Advances in web based learning – ICWL 2016 15th international conference

308 51 0
  • Loading ...
1/308 trang
Tải xuống

Thông tin tài liệu

Ngày đăng: 14/05/2018, 11:06

LNCS 10013 Dickson K.W Chiu · Ivana Marenzi Umberto Nanni · Marc Spaniol Marco Temperini (Eds.) Advances in Web-Based Learning ICWL 2016 15th International Conference Rome, Italy, October 26–29, 2016 Proceedings 123 Lecture Notes in Computer Science Commenced Publication in 1973 Founding and Former Series Editors: Gerhard Goos, Juris Hartmanis, and Jan van Leeuwen Editorial Board David Hutchison Lancaster University, Lancaster, UK Takeo Kanade Carnegie Mellon University, Pittsburgh, PA, USA Josef Kittler University of Surrey, Guildford, UK Jon M Kleinberg Cornell University, Ithaca, NY, USA Friedemann Mattern ETH Zurich, Zurich, Switzerland John C Mitchell Stanford University, Stanford, CA, USA Moni Naor Weizmann Institute of Science, Rehovot, Israel C Pandu Rangan Indian Institute of Technology, Madras, India Bernhard Steffen TU Dortmund University, Dortmund, Germany Demetri Terzopoulos University of California, Los Angeles, CA, USA Doug Tygar University of California, Berkeley, CA, USA Gerhard Weikum Max Planck Institute for Informatics, Saarbrücken, Germany 10013 More information about this series at http://www.springer.com/series/7409 Dickson K.W Chiu Ivana Marenzi Umberto Nanni Marc Spaniol Marco Temperini (Eds.) • • Advances in Web-Based Learning ICWL 2016 15th International Conference Rome, Italy, October 26–29, 2016 Proceedings 123 Editors Dickson K.W Chiu University of Hong Kong Hong Kong SAR China Marc Spaniol University of Caen Normandy Caen France Ivana Marenzi L3S Research Center Hannover Germany Marco Temperini Sapienza University of Rome Rome Italy Umberto Nanni Sapienza University of Rome Rome Italy ISSN 0302-9743 ISSN 1611-3349 (electronic) Lecture Notes in Computer Science ISBN 978-3-319-47439-7 ISBN 978-3-319-47440-3 (eBook) DOI 10.1007/978-3-319-47440-3 Library of Congress Control Number: 2016953289 LNCS Sublibrary: SL3 Information Systems and Applications, incl Internet/Web, and HCI © Springer International Publishing AG 2016 This work is subject to copyright All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed The use of general descriptive names, registered names, trademarks, service marks, etc in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer International Publishing AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland Preface This volume presents the proceedings of the 15th edition of the annual International Conference on Web-based Learning (ICWL) The first ICWL event held was in Hong Kong in 2002 Since then it has been held 13 more times, in three continents: Australia (2003), China (2004, 2008, 2010), Hong Kong (2005, 2011, 2015), Malaysia (2006), UK (2007), Germany (2009), Romania (2012), Taiwan (2013), Estonia (2014) ICWL 2016 was organized by the Sapienza University of Rome a collegiate research university located in Rome, Italy It is the largest European university in terms of enrolments (the third one if distance-learning schools are also considered) and one of the oldest in the world, founded in 1303 “Sapienza” educated numerous notable alumni, including many Nobel laureates, presidents of the European Parliament, heads of several nations, notable religious figures, scientists, and astronauts One trait of (ancient) Romans is that they were able to learn from their interactions with other countries and make their own civilization better In ICWL we mean “interactions” in a more peaceful way, yet with the same aim, of making our community’s insights and innovative ideas about Technology Enhanced Learning better The topics proposed in the ICWL Call For Papers included several relevant issues, ranging over: Learning Models, Collaborative Learning, Serious Games, Technology Enhanced Learning in Education, Massive Open Online Courses (MOOCs), Mobile Learning, and more We had 110 submitted contributions All submissions were assigned to three members of the Program Committee (PC) for review All reviews were checked and discussed by the team of PC chairs, and additional reviews or meta-reviews were elicited if necessary The proceedings include the contributions that were finally presented at the conference: 19 full papers, ten short papers and four posters, for a total of 33 papers, yielding a global acceptance rate of 31.82 % ICWL 2016 featured three distinguished keynote presentations, by renowned scholars: Peter Brusilovsky, University of Pittsburgh, USA (“Data-Driven Education: Using Learners’ Data to Improve Teaching and Learning”); Carlo Giovannella, Tor Vergata University, Rome, Italy (“Uncovering and Supporting the Smartness of Learning Ecosystems”); and Andreja Istenič Starčič, University of Primorska, Slovenia (“Representations in Contemporary Learning Environments”) The conference also provided a plenary presentation about the European Research Council (ERC), aimed to be attractive and useful for young (and less young) researchers attending the conference A doctoral consortium was organized concurrently with the conference and provided an opportunity for PhD students to discuss their work with experienced researchers This year ICWL supported the organization of a new initiative, the “First International Symposium on Emerging Technologies for Education” (SETE) at the same location SETE collected the traditional workshop activities managed by ICWL in the VI Preface past years, and additionally featured a novel organization in tracks Workshops and tracks added new and hot topics on Technology Enhanced Learning, providing a newer 2016 overall conference experience to the ICWL attendees Many people contributed to make the conference possible and successful First of all we thank all the authors who have considered ICWL for their submissions We also thank the PC members, and the additional reviewers, for their evaluations that made possible the selection of the accepted papers For the organization effort of ICWL 2016, additional thanks go to the publicity chair, Martin Homola, the poster co-chairs, Damiano Distante, Luigi Laura, and Filippo Sciarrone, the Web chair, Andrea Sterbini, the doctoral consortium co-chairs, Maria De Marsico, Zuzana Kubincova, and Carla Limongelli, and the proceedings chair, Pavlos Fafalios We also thank the following sponsors, for