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    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>Learning Analytics Summer Institute Spain 2018</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Department of Mechanical</string-name>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Computer Science</string-name>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Aerospace Engineering</string-name>
        </contrib>
        <contrib contrib-type="author">
          <string-name>University of León. Campus de Vegazana</string-name>
        </contrib>
        <contrib contrib-type="author">
          <string-name>-León (Spain)</string-name>
        </contrib>
        <contrib contrib-type="author">
          <string-name>mcong</string-name>
        </contrib>
        <contrib contrib-type="author">
          <string-name>camino.fernandez</string-name>
        </contrib>
        <contrib contrib-type="author">
          <string-name>am.guerrero</string-name>
        </contrib>
        <contrib contrib-type="author">
          <string-name>fjrods}@unileon.es</string-name>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>GRIAL Research Group, Department of Computer Science, Research Institute for Educational Sciences. University of Salamanca. Paseo de Canalejas 169</institution>
          ,
          <addr-line>37008. Salamanca</addr-line>
          ,
          <country country="ES">Spain</country>
        </aff>
        <aff id="aff1">
          <label>1</label>
          <institution>Universidad Politécnica de Madrid</institution>
          ,
          <addr-line>Av. Complutense 30, 28040 Madrid</addr-line>
          ,
          <country country="ES">Spain</country>
        </aff>
      </contrib-group>
      <pub-date>
        <year>2018</year>
      </pub-date>
      <fpage>0000</fpage>
      <lpage>0001</lpage>
      <abstract>
        <p>Preface to the Conference Proceedings</p>
      </abstract>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>-</title>
      <p>
        The pervasive and extended use Information and Communication Technologies (ICTs)
in Education is already a reality. Students and instructors can choose a wide range of
technologies and tools in order to improve their teaching and learning. A common
characteristic of ICT-supported learning is that student and teacher interactions in digital
spaces leave a trail of data that allows collection and identification of learning evidence.
The analysis of such evidence may lead to a better understanding of the
teaching-learning process, facilitating educational decision-making, and to the improvement of
educational processes and student achievement. Learning analytics groups together
different techniques aiming to extract, collect and analyze educational data, gaining
increasing relevance as a tool to support and improve learning in recent years. The different
aspects of learning analytics have been covered so far in many scholarly works and
academic conferences [
        <xref ref-type="bibr" rid="ref1 ref10 ref2 ref3 ref4 ref5 ref6 ref7 ref8 ref9">1-10</xref>
        ].
      </p>
      <p>
        Learning analytics covers a wide range of analysis techniques and methods over
different sources of data (content repositories, interactive systems, multimedia) and
technologies (learning management systems, educational and serious games, virtual
learning environments, mobile devices), including data mining and visualization, among
others. The different techniques and methods focus on different key aspects of learning,
such as detection of at-risk students, reduction of attrition rates, adaptive learning, or
support to instructional design [
        <xref ref-type="bibr" rid="ref11 ref12 ref13 ref14 ref15 ref16 ref8">8, 11-16</xref>
        ].
      </p>
      <p>Copyright © 2018 for this paper by its authors. Copying permitted for private and academic purposes</p>
      <p>The sixth1 edition of the Learning Analytics Summer Institute Spain, LASI Spain
182 was held in León on June 18th and 19th, 2018. The conference was organized by
University of León, in collaboration with the SNOLA (Spanish Network of Learning
Analytics) research network of excellence. The LASI worldwide events, sponsored by
SoLAR (Society for Learning Analytics Research), have become in the past years an
awareness-raising, capacity-building, international network of events, where
researchers and practitioners can meet and share their work, and envision the future of learning
analytics. The programme of LASI Spain 18 comprised a great variety of activities that
gathered representatives of academia and industry, including keynotes by international
experts on learning analytics in Europe, academic paper presentation sessions,
discussion panels and workshops.</p>
      <p>The different activities gave attendants the opportunity to review the state of learning
analytics in a global context, and also to showcase innovative pieces of research on the
field that contribute new advances and knowledge to this field, mainly–but not only–
from Spanish research groups.</p>
      <p>The keynotes of LASI Spain 18 provided a broad but comprehensive overview of
trending topics on learning analytics. More precisely, the keynotes of the conference
were as follows:
• In “Learning Analytics based tools for improving assessment and
intervention in academic contexts”, Rebeca Cerezo (University of Oviedo)
discussed about the application of learning analytics tools in different
educational contexts.
