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EAI Endorsed Transactions on e-Learning

Issue 9, 2016
Editor(s)-in-Chief: Giovanni Vincenti and James Braman

  • Decision Making in the Connected Learning Environment (CLE)

    Appears in:
    el 16(9): e1

    Authors:
    Anas Belahcen, Mounia Abik, Rachida Ajhoun

    Abstract:
    In the last years, we have witnessed to an increasingly heightened awareness of the potential benefits of a challenging and promising educational research area : Adaptive Learning [1]. It has become one of the central technologies in education [2] and was recently named, by Gartner, as the number o…In the last years, we have witnessed to an increasingly heightened awareness of the potential benefits of a challenging and promising educational research area : Adaptive Learning [1]. It has become one of the central technologies in education [2] and was recently named, by Gartner, as the number one strategic technology to impact education in 2015 [3]. In fact, adaptive learning systems become more accessible to educational institutions, corporations, and individuals, however, the challenges encountered are more structural and operational rather than technological [4]. While a lot of research has focused on development and evaluation of technological aspects [5], serious questions remain about the motivation of learners [6],[7] and also the design of the content (or domain) model [8],[9] including the learner's autonomy issues [9],[10],[11] and the lack of the learner's control [9],[12],[13]. In order to overcome those challenges, we propose CLE “Connected Learning Environment” which is an ubiquitous learning environment [14] that provide to the learners of this generation a learning environment adapted to their expectations and their lifestyle habits and stimulate also their motivation. As a pedagogical approach, CLE adopts the connectivism [15] and take advantage from its benefits (adaptation to the current technological advances [16], management of learning in communities [17], openness with respect to external resources[18], etc.) and adapts this approach in a formal context even though the connectivism was conceived as an informal pedagogical approach [19][20]. CLE introduces a new pedagogical process including four phases detailed later (Knowledge construction, Decision making, Validation, Evaluation) and the knowledge construction phase is characterized by the collaboration and communication between heterogeneous communities composed of humans and smart objects [14]. However, the ability to distinguish relevant information among the knowledge constructed by the actors is a vital point. As part of this article, we focus on the decision making process. To do this, a comparison is made between C4.5 [21] decision tree and MLP [22] neural network on the same data set using the same performance measures in order to take a decision on the relevance of knowledge constructed by the CLE actors.
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  • A Service-oriented Architecture for the Provision and Ranking of Student-Oriented Courses

    Appears in:
    el 16(9): e2

    Author:
    Naseem Ibrahim

    Abstract:
    Research has long proved that student learn in different styles. Different students have different capabilities and needs. On the other hands, in the last few years the popularity of online degrees has dramatically increased. In current online learning model the school specifies the courses require…Research has long proved that student learn in different styles. Different students have different capabilities and needs. On the other hands, in the last few years the popularity of online degrees has dramatically increased. In current online learning model the school specifies the courses required to obtain a degree. For each course the instructor specifies the course elements including teaching method and assessments. But this contradicts the fact that different students have different capabilities and constraints. Most institutions provide the same courses. A student should be able to select the course that best matches his capabilities and constraints as long as it satisfies the required course outcomes. To achieve this goal, this paper proposes the use of Service-oriented Architecture (SOA). This paper introduces an extended service oriented architecture and an extended service definition, which will enable the specification and provision of student-oriented courses. This paper also proposes a student-oriented course composition approach and a student oriented course ranking approach.
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  • E-learning project assessment: A new approach through the analysis of learners’ posts on social media

    Appears in:
    el 16(9): e4

    Authors:
    A. Caione, A.L. Guido, R. Paiano, A. Pandurino, S. Pasanisi

    Abstract:
    E-learning assessment is a key aspect in the overall e-learning process. There are several parameters to consider during the assessment. In recent years, several sets of factors, called Critical Success Factors, have been defined to provide a structural approach to assessment. They focus on many as…E-learning assessment is a key aspect in the overall e-learning process. There are several parameters to consider during the assessment. In recent years, several sets of factors, called Critical Success Factors, have been defined to provide a structural approach to assessment. They focus on many aspects but, in our view, they do not properly consider student satisfaction with courses. In e-learning applications, student opinion must be examined where it is expressed: on e learning course social pages and/or social pages outside the platform but specific to the e-learning course. The problem is that these resources are unstructured and thus it is important to structure these resources before using them for assessment. In this paper, we discuss a proposal that can capture student opinion from social pages, combining several techniques, such as Natural Language Processing, Information Extraction; ontologies that help us to understand what and how students discuss about e-learning courses.
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  • Automation of Algorithmic Tasks for Virtual Laboratories Based on Automata Theory

