Farklı yanıtlar farklı duyuşsal özelliklerle ilişkili midir? CHAID analizi çalışması

Öz

Eğitimde öğrencilerin öğrenmelerini detaylı bir şekilde incelemek, güçlü ve zayıf yönlerini belirlemek ve etkili geri bildirim vermek zamanla önem kazanmıştır. Dereceli puanlama anahtarları, bu noktada çok faydalı araçlardır çünkü öğrenciler ve paydaşlar için geri bildirim sağlamada kullanılabilirler. Bu araştırmanın amacı, öğrencilerin farklı bilişsel düzeylerde yazılan okuduğunu anlama başarı testi maddelerine verdikleri yanıtların dağılımını belirlemek ve dereceli puanlama anahtarı ile belirlenen yanlış, boş ve ilişkisiz yanıtlarına göre öğrencileri sınıflandırmada etkili olan duyuşsal özellikleri belirlemektir. Bu amaçla, veri toplamak için okuduğunu anlama başarı testi, öğrenci bilgi formu, algılanan akademik öz-yeterlik ölçeği ve öğrenilmiş çaresizlik eğilimi ölçeği kullanılmıştır. Öğrenci bilgi formunda kararlık, başarı güdüsü, zorbalığa maruz kalma ve test kaygısı alt ölçekleri yer almaktadır. Öğrencilerin yanıt kategorilerini belirlemek dereceli puanlama anahtarı kullanılmıştır. Araştırma bulgularına göre maddelerin bilişsel düzeyi karmaşıklaştıkça boş ve yanlış yanıt oranı artmaktadır. En doğru yanıt oranları azalırken, kısmen doğru yanıtlar göreli olarak artmaktadır. Öğrencilerin öğrenilmiş çaresizlik eğilimleri, en temel okuduğunu anlama düzeyinde verdikleri boş ve ilgisiz yanıtları sınıflandırmada etkili olurken, bilişsel süreç karmaşıklaştıkça öğrenci tepkilerini sınıflandıran duyuşsal özelliklerin sayısı da artmıştır. Bu değişkenlerin öğrencilerin yanıtlarını geliştirmede ve kısmen doğru ve en doğru cevaba yönlendirmede önemli olduğu sonucuna varılmıştır. Öğrencileri bu özellikler bağlamında donatacak ve geliştirecek eğitimler ve sınıf ortamlarının oluşturulması önerilebilir.

Anahtar Kelimeler

• CHAID analysis
• Rubric
• Affective features
• Student answer

Are different responses related to the different affective features? CHAID analysis study

Abstract

In education, examining students' learning in detail, determining their strengths and weaknesses and giving effective feedback have gained importance over time. The aim of this study is to determine the distribution of students’ answers to the reading comprehension achievement test items which were written at different cognitive levels and to investigate the affective variables that are effective in classifying students based on their incorrect, blank, and unrelated answers identified via rubric. For this purpose, a reading comprehension achievement test, a student information form, the perceived academic self-efficacy scale and the learned helplessness tendency scale were used to collect data. The student information form included perseverance, achievement motivation, exposure to bullying and test anxiety subscales. A rubric was used to determine the students’ response categories. According to the findings of the study, the rate of blank and incorrect answers increases as the cognitive level of the items become more complex. While the most correct response rates are decreasing, partially-correct answers are increasing relatively. While students' learned helplessness tendencies were effective in classifying their blank and unrelated answers at the most basic reading comprehension level, as the cognitive process became more complex, the affective characteristics classifying the student responses increased in number. It was concluded that these variables are important in improving the students’ answers and in leading them to the partially correct and the most correct answer. It can be suggested to create trainings and classroom environments that will equip and improve students’ features about these variables.

Keywords

• CHAID analysis
• Rubric
• Affective features
• Student answer

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