Designing a Workplace Digital Curriculum Based on Artificial Intelligence Components

Document Type : Original Article

Authors

1 Ph.D Candidate, Department of Educational Sciences, Faculty of Education and Psychology, Shahid Beheshti University E-mail: fa_fathi@sbu.ac.ir

2 Professor of the Educational Sciences Department, Faculty of Educational Sciences and psychology, Shahid Bahshti University, Tehran, Iran. E-mail: k-fathi@sbu.ac.ir

3 Assisstant Professor of the Educational Sciences Department, faculty of Educational Sciences and psychology, Shahid Bahshti University, Tehran, Iran. E-mail: es.jafari@sbu.ac.ir

4 Assisstant Professor of Computer Engineering, Faculty of engineering and computer science, Shahid bahshti University, Tehran, Iran. E-mail: mo_vahidi@sbu.ac.ir

Abstract
Purpose: developments and the emergence of artificial intelligence in the field of learning education, especially in the field of training managers and human resources, require fundamental changes and innovation in educational approaches.
In this regard, the aim of this study was to design a workplace digital curriculum based on AI components.
Methodology: The present research is based on purpose, application and in terms of how data is collected, qualitative design. the various qualitative methods, the foundation data theory method was used with charmaz's constructivist approach.
The current research community is all specialists in the field of curriculum, educational technology, educational technology and artificial intelligence, and the media included 23 specialists. In order to gather information, a semi-structured interview was used to view and study documents. In order to analyze the information in this study, the three-step Susan freeze method included Attention, collection and thinking with the help of Atlas T.I 7 software.
Findings: The phase curriculum pattern included the Phase 1 curriculum (characteristic pattern-based learning, classification and content organization, linear learning, external supervised learning, reinforcement learning and interlinguistic perception), the Phase 2 curriculum (blended knowledge in learning, learning optimization, learning from incomplete data, reasoning-based learning, predicting learning trends and facing learning issues), and the Phase 3 curriculum (facing nonlinear issues, deep learning, unsupervised learning, learning expertise, semantic similarity, self-directed learning, and flexibility in learning).
Conclusion: This model is based on AI phase logic and can help improve design of workplace digital curriculum. Based on background studies, no research was found to be able to organize a workplace digital curriculum in this way, and therefore, the findings of the present and final output research were completely unique.

Keywords


References
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