Exploring High School Students’ Cognitive Structures for Energy Concept Through Word Association Test
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Notice bibliographique
Résumé
This research, which was conducted in order to reveal the cognitive structures of high school students regarding the concept of energy through the word association test, was designed in a survey model. Word association test was used as a data collection tool. After the necessary information was given to the students, they were given three minutes and they were asked to write the first words that came to mind about the key concept. The study group of the research consists of 202 students studying in a high school in the province of Malatya in the 2019-2020 academic year. 58 of these students are 9th grade, 46 are 10th grade, 45 are 11th grade and 53 are 12th grade. While choosing the study group of the research, one of the purposeful sampling types was chosen based on easily accessible situation sampling. The words obtained related to the concept of energy are tabulated using Microsoft office excel program. The cut-off points of the tables, which were examined in detail and repeated words were taken into account, were determined. Concept networks were created in line with the determined cut-off points. In the research, 189 different words were produced for the concept of energy by high school students. While 114 of these words were not included in the analysis because they had 4 or less frequencies, 75 words were included in the analysis. Among the words included in the analysis, the most repeated word in the 9th grade was “petrol” (f = 30), the most repeated word in the 10th grade was “fossil fuel” (24), the most repeated word in the 11th grade “electricity” (19), the most repeated word in the 12th grade was found to be “potential” (28). In the comparison between the classes, a difference in quantity and quality is observed. It has been observed that as the grade level increases, the quality of the answers given increases.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,021 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle