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Problemlöseargument: Informatikkenntnisse helfen auch beim Lösen von Problemen ausserhalb der Informatikproblem solving argument: knowledge in computer science fosters problem solving

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Beat Döbeli HoneggerGrundkonzepte der Informatik sind hilfreich beim analytischen Denken und Lösen von Problemen über die Informatik hinaus.
Von Beat Döbeli Honegger, erfasst im Biblionetz am 14.04.2011
Der Programmierunterricht fördert Schlüsselkompetenzen wie Problemlösen, Abstrahieren, Analysieren oder im Team arbeiten.
Von Bernhard Matter in der Zeitschrift Schulblatt Aargau und Solothurn 16/12 (2012) im Text Programmieren an der Primarschule
Many strong claims have been made concerning the relationship between learning to program and learning to think. In the process of learning to program a computer, it is assumed, students will also learn about their own thinking processes. This premise underlies many assertions concerning the usefulness of teaching computer programming in schools.
Von Richard E. Mayer, Jennifer L. Dyck, William Vilberg im Text Learning to program and learning to think: what's the connection? (1986)
Jürg KohlasJürg SchmidCarl August ZehnderDie allgemeine Studierfähigkeit sowie die Fähigkeit zum Lösen anspruchsvoller Aufgaben der Gesellschaft setzen allgemeine kognitive Fähigkeiten voraus, so exaktes logisches Denken, konstruktive Lösungssuche, präzise Kommunikation, projektbezogenes Arbeiten, besonders auch im Team. Die Informatik bietet dazu Elemente an, welche die Erlangung dieser Kompetenzen in besonderem Masse fördern können.
Von Jürg Kohlas, Jürg Schmid, Carl August Zehnder im Buch informatik@gymnasium (2013) im Text Argumente für Informatik am Gymnasium auf Seite 25
Beat Döbeli HoneggerInformatik als Denkwerkzeug hat nicht nur im Bildungs- und Wissenschaftsbereich etwas zu bieten. Das Problemlöseargument zielt auf den Alltag: Informatik stellt Werkzeuge und Verfahren zur Verfügung, mit denen sich im Alltag Probleme strukturiert beschreiben, diskutieren und damit besser lösen lassen – auch ohne den Einsatz von Computern. So können zum Beispiel Flussdiagramme helfen, Abläufe zu verstehen und zu optimieren, unterschiedliche Datenstrukturen wie Listen, Tabellen, Bäume und Graphen unterstützen das problemgerechte Erfassen, Verarbeiten und Darstellen von Daten, und Visualisierungstechniken wie Concept-Maps helfen beim Nachdenken über Strukturen und Zusammenhänge. Bei der Beschäftigung mit Informatik lernt man diese Werkzeuge kennen und schult auch das entsprechende Denken. Viele dieser Konzepte und Werkzeuge existieren nicht erst seit der Entstehung der Wissenschaft Informatik. Doch erst die Informatik macht den Umgang mit solchen Werkzeugen explizit zum Thema. Guter Informatikunterricht fördert daher nicht nur die Nutzung solcher Konzepte und Werkzeuge, sondern hilft Schülerinnen und Schülern auch, künftig selbst die geeigneten Denkwerkzeuge zu finden. So eröffnet Informatik die Möglichkeit, über Problemlöseheuristiken oder den Unterschied zwischen Korrektheit und Viabilität nachzudenken.
Von Beat Döbeli Honegger im Buch Mehr als 0 und 1 im Text Wozu Informatik? (2016) auf Seite 94

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Peter DenningThis general claim has never been substantiated with empirical research.
Von Peter Denning im Text Remaining Trouble Spots with Computational Thinking (2017)
Simon Peyton JonesDas beanspruchen ja alle Fächer für sich, sogar Latein. Der Punkt ist: Bei Informatik ist es wirklich so! (lacht)
Von Simon Peyton Jones in der Zeitschrift c't 14/2014 im Text Schulfach "Computing" ab Klasse 1 (2014)
Pea and Kurland failed to find support for the idea that a year of Logo activities improved children’s strategic planning skills.
Von Richard E. Mayer, Jennifer L. Dyck, William Vilberg im Text Learning to program and learning to think: what's the connection? (1986) auf Seite 606
Despite these claims, there have been very few relevant research studies and almost no convincing support of this connection [7, 8, 13, 17, 22].
