Showing papers on "Personalized learning published in 2004"
Book•
1 Jan 2004
TL;DR: Learning style instruments are widely used but not enough is known about their reliability and validity and their impact on pedagogy in post-16 learning as mentioned in this paper, and the implications of learning styles for teaching and learning.
Abstract: Learning style instruments are widely used but not enough is known about their reliability and validity and their impact on pedagogy in post-16 learning. This report documents work from a project commissioned by the Learning and Skills Development Agency (LSDA) to carry out an extensive review of research on post-16 learning styles, to evaluate the main models of learning styles, and to discuss the implications of learning styles for post-16 teaching and learning. The following research questions were addressed: What models of learning styles are influential and potentially influential? What empirical evidence is there to support the claims made for these models? What are the broad implications for pedagogy of these models? What empirical evidence is there that models of learning styles have an impact on students’ learning? The project identified the range of models that are available and influential or potentially influential in research and practice, located these models within identifiable ‘families’ of ideas about learning styles, evaluated the theories, claims and applications of these models, with a particular focus on evaluating the authors’ claims for reliability and validity, evaluated the claims made for the pedagogical implications of the selected models of learning styles, identified what gaps there are in current knowledge and what future research is needed in this area, and made recommendations and drew conclusions about the research field as a whole. In conclusion, the implications for pedagogy are drawn out and recommendations and conclusions are offered for practitioners, policymakers and the research community. The report concludes that it matters fundamentally which model is chosen. A second report (indexed at TD/TNC 79.72) discusses the appeal of learning styles as well as offering an overview of ways in which political and institutional contexts in the learning and skills sector affect the ways that learning styles might be put into practice.
1,851 citations
19 May 2004
TL;DR: This paper shows how to realize personalized learning support in distributed learning environments based on Semantic Web technologies by proposing a service-based architecture for establishing personalized e-Learning, where personalization functionality is provided by various web-services.
Abstract: Personalized support for learners becomes even more important, when e-Learning takes place in open and dynamic learning and information networks. This paper shows how to realize personalized learning support in distributed learning environments based on Semantic Web technologies. Our approach fills the existing gap between current adaptive educational systems with well-established personalization functionality, and open, dynamic learning repository networks. We propose a service-based architecture for establishing personalized e-Learning, where personalization functionality is provided by various web-services. A Personal Learning Assistant integrates personalization services and other supporting services, and provides the personalized access to learning resources in an e-Learning network.
277 citations
1 Jan 2004
TL;DR: Current and ongoing research to automatically personalize a learning experience through adaptive educational hypermedia is described, which includes research on authoring for adaptive learning material and research on modeling adaptive educational applications.
Abstract: This chapter describes recent and ongoing research to automatically personalize a learning experience through adaptive educational hypermedia. The Web has made it possible to give a very large audience access to the same learning material. Rather than offering several versions of learning material about a certain subject, for different types of learners, adaptive educational hypermedia offers personalized learning material without the need to know a detailed classification of users before starting the learning process. We describe different approaches to making a learning experience personalized, all using adaptive hypermedia technology. We include research on authoring for adaptive learning material (the AIMS and MOT projects) and research on modeling adaptive educational applications (the LAOS project). We also cover some of our ongoing work on the AHA! system, which has been used mostly for educational hypermedia but has the potential to be used in very different application areas as well.
96 citations
28 Mar 2004
TL;DR: In this paper, a personalized courseware recommendation system (PCRS) based on the proposed fuzzy item response theory (FIRT) is presented. But, the system is not designed for e-learning.
Abstract: With the rapid growth of computer and Internet technologies, e-learning has become a major trend in the computer assisted teaching and learning field currently. In past years, many researchers made efforts in developing e-learning systems with personalized learning mechanism to assist on-line learning. However, most of them focused on using learner's behaviors, interests, or habits to provide personalized e-learning services. These systems usually neglected to concern if learner's ability and the difficulty of courseware are matched each other. Generally, recommending an inappropriate courseware might result in learner's cognitive overhead or disorientation during a learning process. To promote learning efficiency and effectiveness, we present a personalized courseware recommendation system (PCRS) based on the proposed fuzzy item response theory (FIRT), which can recommend courseware with appropriate difficult level to learner through learner gives a fuzzy response of understanding percentage for the learned courseware. Experiment results show that applying the proposed fuzzy item response theory to Web-based learning can achieve personalized learning and help learners to learn more effectively and efficiently.
