Practices of algorithm education based on discovery learning using a program visualization system

Yamashita, Koichi; Fujioka, Ryota; Kogure, Satoru; Noguchi, Yasuhiro; Konishi, Tatsuhiro; Itoh, Yukihiro

doi:10.1186/s41039-016-0041-5

Cited by 8 publications

(15 citation statements)

References 12 publications

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“…Many existing systems such as Jeliot 3 (Moreno, Myller, Sutinen, & Ben-Ari, 2004; Ben-Ari et al, 2011), NoobLab (Neve, Hunter, Livingstone, & Orwell, 2012), and LEPA (Yamashita et al, 2016) reproduce the behaviors of programs by visualizing logical data structures processed by target program and their changes made by statement execution. However, these visualizations involve certain abstractions of data structures which are established independently in each system.…”

Section: Tedvit: Teacher Explaining Design Visualization Toolmentioning

confidence: 99%

Classroom practice for understanding pointers using learning support system for visualizing memory image and target domain world

Yamashita

Fujioka

Kogure

et al. 2017

RPTEL

Self Cite

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Pointers are difficult learning targets for novice learners of C programming. For such difficult targets, introducing a system visualizing program behaviors is generally expected to support learners to understand the targets. However, visualization in existing systems often conceals the concrete value of variables such as pointers; the way in which each visualized object is located on the memory is not made explicit. In order to address this issue, we focused on a program visualization system called TEDViT. It visualizes simultaneously and synchronously the memory image that is the field that presents the concrete value of variables and the target domain world that is the field that presents logically the data structures processed by the program. We consider that observing and comparing program code, memory image, and target domain world with TEDViT could work for understanding pointers. TEDViT visualizes the status of the target domain world according to the visualization policy defined by the teacher in order to allow teachers to set their instruction content based on the growing variety of learner background knowledge. We also consider that this feature could support teachers’ instructions and class managements appropriately, and improving teachers’ performance by TEDViT’s support would bring improvement of learners’ understanding. We conducted classroom practice for understanding pointers in connection with a memory model, thus introducing TEDViT to a real class. Analysis of answered scores in a questionnaire conducted after the practice suggests that our practice using TEDViT provided useful supports for participants to understand pointers. It also suggests our practice had a certain effect to reduce uneven levels of understanding among participants. Based on these results, we describe that classroom practices in our framework could support learners to understand pointers and support teachers to manage the class.

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Section: Tedvit: Teacher Explaining Design Visualization Toolmentioning

confidence: 99%

Classroom practice for understanding pointers using learning support system for visualizing memory image and target domain world

Yamashita

Fujioka

Kogure

et al. 2017

RPTEL

Self Cite

View full text Add to dashboard Cite

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“…To learn by example sentences is regarded as one type of the learning styles in discovery learning. In discovery learning, we try to find general knowledge by generalizing the observed targets (Johns, 2010;Swaak, Jong, & Joolingen, 2014;Yamashita et al, 2016). Several researches tried to support the discovery learning and provided the simulation environment where we can check whether our generalization is appropriate (Veermans & Joolingen, 2004;Rieber, Tzeng, & Tribble, 2004).…”

Section: Introductionmentioning

confidence: 99%

Generalization support environment for understanding ways to use English words

Kojiri

Yamada

2020

RPTEL

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When we translate Japanese sentence into English, sometimes several English words become the candidates. However, the usage situation of these candidate words is not the same. In order to choose appropriate words from them, we need to understand the usage situation for each candidate words. Usage situation of the words can be inferred by co-existing words in their example sentences. Co-existing words in example sentences are not always the same, so in order to understand usage situation, we need to generalize co-existing words from several example sentences. However, some of us who do not consciously generalize the co-existing words do not acquire the usage situation. This paper proposes the system which provides the environment where we can explicitly generalize co-existing words (keywords) in the example sentences to acquire the usage situation of the target words. This system also has a generalization support mechanism to provide concepts of words acquired through WordNet as hints. According to the experimental results, participants who used the system in learning English words reduced the number of incorrectly choosing the words and promoted to derive the own understanding of the usage situation.

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“…In discovery learning, activities or learning are designed so that students can find concepts and principles through their mental processes. In finding concepts, students make observations, classify, make guesses, explain, draw conclusions and so on to find some concepts or principles (Yamashita et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Discovery Learning based on Natural Phenomena to Improve Students' Science Process Skills

Haryadi

Pujiastuti

2019

jpppf

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The purpose of this research is to find out the science process skills of students through Discovery learning. The process of science is essential for students to have because it is the process of forming science. Science process skills can accustom students to learning through scientific work processes and systematic work. The research method uses a quasi-experiment with one group pretest-posttest design. This study does not use a comparison class, because it already uses a preliminary test so that the magnitude of the effect or effect of using discovery learning can be known with certainty. In this study, research subjects were first given a pre-test (pretest) to find out the extent of the students' initial abilities before being given physics learning by using discovery learning. After the initial test is given, then the student is given treatment, namely learning physics by using discovery learning. After completing physics learning with discovery learning, then all students are given a final test (posttest) to determine the extent of the effect of physics learning by using discovery learning on students' science process skills. The instrument used in this study was a science process skills test on the material elasticity and Hooke law, in the form of 20 multiple-choice tests and tested on 30 students in Prisma City High School. Each question evaluates aspects of conclusions, observations, identification, predictions, and interpretation of data. The results of the analysis show an increase in observational indicators from 39.95 to 66.62, concluding from 53.86 to 69.4, identifying from 36.6 to 73.3, predicting from 39.43 to 68.31 and interpreting from 73, 3 to 98.3. Based on the results of the analysis, the learning of physics-based on natural phenomena through discovery learning models can improve students' science process skills.

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Practices of algorithm education based on discovery learning using a program visualization system

Cited by 8 publications

References 12 publications

Classroom practice for understanding pointers using learning support system for visualizing memory image and target domain world

Classroom practice for understanding pointers using learning support system for visualizing memory image and target domain world

Generalization support environment for understanding ways to use English words

Discovery Learning based on Natural Phenomena to Improve Students' Science Process Skills

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