Utilizing Digital Media for Guidance and Counseling in Education
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 causal correlational study aims to find out the effect of factors of digital technology on guidance and counseling teachers’ usage of guidance and counseling media. It involved eighty-five guidance and counseling teachers in seven regions, recruited using a convenience sampling technique. Data were garnered using the Attitude scale for digital technology developed by Emine [1], which has been considered valid and highly reliable (1.000). Data were analyzed using a linear regression test and path analysis using SPSS. The effect size of these factors varied, with the highest score observed in “technology for me” (75.1%), followed by interest in technology (70.3%), technological use (63.9%), competence (59.6%), social network (54.2%), conscious use (53.7%), recreational use (43.2%), and negative aspects (25.2%). These factors exhibited significant correlations with and influenced the usage of guidance and counseling media among guidance and counseling teachers in this study. Consequently, it is necessary to implement interventions aimed at enhancing the utilization of digital technology for guidance and counseling services.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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 it