• In “Modeling Education with Learning Analytics: Problems and
Opportunities”, David Griffiths (University of Bolton) provided an overview of the
different issues we should consider when adopting learning analytics
policies.</p>
      <p>In addition to the academic keynotes, LASI Spain 18 has held four different sessions:
1) The Academic Session, which included the presentation of the scientific
contributions included in these proceedings; 2) one session on “Application of Learning
Analytics”; 3) one panel that gathered together different contributions from the Industry;
and 4) two Workshops on Learning Analytics.</p>
      <p>The presentation of scientific contributions to the Academic Session includes the
twelve contributions included in these proceedings. The contributions share some
common topics. Three studies present innovative learning analytics applications:
“Automatic Group Formation in MOOCs Based on Homogeneous Engagement Criteria”
1 The previous editions of LASI Spain, as LASI-local event, include the following:
• LASI Spain 2013 in Madrid:
http://www.emadridnet.org/index.php/es/eventos2/312seminario-emadrid-learning-analytics-summer-institue
• LASI Spain 2014 in Madrid: https://canal.uned.es/serial/index/id/1303
• LASI Spain 2015 in Bilbao: https://blogs.deusto.es/lasi2015Bilbao
• LASI Spain 2016 in Bilbao: http://lasi16.snola.es
• LASI Spain 2017 in Madrid: http://lasi17.snola.es
2 https://lasi18.snola.es
(Luisa Sanz-Martínez, Alejandra Martínez-Monés, Miguel L. Bote-Lorenzo, and
Yannis Dimitriadis) proposes methods to achieve higher effectiveness in group formation
in MOOCs; “Learning Analytics to Assess Students’ Behaviour With Scratch Through
Clickstream” (Daniel Amo, Marc Alier, Francisco J. García-Peñalvo, David Fonseca,
and María J. Casañ) analyses the behavior of students using Scratch for learning;
“Towards a Methodology and a Toolkit to Analyse Data for Novices in Computer
Programming” (Tatiana Person, Iván Ruiz-Rube, and Juan M. Dodero) presents a toolkit
for learning analytics; and “Learning Analytics and Recommender Systems Toward
Remote Experimentation” (Alexandre L. Gonçalves, Gustavo R. Alves, Lucas M. Carlos,
Juarez B. da Silva, and João B. da M. Alves) shows how to provide students with
recommendations about which remote labs can better suit their needs. The remaining
group of contributions pivot around the idea of using learning analytics to facilitate
decision making, including competence-based learning in “Supporting
Competencebased Learning in Blended Learning Environments” (Mikel Villamañe, Ainhoa
Álvarez, Mikel Larrañaga, Jessica Caballero, and Oscar Hernández-Rivas) and “Design of
an Extraction, Transform and Load Process for Calculation of Teamwork Indicators in
Moodle” (Ángel Hernández-García, Emiliano Acquila-Natale, Santiago
Iglesias-Pradas, and Julián Chaparro-Peláez), assessment of student performance in “Learning
Analytics to Improve the Effectiveness of Continuous Assessment” (Martín
LizDomínguez, Martín Llamas-Nistal, Manuel Caeiro-Rodríguez, and Fernando
MikicFonte), “SPEET: Visual Data Analysis of Engineering Students Performance from
Academic Data” (Manuel Domínguez, Ramón Vilanova, Miguel Á. Prada, José Vicario,
Marian Barbu, Maria J. Varanda, Michal Podpora, Umberto Spagnolini, Paulo Alves,
and Anna Paganoni) and “Model for Evaluating Student Performance through their
Interaction with Version Control Systems” (Angel M. Guerrero-Higueras, Vicente
Matellán-Olivera, Gonzalo Esteban-Costales, Camino Fernández-Llamas, Francisco J.
Rodríguez-Sedano, and Miguel Á. Conde), or data visualization, such as the
visualization of resource used described in “Visualization Index for Educational Resources by
Learning Analytics” (Noemí DeCastro-García, and Ángel L. Muñoz-Castañeda), or
dashboards with information about employability in “Generation of Customized
Dashboards Through Software Product Line Paradigms to Analyse University Employment
and Employability Data” (Andrea Vaquez-Ingelmo, Francisco J. García-Peñalvo and
Roberto Therón). The presentation of these contributions took place during the two
days of the conference.</p>
      <p>The session on Application of Learning Analytics was also distributed in the two
days of the conference. The session included the participation of several experts in the
field, who shared their expertise and concerns, as well as the main problems they have
faced when applying learning analytics and the benefits derived from the use of such
applications. The researchers involved in this discussion were Manuel Caeiro
(University of Vigo), Mikel Villamañe (University of the Basque Country), Alejandra Martínez
(University of Valladolid), Pedro J. Muñoz (Carlos III University of Madrid) and
Miguel Ángel Conde (University of León).</p>
      <p>The Industry panel of LASI 2018 offered a different perspective on uses and
applications of learning analytics from the business side. Four experts from the industry
shared their expertise about the application of learning analytics in businesses: Nora M.
Villanueva from Gradient presented Applying Learning Analytics to enhance learning
experiences in secondary education and corporate environments”; Camino Antón from
SAP Bussiness One discussed the use of learning analytics in large companies in
“Learning Analytics – Challenges and Oportunities in bussiness”; Agustín Cuenca
from ASPGems showed examples of application of learning analytics in “NeuroK:
what we measure and why”; and Luis A. Oliva from Brambles shared his views and
experience in learning analytics in “Companies learning requirements and learning
analytics”.</p>
      <p>Finally, the conference included the celebration of two workshops that put
conference participants in direct contact with learning analytics technologies: ElasticSearch
and Kibana in “Data Analysis with ElasticSearch and Kibana”, by Antonio Robles and
Llanos Tovarra (National Distance University of Madrid), and the ETL and data mining
application RapidMiner in “RapidMiner”, by second one, by Ángel Hernández-García
(Universidad Politécnica de Madrid).</p>
      <p>Acknowledgements
The authors thank the Spanish Ministry of Economy, Industry and Competitiveness for
the funding and support of the SNOLA Network of Excellence
(TIN2015-71669REDT) to LASI Spain 18.</p>
      <p>The authors also thank the members of the Programme Committee for their
dedication and knowledge, as well as all the authors who submitted their valuable
contributions to LASI Spain 18.</p>
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