their enlightened and much appreciated financial support, which helped make the whole operation sustainable: IAD, Solutions by Competence; Springer, who offered their sponsorship; and UniTelma-Sapienza University, which is also the place where part of the Organizing Committee undertakes research activities in Technology Enhanced Learning We hope that the reader of this volume will be pleased with the relevance of the topics and the contents of the papers, possibly being enticed to contribute to next editions of ICWL October 2016 Dickson K.W Chiu Ivana Marenzi Umberto Nanni Marc Spaniol Marco Temperini Organization Conference Co-chairs Marc Spaniol Marco Temperini University of Caen Normandy, Caen, France Sapienza University, Rome, Italy Steering Committee Representatives Horace H.S Ip Elvira Popescu City University of Hong Kong, SAR China University of Craiova, Romania Technical Program Committee Co-chairs Dickson K.W Chiu Ivana Marenzi Umberto Nanni University of Hong Kong, SAR China L3S Research Center, Hannover, Germany Sapienza University, Rome, Italy Publicity Chair Martin Homola Comenius University in Bratislava, Slovakia Poster Co-chairs Damiano Distante Luigi Laura Filippo Sciarrone Unitelma-Sapienza University, Rome, Italy Sapienza University, Rome, Italy Roma Tre University, Italy Web Chair Andrea Sterbini Sapienza University, Rome, Italy Doctoral Consortium Co-chairs Maria De Marsico Zuzana Kubincova Carla Limongelli Sapienza University, Rome, Italy Comenius University in Bratislava, Slovakia Roma Tre University, Italy Proceedings Chair Pavlos Fafalios L3S Research Center, Hannover, Germany VIII Organization Program Committee Marie-Helene Abel Carlos Alario-Hoyos Dimitra Anastasiou Maria Bielikova Maria Bortoluzzi Yiwei Cao Dickson K.W Chiu Maria Cinque Maria De Marsico Pieter De Vries Michael Derntl Giuliana Dettori Tania Di Mascio Stefan Dietze Damiano Distante Hendrik Drachsler Pavlos Fafalios Baltasar Fernandez-Manjon Giovanni Fulantelli Dragan Gasevic Rosella Gennari Panagiotis Germanakos Denis Gillet Sabine Graf Christian Gütl Eelco Herder Sandra Hofhues Martin Homola Horace Ip Malinka Ivanova Mirjana Ivanovic Jelena Jovanovic Elisabeth Katzlinger Ioannis Kazanidis Michael Kickmeier-Rust Ralf Klamma Tomaž Klobučar Line Kolås Milos Kravcik Marc Krüger HEUDIASYC Université de Technologie de Compiègne, France Universidad Carlos III de Madrid, Spain Luxembourg Institute of Science and Technology Slovak University of Technology in Bratislava University of Udine, Italy Information Multimedia Communication (IMC) AG, Germany The University of Hong Kong, SAR China Università LUMSA, Rome, Italy Sapienza University, Rome, Italy Delft University of Technology, The Netherlands University of Tübingen, Germany Istituto di Tecnologie Didattiche del CNR, Italy University of L’Aquila, Italy L3S Research Center, Hannover, Germany Unitelma Sapienza University, Rome, Italy Open University of The Netherlands L3S Research Center, Hannover, Germany Universidad Complutense de Madrid, Spain Istituto Tecnologie Didattiche, CNR, Palermo, Italy University of Edinburgh, UK Free University of Bozen-Bolzano, Italy University of Cyprus Swiss Federal Institute of Technology in Lausanne (EPFL) Athabasca University, Canada Technical University of Graz, Austria L3S Research Center, Hannover, Germany University of Cologne, Germany Comenius University in Bratislava, Slovakia City University of Hong Kong, SAR China Technical University, Sofia, Bulgaria University of Novi Sad, Serbia University of Belgrade, Serbia Johannes Kepler University, Linz, Austria Eastern Macedonia and Thrace Institute of Technology, Greece Technical University of Graz, Austria RWTH Aachen University, Germany Institut Jozef-Stefan, Slovenia Nord University, Norway RWTH Aachen University, Germany University of Applied Sciences, Coburg, Germany Organization Zuzana Kubincová Vive Kumar Lam-For Kwok Mart Laanpere Jean-Marc Labat Rynson Lau Luigi Laura Elise Lavoué Howard Leung Frederick Li Carla Limongelli Wei Liu George Magoulas Katherine Maillet Ivana Marenzi Alke Martens Harald Mayer Umberto Nanni Wolfgang Nejdl Kyparissia Papanikolaou Kai Pata Elvira Popescu Francesca Pozzi Eric Ras Neil Rubens Demetrios Sampson Olga C Santos Filippo Sciarrone Ruimin Shen Marc Spaniol Marcus Specht Natalia Stash Andrea Sterbini Davide Taibi Gary K.L Tam Marco Temperini Stefan Trausan-Matu Lorna Uden Carsten Ullrich Carlos Vaz de Carvalho Riina Vuorikari Jianxin Wang Fridolin Wild IX Comenius University in Bratislava, Slovakia Athabasca University, Canada City University of Hong Kong, SAR China Tallinn University, Estonia Laboratoire d’Informatique de Paris (LIP6), France City University of Hong Kong, SAR China Sapienza University, Rome, Italy Université Jean Moulin Lyon 3, France City University of Hong Kong, SAR China University of Durham, UK Roma Tre University, Italy Shanghai University, China Birkbeck College and University of London, UK Institut Mines-Télécom, Télécom Ecole de Management, France L3S Research Center, Hannover, Germany University of Rostock, Germany Joanneum Research, Austria Sapienza University, Rome, Italy L3S Research Center, Hannover, Germany School of Pedagogical and Technological Education, Greece Tallinn University, Estonia University of Craiova, Romania Institute for Educational Technology (ITD-CNR), Italy Luxembourg Institute of Science and Technology University of Electro-Communications, Tokyo, Japan University of Piraeus and CERTH, Greece aDeNu Research Group (UNED), Spain Roma Tre University, Italy Shanghai Jiaotong University, China University of Caen Normandy, Caen, France Open University of The Netherlands Eindhoven University of Technology, The Netherlands Sapienza University, Rome, Italy Istituto Tecnologie Didattiche, CNR, Palermo, Italy Swansea University, UK Sapienza University, Rome, Italy University Politehnica of Bucharest, Romania Staffordshire University, UK Shanghai Jiaotong University, China Instituto Politecnico Porto, Portugal Institute for Prospective Technological Studies (IPTS), European Commission Central South University, China Oxford Brookes University, UK 290 5.2 D.J Salas et al Sample Involved in the Training In the population study object 30 students participated a Training for beginning researchers 21 males and females, who were undergoing the eight semester of the system engineering