- Didactics of Informatics
Didactics of computer science (didactics of informatics) is a sub-field of
computer science( informatics). Since 1960 experts of higher education, the pioneers of didactics of computer science, are developing guidelines and curricula recommendations. Ten years later computer science has been a subject of secondary education. Didactics of computer science became also a study subject of teacher education of computer science (informatics).
At present, the educational aims of the subject computer science at schools are completely changing from programming of small imperative solutions to modelling, construction and deconstruction of complex and object oriented systems of computer science. But there is a big gap between the didactic needs and the published research results in this field, e. g., the educational value of computer science, fundamental ideas of computer science, didactic systems of computer science, understanding of computer science systems, educational standards of computer science, international curricula.
Didactics of computer science has to provide successful research results to support comprehension and design of computer science systems and to implement such new methods of learning and teaching on secondary and higher education. This sub-field focuses on cognitive approaches of developing competencies of computer science and specific strategies for analysis, design, implementation and evaluation of excellent lessons in computer science.
The educational value of computer science
The educational value of informatics established a new civilization technology. The composition of the teaching-and-learning-processes for acquiring the informatics civilization technology is known, since the contribution of informatics to general education was analysed very profoundly. Schwill deduced the fundamental ideas of computer science, e. g., algorithmizing, structured decomposition, language, according to pedagogical criteria. Wirth (
Niklaus Wirth) emphasized the educational value of programming with the construction of abstract machines. Computer science, formal science as well as engineering science, have become a basic science of social development. It features and methods for modelling, abstraction, and construction. However, this is not the only reason for its outstanding position in the canon of science. It is its tendency of affecting other fields of science, which makes computer science so unique and important for general education. Yet, it is not about the use of instruments, i. e. computer science systems, in the first place.
For general education the helical development below, which was observed in different sciences under the influence of computer science, is interesting:
* First there are exercises, which are solved completely intuitively, i. e., heuristically.
* On comprehending the problems a secured theoretical environment is created. This leads to computer science modelling for sub-problems.
* From this new heuristics are derived on a higher level.
This way the intellectual techniques of computer science both change research and lecture in other subjects, including pedagogics, and support meta-knowledge in order to master complexity. Thus the educational value of computer science may be found in the importance of computer science structuring as a method of cognition within other sciences even apart from computer science systems.
Fundamental ideas of computer science
"A fundamental idea of computer science is a schema for thinking, acting, describing or explainingwhich satisfies four criteria:
The Horizontal Criterion. A fundamental idea is applicable or observable in multiple ways and indifferent areas of computer science and organizes and integrates a wealth of phenomena.We call this property the Horizontal Criterion, since the idea may be considered as a horizontal line intersecting a large number of fields where it applies.
The Vertical Criterion. A fundamental idea may be taught on every intellectual level.Bruner (1960) (
Jerome Bruner) said that "any subject can be taught effectively in some intellectually honest form to any child at any stage of development". This suggests that a fundamental idea organizes the topics of a field also in a vertical dimension: An idea can be taught on the primary school level as well as on the university level. Presentations differ only by level of detail and formalization. Thus, an idea can serve as a guideline for lessons on every level of the entire educational process and ideas can berevisited periodically in greater depth and complexity (so-called spiral principle).
The Criterion of Time. A fundamental idea can be clearly observed in the historical development ofcomputer science and will be relevant in the long run. This aspect is important for two reasons. First, it gives a clue as to how to find fundamental ideas: Scientific notions, concepts or structures of computer science that have a definite historical background are more likely fundamental ideas than are recent developments. Second, lessons based on fundamental ideas will not become antiquated as quickly as conventional lessons - a major advantage in teaching computer science given its dynamic evolution.
The Criterion of Sense. A fundamental idea also has meaning in everyday life and is related toordinary language and thinking - its context being pretheoretical and unscientific.Only a precise definition turns an idea "with sense" into an exact notion "without sense". Forexample, consider "reversibility" as an idea "with sense" and "inverse function" as a purelymathematical formalization of it "without sense". While we can see examples of reversibility inmany everyday situations - do vs. undo - the term "inverse function" has no everyday meaning.From the pedagogical point of view this criterion is closely linked to the Vertical Criterion. Whenever we have to teach a fundamental idea on a low intellectual level, i. e. we have to give students a first vague impression of the idea, we may begin with those situations in everyday life where a fundamental idea becomes apparent.
