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Exploration of Project-Based Learning Model for Digital Image Processing Education Based on Design, Implementation, and Evaluation

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Title: Exploration of Project-Based Learning Model for Digital Image Processing Education Based on Design, Implementation, and Evaluation
Language: English
Authors: Te Hu (ORCID 0000-0002-8975-0363), Zongmin Fu, Niya Wang, Jinbin Gui, Qinghe Song, Xiaofan Qian
Source: Education and Information Technologies. 2025 30(14):19473-19509.
Availability: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Peer Reviewed: Y
Page Count: 37
Publication Date: 2025
Document Type: Journal Articles
Reports - Descriptive
Descriptors: Student Projects, Active Learning, Models, Computer Uses in Education, Artificial Intelligence, Video Technology, Teaching Methods, Computer Science Education, Program Proposals, Program Implementation, Documentation, Program Evaluation, Reflection
DOI: 10.1007/s10639-025-13541-5
ISSN: 1360-2357
1573-7608
Abstract: Digital image processing is an integral part of the computer vision field. However, traditional digital image processing teaching methods mainly focus on theoretical knowledge, lacking practical teaching content. To address this issue, this article proposes a project-based learning (PBL) model that consists of four key stages: project proposal, implementation, summary, and evaluation. Instructors design one or more digital image processing projects in the project proposal stage with specific objectives, backgrounds, content, and deliverables. During the implementation stage, students work on the projects under close guidance, applying various teaching methods such as independent learning, teamwork, and academic exchange. The summary stage involves students reflecting on and evaluating their project outcomes, challenges, and potential improvements. Finally, the evaluation stage utilizes a comprehensive, operable, impartial, and traceable system to assess project completion quality and student performance. Through case studies, this project-based learning model demonstrates how it can help students better understand the theoretical knowledge of digital image processing, apply it to practical projects, and improve their ability to apply theoretical concepts to practical operations. Ultimately, this improves teaching quality and facilitates the achievement of teaching goals.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1484024
Database: ERIC
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  Data: Exploration of Project-Based Learning Model for Digital Image Processing Education Based on Design, Implementation, and Evaluation
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  Data: <searchLink fieldCode="AR" term="%22Te+Hu%22">Te Hu</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-8975-0363">0000-0002-8975-0363</externalLink>)<br /><searchLink fieldCode="AR" term="%22Zongmin+Fu%22">Zongmin Fu</searchLink><br /><searchLink fieldCode="AR" term="%22Niya+Wang%22">Niya Wang</searchLink><br /><searchLink fieldCode="AR" term="%22Jinbin+Gui%22">Jinbin Gui</searchLink><br /><searchLink fieldCode="AR" term="%22Qinghe+Song%22">Qinghe Song</searchLink><br /><searchLink fieldCode="AR" term="%22Xiaofan+Qian%22">Xiaofan Qian</searchLink>
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  Data: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
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  Data: Digital image processing is an integral part of the computer vision field. However, traditional digital image processing teaching methods mainly focus on theoretical knowledge, lacking practical teaching content. To address this issue, this article proposes a project-based learning (PBL) model that consists of four key stages: project proposal, implementation, summary, and evaluation. Instructors design one or more digital image processing projects in the project proposal stage with specific objectives, backgrounds, content, and deliverables. During the implementation stage, students work on the projects under close guidance, applying various teaching methods such as independent learning, teamwork, and academic exchange. The summary stage involves students reflecting on and evaluating their project outcomes, challenges, and potential improvements. Finally, the evaluation stage utilizes a comprehensive, operable, impartial, and traceable system to assess project completion quality and student performance. Through case studies, this project-based learning model demonstrates how it can help students better understand the theoretical knowledge of digital image processing, apply it to practical projects, and improve their ability to apply theoretical concepts to practical operations. Ultimately, this improves teaching quality and facilitates the achievement of teaching goals.
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