Title :
Learner Modeling in Academic Networks
Author :
Chatti, Mohamed Amine ; Dugoija, Darko ; Thus, Hendrik ; Schroeder, Ulrik
Author_Institution :
Inf. 9 (Learning Technol.), RWTH Aachen Univ., Aachen, Germany
Abstract :
Learning analytics (LA) deals with the development of methods that harness educational data sets to support the learning process. To achieve particular learner entered LA objectives such as intelligent feedback, adaptation, personalization, or recommendation, learner modeling is a crucial task. Learner modeling enables to achieve adaptive and personalized learning environments, which are able to take into account the heterogeneous needs of learners and provide them with tailored learning experience suited for their unique needs. In this paper, we focus on learner modeling in academic networks. We present theoretical, design, implementation, and evaluation details of PALM, a service for personal academic learner modeling. The primary aim of PALM is to harness the distributed publication information to build an academic learner model.
Keywords :
data analysis; data visualisation; educational administrative data processing; LA; PALM model; academic networks; educational data set; learner needs; learning analytics; learning process; personal academic learner modeling; Abstracts; Adaptation models; Analytical models; Arrays; Data mining; Data models; Social network services; adaptation; interest mining; learner modeling; learning analytics; personalization;
Conference_Titel :
Advanced Learning Technologies (ICALT), 2014 IEEE 14th International Conference on
Conference_Location :
Athens
DOI :
10.1109/ICALT.2014.42