We have tried to determine fundamental ideas by abstracting from the contents of computer science to its ideas in three steps:
(1) Analysis of the concrete activities of computerscience and their relationships and analogies. Since a central purpose of computer science is toinvestigate the
softwaredevelopment process in its broadest sense and to provide methods for it, itseemed reasonable to first analyze for fundamental ideas the concrete activities during this processand then to establish relationships and analogies to the field of computer science in general;
(2) Revision and improvement of the results obtained in step 1 by checking whether each idea satisfies the four criteria for fundamental ideas;
(3) Structuring the collection of ideas according to their relevance in computer science.
There are three fundamental ideas that dominate all stages of software development as well as all activities in computer science" [Andreas Schwill, 1997, pp. 286-287] :
* Algorithmizing (
* Structured Decomposition,
* Language (
Didactic systems of computer science
On the World Conference on Computers in Education (WCCE) 2001 of the
International Federation for Information Processing(IFIP) Brinda and Schubert presented a new concept called "didactic systems of computer science" [Torsten Brinda and Sigrid Schubert, 2001] , which influenced in the following years the discussion of educational standards of secondary computer science education and the interface to higher education. The idea of the concept of didactic systems is to make a collection of coordinated teaching-and-learning-materials available, which may lead to different skills very flexibly according to the respective target group.
This representation of computer science knowledge simplifies the communication concerning the state of the didactics of computer science as well as the educational results. Components of such a didactic system are:
* Knowledge structures (KS), i. e., graphs as descriptional structures for knowledge of the subject,
* Exercise classes (EC) with exemplary solutions,
* Exploration modules (EM) and systems.The graphs (
graph (data structure)) show elements of computer science education, which may be measured and evaluated by the means of learning success check-ups. For students their level of education, which they have reached, becomes more concrete.
The complexity of the exercise classes and graphs chosen is well comparable through defined educational standards. But computer science was not involved in the
Programme for International Student Assessment(PISA). So the research community of didactics of computer science needs to connect their activities in another way. The design of PISA studies is appropriate for computer science education because a core curriculum is not necessary and all knowledge sources were treated on an equal basis.
Understanding of computer science systems
"In an education model for understanding of computer science systems, systematic exploration and evaluation of a computer science system is central. Application of selected examples of the learning software [http://www.die.informatik.uni-siegen.de/pgpatternpark "Pattern Park"] focussed on combining real-world example and internal structure. However, the analysis of the case study including the final test has shown that these domains have to be refined. In particular, the experiment to investigate the behaviour of a computer science system was very difficult for students. Evaluation of work sheets with topics queue (
queue (data structure)) and iteration(SA,1) has shown that they were hardly able to formulate adequate hypotheses, which is a prerequisite to conduct a computer science experiment. To describe exercises, we therefore propose the following more fine grained distinction between the domains:
SA. Observable behaviour
Behaviour of a computer science system can be investigated by observation and in computer science experiments. Therefore, hypotheses have to be proved in experiments. Students apply a concrete computer science system, e. g., running a
softwareapplication that implements and illustrates fundamental ideas of computer science by its behaviour. Experiments are repeatable. Animations of behaviour can be provided by learning software. Exercises can also be applied to sensitize students to unexpected behaviour. Subcategories comprise requirements analysis, and description of use cases.
SAB. Combination of behaviour and internal structure
Learners describe the observed behaviour during an experiment by
functional models. During the learning process, one task was: 'Given definition and structure of queue (data structure)on the one hand, and the structure of the combination of Iterator ( Iterator pattern) and queue ( queue (data structure)) on the other hand, which behaviour would arise during the use of softwarebased on both, respectively?' fundamental ideas, necessary concepts, and design problems are identified and represented externally to visualize their structure. The learners are able to explain, why a certain internal structure has been chosen with respect to the intended behaviour of the computer science system.
