Recent Studies About Teaching Algorithms (CS1) and Data Structures (CS2) for Computer Science Students

Silva, Davi Bernardo; Aguiar, Rafael de Lima; Dvconlo, Diogo Steinke; Silla, Carlos N.

doi:10.1109/fie43999.2019.9028702

Cited by 12 publications

(7 citation statements)

References 56 publications

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“…Двконло, С.Н. Силла [3]. Значимым результатом исследования является описание базовых идей подхода, расширяющих представления И.С.…”

Section: использование тренажера «кокла» для отработки действий алгор...unclassified

“…Львова 2 алгоритмы активно используются, учащиеся изучают структуру и принципы построения алгоритма. Учителя-новаторы в школах реализуют варианты организации целенаправленной деятельности на уроках русского языка, литературы по составлению алгоритмов и получению нового знания на основе системно-деятельностного подхода 3 .…”

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“…URL: https://pdf.11klasov.net/16069-russkij-jazyk-6-klass-v-2-hchastjah-uchebnik-razumovskaja-mm-lvova-si-kapinos-vi-lvov-vv.html (дата обращения: 29.04.2022). 3 Активные приемы обучения на уроках русского языка и литературы в школе // Eduneo.ru. URL: https://www.eduneo.ru/aktivnye-priyomy-obucheniya-na-urokax-russkogo-yazyka-iliteratury-v-shkole/ (дата обращения: 28.04.2022).…”

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The use of interactive game simulators for the development of algorithmic thinking of students in Russian language and literature lessons

Novoselova

Smerechinskaya

2022

Vestn. Ross. univ. družby nar., Ser. Informatiz. obraz.

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Problem and goal . The model of formation of competitive qualities of a graduate of a modern digital school assumes that he has a culture of thinking, the ability to generalize, analyze, perceive information, set goals and choose ways to achieve it. The development of relevant skills is actively taking place in the lessons of computer science, mathematics, physics, chemistry. However, the Russian language and literature have a certain didactic potential for the formation of the ability to perform mental operations, choosing the optimal way to achieve the goal, etc. The expediency of using interactive simulators to support the communicative activity of students in the study of the Russian language and literature in order to form algorithmic thinking is substantiated. Metodology. The possibilities of designers of interactive simulators for various purposes are analyzed: for the development of online games (Lingo Play, Kid Mama), quests (Learnis), mobile phones (Alice's Resort, Kotovasia), for creating puzzles, charades, crosswords, metagrams and puzzles with riddles, quizzes. To evaluate the input conditions, testing was used, including blocks on the Russian language, literature, and computer science. The experimental study was conducted in the MOE Secondary School No. 25 of Sochi named after Hero of the Soviet Union S.E. Voitenko at the lessons of Russian language, literature, computer science. The participants of the experiment were 46 schoolchildren from the sixth grades. To create interactive game simulators in the classroom, the online designer of “eTrenics” is used (services “Kokla,” “Krypton,” “Morphanki,” “UFO,” “Potato”). Statistical processing of the results was performed using Pearson's chi-square test. Results. Students study services for creating interactive game simulators, use them to process new words, memorize spelling rules, and the plot of works of art. Statistically significant differences in the qualitative changes that occurred in the system according to the levels of development of algorithmic thinking were revealed. Conclusion. Described the features of the presented version of the use of interactive game simulators for the development of algorithmic thinking of schoolchildren in Russian language and literature lessons: inter-network interaction, the design of simulators according to the rules of the Russian language or the plot of the work, the intensification of learning, taking into account the specifics of the “clip” thinking of adolescents.

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Section: использование тренажера «кокла» для отработки действий алгор...unclassified

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The use of interactive game simulators for the development of algorithmic thinking of students in Russian language and literature lessons

Novoselova

Smerechinskaya

2022

Vestn. Ross. univ. družby nar., Ser. Informatiz. obraz.

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“…However, research has also shown that high school computer science education is a predictor of success in higher education, especially among women, who are notably under-represented in the current field of computer science [ 4 ]. While not a replacement for formal education, interactive tools can be used to ease students into the subject, as well as allow teachers who are not explicitly trained in computer science to convey concepts to students [ 5 ].…”

Section: Introductionmentioning

confidence: 99%

Use of Machine Learning in Interactive Cybersecurity and Network Education

Loftus

Narman

2023

Sensors

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Cybersecurity is a complex subject for students to pursue. Hands-on online learning through labs and simulations can help students become more familiar with the subject at security classes to pursue cybersecurity education. There are several online tools and simulation platforms for cybersecurity education. However, those platforms need more constructive feedback mechanisms, and customizable hands-on exercises for users, or they oversimplify or misrepresent the content. In this paper, we aim to develop a platform for cybersecurity education that can be used either with a user interface or command line and provide auto constructive feedback for command line practices. Moreover, the platform currently has nine levels to practice for different subjects of networking and cybersecurity and a customizable level to create a customized network structure to test. The difficulty of objectives increases at each level. Moreover, an automatic feedback mechanism is developed by using a machine learning model to warn users about their typographical errors while using the command line to practice. A trial was performed with students completing a survey before and after using the application to test the effects of auto-feedback on users’ understanding of the subjects and engagement with the application. The machine learning-based version of the application has a net increase in the user ratings of almost every survey field, such as user-friendliness and overall experience.

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“…As mention by Kukul et al (2017) that the development of other advanced abilities, such as problem-solving, logical inference, and creative thinking, is facilitated by knowledge of computer programming. Due to this advantage, many higher institutions offer programming subject to the non-computer sciences students and even the secondary and primary school is also requiring their students to learn programming, However, programming is the challenging subject to teach because have a high failure rate and dropout (Silva et al, 2019). The subject need the correct comprehension of abstract concepts (Lahtinen et al, 2005).…”

Section: Introductionmentioning

confidence: 99%

Revalidation on Computer Programming Self-Efficacy Scale using Fuzzy-Delphi Method Approach

Ismail¹,

Razak²

2022

IJARBSS

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Computer programming self-efficacy is the tool to measure the students' competencies in programming either success or fail. It is important for the students in all over the world and in Malaysia because if the score is low, the students must work harder and find the solution or ways to learn programming effectively. Then, for the instructor, it can be the guideline to plan the teaching material and mechanism to deliver the subject. This research re-validates the computer programming self-efficacy that can be tailored to Malaysian students. This research was used the Fuzzy-Delphi Method that adopt the questionnaire in the literature. This questionnaire has five main item which are Logical Thinking, Cooperation, Algorithm, Control and Debug to measure the student's self-efficacy. The item in the questionnaire were re-validated by five programming experts in order to tailor the questionnaire in the Malaysia context. The findings of the research were the expert agreement on the acceptance of the item used in the questionnaire. The result shows all the experts agreed almost 100% of the item used.

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Recent Studies About Teaching Algorithms (CS1) and Data Structures (CS2) for Computer Science Students

Cited by 12 publications

References 56 publications

The use of interactive game simulators for the development of algorithmic thinking of students in Russian language and literature lessons

The use of interactive game simulators for the development of algorithmic thinking of students in Russian language and literature lessons

Use of Machine Learning in Interactive Cybersecurity and Network Education

Revalidation on Computer Programming Self-Efficacy Scale using Fuzzy-Delphi Method Approach

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