Adaptive Learning Technologies for Inclusive Education: Enhancing Social Development through Personalized Digital Ecosystems

J. Adharsh Elsin and P. Sathya

International Journal of Scientific Research in Science and Technology, 2024, vol. 11, issue 1, 06-12

Abstract: Adaptive learning technologies, powered by data analytics and artificial intelligence, offer a promising avenue for fostering inclusive education by tailoring learning experiences to individual needs. This article explores the potential of personalised digital ecosystems to enhance social development among learners. By leveraging real-time data on learners' progress, engagement, and preferences, these ecosystems can create collaborative learning opportunities, promote empathy and understanding, and address the diverse needs of learners. Additionally, adaptive learning technologies can facilitate the development of essential social skills, such as communication, problem-solving, and teamwork. Through personalised feedback, adaptive learning technologies can help learners identify their strengths and weaknesses, fostering a sense of self-awareness and confidence. In addition, by providing opportunities for peer interaction and collaboration, these technologies can cultivate empathy, understanding, and respect for diverse perspectives. This paper explores the design implementation strategies for developing adaptive learning technologies that effectively support social interaction, foster a sense of belonging, and contribute to a more equitable and inclusive educational landscape.

Keywords: collaboration; Gamification; translanguaging; curriculum alignment; inclusivity (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
https://ijsrst.com/home/article/view/IJSRST24116502 Abstract page (text/html)
https://ijsrst.com/home/article/download/IJSRST24116502/IJSRST24116502 Full text (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:etm:ijsrst:v11:y2024:i1:id:464

DOI: 10.32628/IJSRST24116502

Access Statistics for this article

More articles in International Journal of Scientific Research in Science and Technology from Technoscience Academy
Bibliographic data for series maintained by Pankaj Sharma ().