SAC. Combination of behaviour and construction of a concrete realization
By systematic testing, behaviour of a computer science system can be investigated. Test data corresponds to the behaviour, whereas checkpoints have to be set in the source code. During the learning process, one task was: 'Change the
algorithmof the Iterator pattern. Classify the behaviour of the system by the order of the resulting sequence of patients in the queue, i. e., the same order means that the results belong to the same equivalence class.'
SB. Internal structure
In general, the internal structure is only known by developers but not by users. It can be investigated rather through analysis of the components than through experiments. Learners apply different diagrams, e. g., class, object, state, and
sequence diagramsto visualize the internal structure. It is necessary to consider dynamic and static representations. Design patternsas solutions to previously identified problems can be applied and connected.
SBC. Combination of internal structure and construction of a concrete realization
Structuring of implementation details is necessary in order to make a specification. Such structuring elements are below the abstraction of
design patterns, e. g., idioms depend on a concrete programming languagebut have a predefined structure.
Construction of a concrete realization needs programming skills and specific knowledge depending on a
programming language. Studies show that learners often fail to construct and design programs ( computer program) even if they know essential programming concepts, because they do not see the whole picture. They fail to network the concepts. Implementation details support advanced understanding of computer science systems, but for general education we will not focus on this aspect.
These exercise classes bring together different views on computer science systems to form the whole picture. Students construct their knowledge and need to prove their cognitive model by matching these views. In particular, misconceptions can be reduced in the learning process because students learn to transfer their knowledge. To achieve basic competencies, it is not sensible to regard every combination of views. In particular, we do not need the categories SC and SBC, because the focus is on general education, not
programming. Instead, we want to demystify behaviour of computer science systems, thus, the categories SA, SAB, and SAC are mandatory. We will include SB, because describing static and dynamic processes is needed in general education." [Peer Stechert and Sigrid Schubert, 2007]
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Educational standards of computer science
There are recommendations, curricula , and demanding tuitional concepts concerning informatics education, however no approved and empirically verified educational standards. Thus a wide spectrum of the students’ learning success exists. There is a tendency towards internationally harmonized test methods for the educational results within subject groups [DdI, 2004] . For the time being such comparative data is missing for computer science class, although it is offered in secondary schools and there chosen by students around the world. For the preparation of educational standards within computer science education comparable teaching-and-learning-materials are necessary. Respectively two accesses are introduced, fundamental ideas [Andreas Schwill, 1997] and didactic systems [Torsten Brinda and Sigrid Schubert, 2001] . Referring to the fundamental ideas the scientific choice is justified, while the didactic systems are used to back up its didactic communication and realization in class.
International Curricula of computer science
Information and communication technology in secondary education – a curriculum for schools
UNESCOand International Federation for Information Processing(IFIP) Curriculum computer science technology (IT) is defined as 'The technological applications (artefacts) of computer science in society' [UNESCO and IFIP, 2002, p. 9] . ICT is IT combined with other technologies, specifically communication technology. Therefore, ICT primarily regards computer science systems from an application oriented, i. e., user-oriented, point of view.
UNESCOand IFIP Curriculum there are four stages of teaching and learning:
* The first stage is called 'ICT Literacy'. The primary objective is to discover ICT tools.
* The second stage is called 'Application of ICT in subject areas', i. e., learning how to use ICT tools.
* The third stage is called 'Infusing ICT across the curriculum' and addresses the understanding how and when to use ICT tools.
* And the last stage is 'ICT specialization' in which specialization refers to the use of ICT tools.
