Kyparisia A. Papanikolaou

Towards new forms of knowledge communication: the adaptive dimension of a web-based learning environment

Adaptive Educational Hypermedia Systems aim to increase the functionality of hypermedia by making it personalised to individual learners. The adaptive dimension of these systems mainly supports knowledge communication between the system and the learner by adapting the content or the appearance of hypermedia to the knowledge level, goals and other characteristics of each learner. The main objectives are to protect learners from cognitive overload and disorientation by supporting them to find the most relevant content and path in the hyperspace. In the approach presented in this paper, learners’ knowledge level and individual traits are used as valuable information to represent learners’ current state and personalise the educational system accordingly, in order to facilitate learners to achieve their personal learning goals and objectives. Learners’ knowledge level is approached through a qualitative model of the level of performance that learners exhibit with respect to the concepts they study and is used to adapt the lesson contents and the navigation support. Learners’ individual traits and especially their learning style represent the way learners perceive and process information, and are exploited to adapt the presentation of the educational material of a lesson. The proposed approach has been implemented through various adaptation technologies and incorporated into a prototype hypermedia system. Finally, a pilot study has been conducted to investigate system’s educational effectiveness. # 2002 Elsevier Science Ltd. All rights reserved.

INSPIRE: An INtelligent System for Personalized Instruction in a Remote Environment

In this paper we present the architecture of an Adaptive Educational Hypermedia System, named INSPIRE. This particular system, throughout its interaction with the learner, dynamically generates lessons that gradually lead to the accomplishment of the learning goals selected by the learner. The lessons are generated according to the learners knowledge level, learning style and follow his/her progress. The adaptive behavior of the system, the functionality of the various modules and the opportunities offered to learners for intervention are presented.

A Group Formation Tool in an E-Learning Context

In this paper we present a Web-based group formation tool that supports the instructor to automatically create both homogeneous and heterogeneous groups based on up to three criteria and the learner to negotiate the grouping. Moreover, the instructor is allowed to manually group learners based on specific criteria. A discriminative feature of this tool is the use of the fuzzy c-means algorithm for homogeneous grouping, which provides for each learner the probability of belonging to different groups. This information is also provided to the instructor to support him/her in manually exchanging learners or intervening in the initial grouping. Moreover, the learners are informed for the groups formed and they are allowed to negotiate their group assignment. Preliminary evaluation results provide indications for the efficiency of the proposed approach informing homogeneous and heterogeneous groups in a real context.In e-learning initiatives, sequencing problem concerns arranging a particular set of learning units in a suitable succession for a particular learner. Sequencing is usually performed by instructors, who create general and ordered series rather than learner personalized sequences. This paper proposes an innovative intelligent technique for learning object automated sequencing using particle swarms. E-learning standards are promoted in order to ensure interoperability. Competencies are used to define relations between learning objects within a sequence, so that the sequencing problem turns into a permutation problem and AI techniques can be used to solve it. Particle Swarm Optimization (PSO) is one of such techniques and it has proven with good performance solving a wide variety of problems. An implementation of the PSO, for learning object sequencing, is presented and its performance in a real scenario is discussed.

Personalizing Assessment in Adaptive Educational Hypermedia Systems

In this paper, we present a comprehensive framework for assessment, developed through the web-based module named PASS-Personalized ASSessment, which can be integrated in an Adaptive Educational Hypermedia System to provide personalized assessment. PASS estimates learners performance through multiple assessment options - pre-test, self-assessment and summative assessment - tailored to learners responses. The adaptive functionality of PASS, which is mainly based on the adaptive testing and the adaptive questions techniques, is described. The first results from the formative evaluation of PASS are encouraging, concerning the total number of questions posed to estimate learners knowledge level, which is usually less than the maximum needed and the accuracy of the outcome results compared to the estimations of the expert-tutor.

