Ilköğretim ingilizce dersi akademik ortalamalari ile seviye belirleme sinavi ingilizce alt testi sonuçlari arasindaki ilişkinin yapisal eşitlik modeli ile incelenmesi

Bu araştırmanın amacı, ilköğretim öğrencilerinin İngilizce dersi akademik ortalamaları ile Seviye Belirleme Sınavı (SBS) İngilizce alt testi sonuçları arasındaki ilişkiyi yapısal eşitlik modeli ile incelemektir. Bu araştırmada, 6. 7. ve 8. sınıf İngilizce dersi yazılı sınav puanları, proje görevi, performans görevi ve ders içi etkinliklere katılım yılsonu akademik başarı puan ortalamaları ile bu sınıfların SBS İngilizce alt testi ham puanları arasındaki ilişki incelenmiştir. Çalışmada İngilizce dersi akademik başarı puan ortalamaları bağımsız değişken, SBS İngilizce alt testine ait ham puanlar ise bağımlı değişken olarak kullanılmıştır. Araştırmanın çalışma grubunu, 2009 yılında Niğde ili Merkez ilçesindeki altı ilköğretim okulunda öğrenim gören ve SBS'ye giren 6. 7. ve 8. sınıflar düzeyinde toplam 375 öğrenci oluşturmaktadır. Araştırmada değişkenler arasında yapısal modelin kurulmasında LISREL 8.51 programından yararlanılmıştır. Araştırmada elde edilen bulgulara göre, model-veri uyum indeksleri yüksek düzeyde bulunmuştur [χ2/sd=1.39; GFI=0.94; CFI=0.97; AGFI=0.91; RMSEA=0.043; RMR=0.068; SRMR=0.049; NFI=0.91; NNFI=0.96]. Regresyon analizinde ise, yazılı sınavlar değişkeninin öğrencilerin SBS İngilizce alt testi akademik başarılarının en önemli yordayıcısı olduğu saptanmıştır. Diğer taraftan, yapılan regresyon analizi neticesinde İngilizce dersi akademik ortalamalarının SBS İngilizce alt testi başarının %60’ını açıkladığı tespit edilmiştir.