program of the University of Córdoba in Colombia The ages varied between 20 and 22 years old They came from institutional beginner research centers (called “semilleros” in Spanish meaning “seedbeds”) 5.3 Results of the Training This section describes the main results obtained by the students in the training for formulating research questions using Binnproject Actors Participation and Interaction Students had an active participation in the discussion forums, 27 students participated with comments and supporting their thoughts about how to formulate research questions, main difficulties in the formulation and how to deal with they Regarding the activity of searching research questions into research papers, 30 students participated coming up with the following results: the average of scientific papers gathered by each student was of 10 papers, 90% of the students were able to identify the questions pertaining to the research in those respective papers and the other 10% of students had difficulties finding and describing the research question in their gathered papers Main research areas in the papers were software engineering, ubiquitous computation, augmented reality and educational video games Table Commentaries and recommendations made by the teachers and the expert Commentaries Writing the questions in the infinitive tense Revising the orthography The question is too general Revising the verbs used to ask the question The question cannot by asked in a way that requires a yes/no answer Revising the coherence of the research question The question is ambiguous The question is obvious It’s a question that generates an opinion and not a research question 10 The question is not clear enough Recommendations The question should be formulated using simple language The question should be concise The question should have answer options Verify if the question is relevant Determine the question of the research The question should have a proper level of complexity Disaggregate the question Do not write questions as affirmations Avoid excessive simplicity 10 The question relates to multiple areas of study Supporting the Acquisition of Scientific Skills by the Use of Learning Analytics 291 The beginning researchers were asked that based on the papers they studied, gathered around the four major research areas: software engineering, ubiquitous computation, augmented reality and video games, to start formulating a research proposal by initiating a process of creating research questions using the BinnProjectt system Beginning researchers were organized in the following manner: eight (8) students were dedicated to formulate research questions in the software engineering area, six (6) students in the area of ubiquitous computation, eight (8) students in the augmented reality area and eight (8) students in the video game area During the process of formulating investigative questions in the BinnProjectt system, on average, this is what was generated: 10 commentaries and recommendations by each revision of the director teacher, co-director teacher and expert, in charge of monitoring the questions being created The main commentaries and recommendations types made by the teachers and the expert about the process of formulating research questions are described in Table Students’ Scores The main results achieved by students in the assessment graded by teachers and experts during the training are shown in Table Table shows no significant differences between the scores given to students by teachers and experts, however scores given by experts were slightly higher average than those give by teachers Table Scores assigned by Teachers and experts to students Teachers and experts Attended Sample Co-director’s Director’s Expert’s Total 30 30 30 90 5.4 Average Score assigned by Teachers and experts 3,19 3,05 3,24 3,16 Standard deviation Variation coefficient Min Max 0,69894 0,844352 0,906148 0,815827 21,9103% 27,6837% 27,9675% 25,8173% 2,0 2,0 1,5 1,5 5,0 5,0 5,0 5,0 Weka Analysis Based on information from the 30 students under study and the assessments made by the teachers and experts in each questions, the K-Means algorithm was applied in Weka in order to determine the behavior of the students on a group level, using four iterations, thirty observations and three variables, as well as defining two clusters, and The first cluster had the initial points [3,4,4] selected in a random manner and the second cluster with the initial points [4,3,3], also selected in the same way as the previous one (Table 4) Related to the cluster set up, it is equivalent to 57%, corresponding to 17 students, whereas within cluster 1, the 43% correspond to 13 students Clusters group students according with their Low or High level of performances It could help teachers to offer special guidance to students located in the Low Level 292 D.J Salas et al Table Results implementing the K-means algorithm in Weka Attributes Director’s assessment Co-director’s assessment Expert’s assessment Complete data (30) Cluster (17) Cluster (13) 3,05 3,5882 2,3462 3,19 3,6059 2,6462 3,24 3,764 2,5538 The results applying the K-Means algorithm indicate that evidently, the 13 junior researches grouped in cluster obtained an assessment varying between 2,3 and 2,6, and that, on the other hand, it is observed that there is a group of 17 junior researchers that obtained a major average assessment, varying between 3,5 and 3,7 However, when observing all the collective data, that is, from all the 30 students, the assessment’s relative average is between 3,05 and 3,24 Conclusions This work showed an outline of analytics supporting the acquisition of scientific skills by junior researchers Equally, a complete process following a specific case study related to the skill of formulating research questions was presented, where the most significant results are related to conceptual appropriations by the junior researchers as a consequence of a training process Another aspect achieved was a process of interaction between junior researchers and reviewers and experts through the BinnProject software, managing to collaboratively elaborate research questions within a research project Through a process of regular and permanent revision, the advancements of the junior researchers were highlighted, obtaining as well feedback that facilitated reflection and analysis of the