Von Richard E. Mayer, Jennifer L. Dyck, William Vilberg im Text Learning to program and learning to think: what's the connection? (1986)
Nicht nur ist damit klar, dass eine vertiefte Beschäftigung mit dem Computer extrem gut zur Problemlösungskompetenz beiträgt – sondern das logisch-analytische Denken so gut schult wie kaum ein anderes Fach.
Von Peter A. Henning in der Zeitschrift L. A. multimedia 1-2017 (2017) im Text Informatik als Kulturtechnologie?
Seymour PapertCynthia SolomonProgramming facilitates the acquisition of rigorous thinking and expression. Children impose the need for precise statement on themselves through attempting to make the computer understand and perform their algorithms.
Von W. Feurzeig, Seymour Papert, M. Bloom, R. Grant, Cynthia Solomon im Buch Programming-Languages as a Conceptual Framework for Teaching Mathematics (1969)
Rolf SchulmeisterStudien, die dem Lernen des Programmierens gewidmet wurden, gründeten ursprünglich auf der Annahme, man hätte mit dem Programmieren eine neue Generalfähigkeit, die Fähigkeit zur allgemeinen Informationsverarbeitung, soz. das »Latein des 20sten Jahrhunderts«, entdeckt.
Von Rolf Schulmeister im Buch Grundlagen hypermedialer Lernsysteme im Text Im Land der Null-Hypothesen (1996) auf Seite 383
Peter DenningThe Computer Science for All education movement, which began around 2006, is motivated by two premises: that computational thinking will better prepare every child for living in an increasingly digitalized world, and that computational thinkers will be superior problem solvers in all fields.
Von Peter Denning im Text Remaining Trouble Spots with Computational Thinking (2017)
Due to a lack of a widespread, positive, statistical relationship between programming language instruction and problem-solving skills, some computer educators and computer researchers question if a link between programming language instruction and problem-solving skills does, in fact, exist (Pea, 1984).
Von David B. Palumbo im Text Programming Language/Problem-Solving Research (1990)
Elliot SolowayTeaching programming in schools is a particularly hot topic now: On the one hand, it is argued that programming is merely a job skill, and that programming instruction should not be included in a general curriculum; on the other hand, it is argued that programming is a subject where one can learn effective problem-solving skills.
Von Elliot Soloway im Text Learning to program = learning to construct mechanisms and explanations (1986)
Shuchi GroverDecades of research with children suggests that young learners who may be programming don’t necessarily learn problem solving well, and many, in fact, struggle with algorithmic concepts especially if they are left to tinker in programming environments, or if the learning is not scaffolded and designed using the right problems and pedagogies.
Von Shuchi Grover im Text Learning to Code Isn't Enough (2013)
Gorman and Bourne found, however, that third graders who learned Logo with one extra hour of computer time per week performed better on tests of logical reasoning than third graders who learned Logo with just one half hour of extra computer time per week. Apparently, gains in thinking skills depend on the student being given heavy doses of Logo rather than just minimal exposure.
Von Richard E. Mayer, Jennifer L. Dyck, William Vilberg im Text Learning to program and learning to think: what's the connection? (1986) auf Seite 606
Roy PeaThis idea - that programming will provide exercise for the highest mental faculties,and that the cognitive development thus assured for programming will generalize or transfer to other content areas in the child's life -is a great hope. Many elegant analyses offer reasons for this hope although there is an important sense in which the arguments ring like the overzealous prescriptions for studying Latin in Victorian times.
Von Roy Pea im Text Logo Programming and Problem Solving (1983)
It is this generalized problem-solving transfer that computer programming educators hope to increase. Certainly, that is one of the claims made about the benefits of Logo instruction (Papert, 1980). Ginther and Williamson (1985), however, state that this type of generalized problem-solving transfer is difficult, if not impossible, to achieve in any context, and there is no reason to claim that programming language instruction will provide contrary evidence.
Von David B. Palumbo im Text Programming Language/Problem-Solving Research (1990)
Shuchi GroverMy own experiences over the last decade engaging middle and high school students in numerous computational activities (from programming games and stories in Scratch to Robotics to mobile app programming using App Inventor, and currently as a middle school CS teacher as part of my doctoral research) have been that while children comfortably learn the WHAT (blocks or syntax) of programming languages and environments, the HOW and WHY is much harder as they construct programming solutions.
Von Shuchi Grover im Text Learning to Code Isn't Enough (2013)
This old claim is called the “transfer hypothesis.” It assumes that a thinking skill automatically transfers into other domains simply by being present in the brain. It would revolutionize education if true. Education researchers have studied automatic transfer of CT for three decades and have never been able to substantiate it. There is evidence on the other side—slavish faith in a single way of thinking can make you into a worse problem solver than if you are open to multiple ways of thinking.