53 citations
1 Jan 2004
TL;DR: The Service-Based Framework (SBF) is introduced a reusable, scalable and flexible architecture for adaptation systems and its application for AdeLE, the research project for personalised adaptive e-learning with Eye-Tracking.
Abstract: E-learning may provide a lot of useful features in a wide range of learning and teaching situations. However, the provision of static learning material will not meet the requirements of the users. We believe that well-tailored, highly personalized learning sessions are needed. Regarding to this background, the research project AdeLE (Adaptive e-Learning with Eye-Tracking) aims to develop and implement a solution framework for personalised adaptive e-learning based on realtime user behaviour. In this paper we introduce the Service-Based Framework (SBF) a reusable, scalable and flexible architecture for adaptation systems and point out its application for AdeLE.
32 citations
1 Jan 2004
TL;DR: The need for using interactive ontology-based user modeling to empower on the fly adaptation in learning information systems is discussed and a promising direction for the implementation of personalized educational semantic web is shown.
Abstract: This position paper discusses the need for using interactive ontology-based user modeling to empower on the fly adaptation in learning information systems. We outline several open issues related to adaptive learning content delivery and present an approach to deal with these issues based on the integration of two existing systems - AIMS (taskbased information retrieval environment) and STyLE-OLM (interactive open learner modeling tool). The work contributes to achieving semanticbased reasoning for educational systems and shows a promising direction for the implementation of personalized educational semantic web.
30 citations
22 Mar 2004
TL;DR: One business course which is particularly appropriate for integrating service-learning into the strategic management course is Strategi-i-management as discussed by the authors, which integrates service learning into the business course.
Abstract: Academia has been ~ritiazed for Its $Upposed isolation from society and its l~c;;k of emphasis on practical applications and h~nds-on experience lrutitLJtions of hlgh&r education are responding to this criticism by incorporating experiential setvice-learning in their curncula One business course which is particularly appropriate fot integrating service-learning · into th~ wrriculum is Strategi~ Management
27 citations
5 Dec 2004
TL;DR: The experimental results reveal that the proposed learning diagnosis system can efficiently help learners to expand their knowledge while surfing in cyberspace Web-based "theme-based learning" model.
Abstract: This work proposes an intelligent learning diagnosis system that supports a Web-based thematic learning model, which aims to cultivate learners' ability of knowledge integration by giving the learners the opportunities to select the learning topics that they are interested, and gain knowledge on the specific topics by surfing on the Internet to search related learning courseware and discussing what they have learned with their colleagues. Based on the log files that record the learners' past online learning behavior, an intelligent diagnosis system is used to give appropriate learning guidance to assist the learners in improving their study behaviors and grade online class participation for the instructor. The achievement of the learners' final reports can also be predicted by the diagnosis system accurately. Our experimental results reveal that the proposed learning diagnosis system can efficiently help learners to expand their knowledge while surfing in cyberspace Web-based "theme-based learning" model.
27 citations
8 Aug 2004
TL;DR: A detailed examination of the opportunities and necessities of Personalized Education (PE) from the perspective of different learning pedagogies is provided and several PES features that can support personalized teaching and learning under pervasive computing are introduced.
Abstract: High potential values drive the commercial sectors towards the rapid development of Personalization Technology. In response to individual needs, personalization in education not only facilitates students to learn better by using different strategies to create various learning experiences, but also caters teacher’s teaching needs in preparing/designing varied teaching/instructional packages. Empirical results show that using the technologies without regarding pedagogical concepts frequently lead to failure. This paper provides a detailed examination of the opportunities and necessities of Personalized Education (PE) from the perspective of different learning pedagogies. To optimize the benefits of meaningful personalization technologies, we also propose a Personalized Education System (PES) Framework and introduce several PES features that can support personalized teaching and learning under pervasive computing.
