Abstract: Burgos, D., Tattersall, C., & Koper, R. (2007). How to represent adaptation in eLearning with IMS Learning Design. Interactive Learning Environments, 15(2), 161-170.

Abstract: With vigorous development of the Internet, especially the web page interaction technology, distant E-learning has become more and more realistic and popular. Digital courses may consist of many learning units or learning objects and, currently, many learning objects are created according to SCORM standard. It can be seen that, in the near future, a vast amount of SCORM-compliant learning objects will be published and distributed cross the Internet. Facing huge volumes of learning objects, learners may be lost in selecting suitable and favorite learning objects. In this paper, an adaptive personalized recommendation model is proposed in order to help recommend SCORM-compliant learning objects from repositories in the Internet. This model adopts an ontological approach to perform semantic discovery as well as both preference-based and correlation-based approaches to rank the degree of relevance of learning objects to a learner’s intension and preference. By implementing this model, a tutoring system is able to provide easily and efficiently suitable learning objects for active learners.

Abstract: The self-regulated learning is a goal-oriented learning strategy and it is very suitable to be applied in self-management learning for promoting learning performance of individual learner in a web-based learning environment. This study proposes a personalized e-learning system with self-regulated learning assisted mechanisms to help learners promote their self-regulated learning abilities. The proposed self-regulated learning mechanisms aim at guiding learners to become as lifelong learners who own autonomous self-regulated learning abilities.

Abstract: The primary objective of the present investigation was to learn what college teachers say and do to create student perceptions of “personalized education,” and to identify any meaningful factor structure underlying these categories of personalized education characteristics. Additionally, this study was designed to identify how the personalized education construct, as it is perceived by students, may be conceptually and theoretically linked to other instructional communication variables and to establish concurrent validity of a measure of personalized education. Finally, this study examined the relationship between personalized education and learning outcomes. Results should demonstrate the role of instructional communication scholarship in institutional and faculty efforts to create systematic and effective personalized educational experiences for students.

Abstract: The use of electronic environment in our life has become inevitable fact In the educational field, the learners find many difficulties to attend a classical mode of learning (in class) that obliges them to be present according to daily schedule Thus, the E-learning allows the process of learning anywhere and any when However, the absence of the teacher, in the E-learning process, leads to the isolation of the learners Generally, these learners have different backgrounds, preferences, needs, objectives, intellectual abilities and personal characteristics; and they do not understand and acquire the knowledge using the same courses and the same learning styles Several aspects influence the effective learning process Thus, different concepts, views and models of learning styles exist in literature Many models and classifications of learning styles were proposed according to several angles of view For this aim, we propose an educational system that provides the accurate learning content and use the most appropriate learning style that meets the needs and preference of each learner (personalized learning) Our system provides several learning styles for the learners; however, the essential task is to find the best course and learner style for each learner according to his characteristics The adaptation of the content and styles allows the dynamicity in the learning process and gives a new chance for many kinds of learners to enhance their knowledge in personal manner Moreover, the modeling of our system using multi-agents system increases its interaction and flexibility

Abstract: One of the most contemporary research ideas for adaptive Web-based educational systems is personalizing the educational contents, based on users' learning styles. Moreover, it is not the technology that students learn from, but its role should be elucidated as a means to enhance learning. By our proposed adaptive e-learning framework, we attempt to bridge in the gap between pedagogy and technology, emerging in recent Web-based learning environments. This framework provides learners with pedagogically personalized learning contents based on their learning styles. Findings of the study indicate differences in performance between matched and non-matched students in one case of the study and in the other case, demonstrate no significant difference. Although these results pertain to an undergraduate educational session, however our proposed framework is general enough to be applied to effective and efficient pedagogy in any area at any level.

