Teaching algorithms and algorithmic thinking using a context-based approach.
Algorithms and algorithmic thinking are at the core of computer science. Studying this topic encompasses both the finding of a solution for algorithmic problems and the analysis of algorithms, including their properties like correctness and efficiency. Teaching students to analyse algorithms is perceived as problematic, it seems abstract and irrelevant. In science education, context-based learning environments have been developed in the last three decades, where realistic contexts are used as a starting point for learning science, giving significance and meaning to the content. This approach is promising for teaching fundamental concepts in computer science, giving significance and meaning to abstract concepts.
The purpose of this research is to identify characteristics of teaching and learning the topic of algorithms and algorithmic thinking when using a context-based learning environment.
The first study is set up to determine what characteristic teachers distinguish regarding teaching algorithms and algorithmic thinkind and regarding context-based teaching. The study will start with an empirical orientation by researching the pedagogical knowledge of teachers in Dutch secondary education.
The basis of the second study is a context-based learning environment for teaching algorithms and algorithmic thinking, which is developed in accordance with the outcomes of the first study. After teaching with this material, students will be interviewed using a think aloud procedure, to determine how students apply knowledge about concepts in a different context (transfer of knowledge). Results of this study will give insight into aspects of learning related to context-based teaching of algorithms and algorithmic thinking.
During the third study, different contexts for teaching algorithms and algorithmic thinking will be developed in collaboration with students. This study will result in design principles for the use of contexts, specifically attending to all students, with different interest and prior experience and knowledge. In addition, it will provide insight in the collaborative design process, student’s experience of the collaborative design process and the perceived effects on their algorithmic thinking.
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