Applying computational analysis of novice learners' computer programming patterns to reveal self-regulated learning, computational thinking, and learning performance

2021 ◽  
Vol 120 ◽  
pp. 106746
Author(s):  
Donggil Song ◽  
Hyeonmi Hong ◽  
Eun Young Oh
Keyword(s):  
Computational Analysis ◽  
Computer Programming ◽  
Computational Thinking ◽  
Learning Performance ◽  
Self Regulated Learning ◽  
Novice Learners ◽  
Regulated Learning ◽  
Programming Patterns

Can Self-Regulated Learning Intervention Improve Student Reading Performance in Flipped Classrooms?

2020 ◽  
Vol 10 (4) ◽  
pp. 1-13
Author(s):  
Christopher C. Y. Yang ◽  
Irene Y. L. Chen ◽  
Anna Y. Q. Huang ◽  
Qian-Ru Lin ◽  
Hiroaki Ogata
Keyword(s):  
Higher Education ◽  
Online Learning ◽  
Self Efficacy ◽  
Learning Strategy ◽  
Learning Performance ◽  
Book Reading ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
Student Reading ◽  
Reading System

The advancement in network technology has stimulated the proliferation of online learning. Online learning platforms, such as the learning management systems (LMS) and e-book reading systems, are widely used in higher education to enhance students' reflection and planning of the learning process. Although many studies have explored the relationships between students' reading patterns and learning performances, few have examined the effects of self-regulated learning, learning strategy, and self-efficacy on the learning performance of students. Here, the authors collected the reading logs from an e-book reading system BookRoll and investigated the correlations between students' abilities of self-regulated learning, learning strategy, self-efficacy, and learning performance. The results of this study provide valuable insights to the teachers in higher education regarding designing courses helpful for students to improve their learning performance.

What Have We Learned About the Link Between Motivation and Learning/Performance?

2007 ◽  
Vol 21 (3/4) ◽  
pp. 263-269 ◽  
Author(s):  
Monique Boekaerts
Keyword(s):  
Learning Performance ◽  
Special Issue ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
Motivation And Learning

Abstract. A brief summary is given of the results reported by the five articles of the special issue. It is explored how each article contributes to our understanding of the motivation-learning/performance link. It is also described how the articles collectively contribute to an increased understanding of the relation between motivation and self-regulated learning. Finally, some of the challenges are addressed that are faced by motivation researcher, focusing mainly on issues that are stimulated by the articles in this special issue, and it is diverged to issues that go beyond the concerns mentioned by the researchers.

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

2019 ◽  
Vol 8 (1) ◽  
pp. 30
Author(s):  
Diah Nuraisa ◽  
Amalina Nur Azizah ◽  
Dian Nopitasari ◽  
Swasti Maharani
Keyword(s):  
Pattern Recognition ◽  
Problem Solving ◽  
Computational Thinking ◽  
Linear Program ◽  
Program Problem ◽  
Self Regulated Learning ◽  
Linear Program Problem ◽  
Regulated Learning ◽  
Depth Interviews

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.

scholarly journals The Effects of Self-regulated Learning Strategies on Computer Programming Achievement in Teacher Education

2021 ◽  
Vol 4 (4) ◽  
pp. p37
Author(s):  
Gary Cheng
Keyword(s):  
Learning Strategies ◽  
Help Seeking ◽  
Computer Programming ◽  
Self Regulation ◽  
Management Strategies ◽  
Cognitive Strategies ◽  
Strategy Training ◽  
Self Regulated Learning ◽  
Java Programming ◽  
Regulated Learning

This study investigates the effects of student use of self-regulated learning (SRL) strategies on their computer programming achievement. Ninety-six students from undergraduate teacher training programmes offered by a Hong Kong university voluntarily participated in the study. Sixty-six of them were first-year students enrolling on an introductory Java programming course, while 30 were second-year students enrolling on an advanced Java programming course. The SRL strategies adopted by participants were measured by the Motivated Strategies for Learning Questionnaire (MSLQ) and were exemplified from the reflective writing of their electronic portfolios. Their achievement in computer programming was evaluated using continuous and end of course assessments. The findings of this study suggest that higher-order cognitive strategies (i.e. elaboration, organization, critical thinking), metacognitive control strategies (i.e. self-regulation) and resource management strategies (i.e. time and study environment management, help seeking) are likely to facilitate a prolonged achievement of computer programming for both novices and non-novices. They can provide insights into designing adequate SRL strategy training to support student learning in computer programming.

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