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.
While researchers working within the Student Learning Research framework have developed or adapted questionnaires to gather information on students' experiences of blended learning, no questionnaire has been developed to enquire about teachers' experiences in such learning environments. The present article reports the development and testing of a novel questionnaire on `approaches to e-teaching', which may be employed to investigate the experience of teaching when e-learning is involved. Results showed suitable reliability and validity. Also, when exploring associations between the novel questionnaire scales and those of the well-known `approaches to teaching' inventory (Prosser and Trigwell, 2006), results from correlation and cluster analyses suggest that student-focused approaches to teaching are needed for significant use of digital technology to emerge. For practice, this relevant outcome implies that teaching needs to be considered holistically when supporting teachers to incorporate e-learning in their practice: because it seems they approach online teaching coherently with the face-to-face side of the blended experience.
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.