Within stage one there is a module called information and communication (A7) and a module called social and ethical issues (A8) which refer directly to the objectives and subject matters as mentioned above. Within stage two and three the computer science system is not centric but subject matters of mathematics etc. or a project topic. There are computer science concepts within stage four but without direct references to the computer science system Internet." [Stefan Freischlad, 2006]
A model curriculum for K–12 computer science
Association for Computing Machinery(ACM) curriculum proposes a dissection of computer science education into four Levels. Level I must provide learners with basics of computer science. It is recommended to integrate this part into other subjects. It ends at grade 8. Level II should be integrated into grade 9 or 10. It is called 'Computer science in the modern world'. The overarching goal is to prepare students to master computer science from the user's point of view rather than from the designer's. It is considered as the last mandatory course and, therefore, the last chance for a majority of students to attain necessary knowledge and abilities. The objective of Level II is to provide all students with an introduction to the principles of computer science. Furthermore, it should provide learners with the ability to apply a computer in their life. The course must provide learners with minimum standards of competences. ACM proposes to implement Level III 'Computer science as analysis and design' as an elective course. The studies of Level II will be continued. 'It places particular emphasis on the scientific and engineering aspects of computer science' [ACM, 2006, p. 11] . Level IV provides depth of study in one particular area of computer science." [Stefan Freischlad, 2006]
* [ACM, 2006] Association for Computing Machinery: " [http://csta.acm.org/Curriculum/sub/k12final1022.pdf A Model Curriculum for K–12 Computer Science] ", Final Report of the ACM K–12 Task Force Curriculum Committee, Second Edition, New York, 2006.
* [Medichi, 2007] László Böszörményi (ed.): Medichi 2007 – Methodic and Didactic Challenges of the History of Informatics. ISBN 978-3-85403-220-5, 2007.
* [Torsten Brinda, 2007] Torsten Brinda: Development of the exercise culture in informatics. In: Benzie, D.; Iding, M. (eds.): Proceedings of IFIP-Conference on "Informatics, Mathematics and ICT: A golden triangle", June 27-29, 2007, Boston, USA, ISBN 13: 978-0-615-14623-2.
* [Torsten Brinda and Sigrid Schubert, 2001] Torsten Brinda and Sigrid Schubert: Didactic System for Object-oriented Modelling. In: Watson, D.; Andersen, J. (eds.): Networking the Learner. Computers in Education. Kluwer, Boston, 2002, pp. 473–482, ISBN 1-4020-7133-7.
* [DdI, 2004] Dagstuhl-Seminar "Concepts of Empirical Research and Standardisation of Measurement in the Area of Didactics of Informatics" 9/2004: " [http://ddi.uni-paderborn.de/gi/materialien.html#c7314] ", 2004.
* [Kathi Fisler, 2007] Kathi Fisler: Teaching problem solving through programming: why it fails and how we are fixing it. In: Benzie, D.; Iding, M. (eds.): Proceedings of IFIP-Conference on "Informatics, Mathematics and ICT: A golden triangle", June 27-29, 2007, Boston, USA, ISBN 13: 978-0-615-14623-2.
* [Stefan Freischlad, 2006] Stefan Freischlad: " [http://www.die.informatik.uni-siegen.de/DIE_BIB/Forschung/Publikationen/2006/learning_media_competences_in_informatics.pdf Learning Media Competences in Informatics] ", In: Proceedings of Second International Conference on "Informatics in Secondary Schools. Evolution and Perspectives - ISSEP", November 7-11, 2006 Vilnius, Lithuania, pp. 591-599, ISBN 9955-680-47-4.
* [Nataša Grgurina and Jos Tolboom, 2007] Nataša Grgurina and Jos Tolboom: The Dutch secondary school informatics curriculum - another "polder model," broad in scope, but not too deep?. In: Benzie, D.; Iding, M. (eds.): Proceedings of IFIP-Conference on "Informatics, Mathematics and ICT: A golden triangle", June 27-29, 2007, Boston, USA, ISBN 13: 978-0-615-14623-2.
* [Peter Hubwieser, 2007] Peter Hubwieser: A smooth way towards object oriented programming in secondary schools. In: Benzie, D.; Iding, M. (eds.): Proceedings of IFIP-Conference on "Informatics, Mathematics and ICT: A golden triangle", June 27-29, 2007, Boston, USA, ISBN 13: 978-0-615-14623-2.
* [Peter Micheuz and Karl Josef Fuchs and Claudio Landerer, 2007] Peter Micheuz, Karl Josef Fuchs, Claudio Landerer: Mission possible - computers in "Anyschool". In: Benzie, D.; Iding, M. (eds.): Proceedings of IFIP-Conference on "Informatics, Mathematics and ICT: A golden triangle", June 27-29, 2007, Boston, USA, ISBN 13: 978-0-615-14623-2.