25 citations
30 Aug 2004
TL;DR: The learning in process approach for contextualizing learning processes in a corporate setting is presented and its nucleus is a matching component compiling personalized learning programs on demand from modular learning objects.
Abstract: Context-steered learning in enterprises promises both from a learner point of view and from an organizational point of view higher learning efficiency and improved quality control. We present the learning in process approach for contextualizing learning processes in a corporate setting. Its nucleus is a matching component compiling personalized learning programs on demand from modular learning objects.
1 Jan 2004
TL;DR: Key areas involve the use of personalized learning and interactive media resources, with learning resources connected to real-world settings and reusable in different contexts, and advanced workplace arrangements integrating ELearning and knowledge work management both in smaller and larger European companies.
Abstract: While E-Learning is increasingly influencing university and workplace education in Europe, several critical issues still have to be solved in order to achieve the full potential of technology enhanced learning in many of these learning scenarios. The EU/IST FP6 PROLEARN Network of Excellence in Technology Enhanced Learning is focussing on these issues, and advancing the state of the art in this area, through a large concerted effort of more than 120 research institutions and companies working together in the PROLEARN Consortium and as PROLEARN Associated Partners. Key issues involve advanced production, deployment and exchange of professional learning resources and the use of these learning resources for professional training in SME's and larger companies. Key areas involve the use of personalized learning and interactive media resources, with learning resources connected to real-world settings and reusable in different contexts. Further PROLEARN key areas cover the use of brokerage platforms and services, appropriate business models and networks for specific markets, and advanced workplace arrangements integrating ELearning and knowledge work management both in smaller and larger European companies.
1 Jan 2004
TL;DR: This paper describes the existing adaptive authoring tool which can be used to convert a non-adaptive course into an adaptive one which uses learning objects.
Abstract: Learning objects are pedagogic software components which are interoperable, exchangeable and reusable between web-based learning environments, and adaptive learning and testing can provide each student with personalized learning content or assessment questions. In this paper, we describe our existing adaptive authoring tool which can be used to convert a non-adaptive course into an adaptive one which uses learning objects. Learning material can be reused in our framework which consists of lesson instructions, pre-tests, performance tests and proficiency tests. Our current metadata for describing the learning material will be merged with a simplified and customised version of Learning Object Metadata to allow the import and export of learning objects between different learning environments.
8 Aug 2004
TL;DR: This paper presents a method for articulating individual learners’ learning requirements, and representing them in a set of computable parameters in Learner’s Profile, which will be mapped onto instructional design strategies which determine a selection of suitable learning content and sequencing of content with adequate instruction in a learning package.
Abstract: As e-Learning environments evolve, learners have become increasingly demanding on personalised learning which allows them to build their own knowledge pathway. This significant change in learning requirements imposes a new learning paradigm which ensures one-to-one learning with flexible mode of content configuration, and adaptive delivery and assessment. Although in the past years, Learning Management Systems (LMS) providers have upgraded system functionality to support instructional design for e-learning package, incorporating individual learners’ personal learning requirements in content design still remains challenging. To involve learners in the content design requires identification of their personal learning requirements. This paper presents a method for articulating individual learners’ learning requirements (e.g., learning styles, and prior knowledge), and representing them in a set of computable parameters in Learner’s Profile. These parameters will then be mapped onto instructional design strategies which determine a selection of suitable learning content and sequencing of content with adequate instruction in a learning package.
TL;DR: An appropriate strategy to progress students up the cognitive ladder by adaptive item selection is explored using the non-symbolic fuzzy-neural network technology to provide personalized learning sequence for other similar students.
