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Intelligent Tutoring Systems in E-Learning Environments: Design, Implementation and Evaluation

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Anatomy of Student Models in Adaptive Learning Systems: A Systematic Literature Review of Individual Differences from 2001 to 2013

This study brings an evidence-based review of user individual characteristics employed as sources of adaptation in recent adaptive learning systems. Twenty-two user individual characteristics were explored in a systematically designed search procedure, while 17 of them were identified as sources of adaptation in final selection. The content analysis of 98 selected publications that include evidence of adaptation efficiency is conducted. The quantitative representation of the findings shows current trends in the research of individual differences, as well as the tendencies of their further employment in student modeling. The article contributes to the body of knowledge on user individual differences and consequently to the research and development of adaptive learning systems. Additional contribution of the study is in-depth description of development and evaluation of the search strategy which makes the method easily replicable as well as suitable for modification and employment in systematic literature review in any research field.

Enabling agent architecture through an RDF query and inference engine

Over the past several years, there has been an increase in the number of heterogeneous information sources, mainly due to the rise of the Internet. In order to select the desired information, large quantities of information must be searched and examined. Various AI techniques are available for such tasks, relying on information semantics. To implement these techniques on a variety of platforms, a common basis for the interchange of semantic information must be defined. The Resource Description Framework (RDF) is a model for the description of semantic information which is suitable for application on the Internet, and it is based on the semantic network model. It should, however, be noted that this model does not provide any means for querying RDF data. In this paper, we propose a model for querying RDF knowledge bases and its accompanying syntax based on XML. The model has been implemented and tested in practice.

Mobile Virtual Laboratory: Learning Digital Design

An important part of learning digital design is the acquisition of knowledge through working experience in a laboratory environment, what will corroborate theoretical knowledge exposed elsewhere (e.g. in lectures, through written exercise solving etc.). This paper describes the foundation of a virtual laboratory available to every student at any moment and regardless of her/his whereabouts, following the concepts of universal access. We discuss the main issues in running a digital design lab, the essentials of contemporary mobile technology and the possible solutions to merge the two with the final objective being the development of a multiplatform system able to run both on (desktop) PCs and on mobile devices (terminals). We also discuss issues in the supporting HCI, especially in making the interaction as simple as possible.

HCI Research for E-Learning: Adaptability and Adaptivity to Support Better User Interaction

The paper provides an overview of our research being performed in the area of interfaces for e-learning, with the emphasis on application of intelligent methods. We especially address the efforts being done in providing a suitable interaction for a class of intelligent e-learning systems --- Intelligent Tutoring Systems (ITSs), within the research framework of our home institutions. The specific issues being thus studied include adaptivity topics related to knowledge representation, interaction style as well as mobility support, along with related usability assessment methods. The dependence on intelligent handling of the former stems from the expected more efficient and effective solution of problems related to the diversity of users of Information and Communication Technology (ICT) supported education. In this respect we also shortly tackle and comment on a number of adaptable and adaptive interfaces for e-learning, which are in this context being conceptualized, implemented, and assessed both in vitro and in vivo .

Usability evaluation issues for computerized educational systems

Contemporary efforts in computer supported learning and teaching has introduced tutoring systems with a certain level of intelligence. Intelligent tutoring systems are a generation of computerized educational systems which are intended to improve the process of learning and teaching by attempting to mimic the capabilities of human tutors. The development of application technology in this field has not been accompanied by an adequate usable, user-centered interface design, possibly resulting in scarce, unusable support for interaction and indeed in the decrease of interfaces effectiveness and efficiency. In order to improve the usability of an intelligent tutoring system, nowadays generally perhaps the most important goal of current research in the field of human-computer interaction, our research addresses the usability concept issues, as well as empirical studies for the sake of its evaluation.

Agent-based messaging system for m-learning

Present day email encompasses a huge information space in which people spend a lot of time, and together with other message transport services (SMS, MMS, instant messaging) contribute in a significant degree to electronic information interchange. Most of the communication in the form of text or multimedia messages consists of unstructured data that is intended to humans, while the lack of semantic description prevents machine reasoning and intelligent message processing on behalf of humans. In order to extend the functionality of personal non-static e-learning systems - m-learning systems with semantic features, in this paper we propose an open and modular semantic SMS-based architecture which is based on multi-agent technology, and the requirements on the agent infrastructure for semantic SMS-based m-learning applications

Application of semantic web and personal agents in distance education system

Personal agents are proactive and adaptable intelligent agents which meet the demands of individuals. The use of personal agents will become fully prominent when the intelligent agents are provided with mechanisms for understanding the contents of document they access. Making it possible for the intelligent agents to understand semantics of the documents published on the Web is the central task in the development of the Semantic Web. Possibility of application of Semantic Web and the personal agents through distance education systems is elaborated in this paper. We also present adaptation of our distance education system DTEx-Sys (Distributed Tutor Expert System) for the use in environment of Semantic Web and personal agents.

Intelligent tutoring interoperability for the new web

Interoperability of systems based on knowledge is a very important element for reducing their development cost and enabling an easy-to-perform service enrichment. Intelligent tutoring systems (ITSs) may be described as distant learning systems, which base their work on the simulation of the “real” teacher in the learning and teaching process. ITSs base their interoperability on the interchange of domain knowledge, knowledge about learning and teaching process and knowledge about students. This paper describes DiSNeT, a distance learning system we designed based on the intelligent tutoring paradigm, on knowledge presentation using distributed semantic networks and on using agents in the learning and teaching process. We also present a methodology for ensuring interoperability between DiSNeT and other ITSs.

Predicting upper-bound text entry speeds for discrete-tilt-based input on smartphones

Motion sensors integrated into contemporary smartphones allow the introduction of new mobile interaction paradigms, here including tilt-based input control in the mobile context. Namely, as opposed to existing implementations that typically apply continuous feedback on tilting, we define Pitch and Roll movement sequences that change the orientation of the mobile device as discrete-tilt input primitives. The respective commands are then used to manage text entry within three discrete-tilt-based methods thus introduced: keyboard bisection, single cursor, and quad cursor. Each method is based on the use of a particular QWERTY-based keyboard layout with related strategy for character input. We model upper-bound text entry speeds for the input methods, taking into account both movement aspects and language context. The movement model corresponds to both the tilt-based shortest path between two consequent characters, which is theoretically defined, and the time of discrete-tilt execution, which is obtained from user testing experiment we conducted. The linguistic model, comprising digraph statistics, is constructed basing on available English corpora. This modeling approach provides discrete-tilt-based text entry speed predictions representing efficiency rates for expert behavior, i.e. for optimal performance. The results obtained enable the evaluation of the proposed designs without need to test with real users, and can furthermore serve as a baseline for efficiency of text entry implementations that rely on discrete tilt.