Instructional methods in computing education judged by computer science teachers and educational experts

2018 ◽  
Vol 60 (2) ◽  
pp. 79-90
Author(s):  
Andreas Zendler

Abstract Answers to the questions of which instructional methods are suitable for school, what instructional methods should be applied in teaching individual subjects and how instructional methods support the act of learning represent challenges to general education and education in individual subjects. This article focuses on empirical examinations of instructional methods for computer science education supporting knowledge processes in the act of learning and their integration into the context of significant learning theories. The results of this article show that certain instructional methods are especially predestined for computer science education. They can also be attributed to behavioristic, cognitivist and constructivist learning theories; they are thereby localized and can profit from the empirical findings of the learning theories, especially in practical use on teaching computer science.

2022 ◽  
Vol 22 (1) ◽  
pp. 1-46
Author(s):  
Sarah Heckman ◽  
Jeffrey C. Carver ◽  
Mark Sherriff ◽  
Ahmed Al-zubidy

Context. Computing Education Research (CER) is critical to help the computing education community and policy makers support the increasing population of students who need to learn computing skills for future careers. For a community to systematically advance knowledge about a topic, the members must be able to understand published work thoroughly enough to perform replications, conduct meta-analyses, and build theories. There is a need to understand whether published research allows the CER community to systematically advance knowledge and build theories. Objectives. The goal of this study is to characterize the reporting of empiricism in Computing Education Research literature by identifying whether publications include content necessary for researchers to perform replications, meta-analyses, and theory building. We answer three research questions related to this goal: (RQ1) What percentage of papers in CER venues have some form of empirical evaluation? (RQ2) Of the papers that have empirical evaluation, what are the characteristics of the empirical evaluation? (RQ3) Of the papers that have empirical evaluation, do they follow norms (both for inclusion and for labeling of information needed for replication, meta-analysis, and, eventually, theory-building) for reporting empirical work? Methods. We conducted a systematic literature review of the 2014 and 2015 proceedings or issues of five CER venues: Technical Symposium on Computer Science Education (SIGCSE TS), International Symposium on Computing Education Research (ICER), Conference on Innovation and Technology in Computer Science Education (ITiCSE), ACM Transactions on Computing Education (TOCE), and Computer Science Education (CSE). We developed and applied the CER Empiricism Assessment Rubric to the 427 papers accepted and published at these venues over 2014 and 2015. Two people evaluated each paper using the Base Rubric for characterizing the paper. An individual person applied the other rubrics to characterize the norms of reporting, as appropriate for the paper type. Any discrepancies or questions were discussed between multiple reviewers to resolve. Results. We found that over 80% of papers accepted across all five venues had some form of empirical evaluation. Quantitative evaluation methods were the most frequently reported. Papers most frequently reported results on interventions around pedagogical techniques, curriculum, community, or tools. There was a split in papers that had some type of comparison between an intervention and some other dataset or baseline. Most papers reported related work, following the expectations for doing so in the SIGCSE and CER community. However, many papers were lacking properly reported research objectives, goals, research questions, or hypotheses; description of participants; study design; data collection; and threats to validity. These results align with prior surveys of the CER literature. Conclusions. CER authors are contributing empirical results to the literature; however, not all norms for reporting are met. We encourage authors to provide clear, labeled details about their work so readers can use the study methodologies and results for replications and meta-analyses. As our community grows, our reporting of CER should mature to help establish computing education theory to support the next generation of computing learners.


2015 ◽  
Vol 32 (4) ◽  
pp. 235-256 ◽  
Author(s):  
Andreas Zendler ◽  
O. William McClung ◽  
Dieter Klaudt

Purpose – The development of a K-12 computer science curriculum based on constructivist principles needs to be informed by knowledge of content and process concepts that are central to the discipline of computer science. The paper aims to discuss this issue. Design/methodology/approach – Taking a cross-cultural approach and using an experimental design (a SPF-2•15×16 split-plot design), this study compares the combinations of content and process concepts identified as important in Germany with those considered relevant in the US context. Findings – First, the combinations of content and process concepts identified in the German context can be generalized to the US context. Second, it is possible to identify combinations of content and process concepts in the US context that are also important in the German context. Third, content and process concepts identified in the two contexts can be integrated to generate a broader perspective that is valid for both contexts. Practical implications – The results can be used for consolidating available curricular drafts for computer science as a teaching subject at school of the type available in many. The present findings are of great relevance for research-based approaches to the pre- and in-service education of computer science teachers. The methodological approach taken is important in efforts to consolidate curricular models of computer science education, as have been initiated by the Bologna process in Europe and by the organizations Association for Computing Machinery, Association for Information Systems, and Institute of Electrical and Electronic Engineers-Computer Society in the USA. Originality/value – Results show that competence areas of central concepts identified in the two contexts can be integrated to generate a broader perspective that is valid for both contexts.


Author(s):  
J. Ángel Velázquez-Iturbide ◽  
Ouafae Debdi ◽  
Maximiliano Paredes-Velasco

Algorithmics is an important core subject matter in computer science education. In particular, optimization algorithms are some of the most difficult to master because their problem statement includes an additional property, namely optimality. The chapter contains a comprehensive survey of the teaching and learning through practice of optimization algorithms. In particular, three important issues are reviewed. Firstly, the authors review educational methods which partially or completely address optimization algorithms. Secondly, educational software systems are reviewed and classified according to technical and educational criteria. Thirdly, students' difficulties and misunderstandings regarding optimization algorithms are presented. The chapter intends to consolidate current knowledge about the education of this class of algorithms for both computer science teachers and computer science education researchers.


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