Maria Knobelsdorf, University of Dortmund, Germany - Didaktik der ...

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Some teachers would use applets or software to do a simulation of a network or to show the pathway of the data through the Internet. Others would use films as a kind of visualization. Some would use newspaper articles to describe a problem that could then be handled in class. Worksheets are also popular materials. 4.7 Integrating Students’ Perspectives Most teachers agreed that students’ perspectives are important in planning the lessons. Only a few said that students’ perspectives are not relevant. They are convinced that students are not interested in finding out how the Internet works. One teacher compared the students with fish which do not need to know what water is. Those teachers who agree that students’ perspectives have to be taken into account, claim to observe students’ perspectives during classes and to take them into consideration. About half of the teachers said that the lessons they plan would change the students’ conceptions of the Internet. We also asked teachers to describe their students’ conceptions of the Internet. Teachers think that students imagine the Internet... • to be like a Super-Computer. • to be like a cloud that surrounds the whole world, and you can connect everywhere with this cloud. • to be like a cupboard filled with information • to consist of unstructured connections between the computer to have something like rays to a radio tower or a satellite • to function like a phone call 5. CONCLUSIONS AND FUTURE WORK In the previous chapter we discussed the different teaching methods and learning objectives which we discovered in our survey. These answers only refer to that part of the interviews dealing with the question of the planning of lessons on the topic of networks and the Internet. An interesting result is that most teachers think that networks and the Internet is an important topic to teach, but for various reasons they do not do it. One widespread reason seems to be the problem of not having enough content knowledge about this topic. This problem can fortunately be solved easily by developing teacher training courses. An obvious result is that teachers have a clear idea on how to plan lessons, although they feel a lack of knowledge about this topic. Their pedagogical knowhow seems to help them in overcoming this lack of knowledge. This might be important in developing teacher training. It shows that teachers rather need training on content knowledge than on pedagogical knowhow. An astonishing result for us was the fact that in CS it seems to be usual that students were allowed to choose the topics they wanted to learn. This can probably be explained by the lack of generally accepted standards and by the teachers’ insufficient confidence in their own knowledge. But some teachers also mentioned that they thought their students might know more about CS than they did themselves and that might explain why students were allowed to make decisions on the content of their lessons. 78 Contrary to our expectation teachers claim to include students’ perspectives in planning lessons. It is not unlikely that they may just have given the expected answer. Another explanation is a presentation about students’ perspectives that some of the teachers of our sample attended. The different ways of planning lessons we discussed have an internal structure, a kind of a pattern which expands over the other topics taught by the teachers. These patterns are formed by the subjective theories of teachers on planning CS lessons. Therefore our next step will be to discover the types of planning CS lessons, based on this subjective theories. These types of planning lessons determine not only the topic networks and the Internet but any kind of lesson planning. By using these types, our final objective is the development of guidelines for teacher training. We do not only want to show in which different ways teachers plan their lessons but also how to include this knowledge into teacher trainingfor the benefit of all teachers. Therefore, the differing ways of planning presented here are a big step towards this goal. 6. REFERENCES [1] P. Denning. Great principles of computing. Communications of the ACM, 46(11):15–20, November 2003. [2] I. Diethelm and S. Zumbrägel. An investigation of secondary school students’ conceptions on how the internet works. In Proceedings of the 12th Koli Calling International Conference on Computing Education Research, Koli, Finland, 2012. (accepted). [3] Gesellschaft für Informatik (GI) e. V. Grundsätze und Standards für die Informatik in der Schule. Number 28,150/151 in LOG IN. Berlin, 2008. [4] N. Groeben, D. Wahl, J. Schlee, and B. Scheele. Forschungsprogramm Subjektive Theorien. Eine Einführung in die Psychologie des reflexiven Subjekts. A. Francke Verlag, Tübingen, 1988. [5] G. A. Kelly. The psychology of personal constructs. Routledge, London, 1991. [6] M. Komorek and U. Kattmann. The model of educational reconstruction. In S. Mikelskis-Seifert, U. Ringelband, and M. B. (Eds.), editors, Four Decades of Research in Science Education - from Curriculum Development to Quality Improvement, chapter 7, pages 171–188. Waxmann, 2008. [7] P. Mayring. Qualitative content analysis. Forum Qualitative Sozialforschung / Forum: Qualitative Social Research, 1(2):10, 2000. [8] Medienpädagogischer Forschungsverbund Südwest. JIM 2010 Jugend, Information, (Multi-)Media. Forschungsberichte. Baden-Baden, 2010. [9] A.-M. Mesaros and I. Diethelm. Exploring computer science teachers’ subjective theories on designing their lessons. In Proceedings of the 5th International Conference on Informatics in Schools: Situation, Evolution and Perspectives ISSEP, Selected Papers, Bratislava, Slovenia, 2011.