Abstract: Adaptive formative assessment is a new approach to implement computerized adaptive learning based on the cognitive scaffolding principle. In adaptive formative assessment, at any stage of a learning session, the system takes into account a student's demonstrated cognitive level to generate the next appropriate formative testing instrument. In this paper, an appropriate strategy to progress students up the cognitive ladder by adaptive item selection is explored using the non-symbolic fuzzy-neural network technology. The proposed model features to learn and memorize good learning paths for different students, and accordingly provide personalized learning sequence for other similar students. The adaptation behavior of the fuzzy neural network to different student categories is investigated by simulated experiments, and its effectiveness is compared with another memory-less binary item selection algorithm. Preliminary results reveal its potential for being an effective adaptive item selection module in adaptive tutoring systems based on cognitive scaffolding with adaptive formative assessment.
22 Aug 2004
TL;DR: This paper describes how learning objects are defined and treated in, a pilot e-learning system that aims to offer a personalized learning experience geared to individual student’s needs.
Abstract: This paper describes how learning objects are defined and treated in , a pilot e-learning system that aims to offer a personalized learning experience geared to individual student’s needs. The term learning object (LO) has been on the educational agenda for several years now and has become the Holly Grail of content creation and aggregation in e-learning, promising smart learning environments, fantastic economies of scale and exciting learning experiences tailored to individual needs. Nevertheless, there are a number of aspects where more research is needed. First, there is a lack of conceptual clarity in the definition, standardization and use of LOs. Also, there has been limited emphasis on the need for introducing adaptable learning features within the LO construct. The objective of this paper is to contribute to the practical application of these concepts by presenting the learning objects and how the system handles personalization features to create an infrastructure for performing an individualized learning.
1 Jan 2004
TL;DR: This paper demonstrates how to realize personalized learning support in dynamic and heterogeneous learning environments by utilizing Adaptive Web technologies and proposes a framework of knowledge structure based visualization tool for representing a dynamic learning process.
Abstract: In order to achieve optimal efficiency in a learning process, individual learner needs his/her own personalized assistance. For a web-based open and dynamic learning environment, personalized support for learners becomes more important. This paper demonstrates how to realize personalized learning support in dynamic and heterogeneous learning environments by utilizing Adaptive Web technologies. We focus on course personalization in terms of contents and teaching materials that is according to each student's needs and capabilities. To accomplish this, a conceptual model based on the Knowledge Structure is presented. Using the hierarchy and association rules of the concepts, we can organize courses and lessons as a multi-layer knowledge network, which has a reasonable classification and interdependent relations among the knowledge. With retrieval based on concept and association among the concepts, we propose a framework of knowledge structure based visualization tool for representing a dynamic learning process to support students' deep learning, efficient tutoring and collaboration in web-based learning environment.
TL;DR: The authors explored the experience of adult learners and their perceptions of learning using computer-based learning materials, mainly Learndirect packages, based on focus group interviews with learners in a range of settings, including centres in community-based organisations, further education colleges and private training providers based in the Midlands region of England.
Abstract: This article explores the experience of adult learners and their perceptions of learning using computer-based learning materials, mainly Learndirect packages. The findings are based on focus group interviews with learners in a range of settings, including centres in community-based organisations, further education colleges and private training providers based in the Midlands region of England. The research forms part of a larger study of partnership working and its role in widening participation in lifelong learning in the Black Country sub-region of England, but this article will focus specifically on the data from focus group interviews with learners. The findings reported here provide an insight into the ability of learners to articulate the benefits and the weakness of learning in this way, and to be clear about their learning goals. The data reveal aspects of the physical, social and psychological learning environment, which help learners participate in learning. This is, of course, useful f...
TL;DR: Important advantages of the project-based online environment are time and place flexibilities, maintaining everyday activities while attending a graduate program, diverse backgrounds of the adult learners, experience with authentic problems of the projects, applicability of learning issues to real life, active participation in the learning process, and combination of online interactions with residencies.
