Predicting Low and High Student Performance in Programming Education Using PLS-SEM Algorithms

The study uses the partial least squares-structural equation modeling (PLS-SEM) algorithm to predict the factors affecting the programming performance (PPE) (low, high) of the students receiving computer programming education. The participants of the study consist of 763 students who received progra...

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Veröffentlicht in:	Technology, knowledge and learning Jg. 30; H. 3; S. 1231 - 1248
Hauptverfasser:	Durak, Aykut, Bulut, Vahide
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Dordrecht Springer Netherlands 01.09.2025 Springer Nature B.V
Schlagworte:	Academic Achievement Active Learning Addition Algorithms Anxiety Basic Skills Careers Cognition & reasoning Cognitive ability Communities of Practice Competence Computer Attitudes Computer programming Computer science Computer Science Education Computer Use Creativity and Arts Education Data Analysis Data Collection Differentiation Education Educational Experience Educational Objectives Educational Technology Empowerment Evaluative Thinking Goal Orientation High Achievement Inferences Influence of Technology Learning Learning and Instruction Learning Processes Original Research Place of Residence Problem solving Programming Science Education Self-efficacy Students Systems design Computational thinking Programming training Anxiety Programming performance Computational identity Empowerment
ISSN:	2211-1662, 2211-1670
Online-Zugang:	Volltext
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