Y. Abinivesh Reddy,
Satyam Kumar Mishra,
Shashwat Kumar,
Samarth B.,
- Student Information Science and Engineering, BMS Institute of Technology and Management, Bengaluru Karnataka India
- Student Information Science and Engineering, BMS Institute of Technology and Management, Bengaluru Karnataka India
- Student Information Science and Engineering, BMS Institute of Technology and Management, Bengaluru Karnataka India
- Student Information Science and Engineering, BMS Institute of Technology and Management, Bengaluru Karnataka India
Abstract
FlexEdify is an innovative adaptive learning platform revolutionizing the educational experience by customizing content to meet the unique needs of each student. Utilizing state-of-the-art machine learning algorithms, the system promptly analyzes students’ real-time errors, meticulously storing them in a centralized database. This database serves as the cornerstone for adaptive questioning, allowing the platform to dynamically adjust subsequent content based on individual weaknesses. The platform features a user-friendly interface, guaranteeing accessibility for students of varying proficiency levels. Immediate feedback and analytics empower learners to comprehend and conquer their mistakes effectively. FlexEdify’s personalized learning paths, coupled with a comprehensive error database, collectively present a robust tool for educators, streamlining the creation of targeted remedial content and fostering a more efficient learning process. This technological advancement signifies a substantial leap in education technology, promoting both student mastery and heightened engagement. FlexEdify not only supports diverse learning styles but also provides educators with detailed insights into student performance, enabling more informed instructional decisions and a more responsive educational environment. Through continuous adaptation and feedback, FlexEdify ensures that learning is both effective and engaging, preparing students for future academic success.
Keywords: Adaptive learning, personalized education, real-time feedback, machine learning algorithms, educational technology
[This article belongs to Journal of Multimedia Technology & Recent Advancements(jomtra)]
References
- Kem D. Personalised and adaptive learning: emerging learning platforms in the era of digital and smart learning. Int J Soc Sci Human Res. 2022; 5 (2): 385–391.
- El-Sabagh HA. Adaptive e-learning environment based on learning styles and its impact on development students’ engagement. Int J Educ Technol Higher Educ. 2021; 18 (1): Article 53.
- Kabudi T, Pappas I, Olsen DH. AI-enabled adaptive learning systems: a systematic mapping of the literature. Computers Educ Artif Intell. 2021; 2: 100017.
- Verdú Pérez E, Regueras Santos LM, Verdú Pérez MJ, Castro Fernández JP, Pérez Juárez MÁ. An analysis of the research on adaptive learning: the next generation of e-learning. WSEAS Trans Inform Sci Appl. 2008; 5 (6): 859–868.
- Ling HC, Chiang HS. Learning performance in adaptive learning systems: a case study of web programming learning recommendations. Front Psychol. 2022; 13: 770637.
- Joshi MA. Adaptive learning through artificial intelligence. Int J Integr Educ. 2024; 7 (2): 41–43.
- Peng H, Ma S, Spector JM. Personalized adaptive learning: an emerging pedagogical approach enabled by a smart learning environment. Smart Learn Environ. 2019; 6 (1): 1–4.
- Jing Y, Zhao L, Zhu K, Wang H, Wang C, Xia Q. Research landscape of adaptive learning in education: a bibliometric study on research publications from 2000 to 2022. Sustainability. 2023; 15 (4): 3115.
- Zawacki-Richter O, Marín VI, Bond M, Gouverneur F. Systematic review of research on artificial intelligence applications in higher education – where are the educators? Int J Educ Technol Higher Educ. 2019; 16 (1): 1–27.
- Fadieieva LO. Adaptive learning: a cluster-based literature review (2011-2022). Educ Technol Q. 2023; 2023 (3): 319–366.
- Minn S. AI-assisted knowledge assessment techniques for adaptive learning environments. Computers Educ Artif Intell. 2022; 3: 100050.
Journal of Multimedia Technology & Recent Advancements
Volume | 11 |
Issue | 02 |
Received | May 4, 2024 |
Accepted | July 15, 2024 |
Published | August 2, 2024 |