    Appears in:
    el 16(9): e6

    Authors:
    Evgeniy A. Efimchik, Mikhail S. Chezhin, Andrey V. Lyamin

    Abstract:
    In the work a description of an automata model of standard algorithm for constructing a correct solution of algorithmic tests is given. The described model allows a formal determination of the variant complexity of algorithmic test and serves as a basis for determining the complexity functions, inc…In the work a description of an automata model of standard algorithm for constructing a correct solution of algorithmic tests is given. The described model allows a formal determination of the variant complexity of algorithmic test and serves as a basis for determining the complexity functions, including the collision concept – the situation of uncertainty, when a choice must be made upon fulfilling the task between the alternatives with various priorities. The influence of collisions on the automata model and its inner structure is described. The model and complexity functions are applied for virtual laboratories upon designing the algorithms of constructing variant with a predetermined complexity in real time and algorithms of the estimation procedures of students’ solution with respect to collisions. The results of the work are applied to the development of virtual laboratories, which are used in the practical part of massive online course on graph theory.
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  • Self-directed learning in e-portfolios: Analysing students’ performance and learning presence

    Appears in:
    el 16(9): e3

    Authors:
    A. Jimoyiannis, P. Tsiotakis

    Abstract:
    E-portfolios constitute a dynamic research topic in e-learning, since they foster a new philosophy for learning and personal development, which is characterised by open, participatory, self-directed, reflective and collaborative processes. This paper presents an investigation on students’ learning …E-portfolios constitute a dynamic research topic in e-learning, since they foster a new philosophy for learning and personal development, which is characterised by open, participatory, self-directed, reflective and collaborative processes. This paper presents an investigation on students’ learning presence in a blended post-graduate course, designed to promote self directed learning through e-portfolio activities. The theoretical foundations and the key dimensions of e-portfolio learning activities are outlined, i.e. students’ construction, reflection and collaboration. Following are presented the organizational and the analysis framework of students’ self-directed learning and constructive activities within the e-portfolio. Combining both, descriptive analysis and Social Network Analysis of the research data, we have revealed important information regarding individual performance and students’ learning presence, interaction and collaboration among participants as well as the overall operation of the e-portfolio community.
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  • Web Log Pre-processing and Analysis for Generation of Learning Profiles in Adaptive E-learning

    Appears in:
    el 16(9): e5

    Authors:
    Radhika M. Pai, Sucheta V. Kolekar, Manohara Pai M.M.

    Abstract:
    Adaptive E-learning Systems (AESs) enhance the efficiency of online courses in education by providing personalized contents and user interfaces that changes according to learner’s requirements and usage patterns. This paper presents the approach to generate learning profile of each learner which he…Adaptive E-learning Systems (AESs) enhance the efficiency of online courses in education by providing personalized contents and user interfaces that changes according to learner’s requirements and usage patterns. This paper presents the approach to generate learning profile of each learner which helps to identify the learning styles and provide Adaptive User Interface which includes adaptive learning components and learning material. The proposed method analyzes the captured web usage data to identify the learning profile of the learners. The learning profiles are identified by an algorithmic approach that is based on the frequency of accessing the materials and the time spent on the various learning components on the portal. The captured log data is pre-processed and converted into standard XML format to generate learners sequence data corresponding to the different sessions and time spent. The learning style model adopted in this approach is Felder-Silverman Learning Style Model (FSLSM). This paper also presents the analysis of learner’s activities, preprocessed XML files and generated sequences.
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Scope

Education is one domain that has accompanied civilization throughout the centuries, adapting its tools to fulfill the expectations of students and the needs of teachers. Such tools can be as obvious and traditional as pencils and notebooks, or as complex and innovative as websites or multi-user vir…

Education is one domain that has accompanied civilization throughout the centuries, adapting its tools to fulfill the expectations of students and the needs of teachers. Such tools can be as obvious and traditional as pencils and notebooks, or as complex and innovative as websites or multi-user virtual environments. Typical in-person learning environments, such as classrooms and meeting rooms, are at times not the best solution to enable and maximize a students ability to learn. Although they do fulfill their purpose of giving students the opportunity to understanding course material and to of reaching their instructors, they sometimes can create barriers that cannot be easily overcome.

