Adaptive Educational Hypermedia Systems

Adaptive hypermedia is a new area of research at the crossroads of hypermedia, adaptive systems, and intelligent tutoring systems. Educational hypermedia systems is cirrently the most popular kind of adaptive hypermedia. The goal of this paper is to uncover the secrets of authoring adaptive educational hypermedia. The paper provides a clear structured view on the process of adaptive hypermedia authoring starting from the early design stage. It also reviews a few modern adaptive hypermedia authoring systems that are oriented to educational practitioners.

Conventional closed-corpus adaptive information systems control limited sets of documents in predefined domains and cannot provide access to the external content. Such restrictions contradict the requirements of today, when most of the information systems are implemented in the open document space of the World Wide Web and are expected to operate on t he opencorpus content. In order to provide personalized access to open-corpus documents, an adaptive system should be able to maintain modeling of new documents in terms of domain knowledge automatically and dynamically. This dissertation explores the problem of open-corpus personalization and semantic modeling of open-corpus content in the context of e-Learning. Information on the World Wide Web is not without structure. Many collections of online instructional material (tutorials, electronic books, digital libraries, etc.) have been provided with implicit knowledge models encoded in form of tables of content, indexes, headers of chapters, links between pages, and different styles of text fragments. The main dissertation approach tries to leverage this layer of hidden semantics by extracting and representing it as coarse-grained models of content collections. A central domain ontology is used to maintain overlay modeling of students' knowledge and serves as a reference point for multiple collections of external instructional material. In order to establish the link between the ontology and the open-corpus content models a special ontology mapping algorithm has been developed. v The proposed approach has been applied in the Ontology-based Open-corpus Personalization Service that recommends and adaptively annotates online reading material. The domain of Java programming has been chosen for the proof-of-concept implementation. A controlled experiment has been organized to evaluate the developed adaptive system and the proposed approach overall. The results of the evaluation have demonstrated several significant learning effects of the implemented open-corpus personalization. The analysis of log-based data has also shown that the open-corpus version of the system is capable of providing personalization of similar quality to the close-corpus one. Such results indicate that the proposed approach successfully supports open-corpus personalization for e-Learning. Further research is required to verify if the approach remains effective in other subject domains and with other types of instructional content.

This paper describes the interactive problem solving support offered by our adaptive educational hypermedia system called MATHEMA. The general goal of the MATHEMA is the support of senior high school students or the beginners of higher education, through an interactive and constructivist environment, in learning physics (electromagnetism) individually and/or collaboratively, and to overcome their possible misconceptions and learning difficulties. Initially, a review of related work about the implemented AEHS/ITS and the didactic design principles of the MATHEMA are presented. Through the interactive problem solving, the system supports the students in solving electromagnetism problems, individually and/or collaboratively, by following an activity that is based on the experimentation with simulations, explorations, guided discovery, and collaboration didactic approaches. An experimental study with senior high school students showed that they improve their performances when following this activity. A questionnaire that we gave to the students to express their opinion about our system helped us to improve the quality of the courses.

This study aims to determine the descriptive properties and methodological tendencies in empirical studies
focusing on academic achievement. Educational research studies taking academic achievement as the dependent
variable were considered in this study. The articles published in SSCI indexed journals in the period between 2012
and 2017 were scanned through Web of Science database. The sample for the study was composed of 80 articles
using experimental research method. Educational Technologies Publication Classification Form was used as the data
collection tool in this study. The articles collected were put to content analysis. On examining the independent
variables influencing academic achievement in the articles, it was found that experimental studies in the categories
of use of materials, teaching approaches/strategies, learning environments, assessment types and teaching
techniques predominated. It was found that such variables as critical thinking, problem solving and attitudes in
addition to academic achievement were also used as the dependent variable in the studies analyzed. Besides, it was
also found that the studies frequently used t-test, variance analysis (ANOVA/ANCOVA) as data analysis methods. It
is thought that the results obtained will guide researchers intending to conduct studies on academic achievement.

The use of adaptations, along with the social affordances of collaboration and networking, carries a great potential for improving e-learning experiences. However, the review of the previous work indicates current e-learning systems have only marginally explored the integration of social features and adaptation techniques. The overall aim of this research, therefore, is to address this gap by evaluating a system

Although doing a dissertation can be a long, lonely process, fortunately it is not done alone. Along the path, many were those who supported and encouraged me. I want to express my profound gratitude for their enormous personal generosity and contribution.

