Critical thinking is a fundamental skill for 21st-century citizens, and it should be promoted from elementary school and developed in computing education. However, assessing the development of critical thinking in educational contexts presents unique challenges. In this study, a systematic mapping was carried out to investigate how to assess the development of critical thinking, or some of its skills, in K-12 computing teaching. The results indicate that primary studies on the development of critical thinking in K-12 computing education are concentrated in Asian countries, mainly focusing on teaching concepts such as algorithms and programming. Moreover, the studies do not present a fixed set of critical thinking skills assessed, and the skills are selected according to specific teaching and research needs. Most of the studies adopted student self-assessment using instruments that are well-known in the literature for assessing critical thinking. Many studies measured the quality of instruments for their research, obtaining favorable results and demonstrating consistency. However, the research points to a need for more diversity in assessment methods beyond student self-assessment. The findings suggest a need for more comprehensive and diverse critical thinking assessments in K-12 computing education, covering different educational stages and computing education concepts. This research aims to guide educators and researchers in developing more effective critical thinking assessments for K-12 computing education.
Prior programming knowledge of students has a major impact on introductory programming courses. Those with prior experience often seem to breeze through the course. Those without prior experience see others breeze through the course and disengage from the material or drop out. The purpose of this study is to demonstrate that novice student programming behavior can be modeled as a Markov process. The resulting transition matrix can then be used in machine learning algorithms to create clusters of similarly behaving students. We describe in detail the state machine used in the Markov process and how to compute the transition matrix. We compute the transition matrix for 665 students and cluster them using the k-means clustering algorithm. We choose the number of cluster to be three based on analysis of the dataset. We show that the created clusters have statistically different means for student prior knowledge in programming, when measured on a Likert scale of 1-5.
In today’s society, creativity plays a key role, emphasizing the importance of its development in K-12 education. Computing education may be an alternative for students to extend their creativity by solving problems and creating computational artifacts. Yet, there is little systematic evidence available to support this claim, also due to the lack of assessment models. This article presents SCORE, a model for the assessment of creativity in the context of computing education in K-12. Based on a mapping study, the model and a self-assessment questionnaire are systematically developed. The evaluation, based on 76 responses from K-12 students, indicates a high internal reliability (Cronbach’s alpha = 0.961) and confirmed the validity of the instrument suggesting only the exclusion of 3 items that do not seem to be measuring the concept. As such, the model represents a first step aiming at the systematic improvement of teaching creativity as part of computing education.
Programming is one of the basic subjects in most informatics, computer science mathematics and technical faculties' curricula. Integrated overview of the models for teaching programming, problems in teaching and suggested solutions were presented in this paper. Research covered current state of 1019 programming subjects in 715 study programmes at total of 218 faculties and 143 universities in 35 European countries that were analyzed. It was concluded that while most of the programmes highly support object-oriented paradigm of programming, introductory programming subjects are mainly based on imperative paradigm.
In this article we report about a study to assess Dutch teachers' Pedagogical Content Knowledge (\small PCK), with special focus on programming as a topic in secondary school Informatics education. For this research, we developed an online research instrument: the Online Teacher \small PCK Analyser (OTPA). The results show that Dutch teachers' \small PCK scores between low and medium. Also we enquired whether there is any relation between teachers' \small PCK and the textbooks they use by comparing the results of this study with those of a previous one in which the \small PCK of textbooks was assessed. The results show that there is no strong relation. Finally, we looked for trends between teachers' \small PCK and their educational backgrounds, as most of the Dutch teachers have a different background than Informatics. The results show that also in this case there is no strong relation.