Supporting Adaptive Learning with a Student Model Repository and Shared Adaptive Variables

2010 ◽  
pp. 1-10 ◽  
Author(s):  
Bakhtiyor Bahritidinov ◽  
Jorge Suárez de Lis ◽  
Eduardo Sánchez ◽  
Manuel Lama
Keyword(s):  
Adaptive Learning ◽  
Student Model ◽  
Model Repository

A Strategy to Join Adaptive and Reputation-Based Social-Collaborative E-Learning, Through the Zone of Proximal Development

2013 ◽  
Vol 11 (3) ◽  
pp. 12-31 ◽  
Author(s):  
Maria De Marsico ◽  
Andrea Sterbini ◽  
Marco Temperini
Keyword(s):  
Collaborative Learning ◽  
Adaptive Learning ◽  
Zone Of Proximal Development ◽  
Learning Activities ◽  
Proximal Development ◽  
Student Model ◽  
Web Based ◽  
E Learning ◽  
Learning Paths ◽  
The One

The educational concept of “Zone of Proximal Development”, introduced by Vygotskij, stems from the identification of a strong need for adaptation of the learning activities, both traditional classroom and modern e-learning ones, to the present state of learner’s knowledge and abilities. Furthermore, Vygotskij’s educational model includes a strong bent towards social and collaborative learning. The joint answer to these two trends can be concretely implemented through a tight integration between personalized learning paths and collaborative learning activities. Along this line, the authors designed the combination of the functions of two pre-existing prototypes of web-based systems, to investigate how the above integration can merge adaptive and social e-learning. LECOMPS is a web-based e-learning environment for the automated construction of adaptive learning paths. SOCIALX is a web-based system for shared e-learning activities, which implements a reputation system to provide feedback to its participants. The authors propose a two-way tunneling strategy to integrate the above prototypes. The result is twofold: on the one hand the use of the student model supported by LECOMPS in an adaptive e-learning course is extended to support choosing exercise activities delivered through SOCIALX; on the other hand the reputation and the skills gained during social-collaborative activities are used to update the student model. Under the social perspective induced by the integration, the authors present a mapping between the student model and the definition of Vygotskij’s Autonomous Problem Solving and Proximal Development regions, with the aim to provide the learner with better guidance, especially in the selection of available social learning activities.

scholarly journals Research on the Construction of a Student Model of an Adaptive Learning System Based on Cognitive Diagnosis Theory

2020 ◽  
Vol 12 (4) ◽  
pp. 20-31
Author(s):  
Yang Zhao ◽  
Yaqin Fan ◽  
Mingrui Yin ◽  
Cheng Fang
Keyword(s):  
Online Education ◽  
Adaptive Learning ◽  
Strong Support ◽  
Individual Characteristics ◽  
Learning System ◽  
Cognitive Diagnosis ◽  
Selection Strategy ◽  
Student Model ◽  
Adaptive Learning System ◽  
The Individual

With the promotion of online education, the adaptive learning system has attracted attention due to its good curriculum recommendation function. The student model is an important interface between the adaptive learning system and the user, reflecting the individual characteristics, knowledge status, and cognitive ability of the student. The accuracy of the information in the student model directly affects the quality of the system recommendation service. The traditional student model only judges students based on the basic information and simple test scores. This paper introduces the self-adaptive item bank and adaptive item selection strategy based on the cognitive diagnosis theory that dynamically detects the students' knowledge and analyzes the state according to the answering habits and knowledge mastering status of different students. This paper analyzes and contrasts a variety of traditional cognitive diagnosis theories and proposes a mixed cognitive diagnosis question bank and a selection strategy model to provide strong support for the construction of student models.

Research on Student Model of Adaptive Learning System Based on Semantic Web

2013 ◽  
Vol 739 ◽  
pp. 562-565
Author(s):  
Jian Qiong Xiao
Keyword(s):  
Semantic Web ◽  
Learning Style ◽  
Adaptive Learning ◽  
Learning System ◽  
Cognitive State ◽  
Student Model ◽  
Four Dimensions ◽  
Student Models ◽  
Adaptive Learning System ◽  
State Learning

This paper came up with introducing four dimensions: learning mood, cognitive state, learning style and interest preference and so on for the semantic web, based on the analysis the present situation student models at home and abroad. Realized to classify learners and establish student models which used an improved similarity algorithm, and the student model applied to adaptive learning system, which not only could solve the lack semantic in adaptive learning system, and greatly improves the practicability, intelligent and personalized.

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