Abstract: Adult learners participating in a project-based distributed learning environment, the MBA Without Boundaries (MBAWB) program at Ohio University, reported that project-based learning in a distributed learning environment is meaningful for adult learners because of the active involvement in the projects and transferability of the learning issues to the work place. According to the adult learners, important advantages of the project-based online environment are time and place flexibilities, maintaining everyday activities while attending a graduate program, diverse backgrounds of the adult learners, experience with authentic problems of the projects, applicability of learning issues to real life, active participation in the learning process, and combination of online interactions with residencies. However, the learners reported teammates who do not make enough contributions to a team project as the most common problem. Some learners complained about the distance barriers, family and work responsibilities, and technological failures during the online interactions.
30 Aug 2004
TL;DR: This article presents a Methodology to model a TLP and to build an automatic adaptation (adaptive) mechanism for ITS Interfaces, based in a Neural Network, and the diabetes education was used as a case study to apply and validate the proposed methodology.
Abstract: In a Teaching-Learning Process (TLP) teachers have to support student’s learning using diverse pedagogical resources One of teachers’ task is to create personalized Learning Environments Intelligent Tutoring Systems (ITS) try to imitate adaptation capacity of a human teacher The Interface is the Learning Environment and the system stores knowledge that defines how to adapt it to respond to certain student’s characteristics Adaptation is particularly important for TLP oriented to carriers of chronic diseases like Diabetes, which represent very heterogeneous groups of persons This article presents a Methodology to model a TLP and to build an automatic adaptation (adaptive) mechanism for ITS Interfaces, based in a Neural Network [1] The diabetes education was used as a case study to apply and validate the proposed methodology The most important results of this work are presented here
1 Mar 2004
TL;DR: The development of a constructivist learning environment scorecard is described and its usefulness in characterizing and comparing online learning courses and subsequently learning outcomes is explored.
Abstract: Over the past five years, the number of individuals engaging in online learning as well as the number of online course offering has grown exponentially. At the same time, outcome research on online learning design is sparse. This paper describes the development of a constructivist learning environment scorecard and explores its usefulness in characterizing and comparing online learning courses and subsequently learning outcomes.
Book•
1 Jan 2004
TL;DR: This chapter discusses the role of the Principal and Supervisory-Management Team, personalizing the Curriculum, and Developments in School Culture, Climate, and School effectiveness.
Abstract: Chapter 1 List of Abbreviations Chapter 2 Introduction: A New education for a New World Chapter 3 1. Comprehensive School Renewal: MSP, LEC, and CES Chapter 4 2. Role of the Principal and Supervisory-Management Team Chapter 5 3. Teacher Role and Advisement Chapter 6 4. Student Role: Large Group, Small Group, and Independent Study Chapter 7 5. Flexible Scheduling to Promote Personalized Learning Chapter 8 6. Personalizing the Curriculum Chapter 9 7. Individualized to Personalized Instruction Chapter 10 8. Developments in School Culture, Climate, and School effectiveness Chapter 11 9. Evaluation and Grading Chapter 12 10. School Structure Chapter 13 11. Retrospective Chapter 14 References Chapter 15 Index Chapter 16 About the Editors and Contributors
30 Aug 2004
TL;DR: Privacy aspects of a smart space for learning that is being developed in the EU 1ST ELENA project are discussed, and several privacy-enhancing technology (PET) based solutions are described.
Abstract: Personalized learning solutions typically involve learner profiles with sensitive information and activities that might breach learner's privacy, such as user profiling. In this paper we discuss privacy aspects of a smart space for learning that is being developed in the EU 1ST ELENA project. The paper presents threats and requirements, and describes several privacy-enhancing technology (PET) based solutions.
30 Aug 2004
TL;DR: The Web-based reflective tutorial dialogue system (W-ReTuDiS) is a system for personalized learning of historical text comprehension on the Web that promotes learners' personalized reflection to accomplish the learning goals and helps learners to be aware of their reasoning and leads them towards the scientific thought.
