Curriculum design using artificial intelligence (AI) back propagation method
Open accessAbstract
With the rapid changes in technologies and industry requirements, goal for the engineering education can be set as the job roles and defining the curriculum of the Program as required to meet the job role. The curriculum design can be done with designing the curriculum and defining the expected outcome of the Program. Then based on the expected outcome, the gap can be identified and the curriculum can be defined to bridge the gap between the Program and the expected outcome. Instead, the Job Roles and the skills required skills can be taken as the as the starting point and the courses required are identified to attain this outcome. In turn, the pre requisite courses can be identified and further prerequisite courses can be identified. The technology of Artificial Intelligence (AI) back propagation method can be effectively used to achieve this. This paper gives an example of such method applied for identifying the curriculum required to meet the job roles in the area of Internet of Things (IoT).
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Applying AI in trend analysis and identifying the information and abilities students will need in the future can help create new curricula and programmes.
“Applying AI in trend analysis and identifying the information and abilities students will need in the future can help create new curricula and programmes.”
From Artificial Intelligence Revolutionizing the Field of Medical Education (2023) · cites this paper as [42]
In the last decade, several works have used AI-informed curriculum design approaches.
“however the last decade saw several works using AI-informed curriculum design approaches.”
From Proactive and reactive engagement of artificial intelligence methods for education: a review (2023) · cites this paper as Somasundaram et al., 2020
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“The gap between the programme and the anticipated result may be determined using the expected result, and the curriculum can be developed to close that gap [42].”
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- Authors
- Somasundaram, M., Latha, P., & Pandian, S. A. S.
- Venue
- Procedia Computer Science
- Publisher
- Elsevier BV
- Published
- 2020
- Volume
- 172
- Pages
- 134-138
- ISSN
- 1877-0509 (ISSN-L)
- OpenAlex
- W3036814778
- Cited by
- 33
- References
- 0
- Citations by year
- 2026: 3 · 2025: 6 · 2024: 9 · 2023: 8 · 2022: 1 · 2021: 5 · 2020: 1
- FWCI
- 7.84
- Type
- conference paper
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- Locations
- Procedia Computer Science (publishedVersion, cc-by-nc-nd)
- Topics
- Physical Sciences › Engineering › Media Technology › Engineering Education and Curriculum Development
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Physical Sciences › Computer Science › Artificial Intelligence › Edcuational Technology Systems
- Keywords
- curriculum development, artificial neural networks, backpropagation, engineering education, job roles, skill requirements, IoT education
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