Although doing a dissertation can be a long, lonely process, fortunately it is not done alone. Along the path, many were those who supported and encouraged me. I want to express my profound gratitude for their enormous personal generosity and contribution.

In this paper we describe the outcomes of experimentation with technical school students (of the same degree as senior high school students) on Physics teaching. Our first goal was to find out if the application of the Kolb's learning cycle on Physics teaching improves the performances of students. The unit of the chapter of electromagnetism we presented was the following: ″Motion of a charged particle in perpendicular to the dynamic lines of a uniform magnetic field″. This unit was presented in four different teaching methods through our Web-based Adaptive Educational Hypermedia (AEH) system under development. Our second goal was to investigate which combinations between Abstract and Concrete learning styles of students, helps them to improve their performances. The results showed that the majority of students improved their performances. Also, their performances were in close relation to the students' learning styles and their abstract and concrete dimensions. The results of experimentation will help to adapt the educational material according to the learning style of each individual student and to support adaptive collaboration through our AEH system.

Providers of products and services are faced with the dual challenge of supporting the languages and individual needs of the global customer while also accommodating the increasing relevance of user-generated content. As a result, the content and localisation industries must now evolve rapidly from manually processing predicable content which arrives in large jobs to the highly automated processing of streams of fast moving, heterogeneous and unpredictable content. This requires a new generation of digital content management technologies that combine the agile flow of content from developers to localisers and consumers with the data-driven language technologies needed to handle the volume of content required to feed the demands of global markets. Data-driven technologies such as statistical machine translation, cross-lingual information retrieval, sentiment analysis and automatic speech recognition, all rely on high quality training content, which in turn must be continually harvest...

The adaptive educational systems within e-learning platforms are built in response to the fact that the learning process is different for each and every learner. In order to provide adaptive e-learning services and study materials that are tailor-made for adaptive learning, this type of educational approach seeks to combine the ability to comprehend and detect a person’s specific needs in the context of learning with the expertise required to use appropriate learning pedagogy and enhance the learning process. Thus, it is critical to create accurate student profiles and models based upon analysis of their affective states, knowledge level, and their individual personality traits and skills. The acquired data can then be efficiently used and exploited to develop an adaptive learning environment. Once acquired, these learner models can be used in two ways. The first is to inform the pedagogy proposed by the experts and designers of the adaptive educational system. The second is to give...

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We present a hypermedia model for educational applications, addressing the problem of exploratory navigation into the hyperspace from the viewpoints of context establishment, assistance against disorientation and reporting on the learner's activities. We argue for the need to extend the conventional hypermedia framework with the introduction of constraint satisfaction and hypothetical reasoning. We focus on constraint programming techniques and abductive reasoning and we show how such an enhanced model can address the aforementioned problem for educational hypermedia applications.

Educational content of today no longer only resides in textbooks and classrooms; more and more learning material is found in a free, accessible form on the Internet. Our long-standing vision is to transform this web of educational content into an adaptive, webscale "textbook", that can guide its readers to most relevant "pages" according to their learning goal and current knowledge. In this paper, we address one core, long-standing problem towards this goal: identifying outcome and prerequisite concepts within a piece of educational content (e.g., a tutorial). Speci cally, we propose a novel approach that leverages textbooks as a source of distant supervision, but learns a model that can generalize to arbitrary documents (such as those on the web). As such, our model can take advantage of any existing textbook, without requiring expert annotation. At the task of predicting outcome and prerequisite concepts, we demonstrate improvements over a number of baselines on six textbooks, especially in the regime of li le to no ground-truth labels available 1. Finally, we demonstrate the utility of a model learned using our approach at the task of identifying prerequisite documents for adaptive content recommendation-an important step towards our vision of the "web as a textbook".

The advancement of computational Artificial Intelligence (AI) in the recent decade has been transformative for many domains, including AI in Education. One direction, where it has caused a noticeable increase in research activity, is application of AI technologies to enhance digital textbooks by making them more interactive, engaging, adaptive, and intelligent. For many researchers coming into this field, it would have seemed as if an intelligent textbook is a completely new idea. We would like to provide a historic outlook on this field and outline the important phases that it went through over the last three decades. We hope that such an account can inform interested readers and help them better understand the problems and the approaches of intelligent textbooks.