Towards a computationally intelligent lesson adaptation for a distance learning course

A neuro-fuzzy approach is introduced to implement lesson adaptation in a Web-based course. Several key points that affect the effectiveness of an adaptive learning environment are investigated the development of the educational material, the structure of the domain knowledge, the instructional design and the evaluation of the learner knowledge under uncertainty. The proposed approach allows the generation of the content of a hypermedia page from pieces of educational material based on goal-oriented teaching and making use of the background knowledge of the learner.

Promoting Collaboration in a Project-Based E-Learning Context

Abstract In this paper we investigate the value of collaboration scripts for promoting metacognitive knowledge in a project-based e-learning context. In an empirical study, 82 students worked individually and in groups on a project using the e-learning environment MyProject, in which the life cycle of a project is inherent. Students followed a particular collaboration script that combines individual and collaborative activities, aiming to promote individual and socially shared reflective thinking during the planning and evaluation phases of the project. We analysed group discussions and evaluation questionnaires, and the results provide evidence about the importance of the design variables considered in the collaboration script for cultivating metacognitive knowledge, such as project phase, roles undertaken by students, degree and type of interaction, type of activities and products, and activity sequencing.

Fuzzy Inference for Student Diagnosis in Adaptive Educational Hypermedia

In this paper we propose a method that implements student diagnosis in the context of the Adaptive Hypermedia Educational System INSPIRE - INtelligent System for Personalized Instruction in a Remote Environment. The method explores ideas from the fields of fuzzy logic and multicriteria decision-making in order to deal with uncertainty and incorporate in the system a more complete and accurate description of the experts knowledge as well as flexibility in students assessment. To be more precise, an inference system, using fuzzy logic and the Analytic Hierarchy Process to represent the knowledge of the teacher-expert on students diagnosis, analyzes students answers to questions of varying difficulty and importance, and estimates the students knowledge level. Preliminary experiments with real students indicate that the method is characterized by effectiveness in handling the uncertainty of student diagnosis, and is found to be closer to the assessment performed by a human teacher, when compared to a more traditional method of assessment.

Computational intelligence in adaptive educational hypermedia

In this paper neuro-fuzzy synergism is applied to implement content sequencing in adaptive hypermedia systems. The level of understanding of the learner is used to construct lessons adapted to the learners knowledge goals and level of expertise on the domain concepts s/he has already studied. The learners evaluation is based on defining appropriate fuzzy sets and relate learners response with appropriate knowledge and cognitive characterizations. A connectionist-based structure of the domain knowledge is adopted for representing knowledge and inferring the planning strategy for generating the hypermedia page from pieces of educational material. The fuzziness associated with the evaluation of the learner is handled well by the proposed connectionist architecture.

A connectionist approach for adaptive lesson presentation in a distance learning course

The issue of implementing adaptation in a Web-based course using an adaptive lesson presentation (or content-level adaptation) method is a promising direction of research. The goal is to adapt dynamically the supplied educational material so that it meets the individual educational needs of each particular learner. An important aspect in producing a learner-adapted system is the structuring of the domain knowledge in such a way that it will be possible to do adaptations. In this paper, a connectionist-based structure of the domain knowledge model is adopted. This approach allows generating the content of a hypermedia page from pieces of educational material based on a goal-oriented way of teaching and making use of the background knowledge of the learner.

Investigating Influences Among Individuals and Groups in a Collaborative Learning Setting

The research presented in this paper aims at investigating factors that reflect Individual to Group I-to-G and Group to Individual G-to-I influences in a collaborative learning setting. An empirical study is described, in which students worked on concept mapping tasks, individually and in groups. Analysing the individual and group concept maps, specific factors were identified that account for G-to-I and I-to-G influences reflecting peer interaction and impact on group and individual achievement during and after collaboration. Dependences were also identified between individual/group characteristics, such as knowledge and style, and individual/group progress. Finally, a discussion about how these factors may inform the learner and group models of the adaptive concept mapping environment COMPASS is given.