Exploring Students Computational Thinking based on Self-Regulated Learning in the Solution of Linear Program Problem

This study aims to analyze the students computational thinking in the solution of the linear program problem based on self-regulated learning. The data were collected by self-regulated learning questionnaire, computational thinking test, and depth interviews. This study was conducted in SMAN 10 Tangerang. Computational thinking in students with high and medium levels of self-regulated learning has no difference. Students still make a solution that is fixated with linear program problem-solving procedures in general, that is using examples, substitution, and elimination. In solving problems, students can reach the stages of decomposition and pattern recognition only. Students still do not evaluate the results of their work. Algorithmic performed is less coherent because the abstraction has not been done. The recommendation for further research is the need for research that can develop student abstraction in solving problems. Besides, there is also a need for research that analyzes the reflective of students in computational thinking when solving problems

Introduction paper special issue computers in human behavior multidisciplinary innovations and technologies for facilitation of self-regulated learning

Technology-enhanced learning environments provide ample opportunities for learners to self-regulate their learning processes and activities for achieving the intended learning outcomes in various disciplines from soft to hard sciences and from humanities to the natural and social sciences. This special issue discusses the emerging technological advancements and cutting-edge research on self-regulated learning dealing with different cognitive, motivational, emotional, and social processes of learning both at the individual and group levels. Specifically, it discusses how to optimally use advanced technologies to facilitate learners’ self-regulated learning for achieving their own individual learning needs and goals. In this special issue, seven researchers/research teams from the fields of collaborative learning, computational thinking, educational psychology, and learning analytics presented contributions to self-regulated learning with the goal of stimulating cross-border discussion in the field.</p