Abstract: The Web-based reflective tutorial dialogue system (W-ReTuDiS) is a system for personalized learning of historical text comprehension on the Web. The system offers a two level open interface: tutor level and learner level. In tutor level, the tutor manages the learner model and makes decisions concerning the appropriate activity and dialogue strategy for the learner according to his learner model, which is based on the diagnostic results. In learner level, the learner participates in the construction of his learner model through dialogue activities, which promote reflective learning. The dialogue generator module, which is activated by the diagnostic results, plans the appropriate sequence of dialogue-parts using the dialogue-parts' library and constructs personalized tutorial dialogue. The system promotes learners' personalized reflection to accomplish the learning goals and helps learners to be aware of their reasoning and leads them towards the scientific thought.
29 Mar 2004
TL;DR: This work describes the implementation methods for the e-math interaction agent distance learning system, which dynamically automates personalized Web-based interactive materials that leverage XML and XSLT technologies.
Abstract: Distance learning systems play an important role in education, enabling students studying on their own to access a variety of Web-based learning materials via the campus network. However, such systems also present some problems, being potentially dull and unhelpful, because the learning materials are the same for every student. Customizing learning materials for individual students is not a cost-efficient way to overcome this situation, owing to the large volume of materials it would require in addition to teacher time. We describe how to resolve this issue using dynamically automate personalized learning materials that leverage XML and XSLT technologies. We describe the implementation methods for our e-math interaction agent distance learning system, which dynamically automates personalized Web-based interactive materials.
23 Mar 2004
TL;DR: A personalized multi-sensory learning model with mobile handheld learning devices to enhance pervasive learning and solve several challenges that the current mobile learning research is facing and unsolved.
Abstract: The objective of this paper is to provide a personalized multi-sensory learning model with mobile handheld learning devices to enhance pervasive learning. This paper distinguishes itself by solving several challenges that the current mobile learning research is facing and unsolved. Our research consists of three phases: Phase one is to develop an ontology and agent based knowledge network framework with content management mechanism for learning content structure, description, representation, retrieval, reuse, revise, retain, exchange and sharing. Phase two is to develop intelligent mobile handheld learning devices with universal access mechanism with personalized learning experience for adaptive and seamless pervasive learning. Phase three is to develop a multi-sensory learning system with compelling examples of pen based, annotation based, context driven, and location based learning service and applications for pervasive learning.
Patent•
10 Mar 2004
TL;DR: In this paper, an education environment management system (EMS) for supporting the customized education considering a characteristic of a leaner is provided to enhance learning efficiency by offering an optimal learning course and environment fit to the learner's characteristic.
Abstract: PURPOSE: An EMS(Education environment Management System) for supporting the customized education considering a characteristic of a leaner is provided to enhance learning efficiency by offering an optimal learning course and environment fit to the learner's characteristic. CONSTITUTION: The EMS system(100) is divided into a front system(110) including the direct interaction with learners and a rear system(120) including the data used by the EMS system. The learner connects to the front system by using a learner computer(140) through the Internet(130). The front system comprises a system operation part(111), a member certification part(112), and a connection part(113). The system operation part checks the certification of the learner by comparing a user ID and a password with a learner related database(121), and displays a customized homepage and a customized learning order of each subject. The rear part comprises the learner related database, an interaction related database(122), a learning object related database(123).
Journal Article•
TL;DR: In this paper, the authors presented a methodology to model a TLP and to build an automatic adaptation mechanism for ITS Interfaces, based in a Neural Network, which was used as a case study to apply and validate the proposed methodology.
Abstract: In a Teaching-Learning Process (TLP) teachers have to support students learning using diverse pedagogical resources. One of teachers' task is to create personalized Learning Environments. Intelligent Tutoring Systems (ITS) try to imitate adaptation capacity of a human teacher. The Interface is the Learning Environment and the system stores knowledge that defines how to adapt it to respond to certain student's characteristics. Adaptation is particularly important for TLP oriented to carriers of chronic diseases like Diabetes, which represent very heterogeneous groups of persons. This article presents a Methodology to model a TLP and to build an automatic adaptation (adaptive) mechanism for ITS Interfaces, based in a Neural Network [1]. The diabetes education was used as a case study to apply and validate the proposed methodology. The most important results of this work are presented here.