scholarly journals Designing and Incorporating Personalized Learning Analytics: Examining Self-Regulated Meaningful Learning

Author(s):  
Muhammad Izzat Izzuddin bin Zainuddin ◽  
Hairulliza Mohamad Judi
Author(s):  
Darcio Costa Nogueira Junior ◽  
Isadora Valle Sousa ◽  
Frederico Cordeiro Martins ◽  
Marta Macedo Kerr Pinheiro

The present work aims at addressing how the use of Learning Analytics (LA) has enabled the retrieval of learning information by the student oneself, by analyzing data availability, self-management and student autonomy in learning processes inside and outside virtual environments. The bibliographic research conducted had a qualitative nature and consisted of a narrative literature review anchored in the theoretical foundations of information (information retrieval and representation) and Learning Analytics. Two relevant user case studies that dealt with LA were selected from the researched articles - the first analyzed the user approach in an adapted learning context with LA whereas the second analyzed the user approach in a personalized learning context with LA. One concluded that the student, as an information user, still has little access to an effective retrieval of what was consolidated throughout one’s own learning process. Besides, in relation to the effectiveness of LA, in the context of adapted and personalized learning, there was a perceived increase in student performance with regard to the use of activities and tasks.


Author(s):  
Mohamed Amine Chatti ◽  
Arham Muslim

Personalization is crucial for achieving smart learning environments in different lifelong learning contexts. There is a need to shift from one-size-fits-all systems to personalized learning environments that give control to the learners. Recently, learning analytics (LA) is opening up new opportunities for promoting personalization by providing insights and understanding into how learners learn and supporting customized learning experiences that meet their goals and needs. This paper discusses the Personalization and Learning Analytics (PERLA) framework which represents the convergence of personalization and learning analytics and provides a theoretical foundation for effective analytics-enhanced personalized learning. The main aim of the PERLA framework is to guide the systematic design and development of effective indicators for personalized learning.


Author(s):  
Susan Bull ◽  
Matthew D. Johnson ◽  
Carrie Demmans Epp ◽  
Drew Masci ◽  
Mohammad Alotaibi ◽  
...  

2021 ◽  
Author(s):  
Nurfadhlina Mohd Sharef ◽  
Masrah Azrifah Azmi Murad ◽  
Evi Indriasari Mansor ◽  
Nurul Amelina Nasharuddin ◽  
Muhd Khaizer Omar ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document