6th Grade Students’ Views about Mathematical Teaching Based on Technology Integration
Bibliographic record
Abstract
The aim of this study is to determine the opinions of 6th grade students towards teaching applications developed onthe basis of Planning-Practicing-Evaluation model which is an ICT integration model for effective mathematicsteaching. While teaching process was designed, Moodle which is a learning management system was used in order touse teaching applications together in a systematic and planned way. Throughout the teaching process, ICT resourcessuch as interactive board, computer, GeoGebra dynamic geometry software, web 2.0 tools (digital stories, videos,animations, games) were used. 33 sixth grade students participated in the research. The case study of qualitativeresearch methods was used in the study. Students' opinions on teaching practices were collected throughsemi-structured interview method. The obtained data were analyzed by content analysis. As a result, it wasdetermined that the students expressed their opinions towards learning practices increases comprehensibility of thesubjects, provides learning opportunities by make and experience, develops positive attitude towards mathematicsteaching, attractive and interesting, they associate daily life with mathematics and increases the desire to participatelessons with having catchy lessons.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".