Von Peter J. Denning, Matti Tedre, Pat Yongpradit im Text Misconceptions About Computer Science (2017)
Roy PeaWhat has been done to evaluate the empirical validity of these important claims? While Papert and colleagues undertook extensive studies of children doing Logo programming in the Brookline school system,their reports of this work were principally qualitative innature,citing and discussing some of the programs that were created by the children, the global differences in programming style that seemed to be intuitively distinguishable (Watt, 1979), and dramatic case studies of great programming progress made by children who had learning difficulties (e.g., Weir, 1981).
Von Roy Pea im Text Logo Programming and Problem Solving (1983)
Shuchi GroverSeymour Papert’s pioneering efforts in the 1980s around children, programming, and the development of procedural thinking skills through Logo programming inspired a large body of these research studies. This previous literature revealed the problems faced by children, and overwhelmingly called for a need to study the pedagogy of programming. Other research studies over the last 2-3 years (including one from the Scratch team at MIT Lab) suggest that tween and teen student projects may point to apparent fluency as evidenced by the computational concepts used in their projects. However, probing deeper sometimes reveals significant conceptual chasms in their understanding of the computing constructs that their programs employ.
Von Shuchi Grover im Text Learning to Code Isn't Enough (2013)
If a link between instruction in computer programming and improved problem solving ability is not proven, then continued instruction in computer programming will have to be justified on some other basis. Other reasons, based on personal beliefs and anecdotal evidence, are that instruction in computer programming is necessary for computer literacy, allows for a better understanding of computer processing, provides an appreciation for commercial software development, increases social interaction between teachers and students and between students, increases selfconfidence from successful programming efforts, provides freedom from repetitive calculations, and provides the ability to simulate complex and/or dangerous situations in experiments and decision making.
Von Craig A. VanLengen, Cleborne D. Maddux im Text Does Instruction in Computer Programming Improve Problem Solving Ability? (1990) auf Seite 13
Elliot SolowayIf introductory programming courses are to teach students something more than a job skill, the underlying abstractions of programming must be made explicit. That is, students must be taught what programming has in common with other problemsolving tasks. By focusing on programs as the output of the programming process, students are naturally led to think that what they have learned in “Computer Science 100" is relevant only to the production of programs. To facilitate the transfer of knowledge from “Computer Science 100" to other problemsolving activities, students must be taught explicitly that programming is a design discipline, and as such the output of the programming process is not a program per se, but rather an artifact that performs some desired function.
Von Elliot Soloway im Text Learning to program = learning to construct mechanisms and explanations (1986)
Rolf SchulmeisterClark (1992) kommentiert diese Annahme nach einer Durchsicht entsprechender Studien: »The original hope that the learning of computer programming would sharpen general thinking and problem-solving skills seems unsupported. Thus, there seems to be a lack of compelling evidence of ›domain-general‹ transfer which is attributable to computer programming expertise« (267ff.). Die Transferqualität des Programmierens sei unbewiesen geblieben, Programmieren bleibe domain-spezifisch (wie es im übrigen ja auch Latein war). Wo Transfer nachgewiesen wurde, war der Computer kein notwendiges Medium, und die Transferfähigkeit wurde mit speziellen didaktischen Methoden trainiert. Clark bezeichnet die Verwechselung der menschlichen Informationsverarbeitung mit dem Programmieren als unzulässige Reifikation einer Metapher für Kognition.
Von Rolf Schulmeister im Buch Grundlagen hypermedialer Lernsysteme im Text Im Land der Null-Hypothesen (1996) auf Seite 383
Roy PeaThe intuitively plausible claims for the cognitive benefits of programming have broadened in scope and in public attention. Although evidence does not support these claims as yet, their presumed validity is nonetheless affecting important decisions in public education, and leading to high expectations for outcomes of programming in the school and home. In the current climate of uncritical optimism about the potential cognitive benefits of learning to program, we run the risk of having naive "technoromantic" ideas become entrenched in the school curriculum by affirmation, rather than by empirical verification through a cyclical process of research and development. Already at the pre-high school level, programming is taught primarily because of its assumed impacts on higher cognitive skills, not because proficiency in programming is itself an educational goal.