Abstract: This paper explores the interrelationships between identity and learning for adult learners participating in vocational education and training programmes situated within workplaces. Identity is understood to be integral to learning. A theoretical position for understanding identity is developed using a narrative standpoint. Adult learners are understood to bring particular dispositions to workplace learning, in particular, their previous experiences and biographies of learning. The notion of wounding learning practices is articulated to discuss the impact of adult learners' previous encounters with learning. These previous experiences may contribute to weaker identities and dispositions to learning in the workplace. Individuals' identities and relationships to learning impact upon their current and future engagement with affordances of workplace learning. Three significant pedagogical practices, from a two-year workplace training programme involving adult learners from a regional Australian town, ...

Abstract: This study describes an approach to learning and teaching that is structured as a project‐based context‐driven inquiry. The approach is positioned at the interface between knowledge‐generation and use, and grounded in a generic notion of responsibility for the future of bodily life. The intention is to move the debate beyond the exhausted language of rigid oppositions between the academic and vocational, the universal and contextual. The purpose is to identify and nurture a personal portfolio of competencies responding to the contemporary material condition of humanity. It is expressed in terms of the student's learning power, a manifold of new assessment criteria and methodological steps constitutive of what a student could achieve having progressed through a given course. This is an approach in which competencies are outcomes supported rather than led by subject knowledge. The course structure combines traditional instruction with innovative project and assessment components and also provides an opportu...

Abstract: Personalized curriculum sequencing is an important research issue for web-based learning systems because no fixed learning paths will be appropriate for all learners. Therefore, many researchers focused on developing e-learning systems with personalized learning mechanisms to assist online web-based learning and adaptively provide learning paths in order to promote the learning performance of individual learners. Generally, inappropriate courseware leads to learner cognitive overload or disorientation during learning processes, thus reducing learning performance. Therefore, compared with the freely browsing learning mode used in most web-based learning systems, this paper assesses whether the proposed genetic-based personalized e-learning system which can generate appropriate learning paths according to the incorrect testing responses of individual learners in a pre-test provides benefits in terms of learning performance promotion. Experiment results indicated that applying the proposed genetic-based personalized e-learning system for Web-based learning is superior to the freely browsing learning mode because of high quality and concise learning path for individual learners.

Abstract: As online environments gain an increasing presence in higher education for both on-campus students and distance learners, there is a need to examine how effective these environments are for student learning. Online environments require essentially different teaching and learning strategies from those used in the traditional face-to-face contexts (for on-campus students) or with print-based material (for distance learners). This article identifies early childhood teacher education students' perceptions of their learning experiences with the advent of an online learning environment. Perceptions of on-campus and distance learners are compared, and implications for teacher education staff interested in providing high quality learning environments within an online space are discussed.

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.

Abstract: In this chapter we examine how to represent adaptive and adaptable Units of Learning with IMS Learning Design in order to promote automation and interoperability. Based on a literature study, a distinction is drawn between eight types of adaptation that can be classified in three groups: a) the main group, with interfaced-base, learning-flow and content-base; b) interactive problem solving support, adaptive information filtering, adaptive user grouping; and c) adaptive evaluation and changes on-the-fly. Several sources of information are used in adaptation: user, teacher and set of rules. In this paper, we focus on the core group a). Taking the various possible inputs to an eLearning process, we analyze how to model personalized learning scenarios related to these inputs explaining how these can be represented in IMS Learning Design.

