Using multimodal learning analytics to understand effects of block‐based and text‐based modalities on computer programming.
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| Title: | Using multimodal learning analytics to understand effects of block‐based and text‐based modalities on computer programming. |
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| Authors: | Sun, Dan, Ouyang, Fan, Li, Yan, Zhu, Chengcong, Zhou, Yang |
| Source: | Journal of Computer Assisted Learning. Jun2024, Vol. 40 Issue 3, p1123-1136. 14p. |
| Subjects: | Learning analytics, High schools, Computer software, Research funding, Data analytics, Research methodology, Learning strategies, Programmed instruction |
| Geographic Terms: | China |
| Abstract: | Background: With the development of computational literacy, there has been a surge in both research and practice application of text‐based and block‐based modalities within the field of computer programming education. Despite this trend, little work has actually examined how learners engaging in programming process when utilizing these two major programming modalities, especially in the context of secondary education settings. Objectives: To further compare programming effects between and within text‐based and block‐based modalities, this research conducted a quasi‐experimental research in China's secondary school. Methods: An online programming platform, Code4all, was developed to allow learners to program in text‐based and block‐based modalities. This research collected multimodal data sources, including programming platform data, process data, and performance data. This research further utilized multiple learning analytics approaches (i.e., clustering analysis, click stream analysis, lag‐sequential analysis and statistics) to compare learners' programming features, behavioural patterns and knowledge gains under two modalities. Results and Conclusions: The results indicated that learners in text‐based modality tended to write longer lines of code, encountered more syntactical errors, and took longer to attempt debugging. In contrast, learners in block‐based modality spent more time operating blocks and attempt debugging, achieving better programming knowledge performances compared to their counterparts. Further analysis of five clusters from the two modalities revealed discrepancies in programming behavioural patterns. Implications: Three major pedagogical implications were proposed based on empirical research results. Furthermore, this research contributed to the learning analytics literature by integrating process‐oriented and summative analysis to reveal learners' programming learning quality. Lay Description: What is currently known about the subject matter: Programming has the potential to improve learners' higher‐order thinking skills.Block‐based and text‐based modalities are two major instructional methods.There has been a growing interest to understand how learning occurs in two modes.Most previous work has evaluated two modalities based on learners' knowledge, skills, and attitudes. What this paper adds: Code4all allows learners to programming in text‐based and block‐based modalities.Quasi‐experimental research was conducted to examine block‐based and text‐based programming modalities.Multimodal learning analytics were used to compare programming under two modalities.Learners' programming features, behaviouralbehavioral patterns, and knowledge gains were identified under two modalities. The implications of study findings for practitioners: Instructors should integrate text‐based and block‐based modalities into programming courses.Process‐oriented assessment should be integrated with summative assessment. Adaptive, timely scaffoldings should be provided with the external support (this should be marked like above two points). [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Computer Assisted Learning is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
| FullText | Text: Availability: 0 |
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| Header | DbId: pbh DbLabel: Psychology and Behavioral Sciences Collection An: 177193471 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Using multimodal learning analytics to understand effects of block‐based and text‐based modalities on computer programming. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Sun%2C+Dan%22">Sun, Dan</searchLink><br /><searchLink fieldCode="AR" term="%22Ouyang%2C+Fan%22">Ouyang, Fan</searchLink><br /><searchLink fieldCode="AR" term="%22Li%2C+Yan%22">Li, Yan</searchLink><br /><searchLink fieldCode="AR" term="%22Zhu%2C+Chengcong%22">Zhu, Chengcong</searchLink><br /><searchLink fieldCode="AR" term="%22Zhou%2C+Yang%22">Zhou, Yang</searchLink> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Computer+Assisted+Learning%22">Journal of Computer Assisted Learning</searchLink>. Jun2024, Vol. 40 Issue 3, p1123-1136. 