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2.7. Method of Data CollectionThe 7
2.7. Method of Data Collection
The 72-item SETES-M that emerged after the preliminary factorial validation was used for data collection. Copies of the 72-item SETES-M were administered to the sample drawn for the study. Thereafter, the MAT was administered to collect data on the dependent measure. The data collection was carried out with the help of the mathematics teachers in the selected schools. The total period of
the data collection spanned six weeks.
2.8. Data Analysis
Research question 1 was answered using factor analysis with varimax rotation. Question 2 was answered using Cronbach coefficient alpha while questions 3 and 4 were answered using multiple regression analysis.
3. RESULTS
Factor analysis (Principal components with varimax rotation) was performed on the responses to the SETES-M, treating males and females separately. Since both male and female teaching effectiveness rating profiles showed pattern and magnitude similarities, the data were combined. The subsequent factor analysis produced seven meaningful factors with eigen values greater than unity, which accounted for a total of 56.7% of variance. These factors had interpretable structures with factor loadings ranged from 0.36 to 0.58.
The 72-item SETES-M that emerged after the preliminary factorial validation was used for data collection. Copies of the 72-item SETES-M were administered to the sample drawn for the study. Thereafter, the MAT was administered to collect data on the dependent measure. The data collection was carried out with the help of the mathematics teachers in the selected schools. The total period of
the data collection spanned six weeks.
2.8. Data Analysis
Research question 1 was answered using factor analysis with varimax rotation. Question 2 was answered using Cronbach coefficient alpha while questions 3 and 4 were answered using multiple regression analysis.
3. RESULTS
Factor analysis (Principal components with varimax rotation) was performed on the responses to the SETES-M, treating males and females separately. Since both male and female teaching effectiveness rating profiles showed pattern and magnitude similarities, the data were combined. The subsequent factor analysis produced seven meaningful factors with eigen values greater than unity, which accounted for a total of 56.7% of variance. These factors had interpretable structures with factor loadings ranged from 0.36 to 0.58.
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2.7. Method of Data Collection
The 72-item SETES-M that emerged after the preliminary factorial validation was used for data collection. Copies of the 72-item SETES-M were administered to the sample drawn for the study. Thereafter, the MAT was administered to collect data on the dependent measure. The data collection was carried out with the help of the mathematics teachers in the selected schools. The total period of
the data collection spanned six weeks.
2.8. Data Analysis
Research question 1 was answered using factor analysis with varimax rotation. Question 2 was answered using Cronbach coefficient alpha while questions 3 and 4 were answered using multiple regression analysis.
3. RESULTS
Factor analysis (Principal components with varimax rotation) was performed on the responses to the SETES-M, treating males and females separately. Since both male and female teaching effectiveness rating profiles showed pattern and magnitude similarities, the data were combined. The subsequent factor analysis produced seven meaningful factors with eigen values greater than unity, which accounted for a total of 56.7% of variance. These factors had interpretable structures with factor loadings ranged from 0.36 to 0.58.
The 72-item SETES-M that emerged after the preliminary factorial validation was used for data collection. Copies of the 72-item SETES-M were administered to the sample drawn for the study. Thereafter, the MAT was administered to collect data on the dependent measure. The data collection was carried out with the help of the mathematics teachers in the selected schools. The total period of
the data collection spanned six weeks.
2.8. Data Analysis
Research question 1 was answered using factor analysis with varimax rotation. Question 2 was answered using Cronbach coefficient alpha while questions 3 and 4 were answered using multiple regression analysis.
3. RESULTS
Factor analysis (Principal components with varimax rotation) was performed on the responses to the SETES-M, treating males and females separately. Since both male and female teaching effectiveness rating profiles showed pattern and magnitude similarities, the data were combined. The subsequent factor analysis produced seven meaningful factors with eigen values greater than unity, which accounted for a total of 56.7% of variance. These factors had interpretable structures with factor loadings ranged from 0.36 to 0.58.
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2.7. Metode Pengumpulan Data 72 item setes-M yang muncul setelah validasi faktorial awal digunakan untuk pengumpulan data. Salinan dari 72 item setes-M diberikan kepada sampel yang diambil untuk penelitian. Setelah itu, MAT itu diberikan untuk mengumpulkan data tentang ukuran tergantung. Pengumpulan data dilakukan dengan bantuan guru matematika di sekolah-sekolah yang dipilih. Periode total pengumpulan data membentang enam minggu. 2.8. Analisis Data Penelitian Pertanyaan 1 dijawab dengan menggunakan analisis faktor dengan rotasi. Pertanyaan 2 dijawab dengan menggunakan Cronbach koefisien alpha sementara pertanyaan 3 dan 4 dijawab dengan menggunakan analisis regresi berganda. 3. HASIL Analisis faktor (komponen utama dengan rotasi) dilakukan pada tanggapan terhadap setes-M, mengobati pria dan wanita secara terpisah. Karena kedua profil Peringkat efektivitas mengajar pria dan wanita menunjukkan pola dan besarnya kesamaan, data digabungkan. Analisis Faktor selanjutnya menghasilkan tujuh faktor yang bermakna dengan nilai eigen lebih besar dari satu, yang menyumbang total 56,7% dari varians. Faktor-faktor ini memiliki struktur ditafsirkan dengan faktor beban berkisar 0,36-0,58.
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