Abstract: Learning performance assessment using learning portfolios or Web log data is essential in the Web-based learning field, owing to the rapid growth of e-learning systems globally and lack of assisted authoring tools for Web-based learning performance assessment. The traditional summative evaluation by performing examinations or feedback forms can be employed to evaluate the learning performance for both traditional classroom learning and Web-based learning environments. However, summative evaluation only considers final learning outcomes without considering learning processes of learners. This means that the interactively controlled learning based on the immediate feedback of learning performance cannot be performed in a Web-based learning system. Based on the reasons mentioned earlier, this study presents a data-mining-based learning performance assessment scheme by combining four computational intelligence theories, i.e., gray relational analysis (GRA), K-means clustering scheme, fuzzy association rule mining, and fuzzy inference, in order to identify the learning performance assessment rules using the gathered Web-based learning portfolios of an individual learner. Experimental results indicated that the evaluation results of the proposed scheme are very close to those of summative assessment results. In other words, this scheme can help teachers assess the learning performance of the individual learner precisely utilizing only the learning portfolios in a Web-based learning environment. Therefore, teachers can devote themselves to teaching and designing courseware since they save a lot of time in evaluating learning performance. More significantly, teachers could understand the factors influencing learning performance in a Web-based learning environment according to the obtained interpretable learning performance assessment rules. Besides, teachers can also tune teaching strategies for learners with various learning performances. This result also provides useful information to Web-based learning systems to perform personalized learning mechanisms for individual learners.

Abstract: There is little doubt that intelligent and adaptive educational technologies are capable of providing personalized learning experiences and improving learning success Current challenges for research and development in this field concern, for example, the design of comprehensive data models for adaptive systems as well as the interoperability of systems and the reusability of learning material across different systems In the present work we introduce an ontology model, basically developed in the context of immersive digital games, which attempts to provide a solution to existing problems in resource description On the one hand, comprehensive data models for adaptive systems are supported by separating static information from adaptive systems as far as possible On the other hand, the ontology model offers a potential solution to precise and, above all, learner-centered resource description by separating latent competencies from observable performance (in learning objects or test items)

Abstract: Acknowledgments. Preface. Introduction. SECTION 1. LEARNERS, ACTIVITIES, AND ASSESSMENTS. Chapter 1. Ideas for Supporting Learners and Learning. Learning Agreements. Prework Verification. Study Schedule. Performance Tips. Move It. Confirm Exercise Instructions. E-Portfolio. Anonymous Weekly Survey. Personal Wishes. Really Simple Syndication Feeds. Contingency Plans. Virtual Office Hours. Chatbots. Chapter 2. Ideas for Making Collaboration Work. Group Formation. Prep for Collaborative Work. Team Agreement Template. Team Assessment. Rules of Engagement Agreement. Team Review Form. Chapter 3. Ideas for Making Discussions Work. Discussion Message Protocols. Evaluate Your Contribution. Karma Points for Contributions. Acronym and Emoticon Help. Chapter 4. Ideas for Self-Directed and Asynchronous Activities. Table Organizers. Red Dog. Enter, Compare, Print, and Discuss. Tell Me Why. Time Me. Digital Stories. Share Bookmarks. Tell Me About Yourself. An Expert View. Email the Author. MiniQuest. Blog It. My Chair. Easy Peer Editing. Introducing Critical Evaluation. Chapter 5. Ideas for Synchronous Activities. Chat Moderator. Come (Back) Early. Low-Tech Listening Exercise. Trainer-Expert Collaboration. Pyramid. Before Ninety. Daring Feats. Spotlights. Vowels. Gordon Mackenzie-Style Lecture. Vanity License Plate. Lighten Up. Where Are You? Word Search. Chapter 6. Ideas for Self-Check Activities and Assessments. Adapted Classroom Assessment Techniques. Review Puzzles and Games. Flash Cards. Know Your Flooring. Board Game Self-Check. Drag-and-Drop Self-Check. Fact-or-Fiction Self-Check. Mixed Signals. Millionaire Game. Show Training Value. SECTION 2. INSTRUCTIONAL DESIGN. Chapter 7. Ideas for the Design and Development Process. Process Flowchart. Design Guidelines. Learner Stories. Personalized Learning Model. Content Templates. Fast E-Learning Templates. Chapter 8. Ideas for Navigation and Usability. Concept Maps and Causal Loops for Navigation. Collapsible and Movable Text Layer. Automated Back and Next Buttons and Page Numbering. Double Use Glossary. Automated Reference. Here's What's New. Chapter 9. Ideas for Creative Design. :Funny Stats. Take the Metro. Metaphors to Aid Learning. Stories to Understand the Big Picture. Virtual Coach. Field Clinic. Outrageous Nonexamples. What I Really Think. Virtual Campus. Visual Ideas. Chapter 10. Ideas for Creative Media. Show Me. Slow or Fast Images. Energy Balance. Interactive History. Interactive Physics. Inside a Cell. Sea Vents. Tsunami. Movement Sensors. Genome Timeline. DNA Sliding Clamp. DNA Sequence Explorer. Build Your Own Instructional Game. It's NOT Ninety-Five. Glossary. Your Ideas. Index. About the Editor.