14p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Learning+analytics%22">Learning analytics</searchLink><br /><searchLink fieldCode="DE" term="%22High+schools%22">High schools</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+software%22">Computer software</searchLink><br /><searchLink fieldCode="DE" term="%22Research+funding%22">Research funding</searchLink><br /><searchLink fieldCode="DE" term="%22Data+analytics%22">Data analytics</searchLink><br /><searchLink fieldCode="DE" term="%22Research+methodology%22">Research methodology</searchLink><br /><searchLink fieldCode="DE" term="%22Learning+strategies%22">Learning strategies</searchLink><br /><searchLink fieldCode="DE" term="%22Programmed+instruction%22">Programmed instruction</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22China%22">China</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Background: With the development of computational literacy, there has been a surge in both research and practice application of text‐based and block‐based modalities within the field of computer programming education. Despite this trend, little work has actually examined how learners engaging in programming process when utilizing these two major programming modalities, especially in the context of secondary education settings. Objectives: To further compare programming effects between and within text‐based and block‐based modalities, this research conducted a quasi‐experimental research in China's secondary school. Methods: An online programming platform, Code4all, was developed to allow learners to program in text‐based and block‐based modalities. This research collected multimodal data sources, including programming platform data, process data, and performance data. This research further utilized multiple learning analytics approaches (i.e., clustering analysis, click stream analysis, lag‐sequential analysis and statistics) to compare learners' programming features, behavioural patterns and knowledge gains under two modalities. Results and Conclusions: The results indicated that learners in text‐based modality tended to write longer lines of code, encountered more syntactical errors, and took longer to attempt debugging. In contrast, learners in block‐based modality spent more time operating blocks and attempt debugging, achieving better programming knowledge performances compared to their counterparts. Further analysis of five clusters from the two modalities revealed discrepancies in programming behavioural patterns. Implications: Three major pedagogical implications were proposed based on empirical research results. Furthermore, this research contributed to the learning analytics literature by integrating process‐oriented and summative analysis to reveal learners' programming learning quality. Lay Description: What is currently known about the subject matter: Programming has the potential to improve learners' higher‐order thinking skills.Block‐based and text‐based modalities are two major instructional methods.There has been a growing interest to understand how learning occurs in two modes.Most previous work has evaluated two modalities based on learners' knowledge, skills, and attitudes. What this paper adds: Code4all allows learners to programming in text‐based and block‐based modalities.Quasi‐experimental research was conducted to examine block‐based and text‐based programming modalities.Multimodal learning analytics were used to compare programming under two modalities.Learners' programming features, behaviouralbehavioral patterns, and knowledge gains were identified under two modalities. The implications of study findings for practitioners: Instructors should integrate text‐based and block‐based modalities into programming courses.Process‐oriented assessment should be integrated with summative assessment. Adaptive, timely scaffoldings should be provided with the external support (this should be marked like above two points). [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Computer Assisted Learning is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1111/jcal.12939 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 14 StartPage: 1123 Subjects: – SubjectFull: Learning analytics Type: general – SubjectFull: High schools Type: general – SubjectFull: Computer software Type: general – SubjectFull: Research funding Type: general – SubjectFull: Data analytics Type: general – SubjectFull: Research methodology Type: general – SubjectFull: Learning strategies Type: general – SubjectFull: Programmed instruction Type: general – SubjectFull: China Type: general Titles: – TitleFull: Using multimodal learning analytics to understand effects of block‐based and text‐based modalities on computer programming. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Sun, Dan – PersonEntity: Name: NameFull: Ouyang, Fan – PersonEntity: Name: NameFull: Li, Yan – PersonEntity: Name: NameFull: Zhu, Chengcong – PersonEntity: Name: NameFull: Zhou, Yang IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 02664909 Numbering: – Type: volume Value: 40 – Type: issue Value: 3 Titles: – TitleFull: Journal of Computer Assisted Learning Type: main |
| ResultId | 1 |
