On the Cognitive Effects of Learning Computer Programming: A Critical Look. Technical Report No. 9 (original) (raw)
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The effects of computer programming on young children's learning
1985
Computers will soon be an integral part of the classroom and home environment of children, yet there are unanswered questions concerning their effects on young children's cognition; Particularly salient are largely unsubstantiated claims concerning the cognitive benefits of computer programming. This study assessed the effects of learning computer programming on children's cognitive style (reflectivity, divergent thinking), metacognitive ability, cognitive development (operational competence, general cognitive measures), and ability to describe directions. Eighteen 6-year-old children were pretested to assess receptive vocabulary, impulsivity/reflectivity, and divergent-thinking abilities. The children were then randomly assigned to one of two treatments, computer programming or computer-assisted instruction (CAI), that lasted 12 weeks. Posttesting revealed that the programming group scored significantly higher on measures of reflectivity and on two measures of divergent thinking, whereas the CAI group showed no significant pre-to posttest differences. The programming group outperformed the CAI group on measures of metacognitive ability and ability to describe directions. No differences were found on measures of cognitive development. The increasing acceptance of the critical necessity for children to become computer literate is leading to an increased prominence of computers in the home and school environment. Yet there are unanswered questions regarding the effects of computer use on children's thinking. The purpose of this study was to investigate the effects of computer programming on 6-year : old children's cognitive style, metacognitive abilities, cognitive development, and ability to describe directions. Seymour Papert, one of the creators of the computer language Logo and a leading exponent of the use of computer programming to expand children's intellectual power, based his ideas on the theories of Piaget, with whom he studied. Papert (1980) has argued that the most beneficial learning is what he calls "Piagetian learning," or "learning without being taught." He has proposed that computer programming environments can create conditions under which intellectual models take root, conditions in which young children can master Requests for reprints should be sent to
Effects of computer programming on young children's cognition
Journal of Educational Psychology, 1984
Computers will soon be an integral part of the classroom and home environment of children, yet there are unanswered questions concerning their effects on young children's cognition; Particularly salient are largely unsubstantiated claims concerning the cognitive benefits of computer programming. This study assessed the effects of learning computer programming on children's cognitive style (reflectivity, divergent thinking), metacognitive ability, cognitive development (operational competence, general cognitive measures), and ability to describe directions. Eighteen 6-year-old children were pretested to assess receptive vocabulary, impulsivity/reflectivity, and divergent-thinking abilities. The children were then randomly assigned to one of two treatments, computer programming or computer-assisted instruction (CAI), that lasted 12 weeks. Posttesting revealed that the programming group scored significantly higher on measures of reflectivity and on two measures of divergent thinking, whereas the CAI group showed no significant pre-to posttest differences. The programming group outperformed the CAI group on measures of metacognitive ability and ability to describe directions. No differences were found on measures of cognitive development.
1984
The five papers in this symposium contribute to a dialog on the aims and methods of computer education, and indicate directions future research must take if necessary information is to be available to make informed decisions about the use of computers in schools. The first two papers address the question of what is required for a student to become a reasonably proficient programmer. The first-"Mapping the Cognitive Demands of Learning to Program" (D. Midian Kurland, Katherine Clement, Ronald Mawby, and Roy D. Pea)-reports a study of high school programming novices who participated in an intensive summer programming course. The second paper-"The Development of Programming Expertise in Adults and Children" (D. Midian Kurland, Ronald Mawby, and Nancy Cahir)-examines how expert programmers acquired their skill, with attention to the amount of time invested and the type of resources available when they were learning to program. The last three papers look beyond programming to the issue of transfer. The third-"Issues and Problems in Studying Transfer Effects of Programming" (Kate Ehrlich, Valerie Abbott, William Salter, and Elliot Soloway)-examines whether learning to program helps students solve problems in other related intellectual domains. The fourth-"What Will It Take to Learn Thinking Skills Through Computer Programming?" (Roy D. Pea)-discusses research on the transfer of high level thinking skills from programming. The final paper-"Making Programming Instruction Cognitively Demanding: An Intervention Study" (John Dalby, Francois. Tourniaire, and Marcia C. Linn)-describes a study in which a curriculum was designed explicitly to make programming more cognitively challenging. A concluding commentary by Jan Hawkins discusses the issues raised in the papers and offers thoughts on current and future directions for research in this field.
Mapping the Cognitive Demands of Learning to Program
Thinking: The Second …, 1987
Defining programming and assessing its cognitive demands is problematic because programming is a complex configuration of activities that vary according to what is being programmed, the style of programming, and how rich and supportive the surrounding programming cnvironment is (Kurland et al., 1984; Pea & Kurland, 1983). One consequence of the fact that programming refers to a configuration of activities is that different combinations of activities may be involved in any specific programming project. These activities include, at a general level. problem definition, design development and organization, code writing. and debugging (Pea & Kurland, 1983). Different combinations of activities will entail different cognitive demands. For example, a large memory span may facilitate the mental simulations required in designing and comprehending programs. Or an;dogical reasoning skill may he important for recognizing the similarity of different programming tasks and for transferring programming methods or procedures from one context to another. An adequate assessment of the cognitive demands of programming will depend on analyses of the programming activity and examination of the demands of different component processes.