Teaching tasks in an adaptive learning environment

TelE-Learning, 2002

Tdx, 2004

2003

This paper describes the methodology of an intelligent agent for building a self-adaptive course on the Web. An important task, therefore, is to combine adaptability with the learner-driven course in order to get a self-adaptive mechanism. For this, we have suggested a new structure for a web course. Based on this structure, we have suggested a new method to evaluate the granularity level of each segment on the course. This method evaluates the segment that a learner most prefers. To achieve this goal, we design and implement an agent called a confidence agent. Our experiment to evaluate our adaptation method shows that our approach greatly improves the domain model, and presents a course better related to the learner's needs.

Expert Systems With Applications, 2011

This paper proposes a model of the componentfor a virtual learning environment (VLE), which enriches it with some adaptive and intelligent features. Such a model explains how the VLE as a system should direct its actions towards the maintenance of learner needs in selecting, studying and controlling the study topics and evaluating the obtained knowledge. The adaptivity is supposed to be understood such as the system’s ability to form and, during the learning process, uniformly update curriculum that satisfies the needs of the learner, and intelligence is expressed by the ability to initiate actions and, referring to the learning process, perform decision making. The implantation of such a component into a VLE enriches the spectrum of the student’s own abilities to purposefully, without the extra help of a tutor, seek some level of acquisition.

Springer eBooks, 2020

To improve the learning process, the evolution of learner's characteristics (cognitive, affective, prior knowledge, workflow, organization, ...) must be taken into account during the personalization or adaptation. This requires generating several scenarios (a description of activities, their order and links in the learning sequence as well as the expected outcome for the learner) adapted to the identified profiles. We propose a model which aims at improving learners' learning processes by giving them control over two key aspects: (1) the steps of the learning scenario to be followed: after each learning goal is completed, the learner chooses the next one among several possible ones (in terms of their current knowledge) while respecting pedagogical constraints (time and quality of the solutions produced according to satisfaction thresholds); (2) the assessment mode: the learner chooses a mode corresponding to their own goals in terms of mastery, while respecting the minimum thresholds set by the teacher. We assess our approach with learners in terms of (a) adequacy of the model with learners' expectations and (b) usability of the system through self-report questionnaires and an analysis of the data collected over 16 learners who used an implementation of our system on the LMS (Learning Management System) in the context of a real computer course. The results reveal that our model is mostly well-received, that various scenarios are indeed followed by the learners and that the 3 assessment modes have been used by learners.

2011

Development of current society requires integration of information technology to every sector, including education. The idea of adaptive teaching in e-learning environment is based on paying attention and giving support to various learning styles. More effective, user friendly thus better quality education can be achieved through such an environment. Learning can be influenced by many factors. In the paper we deal with such factors as student’s personality and qualities – particularly learning style and motivation. In addition we want to prepare study materials and study environment which respects students’ differences. Adaptive e-learning means an automated way of teaching which adapts to different qualities of students which are characteristic for their learning styles. In the last few years we can see a gradual individualization of study not only in distance forms of study but also with full-time study students. Instructional supports, namely those of e-learning, should take this...

This paper presents the ADAPT project, a distance adaptative learning platform whose domain application is, in an initial phase, for digital systems. This LMS (Learning Management System) makes use of some Artificial Intelligence (AI) models and techniques has the ability to adapt course contents to the learning preferences of each student. The followed approaches include Case-Based Reasoning, Educational Adaptive Systems, Intelligent Tutoring Systems, Link-Mining and Evolutionary Computation. Through theses techniques this platform enables: The Capture of students performance and learning style, cases of success and failure and the correspondent appropriateness of the learning content of each profile; The automatic learning, based on the paths of better performance also on success and failure cases, is generated. This paper focuses on the description of the use of alternative representations of the content, in order to accommodate the different learning styles of students. However, an e-learning system to be successful should motivate the student through pedagogic and interactive techniques. So, in this work we gave special attention to the use of interactive animations through appropriate metaphors leading to a better understanding of the students, especially those who have a kinesthetic profile.

2008

A Simple Web-based Adaptive Educational System (SWAES) An adaptive educational system is complex to model. Such a system should allow various didactic, educational and student styles and is traditionally divided into four modules for analysis and building: Domain Knowledge Base, Tutoring, the Student Interface, and the Student. In particular, the system should adapt to differences between students and the changes in a particular student. One of the main problems when trying to develop an adaptive educational system is that definitions used for instructional design by psychologists and pedagogy experts are vague, while developers work with concrete terms like variables, stochastic values and objects. To make the concept of an adaptive educational system more concrete, this work models the simplest possible adaptive educational system that could exist. The contribution of the paper is that it gives a good description of a basic adaptive educational system and reasons about concrete so...