| Project/Area Number |
15300089
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Cognitive science
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| Research Institution | Chukyo University |
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Principal Investigator |
MIYAKE Yoshio Chukyo University, School of Information Science and Technology, Professor, 情報理工学部, 教授 (80099910)
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| Co-Investigator(Kenkyū-buntansha) |
MIYAKE Naomi Chukyo University, School of Information Science and Technology, Professor, 情報理工学部, 教授 (00174144)
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| Project Period (FY) |
2003 – 2006
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| Project Status |
Completed (Fiscal Year 2006)
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| Budget Amount *help |
¥15,900,000 (Direct Cost: ¥15,900,000)
Fiscal Year 2006: ¥3,400,000 (Direct Cost: ¥3,400,000)
Fiscal Year 2005: ¥3,600,000 (Direct Cost: ¥3,600,000)
Fiscal Year 2004: ¥3,600,000 (Direct Cost: ¥3,600,000)
Fiscal Year 2003: ¥5,300,000 (Direct Cost: ¥5,300,000)
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| Keywords | programming learning / cognitive modeling / learning process / programming instruction / knowledge representation / understanding / multiple representations / design of learning environment / Rudy / ビデオデータ / Ruby |
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| Research Abstract |
This study aims at developing a cognitive theory that reveals the complex cognitive processes underlying programming language learning. It also aims at, based on the theory, designing a practical and effective environment for teaching and learning of programming skills.
In order to achieve these goals, we have collected detailed and wide-ranged cases of instructional processes, and analyzed them as the real programming leaning processes to the extent never studied before. Concretely, we have collected the cases of both successful and failed learning occasions at an introductory college level programming classes. We have collected video recordings of the cases where the learners felt difficulties in achieving their tasks at hand; results of carefully designed quizzes implemented at various points of learning. We analyzed and categorized these data into a structure to reflect the reality of programming learning, so that we could use them for further analyses, as well as for further implem
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entation of better teaching practices. This level of collection and the analyses of the data enabled us to understand the complex cognitive processes underlying the acquisition of programming skills.
One of our major results is a general integrative theory of programming learning, based on a framework which grasps the cognitive processes of programming as an overlaying of many different layers of representations involved in programming. This is related to more general cognitive mechanisms (c.f., inferences and degrees of expertise). Based on this theory, we made clear the reality of the complex and unstable states of novice learners of programming, in terms of their cognitive processes where many layered representations interact among themselves.
Then we examined conditions of the learning environment in terms of its effectiveness for novice level programming learning. This led us to a web-based learning environment, which takes into account the partial comprehension characteristic in novice level, realistic learning processes. The strength of this environment relies on its ability to respond to learning blocks; when a learner finds herself blocked, the system guides her to find a necessary piece of information on her own. We have examined the effectiveness of this environment with actual classes we ran, and found its effectiveness. Less
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