Algoritma Öğretiminde Çözümlü Örnek Kullanımının Öğrenci Başarısına ve Bilişsel Yüke Etkileri

Abstract

The aim of the study is to examine the effects of two instructional strategies (traditional and faded worked example) in teaching algorithm on university students' achievement and cognitive load. In this study, randomized pretest-posttest control group research design was used. Participants of the study consisted of 33 (24 female, 9 male) students studying at Department of Computer Education and Instructional Technologies. While faded worked examples presented to experimental group (n=17) through web based learning environment which was developed for this study, traditional worked examples presented to control group (n=16). In the development of learning environment, design principles which had been tested in worked example literature was used. The implementation lasted for 2 weeks in the web based learning environment. During first week the pseudo-code application was performed, while the flow chart application was performed in the second week. Research data consisted of pretest-posttest scores, which were developed to measure students' algorithm performances, cognitive rating scale, which was implemented to measure students' cognitive load, task performance scores in the learning environment, and final exam scores. Pre-test and post-test scores and cognitive load levels of the students were taken into account in order to determine the instructional efficiency of the methods applied. As a result, faded worked example strategy used in teaching algorithm to university students found to be more effective in terms of achievement than the traditional worked example strategy. While there was no significant difference between the cognitive load levels of the learners in the experimental and control groups, faded worked example strategy was more efficient. In addition, the results indicated that the final programming scores of the experimental group were significantly higher than those of control group.