"The Influence of the K-12 Curriculum on College Education and Career Pathways of Peñaranda National High School's 2018 Science Technology Engineering and Mathematics (STEM) Graduates"
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Notice bibliographique
Résumé
This is an exploratory investigation of the STEM graduates’ perceptions of their competence and their teachers in the different senior high school subjects including their college career decisions and success stories. Using quantitative and qualitative research methods, 73 STEM graduates of Peñaranda National High School in the academic year 2017-2018 who were already college graduates in SY 2022-2023 were followed up and profiled. Results revealed that they finished Bachelor of Science programs in Civil Engineering (27.4%), Nursing (16.44%), Electrical Engineering (13.69%), Agriculture (12.33%), and Mechanical Engineering (10.96%). Their GWA for general education is 89.58 major subjects are 84.56 and professional subjects are 88.79. 30.14% of them already have eligibilities, 2.7% were regular/permanent, 38.4% were contractual and most of them were preparing for their board/licensure exams. The students assessed the effectiveness of their teachers in delivering instruction on core, applied, and specialized subjects in Senior High School (SHS). The mean scores exhibited a range between 3.05 and 3.30, thereby classifying them inside the "Proficient in Teaching" group. Interestingly, suggestions for instructors to enhance their performance in each of these domains also aligned with the "Proficient in Teaching" classification. This finding demonstrates a correlation between the effectiveness of teachers in their instructional practices and the degree to which student feedback contributes to their pedagogical improvement. Upon examining academic achievement, it was discovered that a significant proportion of students attained grades categorized as "Outstanding" or "Very Satisfactory" over their high school and college years. Upon closer examination, it became evident that there existed a direct correlation between the academic performance of students and the effectiveness of their teachers in delivering instruction. The study substantiates the significance of effective instruction in fostering the academic achievement of students. It is posited that an average value of 4 is considered optimal, denoting a level of "Highly Proficient" for teacher performance and "Outstanding" for student academic performance. The findings of this study provide valuable insights into strategies for enhancing the quality of instruction and educational outcomes in secondary STEM curricula. The aforementioned findings demonstrate the significance of teachers possessing a comprehensive understanding of fundamental, practical, and specialized subjects concerning the scholastic achievements of the students.
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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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| 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