training process Added up to this, an exercise of behavior analysis was conducted to the junior researchers, using the assessments made by the teachers and experts in regard to the research questions, adjusted to be examined in Weka using the K-means algorithm There, it was observed that evidently, the behavior of a group of 17 junior researchers towards the assessments made to formulate research questions was relatively higher than the one in the second group of 13 researchers The final purpose is to generate new strategies to improve practices in the classroom References Reeves, T.C.: Enhancing the Worth of Instructional Technology Research through “Design Experiments” and Other Development Research Strategies Paper presented Annual Meeting of the American Educational Research Association, New Orleans (2000) Pistilli, M.D., Arnold, K.E.: Course signals at Purdue: using learning analytics to increase student success In: 2nd International Conference on Learning Analytics and Knowledge, May, pp 2–5 (2012) Supporting the Acquisition of Scientific Skills by the Use of Learning Analytics 293 Graf, S., Ives, C., Rahman, N., Ferri, A.: AAT: a tool for accessing and analysing students’ behaviour data in learning systems In: 1st International Conference on Learning Analytics and Knowledge, pp 174–179 (2011) Burkhardt, G., Gunn, C., Dawson, M., Coughlin, E.: Literacy in the digital age Br J Educ Technol 37, 315 (2003) Turiman, P., Omar, J., Daud, A.M., Osman, K.: Fostering the 21st century skills through scientific literacy and science process skills Procedia Soc Behav Sci 59, 110–116 (2012) González, J., Wagenaar, R.: Una introducción a Tuning Educational Structures in Europe La contribución de las universidades al proceso de Bolonia Bilbao Publicaciones la Univ Deusto, p 96 (2009) Beneitone, P., Gonzalez, J., Siufi, R., Wagenaar, G.: Reflexiones y perspectivas de la educación superior en América Latina Inf Final Tuning—América Lat., pp 1–432 (2004) Tobergte, D.R., Curtis, S.: National assessment program science literacy year report J Chem Inf Model 53(9), 1689–1699 (2013) Gil Pérez, D., Macedo, B., Martínez, Torreglosa, J., Sigifredo, C., Valdés, C., Vilches, A.: Cómo promover el interés por la cultura científica (2005) 10 OECD: Pisa 2015 Draft Science Framework (2015) 11 Blikstein, P.: Using learning analytics to assess students’ behavior in open-ended programming tasks Learning, October, pp 110–116 (2011) 12 Worsley, M., Blikstei, P.: What’s an expert? Using learning analytics to identify emergent markers of expertise through automated speech, sentiment, and sketch analysis Educ Data Min 2011, (2011) 13 Bollier, D.: The Promise and Peril of BIG DATA 14 Romero, C., Ventura, S.: Educational data mining: a survey from 1995 to 2005 Expert Syst Appl 33(1), 135–146 (2007) 15 Siemens, G., Baker, R.S.J.: Learning Analytics and Educational Data Mining: Towards Communication and Collaboration (2010) 16 Siemens, G., Gasevic, D., Haythornthwaite, C., Dawson, S., Shum, S.B., Ferguson, R.: Open learning analytics: an integrated & modularized platform proposal to design, implement and evaluate an open platform to integrate heterogeneous learning analytics techniques (2011) 17 Siemens, G.: What are Learning Analytics? Pagine Web (2011) 18 Elias, T.: Learning analytics: definitions, processes and potential Learning, p 23 (2011) 19 Duval, E.: Learning Analytics and Educational Data Mining (2012) 20 Shum, S.B.: Learning analytics J Interact Online Learn Soc Behav 53(4), 395 (2012) 21 Ferguso, R., Shum, S.B.: The Open University’ s repository of research publications Social Learning Analytics: Five Approaches Conference Item Social Learning Analytics: Five Approaches (2012) 22 Shum, S.B., Ferguson, R.: Social learning analytics KMi Technical Report (2011), vol 15, June (2011), p 2330616 (2012) 23 Ferguson, R., Shum, S.B.: Social Learning Analytics: Five Approaches, Open Univ.’s Repos Res Publ (2012) 24 Fergunson, R.: Learning analytics: visions of the future In: The “LASI Spain 2016” International Workshop is Organized by the University of Deusto (UD) with the Collaboration of SNOLA (Spanish Network of Learning Analytics) (2016) 25 NPA: National Postdoctoral Associate Core Competencies Self-Assessment Checklist 26 Shavelson, R., McDonnell, J.: What are educational indicators and indicator systems? Pract Assessment Res Eval (1991) 27 Scheffel, M., Drachsler, H., Stoyanov, S., Spech, M.: Quality Indicators for Learning Analytics, vol 17, pp 124–140 (2014) Using Personal Learning Environments to Support Workplace Learning in Small Companies Miloš Kravčík(&), Kateryna Neulinger, and Ralf Klamma Advanced Community Information Systems (ACIS), RWTH Aachen University, Informatik 5, Aachen, Germany {kravcik,neulinger,klamma}@dbis.rwth-aachen.de Abstract Small companies play a crucial role in developed economies In order to address new challenges they have to fill promptly their competence gaps, when these appear To achieve this, suitable forms of informal learning at the workplace are usually needed As a possible solution we have developed a customized Personal Learning Environment for this purpose and evaluated it in the German Information Technology sector Our experimental study has shown that although it is not easy to get small companies involved in this kind of piloting, the approach can be viable and has a potential for further improvements Keywords: Informal workplace learning Á Personal Learning Environments Introduction Small and Medium Enterprises (SMEs) represent a majority of all companies and employ most people They are also responsible for driving innovation and competition in many economic sectors However, the participation of small enterprises in Vocational Education and Training (VET) is declining in the EU, so it is a challenge to engage them in developing a positive attitude towards training [1] Informal learning at the workplace attracts the attention of many researchers and developers, who can benefit from various funding opportunities in this field The EU Leonardo-Da-Vinci project BOOST (Business perfOrmance imprOvement through individual employee Skills Training) aimed to support the participation of small enterprises (with less than 20 employees) at VET programmes With the system developed in BOOST, small enterprises can identify their critical business needs and then organize the learning