BackgroundStudies on the effectiveness of block-based environments continue to produce inconsistent results. A strong reason for this is that most studies compare environments that are not equivalent to each other or ...
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BackgroundStudies on the effectiveness of block-based environments continue to produce inconsistent results. A strong reason for this is that most studies compare environments that are not equivalent to each other or to the level of learners. Moreover, studies that present evidence of the effectiveness of block-based environments by comparing equivalent environments are limited. ObjectivesThis study aims to scrutinize the effects of programming training to be held in equivalent environments (block-based and text-based) with university students who do not have prior programming knowledge and experience on achievement, logical thinking, and motivation. MethodsThe study was conducted by using an experimental pretest-posttest control group design. The study was conducted with 60 students, the total consisting of 30 students in the experimental group and 30 students in the control group. In the experimental group, block-based visual programming training with Scratch was conducted and the control group received text-based programming training with Small Basic. The training was maintained for 10 weeks, for 4 h a week in each group. The programming achievement test, the logical thinking skills test, and the motivation scale were used to collect the data. Results and ConclusionsThe results showed that the use of a block-based environment in programming training contributed positively to the development of students' logical thinking skills, and motivation for learning programming. In contrast, there was evidence that this training did not make a difference on programming success. ImplicationsThe findings of the study provided evidence of the effectiveness of block-based training in comparisons made in equivalent environments. Focusing research on this issue may contribute to the improvement of the current understanding.
This paper illustrates uses of high level and declarative programming environments for the teaching of machine transients. It demonstrates the clarity and flexibility afforded by this new generation of mathematical so...
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The commenter maintains that most novice Smalltalk programmers have different experiences from those described by the authors of the abovementioned article (ibid., vol.6, no.5, p.73-7, May 1989). She points out that t...
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The commenter maintains that most novice Smalltalk programmers have different experiences from those described by the authors of the abovementioned article (ibid., vol.6, no.5, p.73-7, May 1989). She points out that they tried to learn a new programming language, programming environment, design methodology, and window system through unguided exploration. She then examines a number of the authors' points in this context, arguing that many of their objections seem to stem from their fundamental misunderstanding of the system's tools. The authors reply that the commenter speaks from the perspective of someone skilled in Smalltalk, and they present counterarguments to a number of her points.< >
A challenging issue in the construction and maintenance of large application systems is how to determine which components need to be rebuilt after change, when and in which order. Rebuilding is typically recompilation...
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When students are learning to develop algorithms, they very often spend more time dealing with issues of syntax than solving the problem. Additionally, the textual nature of most programming environments works against...
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When students are learning to develop algorithms, they very often spend more time dealing with issues of syntax than solving the problem. Additionally, the textual nature of most programming environments works against the learning style of the majority of students. RAPTOR is a flowchart-based programming environment, designed specifically to help students visualize their algorithms and avoid syntactic baggage. RAPTOR programs are created visually and executed visually by tracing the execution through the flowchart. Required syntax is kept to a minimum. Students preferred using flowcharts to express their algorithms, and were more successful creating algorithms using RAPTOR than using a traditional language or writing flowcharts without RAPTOR.
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