The shared whiteboards allow the establishment of a communicationinteraction feature between teachers and students to clarify specific terms of the didactic material exposed by means of a web virtual course. Bookmarks and notebooks are navigation tools with historical characteristics in adaptive and educative hypermedia systems [1] that allow the student to take notes on the learning material exposed and to identify and extract relevant references about the web pages visited in order to facilitate their later revision. This work presents the performance of a shared whiteboard manager created to support virtual teaching through the Internet and a student notebook manager that allows students to take private notes on different sections of a web course and to generate bookmark files to export and maintain them as bookmarks through any Internet browser. The virtual environment of teaching-learning used for these tools is the one offered by the PLAN-G [2] project. [1] PhD student from the Universidad Industrial de Santander (Colombia) [2] This work was partially funded by the CICYT TEL98-0408-C02-01 and CICYT TEL98-0976 projects. Study and implementation of a PLAtaforma telemática de Nueva Generación to support open and distance learning (PLAN G).

This paper describes some features of the telematics platform named Teaching Support Units (TSU), developed by PLAN-G [2] using WWW technology. The platform provides a set of tools that enable teachers to create and edit didactic materials, generate and manage different types of interactive exercises and create and manage teaching units. The main goal of these tools is to sidestep the problem of teachers having to understand various applications and languages in order to make dynamic and interactive didactic material. The system was set up with structures and transversal navigation which make learning easier and guide the student during its use. The student's activities are collected in a personalized database, which enables teachers to follow his/her navigation and performance. This information may provide criteria for improving the didactic contents. We place special emphasis on the personalization of the system so that it can be adapted to the student's preferences (presentation, languages, etc.), to his/her way of working and to his/her ability to understand the contents provided.

This paper constitutes a literature review on student modeling for the last decade. The review aims at answering three basic questions on student modeling: what to model, how and why. The prevailing student modeling approaches that have been used in the past 10 years are described, the aspects of students' characteristics that were taken into consideration are presented and how a student model can be used in order to provide adaptivity and personalisation in computer-based educational software is highlighted. This paper aims to provide important information to researchers, educators and software developers of computer-based educational software ranging from e-learning and mobile learning systems to educational games including stand alone educational applications and intelligent tutoring systems. In addition, this paper can be used as a guide for making decisions about the techniques that should be adopted when designing a student model for an adaptive tutoring system. One significant conclusion is that the most preferred technique for representing the student's mastery of knowledge is the overlay approach. Also, stereotyping seems to be ideal for modeling students' learning styles and preferences. Furthermore, affective student modeling has had a rapid growth over the past years, while it has been noticed an increase in the adoption of fuzzy techniques and Bayesian networks in order to deal the uncertainty of student modeling.

Abstract. Personalized support for learners becomes very important in the context of increasing re-use of resources from heterogeneous and distributed learning repositories. This paper presents OrPAF, an Adaptive Educational Hypermedia (AEHS) and web-based ...

Educational content of today no longer only resides in textbooks and classrooms; more and more learning material is found in a free, accessible form on the Internet. Our long-standing vision is to transform this web of educational content into an adaptive, webscale "textbook", that can guide its readers to most relevant "pages" according to their learning goal and current knowledge. In this paper, we address one core, long-standing problem towards this goal: identifying outcome and prerequisite concepts within a piece of educational content (e.g., a tutorial). Speci cally, we propose a novel approach that leverages textbooks as a source of distant supervision, but learns a model that can generalize to arbitrary documents (such as those on the web). As such, our model can take advantage of any existing textbook, without requiring expert annotation. At the task of predicting outcome and prerequisite concepts, we demonstrate improvements over a number of baselines on six textbooks, especially in the regime of li le to no ground-truth labels available 1. Finally, we demonstrate the utility of a model learned using our approach at the task of identifying prerequisite documents for adaptive content recommendation-an important step towards our vision of the "web as a textbook".

This paper describes research and development efforts related to adaptive technologies, which can be combined with other technologies and processes to form an adaptive system. The goal of an adaptive system, in the context of this paper, is to create an instructionally sound and flexible environment that supports learning for students with a range of abilities, disabilities, interests, backgrounds, and other characteristics. After defining key terms and establishing a rationale for adaptation, we present a general framework to organize adaptive technologies. We then describe experts' thoughts on what to adapt and how to adapt and conclude with a summary of key challenges and potential futures of adaptive technologies.

