The Influence of Using WhatsApp Media on Motivation and Science Learning Outcomes during Online Learning
Bibliographic record
Abstract
Learning motivation serves as a significant driving force for students, as it encompasses their engagement in learning activities, ensures the continuity of these activities, and provides direction towards achieving desired goals. The primary objective of this study was to examine the impact of WhatsApp usage on students' motivation to learn science, its influence on science learning outcomes, and its effect on both motivation and learning outcomes before and after using WhatsApp. The research was conducted among 5th grade students in the Se'seng cluster, Tana Toraja Regency. The population consisted of 95 students from SDN Gugus Se'seng. The study employed a pre-experimental model with a one-group pretest-posttest design. Prior to the treatment, a pretest was administered to assess the group's initial condition, followed by a post-test after the treatment to evaluate the group's condition post-intervention. Descriptive statistical analysis and inferential statistical analysis using SPSS 24 were employed in this study. The descriptive analysis of learning motivation among 5th grade students in the Se'seng cluster indicated an average score of 54.1667 during online learning. This average score suggests that students' motivation is still below the desired expectation of 65. In accordance with the learning process and cognitive characteristics, students were evaluated to measure their learning outcomes. The students' initial abilities were determined through a pretest, with an average score of 53.3333 in the descriptive analysis. This demonstrates that students' pretest abilities were still low and did not meet the required minimum passing grade of 75. The results of the learning motivation hypothesis test showed a t-value of -5.801, with a significance of 0.000 (p < 0.05), indicating that the use of WhatsApp media in online learning did not have a significant impact on students' learning motivation. However, based on the results of the t-test, it was determined that learning through WhatsApp media had an effect on the learning outcomes of 5th grade students in the Se'seng cluster.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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; 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".