* [Ralf Romeike, 2007] Ralf Romeike: Three drivers for creativity in computer science education. In: Benzie, D.; Iding, M. (eds.): Proceedings of IFIP-Conference on "Informatics, Mathematics and ICT: A golden triangle", June 27-29, 2007, Boston, USA, ISBN 13: 978-0-615-14623-2.
* [Emmanuel Schanzer, 2007] Emmanuel Schanzer: Bootstr
* [Andreas Schwill, 1997] Andreas Schwill: " [http://ddi.cs.uni-potsdam.de/didaktik/Forschung/Israel97.pdf Computer science education based on fundamental ideas] ", In: Passey, D.; Samways, B. (eds.): Information Technology. Supporting change through teacher education. Chapman Hall, 1997, pp. 285–291.
* [Peer Stechert, 2006] Peer Stechert: " [http://www.springerlink.com/content/82m85lj62hh851g3/ Informatics System Comprehension - A learner-centred cognitive approach to networked thinking] ", In: Education and Information Technologies, ISSN: 1573-7608, Springer Netherlands, 2006.
* [Peer Stechert and Sigrid Schubert, 2007] Peer Stechert and Sigrid Schubert: " [http://www.die.informatik.uni-siegen.de/gruppe/stechert/publikationen/2007_Boston_stechert_schubert.pdf A Strategy to Structure the Learning Process Towards Understanding of Informatics Systems] ", In: Benzie, D.; Iding, M. (eds.): Proceedings of IFIP-Conference on "Informatics, Mathematics and ICT: A golden triangle", June 27-29, 2007, Boston, USA, ISBN 13: 978-0-615-14623-2.
* [Markus Steinert, 2007] Markus Steinert: Functional modelling and the graph of learning objectives. In: Benzie, D.; Iding, M. (eds.): Proceedings of IFIP-Conference on "Informatics, Mathematics and ICT: A golden triangle", June 27-29, 2007, Boston, USA, ISBN 13: 978-0-615-14623-2.
* [UNESCO and IFIP, 2002] UNESCO and IFIP: " [http://unesdoc.unesco.org/images/0012/001295/129538e.pdf Information and Communication Technology in Secondary Education – A Curriculum for Schools] ", Edited by Tom van Weert. Paris: UNESCO, 2002.
* [Michael Weigend, 2007] Michael Weigend: Origins of action – protagonists in drama-like interpretations of computer programmes. In: Benzie, D.; Iding, M. (eds.): Proceedings of IFIP-Conference on "Informatics, Mathematics and ICT: A golden triangle", June 27-29, 2007, Boston, USA, ISBN 13: 978-0-615-14623-2.
* [Per A. Godejord, 2007] Per A. Godejord: Fighting child pornography: Exploring didactics and student engagement in social informatics, Journal of the American Society for Information Science and Technology, Volume 58, Issue 3.
* DOSTÁL, J. [http://mict.upol.cz/pocitac_ve_vzdelavani_1.pdf Computer in education.] Olomouc, EU: Votobia, 2007. 125 s. ISBN 978-80-7220-295-2.
* [http://www-itec.uni-klu.ac.at/medichi2007/Home/ László Böszörményi (ed.): Medichi 2007 – Methodic and Didactic Challenges of the History of Informatics – ISBN 978-3-85403-220-5]
* [http://www.informatica-didactica.de Electronic journal "Informatica Didactica – Magazine for didactic basics of Informatics", ISSN: 1615-1771]
* [http://www.wcce2009.org/ "IFIP World Conference on Computers in Education (WCCE) 2009 – Education and technology for a better world"]
* [http://cidt.oum.edu.my/lyict/ Joint Open and Working IFIP-Conference "ICT and Learning for Net Gerneration - LYICT 2008"]
* [http://www.rsei.umk.pl/issep/ "International Conference on Informatics in Secondary Schools: Evolution and Perspectives – ISSEP 2008"]
* [http://www.ccs.neu.edu/imict2007/Home.html Working Joint IFIP-Conference "Informatics, Mathematics, and ICT: a golden triangle – IMICT 2007"]
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