This paper illustrates and evaluates a generic adaptive tutoring environment, structural example-based adaptive tutoring system (SEATS), based on the theory of cognitive knowledge acquisition. The system teaches by presenting side-by-side examples and highlighting their common structural components. This technique assists the process of generalization and reduces mapping by surface features, allowing students to apply their newly gained knowledge to different sets of problems. SEATS also implements adaptive presentation based on a straightforward model of student/user performance. SEATS was evaluated with a recursion tutorial used by 117 students in a 1-hour tutorial session. Results indicate that using adaptation in combination with the structural example-based feature produces an effect on rate and extent of learning significantly greater than when the features are used alone, or when both are absent. The study further points out that future evaluations will have to take students' curiosity into account, since many of them are likely to give at least some incorrect answers on purpose, to test the response of the system. The results indicate that building SEATS with simple adaptive mechanisms is an efficient way of teaching electronically.

There is a misconception of what programming is at the early stages of learning programming for Computer Science (CS) minors. More researches in this field have revealed that the lack of problem-solving skills, which is considered as one of the prominent shortcomings that novices deal with, is exacerbated by language syntax that the novices employ. A Flowchart-based Intelligent Tutoring System (FITS) is proposed in this research aimed at introducing the early stages of learning programming (CS1) to put the record straight. The students who have no prior knowledge of programming are the target audience of this research. In order to support novice programmers in beginning of programming, Bayesian network approach is applied mainly for decision making and to handle uncertainties in knowledge level of students. How to use Bayesian network to take full advantage of it as an inference engine for providing users with various guidance is described in this paper. Therefore, our proposed system provides users with dynamic guidance such as recommend learning goals, recommend options for flowchart development, and generate appropriate reading sequences. Additionally, our proposed system's architecture and its components are elaborated. Our future work is to evaluate the FITS by conducting an experimental study using novices.

For providing the personalization feature to e-learning systems, a Human Computer Interaction HCI technique, User Modeling was considered in system design. This study was undertaken to propose a technique to model the students' learning styles for personalized e-learning system. Bayesian Network BNwas used to model the students' learning styles and Kolb's learning styles theory was used to know the students' learning styles and preferences. The objective of the study was to propose a user modeling technique for personalized e-learning systems to understand the elearners' requirements and needs to enhance their learning.Using BN, Conditional Probability Tables CPTs were determined for all four learning styles provided by Kolb's theory. The threshold values were used to determine the learning styles of students during an online course. We found that BN technique determined successful as from the Divergers 100%., 75% Assimilator, 50% Accommodators and 75% Convergers were identified accurately.

Personalization is one of the emerging ways to increase the power of modern Digital Libraries. The Knowledge Sea II system presented in this paper explores social navigation support, an approach for providing personalized guidance within the open corpus of educational resources. Following the concepts of social navigation we have attempted to organize a personalized navigation support that is based on past learners' interaction with the system. The study indicates that Knowledge Sea II became the students' primary tool for accessing the open corpus documents used in a programming course. The social navigation support implemented in this system was considered useful by students participating in the study of Knowledge Sea II. At the same time, some user comments indicated the need to provide more powerful navigational support, such as the ability to rank the usefulness of a page.

Learning activities play an essential role in the act of teaching/learning. They highlight the nature of the learners and their ability to perform the tasks easily and make it possible to give meaning to the learning. The idea developed in our article lies in the design and development of a computer system for managing learning activities according to the experiential model of Kolb. For this, we evoke after having defined our problem and our research questions, our theoretical framework, which includes the learning styles, the styles of Kolb, and the bases of the experiential activity of Kolb, our methodology of research, which is articulated on a case study through a survey whose purpose is to define the learning styles of our sample. Then, we suggest learning activities according to the style of each learner, to experiment with them on our sample and make an evaluation to analyze the results obtained which allow us the transition to a model in the form of a pedagogical scenario. Finally, our model will be managed by a learning management computer system adapted to each learner according to his learning style according to Kolb.

The more the web grows, the harder it is for users to find the information they need. As a result, it is even more difficult to identify when documents are related. To find out that two or more documents are in fact related, users have to navigate by the documents in carry out an analysis about their content. This paper presents an infrastructure allowing the use of latent semantic analysis and open hypermedia concepts in the automatic identification of relationships among web pages. Latent Semantic Analysis has been proposed by the information retrieval community as an attempt to organize automatically text objects into a semantic structure appropriate for matching. In open hypermedia systems, links are managed and stored in a special database, a linkbase, which allows the addition of hypermedia functionality to a document without changing the original structure and format of the document. We first present two complementary link-related efforts: an extensible latent semantic indexing service and an open linkbase service. Leveraging off those efforts, we present an infrastructure that identifying latent semantic links within web repositories and makes them available in an open linkbase. To demonstrate by example the utility of our open infrastructure, we built an application presenting a directory of semantic links extracted from web sites.

