Computer science education should not be based on short-term developments but on content that is observable in multiple domains of computer science, may be taught at every intellectual level, will be relevant in the longer term, and is related to everyday language and/or thinking. Recently, a catalogue of central concepts for computer science education such as algorithm, computer, and data has been empirically determined. This paper now concentrates on central processes relevant for computer science education. Experts of computer science rated 44 general-education processes regarding four criteria. By using a cluster analysis approach the following central processes for computer science education have been identified: problem solving and problem posing, analyzing, generalizing, finding relationships, classifying, and investigating.

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The authors discuss empirically determined competence areas to K-12 computer science education, emphasizing the cognitive level of competence. The results of a questionnaire with 120 professors of computer science serve as a database. By using multi-dimensional scaling and cluster analysis, four competence areas to computer science education characterized by the degree of process-related coverage and educational accessibility can be defined: Information technology, computer communication and cooperation, model building, and software engineering. These competence areas consist of central content concepts of computer science (e.g., algorithm, system, and process) combined with central process concepts of computer science (e.g., analyzing, classifying, problem solving, and posing).

This study contributes on instructional methods from a validation technical point of view. The focus is on the assessment of instructional methods in relation to knowledge processes in the act of learning. By using questionnaires, computer science teachers, mathematics teachers, and English teachers assessed 20 instructional methods in terms of knowledge processes (build, process, apply, transfer, evaluate, and integrate). The findings show that computer science teachers and mathematics teachers differ compared to English teachers on the assessment of instructional methods with respect to knowledge processes. The findings represent important contributions for teacher education programs and theory construction concerning effectiveness of instructional methods.

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