process accordingly It is important to consider the interests of various types of users in order to motivate them to use the tools This paper makes the following contributions to the field: In an innovative methodology we further developed the self-regulated learning approach to open it for organizational roles like managers and employees Based on the open-source software development kit for personal learning environments, we implemented eight new adaptive learning widgets and localized them for five languages © Springer International Publishing AG 2016 D.K.W Chiu et al (Eds.): ICWL 2016, LNCS 10013, pp 294–302, 2016 DOI: 10.1007/978-3-319-47440-3_33 Using PLEs to Support Workplace Learning in Small Companies 295 We evaluated our approach in the German Information Technology (IT) sector in a qualitative way In the rest of the paper we first introduce the related work Then an explanation of the BOOST methodology follows, complemented by an illustration of the BOOST technological platform The core of this article is a description of the qualitative evaluation in the German IT sector, considering various user perspectives Finally, we conclude summarizing the main findings Related Work Although SMEs play an important role in economic development, research shows that often their managers and employees lack specific education, which hampers their ability to succeed and develop [2, 3] Nevertheless, many SMEs did recognize the potential value of workplace learning and training for the performance of their business [4] This concept has received a lot of attention already in the 90ies Much of this research has been reviewed in [5] and based on his analysis the author identified the importance to perform learning activities while people are at work He also specified main problems associated with engaging SMEs in training activities One of them is a lack of internal capacity and motivation to provide learning opportunities for employees This finding is supported by [6], claiming that in SMEs a lot of learning takes place through work processes, is multi episodic, often informal, problem based, and takes place on a just in time basis Moreover, [7] describes several design requirements and objectives derived from SME managers’ business needs, in order to learn more effectively at the workplace For example, people should be able to communicate effectively, cultivate networks and relationships, and manage tasks In a recent review, [8] summarizes that training provided through government courses is typically perceived by owner-managers as lacking value in improving business performance Especially within fast-changing workplace recently, there is an increased need to identify the most constructive and cost-effective ways for workplace learning support by technology [9] In the context of lifelong and informal learning at the workplace, also Self-Regulated Learning (SRL) plays an important role The SRL skills need to be cultivated and can be supported by properly designed Personal Learning Environments (PLEs) [10] Based on these requirements, in the BOOST project we addressed the issues of informal workplace learning considering the demands both of managers and employees by providing tailored PLEs BOOST Methodology According to the European Commission small enterprises have up to 50 employees In the BOOST project (http://www.boost-project.eu/) the target group was specified as small enterprises with less than 20 employees The main challenge was to integrate and further develop the sound methodology from the BeCome project (http://become.dedi 296 M Kravčík et al velay.greta.fr/) and the widget-based technology from the ROLE project (http://www role-project.eu/), in order to satisfy the relevant requirements of small companies and their employees Our main aim was to ensure that the provided tools were interesting and useful for end-users, easy to use, and support workplace learning processes Based on the previously mentioned SRL research, we wanted to support specific learning processes that appear in four major phases: planning, tutoring, learning, and reflection In Planning critical business goals in the company (with related competences) are specified and suitable employees to address them are selected In Tutoring phase relevant learning resources are assigned to target competences In Learning phase access to relevant learning resources is provided and search facilities enable to look for additional ones Reflection means monitoring of the learning progress of the whole company, as well as of individual employees The created data hierarchy has Business Goals at the top Each of them refers to relevant Learning Indicators (competences) and for those appropriate Learning Resources (materials, tools, and peers) are recommended We distinguished two user roles: manager (also as trainer) and employee Manager specifies business goals with learning indicators and assigns them to suitable employees This role does also assignment of learning resources to learning indicators and monitoring of the learning progress at both the company and individual level Employees can view their learning tasks, learn by accessing the resources, and reflect on their progress BOOST Technology The BOOST learning platform [11, 12] is a widget-based web application, developed with the ROLE Software Development Kit (https://github.com/rwth-acis/ROLE-SDK) This approach enables creation of tailored learning environments (Start, Management, and Learning) from simple software components for each particular phase that we consider The advantage of PLEs is that users can easily adjust the arrangement and functionality of these environments according to their current needs and preferences The platform enables inter-widget communication and supports also real-time chats The BOOST software is open source and currently available in five languages English, Greek, Czech, French, and German After login users enter the Start area, where an introduction and usage instructions are available, the preferred language can be chosen and managers can also assign roles to users In the Management area (Fig 1) managers specify business goals and assign them learning indicators with priorities in Goals widget Then they can assign learning goals with target proficiency levels and deadlines to employees in Personnel widget The overall and individual