We discuss architectural problems of the studentmodel centered approach to building intelligent learning environments (JLB). By this approach different componentsofELE including tutoring, coaching, environment, and manual components use the central student model to adapt its behavior to the given student The implementation of this approach is based upon ideas from the fields of intelligent tutoring systems, adaptive interfaces and intelligent help systems. We introduce a simple student model centered architecture for ILE which we have appliedin several implemented systems, report some problems and limitations of our original simple architecture, andpresentanadvanced studentmodel centered open architecture forILE.

Adaptive Learning concept has apprehended the interest of educational actors and partners, especially in higher education. However, the implementation of this concept has faced many challenges, particularly in Adaptive Learning Systems (ALS). The present paper aims to give the foundation of a framework for an ALS that gives extensive attention at each stage of the design process to the end-user: learners. The system proposed is based on Agile Learning Design approach and integrating learner-centered design to improve teaching effectiveness, facilitate learning among learners, encourage long life learning and maximize motivation as well as reducing the dropout rates.

Most approaches to adaptive hypermedia were based around acquiring and representing learner's knowledge. While this is crucial for user modelling in general adaptive hypermedia, it is very limited for e-learning because it does not address the far more fundamental problem which is "learners learn in different ways, different learning styles and different thinking styles". The design of adaptive e-learning hypermedia system (AEHS) in this work is based on quantitative and qualitative research; the adaptive rules are deduced from the results of a psychological and pedagogical questionnaire. Pedagogical activities are the outcome of a series of deductions; the final activity sets are manifested in AEHS. In order to assess the positive effect and validity of adaptation on the basis of learners' thinking and learning styles, this study presents two subsequent experiments. The first experiment explores the relationship of thinking style and pedagogical activities to validate this specific psychological construct in the context of educational hypermedia. The second experiment presents the effect of a set of human factors (thinking style, learning style) in AEHS.

We try in this paper to propose a domain model for both author's and learner's needs concerning learning objects reuse. First of all, we present four key criteria for an efficient authoring tool: adaptive level of granularity, flexibility, integration and interoperability. Secondly, we introduce and describe our six-level Semantic Learning Model (SLM) designed to facilitate multi-level reuse of learning materials and search by defining a multi-layer model for metadata. Finally, after mapping different learning content models ...

What follows is a contribution to the field of user modeling for adaptive teaching and learning programs especially in the medical field. The paper outlines existing approaches to the problem of extracting user information in a form that can be exploited by adaptive software. We focus initially on the so-called stereotyping method, which allocates users into classes adaptively, reflecting characteristics such as physical data, social background, and computer experience. The user classifications of the stereotyping method are however ad hoc and unprincipled, and they can be exploited by the adaptive system only after a large number of trials by various kinds of users. We argue that the remedy is to create a database of user ontologies from which readymade taxonomies can be derived in such a way as to enable associated software to support a variety of different types of users.

The aim of this paper is to discuss the pertinence of experience of hypertext structures regarding the development of perceptual patterns when using contemporary time based interactive media. Therefore we discuss first the idea of time based hypermedia and related works in arts and education. Then we describe the design and implementation of the pilot project WeHype 1 , where hypervideos were created at school using YouTube Annotations. Then we focus on the transfer of the experiences at school into teacher education. Results of a comparative evaluation verify that, due to the fact that youngsters communicate and interact more in social nets, they are more familiar with hypermedia spaces than their teachers. Furthermore the evaluation shows, that teachers as well as students think that the easy-to-use tool YouTube Annotations is suitable for understanding hyper-structures and leads to sustainable learning. This leads us to reflect about the importance of artistic approaches for understanding non-linear narrative structures using video. Finally we discuss why teaching with interactive time based hypermedia should be transferred into teacher education.

