Treffer: Using Multimodal Learning Analytics to Understand Effects of Block-Based and Text-Based Modalities on Computer Programming

Title:
Using Multimodal Learning Analytics to Understand Effects of Block-Based and Text-Based Modalities on Computer Programming
Language:
English
Authors:
Dan Sun, Fan Ouyang (ORCID 0000-0002-4382-1381), Yan Li, Chengcong Zhu, Yang Zhou
Source:
Journal of Computer Assisted Learning. 2024 40(3):1123-1136.
Availability:
Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Peer Reviewed:
Y
Page Count:
14
Publication Date:
2024
Document Type:
Fachzeitschrift Journal Articles<br />Reports - Research
Education Level:
Secondary Education
Geographic Terms:
DOI:
10.1111/jcal.12939
ISSN:
0266-4909
1365-2729
Entry Date:
2024
Accession Number:
EJ1424086
Database:
ERIC

Weitere Informationen

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.

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