Recently, computational thinking has attracted much research attention, especially within primary and secondary education settings. However, incorporating computational thinking (CT) in mathematics or other disciplines is not a straightforward process and introduces many challenges concerning the way disciplines are organised and taught in school. The aim of this paper is to identify what characterises CT in mathematics education and which CT aspects can be addressed within mathematics education. First, we present a systematic literature review that identifies characteristics of computational thinking that have been explored in mathematics education research. Second, we present the results of a Delphi study conducted to capture the collective opinion of 25 experts in both the fields of mathematics education and computer science regarding the opportunities for addressing computational thinking in mathematics education. The results of the Delphi study, which corroborate the findings of the literature review, highlight three important aspects of computational thinking to be addressed in mathematics education: problem solving, cognitive processes, and transposition.
Automating software testing activities can increase the quality and drastically decrease the cost of software development. Towards this direction various automated test data generation tools have been developed. The majority of them aim at branch testing, while a quite limited number aim at a higher level of testing thoroughness such as mutation. In this paper an automated framework that makes a joint use of diverse techniques and tools is introduced in the context of automating mutation based test generation. The motivation behind this work is the use of existing techniques and tools such as symbolic execution and evolutionary testing towards automating the test input generation activity according to the weak mutation testing criterion. The proposed framework integrates existing automated tools for branch testing in order to effectively generate mutation test data. To fulfill this suggestion three automated tools are used for illustration purposes and preliminary results are obtained by applying the proposed framework to a set of java program units indicating the applicability and effectiveness of the proposed approach.
Background and Context: With computing now becoming a mandatory subject in school in many countries, there is a need for clearly defined pedagogical strategies to support all learners; this is particularly pertinent when teaching computer programming, which novice adults have struggled with for decades. Vygotsky's sociocultural theory emphasises the importance of language, mediation, and the transfer of skills and knowledge from the social into the cognitive plane. This perspective has influenced the development of PRIMM (Predict, Run, Investigate, Modify, Make), a structured approach to teaching programming. Objective: The objective of the study was to find out if using PRIMM to teach programming had an impact on learner attainment in secondary school, and the extent to which it was a valuable method for teachers. Method: We evaluated the use of PRIMM in 13 schools with 493 students aged 11-14 alongside a control group, using a mixed-methods approach. Teachers delivered programming lessons using the PRIMM approach for 8-12 weeks. Data were collected via a combination of a baseline test, a post-test to compare control and experimental groups, and teacher interviews. Findings: Learners who participated in the PRIMM lessons performed better in the post test than the control group. Teachers reported several benefits of the PRIMM approach, including that PRIMM helped them to teach effectively in mixed-ability classes, enabling all learners to make progress. Implications: We hope that PRIMM makes a contribution to programming education research, as it builds on previous work in effective pedagogy for teachers, and encourages the use of language and dialogue to facilitate understanding. Through our evaluation of PRIMM and engagement with classroom teachers, we propose a framework for understanding the learning of programming in the classroom, and present this as an avenue for further research.
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