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Topics

  • Accessibility and usability of web-based instruction in the classroom
  • Assessment
  • Best Practices
  • Collaborative learning and social networks
  • e-Learning workflow
  • Educational/learning repositories
  • Mobile learning
  • Security and privacy in education and e-learning systems …
  • Accessibility and usability of web-based instruction in the classroom
  • Assessment
  • Best Practices
  • Collaborative learning and social networks
  • e-Learning workflow
  • Educational/learning repositories
  • Mobile learning
  • Security and privacy in education and e-learning systems
  • Social and organizational perspectives
  • Standards and infrastructures
  • Student engagement
  • Teaching/Educational Models and Frameworks
  • Virtual Learning Environments
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Special Issues

SI Editor: Dagmar Caganova (Slovak University of technology)

Call for Papers: [SI on Information systems enabling digitalized advances in society](https://escripts.eai.eu/publication/192-information-systems-enabling-digitalized-advances-in-s…

SI Editor: Dagmar Caganova (Slovak University of technology)

Call for Papers: SI on Information systems enabling digitalized advances in society (Submission Deadline: June 30, 2018)

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Editorial Board

  • Abdullah Abonamah (Abu Dhabi School of Management, United Arab Emirates)
  • Alberto Bucciero (Università del Salento, Italy)
  • Aldo Torrebruno (Politecnico di Milano, Italy)
  • Amber Chelette (Ouachita Baptist University, USA)

  • Amruth Kumar (Ramapo Co…

  • Abdullah Abonamah (Abu Dhabi School of Management, United Arab Emirates)
  • Alberto Bucciero (Università del Salento, Italy)
  • Aldo Torrebruno (Politecnico di Milano, Italy)
  • Amber Chelette (Ouachita Baptist University, USA)
  • Amruth Kumar (Ramapo College of New Jersey, USA)
  • Anasol Pena Rios (University of Essex and British Telecom)
  • Andrea Pandurino (Università del Salento, Italy)
  • Andrey Lyamin (ITMO University, Russia)
  • Anna Lisa Guido (Università del Salento, Italy)
  • Athanassios Jimoyiannis (University of Peloponnese, Greece)
  • Debbie Holley (Bournemouth University, UK)
  • Dudley Turner (University of Akron, USA)
  • Ed Currie (Middlesex University, UK)
  • Edward Currie (Middlesex University)
  • Eric Ward (The Community College of Baltimore County, USA)
  • Eusebio Scornavacca (University of Baltimore, USA)
  • Evgeniy Efimchik (ITMO University, Russia)
  • Francisco Bellido (Universidad de Córdoba, Spain)
  • George Evangelinos (Anglia Ruskin University, UK)
  • Goran Trajkovski (Western Governors University, USA)
  • Gordon Hunter (Kingston University, UK)
  • Jaime Meza (Universitat Politècnica de Catalunya, Spain)
  • Jamshid Beheshti (McGill University, Canada)
  • Jia Chen (Associate Professor of English and eLearning, Shanghai International Studies University)
  • John Carfora (Loyola Marymount University, USA)
  • John O'Connor (Dublin Institute of Technology, Ireland)
  • Jonathon Richter (Director of iLRN)
  • Krishnashree Achuthan (Amrita University, India)
  • Leandros Maglaras (University of De Montfort, UK)
  • Luca Ferrari (Università di Bologna, Italy)
  • Maha Althobaiti (University of East Anglia, UK)
  • Marco Zappatore (Università del Salento, Italy)
  • Mark J. W. Lee (School of Education Charles Sturt University AUSTRALIA)
  • Markus Helfert (Dublin City University, Ireland)
  • Matthias Glowatz (University College Dublin, Ireland)
  • Melody Buckner (University of Arizona, USA)
  • Michele Sesana (TXT e-solutions, Italy)
  • Michelle Crosby-Nagy (International Business School, Hungary)
  • Nian-Shing Chen (Editor of Educational Technology and Society)
  • Nicoletta Adamo-Villani (Purdue University, USA)
  • Nicoletta Di Blas (Politecnico di Milano, Italy)
  • Nurul Badrul (Centre for Instructor and Advanced Skill Training, Malaysia)
  • Radhika Pai (Manipal Institute of Technology, India)
  • Regina Kaplan-Rakowski (Southern Illinois University, USA)
  • Richard Boateng (University of Ghana, Ghana)
  • Robert Law (Glasgow Caledonian University, UK) (WRONG WRITTEN GRAMMARLY)
  • Roberto Paiano (Università del Salento, Italy)
  • Sabrina Leone (Università Politecnica delle Marche, Italy)
  • Shyam Diwakar (Amrita University, India)
  • Stefano Za (Università degli Studi eCampus, Italy)
  • Steven Truxal (City University of London, UK)
  • Sujan Shrestha (University of Baltimore, USA)
  • Victor Zamudio (Instituto Tecnologico de Leon, Mexico)
  • Vijayakumar Ponnusamy (SRM University, India)
  • Vladimír Bradáč (Ostravská Univerzita, Czech Republic)
  • Vladimir Bradac (University of Ostrava)
  • Vladimir Uskov (Bradley University, USA)
more »
Publisher
EAI
ISSN
2032-9253
Volume
3
Published
10th Mar 2016