Von Roy Pea, D. Midian Kurland im Text On the cognitive effects of learning computer programming (1984)
Roy PeaThe contrasting belief, in part a reaction to the first belief, is that through learning to program. children are learning much more than programming, far more than programming "facts". It is said that children will acquire powerfully general higher cognitive skills such as planning abilities. problem-solving heuristics and reflectiveness on the revisionary character of the problem solving process itself. This belief. although new in its application to this domain, is an old idea in a new costume which has been worn often before. In its common extreme form, it is based on an assumption about learning - that spontaneous experience with a powerful symbolic system will have beneficial cognitive consequences, especially for higher order cognitive skills. Similar arguments have been offered in centuries past for mathematics, logic. writing systems, and Latin (e.g. see Bruner, 1966; Cole & Griffin, 1980; Goody, 1971; Olson, 1976; Ong, 1982; Vygotsky, 1978).
Von Roy Pea, D. Midian Kurland im Text On the cognitive effects of learning computer programming (1984)
Despite the absence of substantial proof of a positive relationship, there are still those who support the proposed link between programming language instruction and problem-solving skills. These researchers address deficiencies in those research studies that have not found these predicted positive relationships. These deficiencies can be characterized according to four major issues:
  • (a) programming language/ problem-solving studies not being firmly grounded in problem-solving theories (Burton & Magliaro, 1987-1988);
  • (b) quality, length, and intensity of the treatment presented (Burton & Magliaro; Palumbo & Reed, 1987-1988; Seidman, 1988; Soloway, Spohrer, & Littman, 1988);
  • (c) appropriateness of the programming language selected in increasing problem-solving skills and the method of instruction (Burton & Magliaro; Littlefield, Delclos, Lever, Clayton, Bransford, & Franks, 1988; Reed et al., 1987-1988); and
  • (d) selection of an appropriate sample of students, whose age range and ability level will provide the necessary background to benefit from programming language instruction (Linn & Dalbey, 1985; Pea, 1984).
Von David B. Palumbo im Text Programming Language/Problem-Solving Research (1990)
Juraj HromkovicOne of the main arguments for teaching mathematics is the development of the exact way of thinking that finally results in the ability to use the exact language of mathematics for describing, analyzing and solving problems in all areas of our life. This ability becomes more and more important. Some colleagues tend to call informatics the “new" mathematics or at least a constructive mathematics. Jeannette Wing, head of the computer science department at Carnegie Mellon University, even envisions that “thinking like a computer scientist" should be a fundamental skill such as reading, writing and arithmetics. Cohen and Haberman regard computer science as one of the five “languages" every citizen should acquire.
The reason for that is the way of working in computer science. Similarly as in mathematics, we begin with an abstract description of a problem and continue with its analysis. But additionally, computer scientists do not only discover an efficient way of solving it, but they also implement the discovered method and provide a product (program) for solving problems of this kind. This work is more constructive than the typical work of a mathematician and ties the exact way of thinking in mathematics with the pragmatic way of working in engineering.
Von Juraj Hromkovic, Björn Steffen im Konferenz-Band Informatics in Schools im Text Why Teaching Informatics in Schools Is as Important as Teaching Mathematics and Natural Sciences (2011) auf Seite 25
Studies of computer programming and problem solving have yielded mixed results. Studies that failed to find a relationship between computer programming and problem solving had various weaknesses in experimental design and instructional approach. Specifically, many studies employed small samples [8, 12], did not use random selection and/or assignment of the subjects [8, 9, 10, 11 ], or lacked control groups [9].
In addition, the main instructional approach in the non-support studies was non-directive (discovery) [8, 9]. Program planning, development, and debugging were not specifically taught [8, 9]. This is a problem, since using a non-directive instructional approach with a limited amount of treatment time does not appear to be effective.
Another difficulty is that mastery of programming was not measured [8, 12, 10, 11]. Without ensuring that programming is mastered, it makes little sense to talk of problem solving transfer [13].
A number of other studies showed some positive relationship between computer programming and problem solving ability. Some of these studies used random selection and/or assignment [14, 15, 16, 12, 17, 18]. Random selection should result in sample groups that are more closely related to the population. Several studies were for longer periods of time (semester or more) [19, 17, 20]. Longer studies should allow for more treatment time. The instructional strategy used in a number of these studies was directed with specific instruction in program planning and development [15, 16, 12, 17, 18). Tbe results of some of the studies are not conclusive since the programming activities and dependent variables appeared to be highly related [16, 18]. Even though the inferences were not clearcut, these studies are a beginning of an experimental process directed at investigating a possible link between computer programming instruction and generat problem solving ability.
Von Craig A. VanLengen, Cleborne D. Maddux im Text Does Instruction in Computer Programming Improve Problem Solving Ability? (1990) auf Seite 11

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