In this paper we focus on adaptive instruction and especially on the educational perspective that should underlie the development of web-based Adaptive Educational Hypermedia (AEH) systems used for Internet-based distance education. A design rational and guidelines are proposed for adaptive instruction in the context of AEH systems, which unify several processes that formulate system's adaptation such as structuring the domain knowledge, developing the content, planning individualised instruction and support, assessment, and learner control opportunities. The main aim of this approach is to incorporate a variety of pedagogical models and learning theories in order to accommodate the diversity needs and perspectives of learners and teachers. Paradigms of the way these guidelines have been implemented mainly in AEH systems, are provided.

The process of training and learning in Web-based and ubiquitous environments brings a new sense of adaptation. With the development of more sophisticated environments, the need for them to take into account the user's traits, as well as the user's devices on which the training is executed, has become an important issue in the domain of building novel training and learning environments. This chapter introduces an approach to the realization of personalized adaptation. According to the fact that we are dealing with the stereotypes of e-learners, having in mind emotional intelligence concepts to help in adaptation to the e-learners real needs and known preferences, we have called this system eQ. It stands for the using of the emotional intelligence concepts on the Web.

Adaptive content selection is recognized as a challenging research issue in adaptive educational hypermedia systems (AEHS). Several efforts have been reported in literature aiming to support the Adaptation Model (AM) design by providing AEHS designers with either guidance for the direct definition of adaptation rules, or semi-automated mechanisms which generate the AM via the implicit definition of such rules. The goal of the semi-automated, decisionbased approaches is to generate a continuous decision function that estimates the desired AEHS response, aiming to overcome the insufficiency and/or inconsistency problems of the defined adaptation rule sets. Although such approaches bare the potential to provide efficient AMs, they still miss a commonly accepted framework for evaluating their performance. In this paper, we propose an evaluation framework suitable for validating the performance decision-based approaches in adaptive learning objects selection in AEHS and demonstrate the use of this framework in the case of our proposed decision-based approach for estimating the desired AEHS response.

In spite of the interest in AHS, there are not as many applications as could be expected. We have previously pinpointed the problem to rely on the difficulty of AHS authoring. Adaptive features that have been successfully introduced and implemented until now are often too fine grained, and an author easily looses the overview. This paper introduces a three-layer model and classification method for adaptive techniques: direct adaptation rules, adaptation language and adaptation strategies. The benefits of this model are twofold: on one hand, the granulation level of authoring of adaptive hypermedia can be precisely established, and authors therefore can work at the most suitable level for them. On the other hand, this is a step towards standardization of adaptive techniques, especially by grouping them into a higher-level adaptation language or strategies. In this way, not only adaptive hypermedia authoring, but also adaptive techniques exchange between adaptive applications can be enabled.

In this chapter we present one of the pioneer approaches in supporting users in navigating the complex information spaces, social navigation support. Social navigation support is inspired by natural tendencies of individuals to follow traces of each other in exploring the world, especially when dealing with uncertainties. In this chapter, we cover details on various approaches in implementing social navigation support in the information space as we also connect the concept to supporting theories. The first part of this chapter reviews related theories and introduces the design space of social navigation support through a series of example applications. The second part of the chapter discusses the common challenges in design and implementation of social navigation support, demonstrates how these challenges have been addressed, and reviews more recent direction of social navigation support. Furthermore, as social navigation support has been an inspirational approach to various other social information access approaches we discuss how social navigation support can be integrated with those approaches. We conclude with a review of evaluation methods for social navigation support and remarks about its current state.

Adapting the presentation of learning material to the specific student?s characteristics is useful to improve the overall learning experience and learning styles can play an important role to this purpose. In this paper, we investigate the possibility to distinguish between Visual and Verbal learning styles from gaze data. In an experiment involving first year students of an engineering faculty, content regarding the basics of programming was presented in both text and graphic form, and participants? gaze data was recorded by means of an eye tracker. Three metrics were selected to characterize the user?s gaze behavior, namely, percentage of fixation duration, percentage of fixations, and average fixation duration. Percentages were calculated on ten intervals into which each participant?s interaction time was subdivided, and this allowed us to perform time-based assessments. The obtained results showed a significant relation between gaze data and Visual/Verbal learning styles for an ...