Abstract: Educational resources available on the Web are invaluable learning objects that should not only be accessible, sharable and informative, but also reusable, constructive, and responsive to various pedagogical aspects. Using “Ontology”, the knowledge representation core of the Semantic Web, to organize, personalize, and publish learning resources and to discover, generate and compose learning objects has been widely proposed. In response to the diverse education needs, especially learning on the Web, this chapter addresses the issues and methodologies in the design and construction of education ontology and discusses the necessities of such an education ontology that can help retrieving, organizing, and recommending educational resources for personalized learning. Follow a systematic ontology construction approach, the design and implementation of a Personalized Education Ontology (PEOnto) will demonstrate the flexibilities of ontology usages in performing different education tasks as well as enhancing system extensibilities and exchangeabilities.

Abstract: The educational society faces the challenge of improving the quality of education, while increasing the percentage of students that pass a class, given limited teaching resources. In response to this demand, this work reports on the architecture and the implementation of a system for adaptive multi-user assessment of students. The software is a client/server platform developed in Java programming language, which is termed platform for adaptive and reliable evaluation of students (PARES). Hypertext markup language is used for the development of pages including text and figures. PARES includes three modules, which can be remotely connected to the system database on server through network. The Bayesian decision model is applied to adaptive testing, instead of the traditional item response theory. PARES can be used interactively by administrators, course instructors and students. When PARES is used for self-assessment, feedback is provided to the student's answer. As a result, personalized learning assistance is provided to improve a student's level of proficiency. Experimental results show that when students take self-assessment tests a week before scheduled formative tests, their scores are increased.

Abstract: Information about a studentâ??s level or state of knowledge is a key aspect for efficient, personalized learning activities. E-learning systems gain such information in two ways: directly by examining usersâ?? self-assessment and administering predefined tests and indirectly by making inferences on observed user behaviors. However, most of the current solution approaches either demand excessive manpower or lack required reliability. To overcome these problems, we have developed the e-Examiner, an assessment tool that supports the assessment process by creating automatically test items, assessing studentsâ?? answers and providing feedback. In this paper, we firstly give an overview about a variety of computer-assisted and computer-based assessment systems and methods that support formative assessment activities. Secondly, we introduce the overall concept and architecture of the e-Examiner. Thirdly, we outline implementation details and evaluation results of our prototype implementation. Our solution approach is based on the set of statistical similarity measures defined by the ROUGE toolset for automatic summary evaluation.

Abstract: Networked education is developing increasingly toward the direction of personalization. Inspired by the personality analysis process based on a learner model, a method for customizing personalized learning strategies was presented. Its process is as follows, firstly, aiming at the weakness of the personality description method and the lack of effective personality analysis method in current researches of learning strategies personalization, a learner personality model which can support learner personality analysis by static and dynamic methods in an intelligent e-learning environment was proposed. Secondly, a personality analysis process using data mining technologies based on the learner model was introduced. Finally, a prototype system of learning strategies personalization was designed and implemented according to the learner model and process. The experiment results showed the process's availability and functionality, such as acquiring learners' personalities by static and dynamic methods, and customizing individual learning strategies. Keywords:

Abstract: In this paper we propose an algorithm for personalized learning based on a user's query and a repository of lecture subparts --i.e., learning objects-- both are described in a subset of OWL-DL. It works in two steps. First, it retrieves lecture subparts that cover as much as possible the user's query. The solution is based on the concept covering problem for which we present a modified algorithm. Second, an appropriate sequence of lecture subparts is generated. Indeed, the different lecture subparts are only reachable when a given prerequisite is fulfilled, i.e., the learner must have a minimal background knowledge to be able to assimilate the requested learning object. Therefore, our algorithm takes into account the user's knowledge to generate a personalized lecture composition and suggests a flow of learning objects to the user.