progress of all employees (corresponding to their assigned goals) can be monitored in Progress widget by managers The main difference for employees here consists in having access only to their own data, which was a crucial requirement from our users Managers their tutoring and employees their learning tasks in Learning area (Fig 2) Here Resources widget shows learning resources assigned to learning indicators (and business goals), Viewer widget displays the selected learning resource, and Using PLEs to Support Workplace Learning in Small Companies 297 Fig Manager in Management area Fig Employee in Learning area Search widget allows searching for learning materials in several repositories: YouTube (https://www.youtube.com), Scribd (https://www.scribd.com), Wikipedia (https://en wikipedia.org), and SlideShare (http://www.slideshare.net) Newly found documents can be displayed in Viewer and added easily to Resources Both managers and employees can add new learning resources, either as public or private ones BOOST Evaluation The BOOST project performed extensive evaluations with 97 participants from 55 small enterprises in the partner countries The target group included small enterprises with less than 20 employees In each of five participating countries a particular sector was addressed (Table 1) A special installation of the BOOST platform has been set up for each company and if needed, assistance has been provided to prepare the data properly The whole evaluation phase lasted from November 2014 to August 2015 The evaluation has been performed with the help of questionnaire guided structured interviews as follow-up to test sessions with the BOOST methodology and system The test session covered a span from short-term usage (several hours) to long-term evaluations (several weeks of usage) The piloting experiences in various cultural and 298 M Kravčík et al Table BOOST evaluation per country Partner DE UK CZ GR FR Total Sector/Type of enterprise IT communications - Internet technology Food - Rural deprived areas Production - Engineering and services Social enterprises Hospitality & other - Rural deprived areas No of cmpanies No of participants 13 11 22 12 25 12 25 11 12 55 97 industrial contexts were extensively investigated in the evaluation process, considering both the quantitative and qualitative approaches The participants provided their feedback in two forms face to face interviews and questionnaires Three different types of questionnaires were prepared for company managers, for their employees, as well as for VET providers A summary [13] of the BOOST Final Piloting Report [14] includes outcomes of qualitative evaluation in all the consortium countries The participating enterprises and their employees highly valuated the relevance and overall helpfulness of the BOOST approach Some of them reported also issues (e.g with the stability of the platform) and proposed further improvements (e.g towards better usability) These experiments revealed that the problem of addressing small enterprises with tailored VET offers is more complex than previously thought, but at the same time showed some clear benefits in easy organization of workplace learning and progress monitoring Data analysis of workplace learning in BOOST can be found in [15] Its outcomes show certain difficulties with finding enough time for a comprehensive evaluation But we could find also intensive periods of work, when participants followed the envisioned workflow, dividing their activities among planning, tutoring, learning, and reflection accordingly It was also interesting to observe that openness and sharing were not very common in the corporate settings Consequently, requirements for different levels of privacy and data security have been formulated, which would enable organizations to tailor the infrastructure for their specific needs Here we focus on the qualitative part of our evaluation in Germany, where the target sector was Information Technology (IT) Communications Internet Technology After realizing that the limit of 20 employees was too restrictive (some very small companies did not need this kind of support or used alternative solutions), we decided to include also slightly bigger companies (up to 100 employees) Finally, from 91 German IT companies contacted directly, 18 responded and participated in the BOOST piloting phase, with 13 persons in total One company could use the system for months and the other ones did it just for a short time, in order to become familiar with the platform The evaluation was organized mostly in the form of face-to-face meetings and questionnaires In the following we give an overview of the collected responses, divided into three different categories managers of companies, their employees, and VET providers Using PLEs to Support Workplace Learning in Small Companies 5.1 299 Company Perspective in Germany The participating German IT companies (represented by their managers) found the BOOST approach from their perspective quite useful Some considered it very helpful for SMEs, especially those operating in dynamic project environments with changing consortia Others appreciated the opportunity to set up the learning goals for employees and then to see their learning performance They found it useful for documenting the progress made, but mentioned that the BOOST system has no business process support The companies rated the support in understanding the methodology and tools mostly as good The online tool was also rated as good, but its graphical presentation was only adequate Several suggestions have been made, e.g to provide a methodological guideline for managers, to rename business goals to learning goals, to create a version for mobile learning The managers rated also the usability, user friendliness, and graphical representation of the BOOST online tool Our participants found the user interface “a bit demanding”, especially for novice users Some considered it old-fashioned and not intuitive enough As most useful widgets were named mostly those visualizing the learning progress of employees compared to the target levels On the other hand, the most required additional feature was grouping employees into a team, in order to assign them a common business goal, let them work together, and monitor their learning progress When asked about the results of BOOST piloting, the respondents