When “going digital” in the field of education one possible option – typically adopted in higher and adult education – is, so to speak, to “enhance the real world” through technology. Course materials are provided in digital format, face-to-face interaction is replaced by forums or social spaces, exercises and activities are remotely performed and scored, etc. Another option is to create “innovative learning experiences”, that without technology would not be possible nor conceivable. Innovative learning experiences are more difficult to conceive, and also riskier to introduce in an established learning environment: they are also more difficult to explain and to evaluate. Innovative learning experiences, however, have also a great potential: they can generate “excitement” (something new!) and non-traditional educational benefits (still alongside with the „traditional‟ ones), like increased media literacy, professional skills and attitudes and more. In this paper, we will present two ...

Adaptive learning support for learners becomes very important in the context of increasing re-use of resources from heterogeneous and distributed learning repositories. This paper presents OrPAF, an Adaptive Educational Hypermedia (AEHS) and web-based System which integrates semantic web models and technologies in order to achieve interoperability with e-learning systems. The key feature of OrPAF is the construction of adaptive hypermedia courses: both the course structure and the course content are dynamically generated and adapted to learners. We experimented the realized prototype on learners in order to evaluate the usability of OrPAF and the conceptual capabilities developed by the learners who used it.

This paper focuses on a vital aspect for educational adaptive hypermedia (AEH): the design. The proper design is the first step towards common design patterns, leading to better, semantically enhanced authoring systems for AEH. This can mean easier access to these special tools for personalization for the domain expert without computer knowledge. A high-level taxonomy is proposed here, as a result of many brainstorming sessions within the European Community project, ADAPT. This taxonomy is justified with the help of both AEH implementations and theoretical frameworks.

A number of studies in traditional class based education show that students whose learning styles match with the instructional approach "tend to retain information longer, apply it more effectively, and have more effective post course attitudes towards the subject than do their counterparts who experience learning/teaching mismatch. Thus, the goals of a "good instructor" should be both to adapt, at some degree and at least part of the time, his or her instructional approach according to students' learning preferences, and to help students build their skill in their preferred and less preferred learning modes. Taking for granted that in a "student-centered" hypermedia learning environment, learning preferences and design of hypermedia learning applications should be also related, this paper aims to define the structure of the hypermedia design patterns that provide solutions to the problem of how to best support learning preferences via educational hypermedia applications and more specifically via adaptive/adaptable educational hypermedia applications.

This work is an approach that brings together Learning Analytics and Ontologies for a data classification that promotes improvements and behavioral changes for students and teachers on e-Learning platforms. Combining training courses, dashboards, user's evaluations, and based on Design Science Research (DSR) methodology, artifacts were created. One of the most important artifacts of our work is the Sapes tool that aims to improve students’ perceptions of their learning path and to promote a better teacher overview to follow their students' progress. The results showed high approval by the participating students and teachers, who perceived the Sapes tool as a good facilitator of the teaching-learning process, with possibilities for self-monitoring, dynamization of the learning sequence and better interactivity with colleagues, highlighted as absent in standard e-Learning courses. In addition, the application changed the behavior of users towards the content provided by the te...

Web-based distance learning is becoming increasingly prevalent as the Internet permeates every aspect of our culture, and many educational content management systems are now in use on the web. However, learners' experiences of these systems are almost invariably static, with information being delivered regardless of their background or knowledge. Due to variation between learners', it is suggested that these web-based distancelearning systems would benefit from the capability of adapting their content to meet individual needs. To effectively implement this adaptation of educational material, we require a user model that supplies the system with information about the learners using the system, such as their backgrounds, knowledge, interests and learning styles. This paper focuses on presenting a user model that combines the advantages of two techniques (overlay and stereotyping) in a way that provides the system with the ability to deliver information that is fully informed by the requirements of individual users.

The aim of the present study is to develop a model that grasps the complexity of the concepts of personality and affect in a web-based learning environment. Furthermore, it presents the implications that these theoretical and empirical representations can have in an experimental setting. We are investigating the connection between personality factors, emotion regulation and cognitive processing tasks, decision making and problem solving styles. Decision-making and problem solving are cognitive processes where the outcome is a choice between alternatives. They are both an indirect way to make inferences to a person's learning pattern since learning includes continuous decision making and problem resolution. By implementing our model in the design of a web-based learning personalized setting, we provide evidence that behavior is altered by affective elements in decision making and problem solving routines as is performance in cognitive processing tasks.

The use of adaptations, along with the social affordances of collaboration and networking, carries a great potential for improving e-learning experiences. However, the review of the previous work indicates current e-learning systems have only marginally explored the integration of social features and adaptation techniques. The overall aim of this research, therefore, is to address this gap by evaluating a system