A New Informatics Curriculum for Secondary Education in The Netherlands

Bayram-Jacobs

Computer Science Education

et al. 2020

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Background and Context: Although context-based teaching and learning has been investigated extensively in science education, little is known regarding the use of contexts for teaching CS in secondary education. Objective: The aim of this study was to examine the characteristics of contexts suitable for teaching algorithms and to investigate teachers' considerations regarding those contexts. Method: This study examines teachers' practices and reasoning concerning the use of contexts and is based on explorative, empirical research. Data were collected through semi-structured interviews with seven CS teachers and analyzed qualitatively. Findings: The results of this study reveal several characteristics of effective contexts for teaching algorithms and show teachers' ambitions to address the variation within the student population when selecting contexts that advance students' algorithmic thinking. Implications: The found characteristics may serve as recommendation for designing contexts. Development of teacher education and professionalization activities may benefit from the discussion of teachers' motives and concerns.

Section: Educational Settingmentioning

confidence: 99%

“…In the recent Dutch CS curriculum reform, concepts were specified explicitly but contexts were described in a generic way only, to make the curriculum more sustainable (Barendsen et al, 2016). Consequently, the selection of up-to-date engaging contexts was left to the teachers.…”

Section: Introductionmentioning

confidence: 99%

Omnipresent yet elusive: Teachers’ views on contexts for teaching algorithms in secondary education

Bayram-Jacobs

Computer Science Education

et al. 2020

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“…because they were involved in the development of teaching materials. In the new curriculum, algorithms are mentioned as an explicit learning goal, both in the skills domain and in the knowledge domain (Barendsen et al, 2016). Students should learn problem-solving skills and find solutions in terms of algorithms and data.…”

Section: Participants and Contextmentioning

confidence: 99%

“…Computing at School Working Group, 2012;CSTA, 2017). Likewise, in the new CS curriculum in the Netherlands, launched in 2019, the topic of algorithms is much more prominent than it was previously (Barendsen et al, 2016). It is presumed that the focus in CS education should not be on students mastering a specific programming language but on the learning of fundamental concepts (such as algorithms) and problem-solving skills (Solomon, 2007).…”

Section: Introductionmentioning

confidence: 99%

Teaching algorithms in upper secondary education: a study of teachers’ pedagogical content knowledge

Bayram-Jacobs

Computer Science Education

et al. 2021

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Background and Context: Computing education is expanding, while the teaching of algorithms is less well studied. Objective: The aim of this study was to examine teachers' pedagogical content knowledge (PCK) for teaching algorithms. Method: We conducted semi-structured interviews with seven computer science (CS) teachers in upper secondary education (students aged 15-18). The data were analyzed qualitatively. Findings: We found two patterns of variation in teachers' PCK. First, we detected variation in the teachers' goals related to their view of algorithms: they either focused on "thinking" about the algorithm as an object, or focused on "thinking and making", where the algorithm is also regarded as a program. Second, we found variation in teachers' knowledge about responding to differences between students, which may be generic or topic-specific. Furthermore, our findings reveal that teachers consider class discussions to play a significant role as an instructional method for provoking reflection. Implications: Our findings regarding PCK may be beneficial for the development of teacher education and professionalization activities for CS teachers.

“…CS curricula in secondary education often involve the teaching of algorithmic problem-solving and standard (or 'classic') algorithms (e.g., CSTA, 2017; Barendsen et al, 2016). To be able to apply this knowledge when solving new problems, students are required to recognize the underlying algorithmic concepts in a new problem.…”

Section: Introductionmentioning

confidence: 99%

Recognizing Algorithmic Concepts in New Contexts: An Analysis of Students’ Reasoning

Bayram-Jacobs²,

Informatics in Education

et al. 2021

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Teaching algorithmic thinking enables students to use their knowledge in various contexts to reuse existing solutions to algorithmic problems. The aim of this study is to examine how students recognize which algorithmic concepts can be used in a new situation. We developed a card sorting task and investigated the ways in which secondary school students arranged algorithmic problems (Bebras tasks) into groups using algorithm as a criterion. Furthermore, we examined the students' explanations for their groupings. The results of this qualitative study indicate that students may recognize underlying algorithmic concepts directly or by identifying similarities with a previously solved problem; however, the direct recognition was more successful. Our findings also include the factors that play a role in students' recognition of algorithmic concepts, such as the degree of similarity to problems discussed during lessons. Our study highlights the significance of teaching students how to recognize the structure of algorithmic problems.