Abstract: Motivation -- The mismatch between current e-Learning design and user needs has drawn the research attention on personalized instruction. Our research intends to investigate the impact on e-Learners' learning performance and experience using various modalities presenting the learning content based on Felder-Silverman's learning style theory, and eventually to provide the possible suggestions on content modality design.Research approach -- Laboratory experiment is our main approach to conduct this research. 28 participants with similar profiles pertaining to the dominant styles will be recruited from Computing and Information Systems subjects. A two-group design with repeated measures is selected so the same participants will use two different e-Learning environments in order to investigate their influences on the students' learning performance and experience.Findings/Design -- Our previous studies claimed the suitability of Felder-Silverman's theory as the theoretical basis for the research. A framework was also developed to identify the main e-Learning system features accommodated to typical science and technology students.Take away message -- As learning styles are believed to be considerably important to instruction, our research on content modality design is likely to help facilitate the users' learning performance and experience in e-Learning.

Abstract: Personalized E-Learning is a research area with the grandiose goal of automatically or semi-automatically matching the learning contents with the needs and preferences of the learners. This paper proposes a modest goal of creating learning contents to help the learners engaged in self-paced E-Learning learn effectively at appropriate levels of difficulty and detail. It also proposes a goal of making it easier for the content creators to create new learning contents by reusing and adapting existing content fragments. More ambitious goals may be addressed by building on the results of these modest goals.

Abstract: The creation of personalized learning experiences is considered as a necessity to cope with the overwhelming amount of available learning material. This paper presents a personalization framework and an algorithm that allows for the creation of pedagogically sound learning experiences taking into account the variety of the learners and their individual needs.

Abstract: This paper focuses on the design of learning tools that appropriately support ‘Learning Design’ (Koper and Tattersall, 2005). Specifically, these tools can be used in lesson planning to encourage the development of critical thinking in learners. In particular, a Cognitive Skill-based Question Wizard (CSQ-Wizard) is proposed as a supporting tool for teachers in their attempts to design appropriate lesson plans that can encourage the development of cognitive skills in learners. The design of this CSQ-Wizard is based on modern social and constructivist views of learning. The idea, the rationale, the architecture and the interface associated with the proposed CSQ-Wizard is presented through a specific example of possible implementation within LAMS; a web-based open source environment that supports Learning Design.

Abstract: A major drawback of current e-learning systems is that they are too disconnected from learner's learning preferences and learning goals. There has been a high demanding for learner centric e-learning systems. Research on personalized e-learning is emerging in recent years. However, most of the current research is focused on user profile modeling, and learning styles research, etc. In this paper, we propose a novel goal oriented approach towards learner centric and personalized e-Learning. With this approach, learning goals are immersed into the courses or learning objects to bridge the gap between the individual learner's goal and the learning objects. Personalized learning path which satisfies the learner's goals can be generated for individual learners. A prototype system is demonstrated as the proof of concept.

Abstract: Learners in traditional or web-based learning environment might get little learning effect by just memorizing the lecture contents. Mobile learning can give learners a chance to remedy their weakness parts in the real world with touch, feel, and observation. This paper develops a learning path planner for learning in a museum according to learners' misconception. The planner gives learners a personalized learning path in a museum in order to make individual do an efficiently remedial study. This paper mainly describes the operational process of the learning path planner and uses a complete example as demonstration. The related detailed theories and calculation methodologies are not this paper's focus.