Be Constructive: Learning Computational Thinking Using Scratch™ Online Community

Chowdhury, Bushra; Johri, Aditya; Kafura, Dennis; Lohani, Vinod K.

doi:10.1007/978-3-030-35758-0_5

Cited by 4 publications

(2 citation statements)

References 28 publications

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“…These existing frameworks adopt diverse approaches, concentrating on elements such as curriculum design, assessment methods, and the integration of ER tools. As for this study, the learning material used were specially designed followed the constructive alignment approach [7,11] which is also based on the conceptual model invented by [24].…”

Section: Al Framework For Learning Ctermentioning

confidence: 99%

Adaptive learning framework for learning computational thinking using educational robotics

Jamal,

Jawawi,

Hassan

et al. 2024

Comp Applic In Engineering

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Computational thinking (CT) has been promoted worldwide by educational systems and is an essential skill for technological citizens. Various strategies have been planned and developed to help in introducing, improving, and delivering CT. One of the strategies is by creating and developing the supporting tools for CT learning. In this article, educational robotics (ER) is chosen as the focus tool to support CT learning. Each CT and ER has a massive field of study. There are various available reports determining the suitability of CT subject integrated with ER for students' learning. However, all students do not develop similar style of learning and thinking. There is difference in their personal traits. There is a lack of research that designed CT learning through ER specifically based on student's preferences. Besides, it resulted in a challenge to determine the suitability of CT and ER for different kind of preferences. Therefore, this study aimed to develop an adaptive learning (AL) framework for students to deliver learning of CT through ER. The framework consists of three submodels: domain model, student model, and adaptation model. One case study is defined, which is learning the introductory level of CT through ER (CTER). At the end of the study, it can be observed that the AL framework produced positive results in performance and perception for various student categories. It was noted that students utilizing the AL framework had superior understanding of CTER. Individually or collaboratively, all students who applied or did not apply the AL framework in studying the CTER introduction had positive learning outcomes.

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Section: Al Framework For Learning Ctermentioning

confidence: 99%

Adaptive learning framework for learning computational thinking using educational robotics

Jamal,

Jawawi,

Hassan

et al. 2024

Comp Applic In Engineering

View full text Add to dashboard Cite

show abstract

“…Although online learning can provide richer learning resources and more flexible learning methods, for reluctant students with poor consciousness and initiative, it's hard to get ideal learning effects [1][2][3][4][5][6][7][8]; as for independent students who learn by themselves, it's hard to enhance their learning abilities [9][10][11][12][13]. So, in order to give full play to the real effects of hybrid learning, Hybrid Learning Community Network (HLCN) could be built to integrate online and offline learning and form hybrid learning network communities [14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the Effectiveness of Hybrid Learning Activities Based on a Learning Community Network

Xie¹

2022

Int. J. Emerg. Technol. Learn.

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Hybrid Learning Community Network (HLCN) can link individuals to collectives systematically, support both virtual and actual scenarios, and share and trade knowledge, experience, and learning resources. Existing studies on HLCN are mostly theoretical research, there’re very few empirical evidences, and the integrity of the research systems is yet to be improved further. In view of these shortcomings, this paper proposed a theoretical model for HLCN and built an Evaluation Index System (EIS) for assessing the effectiveness of the hybrid learning activities and analyzing the feature parameters and centrality of the HLCN. Then in the paper, a Hybrid Learning Interactive Activity Content Network Relation (HL-IAC-NR) matrix was established based on learning community, and the indexes such as students’ learning attention on knowledge points and their learning sentiments were attained. At last, this paper used the Charnes-Cooper-Rhodes (CCR) model in Data Envelope Analysis (DEA) to evaluate the relative effectiveness, and the real-time effects of different types of hybrid learning interactive activities were analyzed. The effectiveness of the proposed model and evaluation method was verified via experiments.

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Understanding the relationship between computational thinking and computational participation: a case study from Scratch online community

Jiang

Zhao

et al. 2021

Education Tech Research Dev

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Be Constructive: Learning Computational Thinking Using Scratch™ Online Community

Cited by 4 publications

References 28 publications

Adaptive learning framework for learning computational thinking using educational robotics

Adaptive learning framework for learning computational thinking using educational robotics

Evaluation of the Effectiveness of Hybrid Learning Activities Based on a Learning Community Network

Understanding the relationship between computational thinking and computational participation: a case study from Scratch online community

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