Seviye Belirleme Sınavı ,

İngilizce alt testi ,

İngilizce dersi ,

akademik ortalamaları ,

Purpose and Significance: The central examinations have been performed with the aim of selecting and placing the students in the various education institutions for a long time in Turkey. Among these central examinations come the ones that are performed in the transition from elementary education to secondary education first (Karakaya, 2012). In the transition from elementary education to secondary education, the results of the Level Determination Examination, known as SBS are used. In order to select students and place them in secondary schools, the Level Determination Examination (LDE) has been performed for the 6th, 7th, and 8th grades since the academic year 2007–2008 (MEB, 2010a). The Level Determination Examination includes five sub-tests, which are Turkish, mathematics, science and technology, social sciences, and foreign languages (MEB, 2010b). After the elementary curriculum has been renewed in 2005-2006 academic year, alternative measurement and assessment approaches are being used in the classrooms such as project work, classroom involvement, performance work, portfolio, etc. (Atılgan, Kan & Doğan, 2011). Amongst these, project work, classroom involvement, performance work, and formal examinations at school are being used for the transition from elementary education to secondary education as well as the result of the Level Determination Examination (MEB, 2010a). When the related literature is viewed, it is seen that there are many studies on the effects of the LDE (Sevindik, 2009; Üzkurt & Koçakoğlu, 2009; Anıl et al., 2010; Güler, 2010; Erdoğan, Giorgietti & Çifçili, 2010; Kelecioğlu, Atalay & Öztürk, 2010; Kurt, 2010; Yılmaz, 2010; Anıl & Güzeller, 2011; Bal, 2011; Şahin, 2011; Güzeller, 2012; Karakaya, 2012; Karakaya & Kutlu, 2012). These studies are seen that they have mostly focused on mathematics and science and technology sub-tests in the LDE. However, it is understood that there are no studies which focuses on other sub-tests of the LDE such as Turkish, social sciences, and foreign languages. Therefore, more studies are needed in order to investigate factors affecting students’ performance in the LDE. Hence, it is thought to be important to analyze the relationship between the means of the academic achievement scores of the students in English course that they had from different means of measurement and the raw scores of LDT English sub-test. In this regard, the purpose of this study is to investigate the correlation between academic averages of elementary English course and English sub-test scores in the Level Determination Examination (LDE) with structural equation modeling. Method: The correlative investigation model was used in the research (McMillan & Schumacher, 2006). This model is one of the most commonly applied models in the related literature (Cohen, Manion & Morrison, 2003). A structural equation model was formed in order to better illustrate the correlation between variables in the research (Brown, 2006). Structural equation model connects the predictive structural correlations holding between the variables in the regression model to the covered factor structures in the factor analysis through a comprehensive analysis (Sümer, 2000). The population of this study consisted of students in elementary schools within the borders of Nigde province of Turkey. In order to detect the sampling of the study, from elementary schools in cosmos, 375 students from six public elementary schools were chosen according to random sampling method (Karasar, 2005). In this research, LISREL 8.51 structural equation programme was used in model establishing by using the observed variables predicted. Discussion: It was found a linear positive significant high correlation between written exams variable to academic scores in relation to the Level Determination Examination English sub-test in the research. Verim (2006) and Güzeller (2012) found similar findings to the related finding of this study. Also, Sevindik (2009) and Üzkurt and Koçakoğlu (2009) found similar findings which support the related finding of this study. According to the results of the study, it became evident that the second most crucial factor determining students’ academic scores in relation to the Level Determination Examination English sub-test was performance work variable. Kurt (2010), Şahin (2011) and Güzeller (2012) found similar results to the related finding of this study. In addition, Öztürk (2010) found a strong correlation between performance work and academic success in Turkish course. Hence, it can be stated that the result obtained in this study is not paralleled to the findings obtained in the related literature. Besides, a linear positive correlation was found out between students’ academic scores in relation to the Level Determination Examination English sub-test and participation in course variable in English course, where the connection coefficient value was found as =0.85 in the research. According to the researches carried out in the related literature, there is a strong correlation between student involvement in course and their academic success (Hafeez & Wilson, 2007; Adeyemo, 2010; Garland, 2010; Hawkins, 2010). However, Güzeller (2012), in his study, could not find any significant finding similar to the related finding of this study. Finally, it was also found out a linear positive significant high correlation between participation in course variable to academic scores in relation to the Level Determination Examination English sub-test in the study. Also a positive significant linear correlation which was determined between project work variable and students’ academic scores in relation to the Level Determination Examination English sub-test in the model. As the literature is viewed, it is seen that there is significant correlation between project work and academic success (Kaya, 2011). However, Güzeller (2012), in his study, could not find any significant finding similar to the related finding of this study. As the related literature is viewed, it is seen that there are studies which support the general findings obtained in this study (Deniz &Kelecioğlu, 2005; Verim, 2006; Sevindik, 2009; Üzkurt & Koçakoğlu, 2009; Kurt, 2010; Öztürk, 2010; Şahin, 2011; Güzeller, 2012). Conclusion: On examining the compatibility index results of the constructed equation model, the model-data compatibility was found out to be high enough. As a result of path analysis, χ2/df ratio was 1.39 (χ2/df=100.24/72). In the study, GFI value was 0.94 and AGFI value was found out as 0.91 so that they can be perceived as sufficient. In this research, RMSEA value was found as 0.043 so that it is considered as an excellent goodness of fit. Besides, RMR value was found as 0.068 and SRMR value was found as 0.049 in the study. In this study, CFI value was found out as 0.97. Lastly, NFI value was 0.91 and NNFI value was found as 0.96 in this study. On examining the structural equation modeling, it was seen that the variable best predicting elementary students’ academic scores in relation to the Level Determination Examination English sub-test was written exams variable. It was found a linear positive significant high correlation between written exams variable to academic scores in relation to the Level Determination Examination English sub-test in the research. It became evident that the second most crucial factor determining students’ academic scores in relation to the Level Determination Examination English sub-test was performance work variable. Besides, a linear positive correlation was found out between students’ academic scores in relation to the Level Determination Examination English sub-test and participation in course variable in English course in the research. It was found a linear positive significant high correlation between participation in course variable to academic scores in relation to the Level Determination Examination English sub-test in the study. Also, a positive significant linear correlation which was determined between project work variable and students’ academic scores in relation to the Level Determination Examination English sub-test in the model. On the other hand, to determine the direct effect of the academic averages in English course on academic scores in relation to the Level Determination Examination English sub-test, a regression analysis was used. On examining the regression equation of the covered variables predicted by variables that were included in the structural equation model, the statement coefficient value of the model was found as 0.60 in the study. The model created [Academic Averages in English Course= 0.91*Written Exam+0.86*Performance Work+0.78*Participation+0.51*Project Work, Error var.= 0.39, R²= 0.60] was found out to be statistically significant at p<.01 level in the research. In this regard, it can be well understood that all four predictor variables that were included in the regression equation accounted for 60% of the overall variance of the academic scores in relation to the Level Determination Examination English sub-test in the research.

Level Determination Examination, ,

English sub-test, ,

English course academic averages ,