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Adaptive learning model for learning computational thinking through educational robotic

Computational thinking (CT) has been promoted worldwide by educational systems and is an essential skill for technological citizens. In delivering CT, various kinds of educational tools were developed by researchers to support the learning. One of the attractive tools in providing the CT is educatio...

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Main Author: Jamal, Nurul Nazihah
Format: Thesis
Language:English
Published: 2021
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://eprints.utm.my/id/eprint/102856/1/NurulNazihahJamalMSC2021.pdf.pdf
http://eprints.utm.my/id/eprint/102856/
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spelling my.utm.1028562023-09-26T05:57:47Z http://eprints.utm.my/id/eprint/102856/ Adaptive learning model for learning computational thinking through educational robotic Jamal, Nurul Nazihah QA75 Electronic computers. Computer science Computational thinking (CT) has been promoted worldwide by educational systems and is an essential skill for technological citizens. In delivering CT, various kinds of educational tools were developed by researchers to support the learning. One of the attractive tools in providing the CT is educational robotic (ER). However, delivering CT to students through ER has many challenges. There is a lack of studies presenting the general view on the integration of ER and CT as both subjects have big scope in terms of teaching and learning. Thus, this study designed a conceptual data model to represent the relationship between CT and ER. In addition to the complexity in determining the suitability of both subjects for students’ learning, students also have differences in their personal traits, resulting in different learning styles and thinking styles. Therefore, this study aimed to enhance an adaptive learning (AL) model for students, which is based on the students’ learning style and knowledge level. The enhanced AL model comprised three sub-models: domain model, student model, and adaptation model. Two case studies were selected, which are learning advance of CT and the introductory of computational thinking through educational robotic (CTER). At the end of the study, it can be observed that the enhanced AL model produced positive results in performance and perception for various student categories. In learning advanced CT, both groups of students exhibited a positive perception of using the AL model. Nevertheless, the group of students who applied the enhanced AL model outperformed the other group in term of performance. Additionally, in learning CTER, it can be observed that students had a good perception in using enhanced AL model, while the group of students who either applied AL model or did not in learning CTER introduction had a good result towards the learning performance. In conclusion, this study showed that the enhanced AL model could improve learning performance, especially for learning advanced CT and can be used for learning CTER. 2021 Thesis NonPeerReviewed application/pdf en http://eprints.utm.my/id/eprint/102856/1/NurulNazihahJamalMSC2021.pdf.pdf Jamal, Nurul Nazihah (2021) Adaptive learning model for learning computational thinking through educational robotic. Masters thesis, Universiti Teknologi Malaysia. http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:150762
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Jamal, Nurul Nazihah
Adaptive learning model for learning computational thinking through educational robotic
description Computational thinking (CT) has been promoted worldwide by educational systems and is an essential skill for technological citizens. In delivering CT, various kinds of educational tools were developed by researchers to support the learning. One of the attractive tools in providing the CT is educational robotic (ER). However, delivering CT to students through ER has many challenges. There is a lack of studies presenting the general view on the integration of ER and CT as both subjects have big scope in terms of teaching and learning. Thus, this study designed a conceptual data model to represent the relationship between CT and ER. In addition to the complexity in determining the suitability of both subjects for students’ learning, students also have differences in their personal traits, resulting in different learning styles and thinking styles. Therefore, this study aimed to enhance an adaptive learning (AL) model for students, which is based on the students’ learning style and knowledge level. The enhanced AL model comprised three sub-models: domain model, student model, and adaptation model. Two case studies were selected, which are learning advance of CT and the introductory of computational thinking through educational robotic (CTER). At the end of the study, it can be observed that the enhanced AL model produced positive results in performance and perception for various student categories. In learning advanced CT, both groups of students exhibited a positive perception of using the AL model. Nevertheless, the group of students who applied the enhanced AL model outperformed the other group in term of performance. Additionally, in learning CTER, it can be observed that students had a good perception in using enhanced AL model, while the group of students who either applied AL model or did not in learning CTER introduction had a good result towards the learning performance. In conclusion, this study showed that the enhanced AL model could improve learning performance, especially for learning advanced CT and can be used for learning CTER.
format Thesis
author Jamal, Nurul Nazihah
author_facet Jamal, Nurul Nazihah
author_sort Jamal, Nurul Nazihah
title Adaptive learning model for learning computational thinking through educational robotic
title_short Adaptive learning model for learning computational thinking through educational robotic
title_full Adaptive learning model for learning computational thinking through educational robotic
title_fullStr Adaptive learning model for learning computational thinking through educational robotic
title_full_unstemmed Adaptive learning model for learning computational thinking through educational robotic
title_sort adaptive learning model for learning computational thinking through educational robotic
publishDate 2021
url http://eprints.utm.my/id/eprint/102856/1/NurulNazihahJamalMSC2021.pdf.pdf
http://eprints.utm.my/id/eprint/102856/
http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:150762
_version_ 1778160792361762816
score 13.211869

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