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Jin, Hao-Yue; Cutumisu, Maria – Education and Information Technologies, 2023
Computational thinking (CT) skills of pre-service teachers have been explored extensively, but the effectiveness of CT training has yielded mixed results in previous studies. Thus, it is necessary to identify patterns in the relationships between predictors of CT and CT skills to further support CT development. This study developed an online CT…
Descriptors: Preservice Teachers, Computation, Thinking Skills, Predictor Variables
Göktepe Yildiz, Sevda; Göktepe Körpeoglu, Seda – Education and Information Technologies, 2023
Traditionally, students' various educational characteristics are evaluated according to the grades they get or the results of their answers to the scales. There are some limitations in making an evaluation based on the results. The fuzzy logic approach, which tries to eliminate these limitations, has recently been used in the field of education.…
Descriptors: Foreign Countries, Students, Student Attitudes, Problem Solving
Senkbeil, Martin – Education and Information Technologies, 2022
This study examined the incremental validity of different information and communication technologies (ICT)-related person characteristics over and above intelligence and and prior achievement when predicting ICT literacy across a period of three years. Relative weights analyses were performed to determine the relative contribution of each…
Descriptors: Technological Literacy, Information Technology, Validity, Individual Characteristics
Erdogdu, Funda – Education and Information Technologies, 2022
The main drive for this study is to look into potential predictors of educational achievement using OECD's original Pisa 2018 dataset. This paper explores (i) access to ICT, (ii) physical characteristics of learning environment at school, (iii) quality of teaching staff and educational material, (iv) student characteristics and learning climate,…
Descriptors: Academic Achievement, Predictor Variables, International Assessment, Secondary School Students
Giannakos, Michail N.; Pappas, Ilias O.; Jaccheri, Letizia; Sampson, Demetrios G. – Education and Information Technologies, 2017
Researchers have been working to understand the high dropout rates in computer science (CS) education. Despite the great demand for CS professionals, little is known about what influences individuals to complete their CS studies. We identify gains of studying CS, the (learning) environment, degree's usefulness, and barriers as important predictors…
Descriptors: College Students, School Holding Power, Computer Science Education, Environmental Influences