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检索条件"主题词=Programming competence"

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Variables Affecting Students' Success in CS2 2023

Variables Affecting Students' Success in CS2

引用

28th Annual Conference on Innovation and Technology in Computer Science Education (ITiCSE)

作者： Bjorn, Camilla Kann, Viggo KTH Royal Inst Technol Stockholm Sweden

ISBN: (纸本)9798400701382

When trying to understand student success in computer science, much of the attention has been focused on CS1, leaving followup courses such as CS2 less researched. Prior studies of CS2 have often taken a deductive approach by focusing on predetermined variables such as CS1 grades, the impact of different paths from CS1 to CS2, gender and race. Although this has resulted in a better insight into these variables, we wonder if there might be another way of viewing which variables affect the students' success in the course. We have therefore chosen an inductive approach to better understand what these variables might be and how they interplay. This was done by analysing 16 semi-structured interviews with students enrolled in CS2 who have another speciality than computer science. The interviews focused mainly on the students' methods for succeeding in the course, experiences of the course and programming background. Through a thematic analysis of the interviews, we found the following five main success variables for CS2: programming competence, computer literacy, opportunity to receive help, ability to help oneself and teaching. These variables can in several cases be related to the ones previously addressed, however, they can also offer a different perspective on student success in the course.

关键词： Student Performance CS2 programming competence Computer Literacy Help

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Towards Deriving programming Competencies from Student Errors 4

Towards Deriving Programming Competencies from Student Error...

引用

4th International Conference on Learning and Teaching in Computing and Engineering (LaTICE)

作者： Berges, Marc Striewe, Michael Shah, Philipp Goedicke, Michael Hubwieser, Peter Tech Univ Munich TUM Sch Educ Arcisstr 21 D-80333 Munich Germany Univ Duisburg Essen Ruhr Inst Software Technol Gerlingstr 16 D-45127 Essen Germany

ISBN: (纸本)9781509025046

Learning outcomes are more and more defined and measured in terms of competencies. Many research projects are conducted that investigate combinations of knowledge and skills that students might learn. Yet, it is also promising to analyze what students might fail to learn, which provides information about the absence of certain competencies. For this purpose, we are evaluating the outcomes of automatic assessment tools that provide automatic feedback to the participating students. In particular, we analyzed the errors of the students that participated in an introductory programming course. The 604 students participating in the course had to solve six tasks during the semester, resulting in a total of 12274 submissions. The error analysis is done by evaluating the data from the automatic assessment tool JACK, which provides automatic feedback on programming tasks. To derive information about prospective competencies, we conducted a qualitative analysis of the different errors the students made in their solutions. The results provide interesting insights into missing competencies. In further research our findings have to be validated by investigating the cognitive processes involved during programming.

关键词： Electronic assessment programming competence programming errors Qualitative text analysis

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Towards a competence Model for the Novice Programmer Using Bloom's Revised Taxonomy - An Empirical Approach 20

Towards a Competence Model for the Novice Programmer Using B...

引用

25th Conference on Innovation and Technology in Computer Science Education

作者： Kiesler, Natalie Goethe Univ Acad Educ Res & Teacher Educ Frankfurt Germany

ISBN: (纸本)9781450368742

Thiswork addresses the demand of an empirically developed competence model for programming as challenging core tier of computer science curricula. The presented paper investigates the application of Bloom's revised taxonomy for learning, teaching and assessing by Anderson and Krathwohl for the specification of currently used learning objectives in programming education. Accordingly, 129 module descriptions of beginner level programming courses from 35 German universities constitute the sample. Learning goals are evaluated using Mayring's qualitative content analysis. In addition, seven guided interviews with computer science professors as experts are categorized according to Mayring's qualitative analysis method. As a result, a model comprised of deductively-inductively built cognitive categories is proposed, proving the adequacy of Bloom's revised taxonomy for computer science and programming in particular. The categories depict current operationalized learning objectives and cognitive competencies of novice programmers, as well as additional non-cognitive competencies. Thus, the results can help classify competency levels and support the didactic design of introductory programming classes and assessment. This research also constitutes a basis for the development of a measuring instrument of programming competence in the future.

关键词： competence model programming competence Bloom's revised taxonomy qualitative content analysis

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