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Mariyam Abdulhadi; Fred Awaah; Deborah Agbanimu; Emmanuel Okyere Ekwam; Emmanuella Sefiamor Heloo – Journal of Research in Innovative Teaching & Learning, 2024
Purpose: The lecture method has been compared with teaching methods such as flip learning, cooperative learning and simulations to establish which holds the key to students' understanding of concepts. What is bereft in the education literature is its comparative efficiency with the culturo-techno contextual approach (CTCA) in the teaching of…
Descriptors: Foreign Countries, Developing Nations, Computer Science Education, Cultural Context
Ramon Mayor Martins; Christiane G. Von Wangenheim; Marcelo F. Rauber; Adriano F. Borgatto; Jean C. R. Hauck – ACM Transactions on Computing Education, 2024
As Machine Learning (ML) becomes increasingly integrated into our daily lives, it is essential to teach ML to young people from an early age including also students from a low socioeconomic status (SES) background. Yet, despite emerging initiatives for ML instruction in K-12, there is limited information available on the learning of students from…
Descriptors: Artificial Intelligence, Computer Science Education, Socioeconomic Status, Correlation
Yun Dai – Education and Information Technologies, 2025
There is a growing consensus that AI literacy requires a holistic lens, including not only technical knowledge and skills but also social and ethical considerations. Yet, providing holistic AI education for upper-primary students remains challenging due to the abstract and complex nature of AI and a lack of pedagogical experiences in schools.…
Descriptors: Integrated Activities, Holistic Approach, Artificial Intelligence, Computer Science Education
Yuan-Chen Liu; Tzu-Hua Huang; Chien-Chia Huang – Interactive Learning Environments, 2024
In this study, an interactive programming learning environment was built with two types of error prompt functions: 1) the key prompt and 2) step-by-step prompt. A quasi-experimental study was conducted for five weeks, in which 75 sixth grade students from disadvantaged learning environments in Taipei, Taiwan, were divided into three groups: 1) the…
Descriptors: Programming, Computer Science Education, Cues, Grade 6
Li, Wei; Liu, Cheng-Ye; Tseng, Judy C. R. – Education and Information Technologies, 2023
Collaborative programming can develop computational thinking and knowledge of computational programming. However, the researchers pointed out that because students often fail to mobilize metacognition to regulate and control their cognitive activities in a cooperation, this results in poor learning effects. Especially low-achieving students need…
Descriptors: Correlation, Metacognition, Thinking Skills, Programming
Yamaguchi, Ryoko; Hankerson Madrigal, Veronica; Eaton, Cyntrica N.; Burge, Jamika D. – Journal for Multicultural Education, 2023
Purpose: There is a critical need to understand how to attract Black girls and other girls of color to the science, technology, engineering, math, and computer science (STEM+CS) field. This study aims to look at the design and implementation of a CS learning ecosystem that supports girls of color in acquiring critical CS skills starting in middle…
Descriptors: STEM Education, Computer Science Education, Minority Group Students, Females
Shian-Shyong Tseng; Tsung-Yu Yang; Wen-Chung Shih; Bo-Yang Shan – Interactive Learning Environments, 2024
In this paper, to handle the problem of the quick evolution of cyber-security attacks, we developed the iMonsters board game and proposed the attack and defense knowledge self-evolving algorithm. Three versions of the iMonsters were launched in 2013, 2017, and 2019, respectively. Accordingly, the cyber-security ontology can be refined by the…
Descriptors: Educational Games, Computer Security, Computer Science Education, Game Based Learning
Saba, Janan; Hel-Or, Hagit; Levy, Sharona T. – Instructional Science: An International Journal of the Learning Sciences, 2023
This article concerns the synergy between science learning, understanding complexity, and computational thinking (CT), and their impact on near and far learning transfer. The potential relationship between computer-based model construction and knowledge transfer has yet to be explored. We studied middle school students who modeled systemic…
Descriptors: Transfer of Training, Science Instruction, Learning Management Systems, Learning Processes
Wanxue Zhang; Lingling Meng; Bilan Liang – Interactive Learning Environments, 2023
With the continuous development of education, personalized learning has attracted great attention. How to evaluate students' learning effects has become increasingly important. In information technology courses, the traditional academic evaluation focuses on the student's learning outcomes, such as "scores" or "right/wrong,"…
Descriptors: Information Technology, Computer Science Education, High School Students, Scoring
Lavy, Ilana – International Journal of Information and Communication Technology Education, 2021
This article describes a unique ongoing experience of learning programming via engagement in music programming of known melodies. Seventh and eighth graders participated in 10 lessons of weekly activity. Via the programming of melodies, using the Scratch 2.0 environment, they became acquainted with basic concepts of programming such as methods,…
Descriptors: Teaching Methods, Computer Science Education, Programming, Music
Jenks, Theodore G. – ProQuest LLC, 2022
The purpose of this action research was to implement a digital game development project and describe its effects on the performance and attitudes of eighth-grade students in a required computer science course at South Carolina School District Alpha. The following research questions were explored: (1) How does the game development project impact…
Descriptors: Middle School Students, Active Learning, Student Projects, Games
Gresse Von Wangenheim, Christiane; Da Cruz Alves, Nathalia; Rauber, Marcelo F.; Hauck, Jean C. R.; Yeter, Ibrahim H. – Informatics in Education, 2022
Although Machine Learning (ML) is used already in our daily lives, few are familiar with the technology. This poses new challenges for students to understand ML, its potential, and limitations as well as to empower them to become creators of intelligent solutions. To effectively guide the learning of ML, this article proposes a scoring rubric for…
Descriptors: Performance Based Assessment, Artificial Intelligence, Learning Processes, Scoring Rubrics
Colon-Acosta, Nirmaliz – ProQuest LLC, 2019
As new introductory block-based coding applications for young students to learn basic computer science concepts, such as, loops and conditionals, continue to increase in popularity, it is necessary to consider the best method of teaching students these skills. Many of these products continue to exhibit programmatic misconceptions of these concepts…
Descriptors: Coding, Game Based Learning, Instructional Effectiveness, Programming Languages
Saito, Daisuke; Kaieda, Shota; Washizaki, Hironori; Fukazawa, Yoshiaki – Journal of Information Technology Education: Innovations in Practice, 2020
Aim/Purpose: Although many computer science measures have been proposed, visualizing individual students' capabilities is difficult, as those measures often rely on specific tools and methods or are not graded. To solve these problems, we propose a rubric for measuring and visualizing the effects of learning computer programming for elementary…
Descriptors: Scoring Rubrics, Visualization, Learning Analytics, Computer Science Education
Maruyama, Ryoga; Ogata, Shinpei; Kayama, Mizue; Tachi, Nobuyuki; Nagai, Takashi; Taguchi, Naomi – International Association for Development of the Information Society, 2022
This study aims to explore an educational learning environment that supports students to learn conceptual modelling with the unified modelling language (UML). In this study, we call the describing models "UML programming." In this paper, we show an educational UML programming environment for science, technology, engineering, art, and…
Descriptors: Case Studies, Programming Languages, Learning Processes, Models
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