stressed the importance of the introduction process on the motivation of users They said that the BOOST platform could be used as a planning tool for learning processes and if high quality learning content was available, the platform could contribute to the development of employees’ skills Regarding their interest in using the BOOST methodology and tools in the future, our respondents appreciated the BOOST platform as a good start, because”there is currently not much support for organizing training for SME” As the problems of SMEs are very diverse, “the system probably needs to be even more flexible in terms of adaptability to specific business needs” including a request for learning assignments from employees and spontaneous definition of learning assignments out of project needs 5.2 Employee Perspective in Germany Most of the participating German employees found the BOOST approach quite or very useful in increasing their personal skills Some of them liked the easy log-in with their Google account and the possibility to directly monitor their learning progress, having their learning resources with them Others liked to store their learning links at one place, but missed more support, like bookmark, directly from the viewer Some also missed the option to add their own learning goals In terms of usability, user friendliness, and graphical presentation, the rating of the BOOST online tool tended from good towards adequate Some of our employee respondents suggested more support for learning in a group, others would prefer 300 M Kravčík et al different learning repositories (e.g Google Scholar), and several persons thought the user interface could be more modern Most of the participating employees found the results of the BOOST pilots quite or very useful and thought the system would contribute to the development of their competences towards the company goals They would appreciate a more modern design and an opportunity of using the system on various devices, including mobile learning support 5.3 VET Perspective in Germany The only participating German VET provider appreciated that BOOST was a light-weight learning environment allowing quick planning of the learning activities and using any resources available on the web, that learning goals could be defined and learning resources could be assigned, as well as that employee could search for learning resources and assign preferred ones to the learning goals On the other side, the employee had no influence either on planning or on the progress evaluation, there was no collaborative learning possible, and no social sharing According to the project external evaluator (an independent expert hired by the project, who works also for a company developing learning technology solutions), the BOOST system offered flexible ways to organize, create, plan and include educational processes on various levels of granularity (from small scale learning objects in the form of linked video lectures to longer courses) One aspect of the prototype, however, needs to be elaborated further, if the sustainability and impact aspects should be fulfilled: the process of planning learning goals seems to be oriented towards SMEs of a larger size than the targeted small enterprises up to 20 employees At the level of micro enterprises (less than 10 employees), we cannot assume a separation of management level and operational level in the planning of educational processes and outcomes Here, a more flexible approach seems to be required Conclusion The BOOST project performed a significant step by developing an innovative methodology together with a corresponding technological platform to support VET in SMEs Our approach is based on the principles of SRL, which are supported by means of PLEs and customized for the needs of workplace learning in small companies The provided solution was to be interesting and useful for different types of users involved, including managers and employees, in order to stimulate their motivation for its usage One of the key findings is that the involvement of SMEs into VET is harder than initially thought, due to various reasons (e.g strong market pressure, little relevance of VET offers to SME requirements, specific educational needs) The target group is diverse and it implies difficulties to address them in a scalable way: best results in involving SMEs into BOOST have been achieved through intense work with them through personal contacts Using PLEs to Support Workplace Learning in Small Companies 301 However, BOOST points into the right direction: addressing critical needs of SMEs with tailored educational offers paves a path towards their better inclusion in VET programmes BOOST results show the high relevance of addressing SMEs as target group but also highlight that the problem of attracting them into VET is a complex issue, which requires activities along various societal dimensions (including political, educational, infrastructural, technological, economical, and scientific ones) This leads to the conclusion that follow-up activities are needed In order to further improve the BOOST platform, users can specify their requirements in our Requirements Bazaar (https://requirements-bazaar.org/#!/projects/8) Moreover, our workplace learning research continues in several other projects: Learning Layers, WEKIT, and VIRTUS Learning Layers (http://learning-layers.eu/) aims at scaling up technologies for informal learning in SME clusters Based on a new methodology, it develops various social, multimedia, and collaborative tools for professional learning communities These are tested in two professional fields construction and healthcare WEKIT (http://www.wekit.eu/) deals with wearable experiences for knowledge intensive training in environments where effective decision making has high impact on effectiveness in production It will enable training in situ with live expert guidance, a tacit learning experience, and a re-enactment of the expert This will be provided via task-sensitive Augmented Reality (AR) technology VIRTUS (http://www.virtus-project.eu) develops an innovative virtual VET Centre, which will offer modular and certified courses in the fields of Tourism and Hospitality Services, as well as Social Entrepreneurship, designed according to the latest developments in distant, open and collaborative learning Acknowledgments The presented