The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
AI-Driven Learning Analytics for Personalized Feedback and Assessment in Higher Education
|
|
Author(s): Tarun Kumar Vashishth (IIMT University, India), Vikas Sharma (IIMT University, India), Kewal Krishan Sharma (IIMT University, India), Bhupendra Kumar (IIMT University, India), Rajneesh Panwar (IIMT University, India)and Sachin Chaudhary (IIMT University, India)
Copyright: 2024
Pages: 25
Source title:
Using Traditional Design Methods to Enhance AI-Driven Decision Making
Source Author(s)/Editor(s): Tien V. T. Nguyen (Industrial University of Ho Chi Minh City, Vietnam)and Nhut T. M. Vo (National Kaohsiung University of Science and Technology, Taiwan)
DOI: 10.4018/979-8-3693-0639-0.ch009
Purchase
|
Abstract
Advancements in artificial intelligence (AI) and learning analytics have opened up new possibilities for personalized education in higher education institutions. This chapter explores the potential of AI-driven learning analytics in higher education, focusing on its application in personalized feedback and assessment. By leveraging AI algorithms and data analytics, personalized feedback can be provided to students, targeting their specific strengths and areas for improvement. Adaptive and formative assessments can also be facilitated through AI-driven learning analytics, enabling personalized and accurate evaluation of students' knowledge and skills. However, ethical considerations, implementation challenges, and faculty training are crucial aspects that must be addressed for successful adoption. As technology continues to evolve, embracing AI-driven learning analytics can enhance student engagement, support individualized learning, and optimize educational outcomes.
Related Content
|
Kamel Mouloudj, Vu Lan Oanh LE, Achouak Bouarar, Ahmed Chemseddine Bouarar, Dachel Martínez Asanza, Mayuri Srivastava.
© 2024.
20 pages.
|
|
José Eduardo Aleixo, José Luís Reis, Sandrina Francisca Teixeira, Ana Pinto de Lima.
© 2024.
52 pages.
|
|
Jorge Figueiredo, Isabel Oliveira, Sérgio Silva, Margarida Pocinho, António Cardoso, Manuel Pereira.
© 2024.
24 pages.
|
|
Fatih Pinarbasi.
© 2024.
20 pages.
|
|
Stavros Kaperonis.
© 2024.
25 pages.
|
|
Thomas Rui Mendes, Ana Cristina Antunes.
© 2024.
24 pages.
|
|
Nuno Geada.
© 2024.
12 pages.
|
|
|