recitation, performance tasks and written works and (3) the significant effect of using Google Applications to the academic performance of the selected Grade 7 students in learning Social Studies. Descriptive method was used in this study to be able to answer the hypothesis based from what was observed. The researcher used random sampling. The respondents of this study were one hundred (100) Grade 7 students of Pedro Guevara Memorial National High School. This study was conducted during the Third Quarter of the Academic Year 2020-2021. A self-made questionnaire was formulated and utilized to gather data in determining the level of satisfaction of the students on the use of Google Applications. The researcher used pre-test and posttest to examine the effect of Google Applications to the students’ academic performance in learning Social Studies. After the data collection, the researcher analyzed, presented and interpreted them. The students were satisfied on using of Google Applications in which the Google Classroom got an overall mean of 3.45 (Very Satisfied); Google Forms got an overall mean of 3.31 (Somewhat Satisfied) and Google Meet got an overall mean of 3.41 (Very Satisfied). The students felt satisfied in a sense that these applications are affordable, user-friendly, and easy to use. Moreover, it was found out that there was a “significant effect” of using Google Applications to the academic performance based on pre-test and post-test of the selected Grade 7 students in learning Social Studies. The hypothesis there is no significant effect on using Google Applications to the academic performance of the selected Grade 7 students in learning Social Studies is “not supported”.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".