research work was partially funded by the 7th Framework Programme large-scale integrated project Learning Layers (grant no: 318209), the H2020 project WEKIT (grant no: 687669), and the Erasmus+project VIRTUS (grant no: 562222-EPP-1-20151-EL-EPPKA3-PI-FORWARD) We appreciate very much the contributions of all the BOOST partners as well as of the external evaluator References European Commission Rethinking Education: Investing in skills for better socio-economic outcomes COM, 669 (2012) Morgado, L., Varajao, J., Coelho, D., Rodrigues, C., Sancin, C., Castello, V.: The attributes and advantages of virtual worlds for real world training J Virtual Worlds Educ 1, 15–36 (2010) Clarke, J., Thorpe, R., Anderson, L., Gold, J.: It’s all action, it’s all learning: action learning in smes J Eur Ind Training 30(6), 441–455 (2006) Winch, G., McDonald, J.: SMEs in an environment of change: computer–based tools to aid learning and change management Ind Commercial Training 31(9), 49–56 (1999) Johnson, S.: Lifelong learning and SMEs: issues for research and policy J Small Bus Enterp Dev 9(2), 285–295 (2002) 302 M Kravčík et al Attwell, G., Deitmer, L.: Developing work based personal learning environments in small and medium enterprises In: The PLE Conference, Melbourne (2012) Moon, S., Birchall, D., Williams, S., Vrasidas, Ch.: Developing design principles for an e-learning programme for SME managers to support accelerated learning at the workplace J Workplace Learn 17(2), 370–384 (2005) Jones, P., Beynon, M.J., Pickernell, D., Packham, G.: Evaluating the impact of different training methods on SME business performance Gov Policy 31(3), 56–81 (2013) Moon, S., Birchall, D., Williams, S., Vrasidas, C.: Developing design principles for an e-learning programme for SME managers to support accelerated learning at the workplace J Workplace Learn 17(5/6), 370–384 (2005) 10 Nussbaumer, A., Kravcik, M., Renzel, D., Klamma, R., Berthold, M., Albert, D.: A Framework for Facilitating Self-Regulation in Responsive Open Learning Environments (2014) arXiv preprint arXiv:1407.5891 11 Kravčík, M., Neulinger, K., Klamma, R.: Supporting workplace learning in small enterprises by personal learning environments In: Posters, Demos, Late-breaking Results and Workshop Proceedings of the 22nd Conference on User Modeling, Adaptation, and Personalization, CEUR 2014, Aalborg, Denmark, 7–11 July 2014, vol 1181 (2014) 12 Kravčík, M., Neulinger, K., Klamma, R.: Boosting informal workplace learning in small enterprises In: Proceedings of the 4th Workshop on Awareness and Reflection in Technology Enhanced Learning (ARTEL), In: Conjunction with the 9th European Conference on Technology Enhanced Learning (EC-TEL): Open Learning and Teaching in Educational Communities, CEUR, Graz, Austria, 16 September 2014, vol 1238, pp 73– 75 (2014) 13 Kravcík, M., Neulinger, K., Klamma, R.: Boosting vocational education and training in small enterprises In: Verbert, K., Sharples, M., Klobucar, T., Camenisch, J., Wu, H (eds.) EC-TEL 2016 LNCS, vol 9891, pp 600–604 Springer, Heidelberg (2016) doi:10.1007/ 978-3-319-45153-4_72 14 BOOST Final Piloting Report (2015) 15 Kravčík, M., Neulinger, K., Klamma, R.: Data analysis of workplace learning with BOOST In: To appear in Proceedings of the Workshop on Learning Analytics for Workplace and Professional Learning (LA for work), In: Conjuction with the 6th International Learning Analytics and Knowledge Conference, Edinburgh, UK, 25–29 April 2016 (2016) Author Index Abd El Rahman, Shaimaa 161 Abed, Hamza 185 Akahori, Kanji 118 Anzai, Yayoi 118 Aouadi, Nada 206 Baldiris, Silvia 281 Bartuskova, Aneta 20 Ben Amar, Chokri 91, 102, 185, 206 Carron, Thibault 91, 102, 185, 195, 206 Celik, Dilek 3, 14 De Medio, Carlo 261 Durcheva, Mariana 178 El-Hmoudova, Dagmar 29 Fabregat, Ramón 281 Felea, Cristina 253 Fronza, Ilenia 141 Gallo, Daniel 141 Gasparetti, Fabio 261 Graf, Sabine 281 Hansen, Preben 266 Hernández-Leo, Davinia 225 Hjeltnes, Thorleif 123 Höhn, Sviatlana 172 Horgen, Svend Andreas 123 Ilie, Sorin 131 Ioannou, Andri 266 Ip, Horace Ho Shing 112 Ivanova, Malinka 178 Ivanović, Mirjana 131, 236 Iwata, Jun 151 Jeladze, Eka 60 Jürgens, Pirje 40 Kahouf, Samir A 161 Klamma, Ralf 294 Klašnja-Milićević, Aleksandra Kravčík, Miloš 294 Kredens, Elodie 102 Krejcar, Ondrej 20 236 Laanpere, Mart 40 Leoni, Selena 112 Li, Chen 112 Limongelli, Carla 261 Loizides, Fernando 266 Lombardi, Matteo 261 Ludovico, Luca Andrea 72 Ma, Ka Fai 112 Maalej, Wiem 102 Magoulas, George D 3, 14 Manathunga, Kalpani 225 Marani, Alessandro 261 Milkova, Eva 29, 50 Mine, Tsunenori 161 Msaed, Sahar 91 Muratet, Mathieu 195 Murphy, Lynne 151 Neulinger, Kateryna 294 Pata, Kai 60, 83, 215 Pernelle, Philippe 91, 102, 185, 206 Põldoja, Hans 40 Popescu, Elvira 131 Quaicoe, James Sunney Ras, Eric 172 Rozeva, Anna 178 Salas, Daniel J 281 Sciarrone, Filippo 261 Sham, Sin Hang 112 Simonova, Ivana 273 Sorour, Shaymaa E 161 83 304 Author Index Stanca, Liana 253 Stefan, Constantin 131 Telloyan, John 151 Temperini, Marco 261 Uchino, Kanji Wang, Jun 246 Wong, Hoi To 112 Wong, Yat Wai 112 Xiang, Junfu 246 246 Väljataga, Terje 215 Vesin, Boban 236 Vymetalkova, Danuse 50 Yessad, Amel 195 Zambelli, Claudia 72 ... Nanni Marc Spaniol Marco Temperini (Eds.) • • Advances in Web- Based Learning – ICWL 2016 15th International Conference Rome, Italy, October 2 6–2 9, 2016 Proceedings 123 Editors Dickson K.W Chiu... Release date 2003 – still running 2007 – still 2004 – still 2011 – still running running running 2009 – still running 2006 – still 2005/06 – 2004/2005 running still running – still running Target users... Education The conferences searched include European Conference on Technology Enhanced Learning, Interna‐ tional Conference on Web- based Learning, International Conference on Advanced Learning Technologies
- Xem thêm -

Xem thêm: Advances in web based learning – ICWL 2016 15th international conference , Advances in web based learning – ICWL 2016 15th international conference , 2 The Second Iteration: Multiple Levels of Badges, 3 Requirements on Modern Education from the Studentʼs Point of View, 2 Methodology, Objectives and Hypotheses, Protus 2.1: Applying Collaborative Tagging for Providing Recommendation in Programming Tutoring System

Từ khóa liên quan

Mục lục

Xem thêm

Gợi ý tài liệu liên quan cho bạn

Nhận lời giải ngay chưa đến 10 phút Đăng bài tập ngay