Promoting Computational Thinking with Programming Cynthia C. Selby University of Southampton Highfield Southampton UK 44 (0) 2380 593475 ABSTRACT The term computational thinking has received some discussion in the field of computer science education research. The term is defined as the concept of thinking about problems in a way that can be implemented in a computing device. Of course, after having thought about a problem using computational thinking skills, the next step should be to use programming skills to implement the solution. This work in progress is exploring ways in which programming can be employed as a tool to teach computational thinking and problem solving. Data is collected from teachers, academics, and professionals from various industries. They are purposively selected because of their knowledge of or interest in the topics of problem solving, computational thinking, and the teaching of programming. This data is analyzed within the paradigm of the grounded theory approach. The results of an initial analysis imply an ordering of complexity associated with computational thinking skills, imply connections between computational thinking skills and programming activities, and imply a relationship between computational thinking skills and other taxonomies of learning. Categories and Subject Descriptors K.3.2 [Computers and Education]: Computers and Education, Curriculum General Terms Design, Experimentation, Theory Keywords Computational thinking, pedagogy of programming, problem solving 1. INTRODUCTION Problem solving skills are used in developing or implementing strategies to solve problems in many domains. These skills are often expressed as heuristics [12], appropriate and plausible approaches to a problem. Effective problem solving has been promoted by the use of strategies including means-ends analysis, schema acquisition, algorithmic approaches, and targeted frameworks [19, 12, 9]. C.Selby@soton.ac.uk 79 However, in the domain of computer science, some research [11] has found that learners do not naturally solve problems in ways that can be translated to computing devices by the use of programming. This disparity is highlighted in the Lister study [6], where it is suggested that ineffective problem solving skills, including the ability to work through lines of logic, may be the cause of ineffective programming skills. Additional studies [15, 13] suggest that problems in learning to program are exacerbated by a lack of strategic tools. The strategic tools, identified as useful for those attempting to solve problems with the aid of computational devices in various domains, include, but are not limited to, decomposition, abstraction, simulation, and generalization [10]. The name given to these specialized mental skills, resulting in solutions to problems directly translatable to a computing device, is computational thinking [21]. Actually implementing these solutions requires a different set of skills. Programming skills are the specific technical skills needed to produce specific solutions using a set of defined digital tools, often associated with a programming language [9]. Research often reports that learners struggle with programming skills such as tracing [3, 6] and understanding a model of the machine [2, 9]. Having recognized this issue, other researchers [7, 20] highlight the need for a defined hierarchy of programming skills. One study [16] attempted to provide such a hierarchy for objectoriented programming. The researchers found that teachers interpreted the hierarchy as a capability hierarchy. Given that a hierarchy of generic programming skills could be developed and interpreted as capability, the levels could be aligned with existing hierarchies, such as the cognitive domain of Bloom’s Taxonomy. These same programming skills could be mapped to the higher-level computational thinking skills that they evidence, thereby defining a hierarchy of computational thinking skills. This setting provides the context for an ongoing investigation into the relationship between the teaching of programming and its effect on the acquisition of computational thinking skills by learners. 2. STUDY METHOD This study is based on a grounded theory approach employing qualitative data collection methods and qualitative data analysis techniques. The first activity is the administration of an Internet based questionnaire. The second activity is the collection of data from an Internet based community of practice forum. The third activity is the administration of a face-to-face, audio recorded, semi-structured interview schedule for respondents previously identified by an analysis of the questionnaire results and community of practice discussions. All data is iteratively augmented and analyzed guided by Strauss and Corbin’s [18] grounded theory procedures and techniques until theoretical
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Fakultät für Mathematik, Informat
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Program Committee Michal Armoni Wei
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Challenge and Creativity: Students
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Challenges in Computer Science Educ
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These echo a 2008 report from the N
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examples, and in practice teachers
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Figure 3: A trace of bubble sort fr
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either their own program or another
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ital system used a variety of inter
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computer science, and with the less
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effect of different factors on the
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(GE) and freshmen CS and Lyceum (GR
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Performance Expectancy (PE) Satisfa
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We have learnt that we can both loo
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Comparing CSTA K-12 Computer Scienc
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grade 4, 5, 6 or 8, depending on ch
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Table 1. Scoring Scale for the Impl
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the highest rate of implementation
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Information Theory on Czech Grammar
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of information in a message M, repr
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Data modeling and database systems
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the knowledge about ICT and CS (see
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The Mindstorm Effect: A Gender Anal
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Exploring the processing of formatt
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Teachersʼ Perceptions Of The Value
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Technocamps: Bringing Computer Scie
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Abenteuer Informatik - Hands-on exh
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Gaming and Mathematics: A Cross Cur
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Turi: Chatbot software for schools
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ABSTRACT Learning Fields in Vocatio
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ABSTRACT This study examines the po
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