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        <article-title>Learning Analytics Summer Institute Spain 2020: Learning Analytics. Time for Adoption?</article-title>
      </title-group>
      <contrib-group>
        <aff id="aff0">
          <label>0</label>
          <institution>Department of Computer Languages and Systems, Universidad del País Vasco UPV/EHU</institution>
          ,
          <country country="ES">Spain</country>
        </aff>
        <aff id="aff1">
          <label>1</label>
          <institution>Department of Computer Science, Universidad de Valladolid</institution>
          ,
          <country country="ES">Spain</country>
        </aff>
        <aff id="aff2">
          <label>2</label>
          <institution>Department of Telematics Engineering, Universidade de Vigo</institution>
          ,
          <country country="ES">Spain</country>
        </aff>
        <aff id="aff3">
          <label>3</label>
          <institution>Department of Theory of Signal and Communications and Telematics Engineering. Universidad de Valladolid</institution>
          ,
          <country country="ES">Spain</country>
        </aff>
        <aff id="aff4">
          <label>4</label>
          <institution>Preface to the Conference Proceedings</institution>
        </aff>
      </contrib-group>
      <fpage>0000</fpage>
      <lpage>0003</lpage>
      <abstract>
        <p>The eight edition of the Learning Analytics Summer Institute Spain, LASI Spain 2020 1 was held on June 15th and 16th, 2020. Under the main theme of “Learning Analytics: Time for adoption?”, the conference was organized by the University of Valladolid, in collaboration with the SNOLA (Spanish Network of Learning Analytics) research network. This conference is part of the global LASI network2, conceived as a platform to catalyze educators, technologists, researchers, enterprise and policymakers around shaping the next generation of learning infrastructures to truly serve the needs that the education sector is facing. The event was backed by the official support from the Society of Learning Analytics Research (SoLAR). This LASI Spain 2020 edition was planned to happen in Valladolid, but due to the situation of uncertainty derived from the CoVid-19 outbreak, it was held online. We tried to take advantage of this (a priori negative) situation by promoting the participation of members of the Latin American Learning Analytics community. This was materialized in the organization of a panel with experts from Latin America that closed the conference. The benefits of the transition to an on-line event were reflected in the high number of registered participants. LASI Spain 2020 had up to 120 people registered, with more than 80 people participating in the keynotes and an average of 60 participants in the 1 https://lasi20.snola.es/ 2 https://www.solaresearch.org/events/lasi</p>
      </abstract>
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    <sec id="sec-1">
      <title>-</title>
      <p>Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons</p>
      <p>License Attribution 4.0 International (CC BY 4.0).
sessions. The participants of the conference came mainly from Spain and Latin
American countries like Uruguay, Brazil, Mexico, Chile, Costa Rica, and Ecuador, but
there were also researchers connecting from UK, Finland, Sweden, Switzerland and
Greece.</p>
      <p>The main theme this year was adoption of Learning Analytics (LA). Learning
Analytics has been called to improve learning practice by transforming the ways we
develop and carry out learning and teaching activities and processes. The Horizon
Report 2019 considers Learning Analytics a technology ready for short-term adoption,
a signal of the maturity this area has reached in a relatively short period of time.
However, many challenges still remain to reach all the potential benefits attributed to
this field, and there exist open debates regarding the evolution of Learning Analytics
and its consequences on learning and on the educational system overall. LASI Spain
2020 aimed at contributing with reflections and experiences related to this issue.</p>
      <p>LASI Spain 2020 included two keynotes by international experts and the
aforementioned panel that gave us the opportunity to get closer to research in LA in
Latin America. The keynotes and the panel offered a rich panorama of experiences and
perspectives related to the main theme of adoption. The conference included 4 paper
sessions, and, for the first time in the LASI Spain series, a Doctoral Consortium.
Altogether, the conference provided an updated panorama of research in LA at different
parts of the globe, with a special coverage of the current research efforts being made
by different groups in Spain.
1.1</p>
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      <title>Keynote Speakers</title>
      <p>LASI Spain 2020 had the honor to count with two outstanding researchers from the LA
field, coming from two remote places in the world: Abelardo Pardo and Michail
Giannakos.</p>
      <p>Under the title “Effective adoption of Learning Analytics in Educational Institutions”
Abelardo Pardo, current President of SoLAR, and Professor at the University of South
Australia (UniSA), Australia, shared his experience and reflections related to adoption
of Learning Analytics technologies. In his talk, he stressed the importance of the
productive tensions between two parts involved in adoption at institutional levels:
actors involved in innovation and entrepreneurship on the one side, and people
concerned about operational functions and administration on the other. On top of
previous research, he presented the SPARK model for Learning Analytics adoption.
Prof. Pardo pointed out the need to construct an intermediate space where the
“commons” emerge from the productive tensions. This intermediate space should
contain elements such as multidisciplinary teams, boundary objects, a shared sense of
ownership and inclusive discussions. The process of adoption should go through the
following phases: a very clear definition of the problem, the deployment, assignment
of resources and should strive to move from pilots to full-scale adoption. All these ideas
were illustrated with three examples from real practice.</p>
      <p>The second keynote was given by Michail (Michalis) Giannakos under the title
“Sensing-based Analytics to Support Learning Design” reported his work at the
Norwegian University of Science and Technology (NTNU), Norway, with a holistic
perspective of learning design that includes space and interaction design. He explained
the capabilities of SbA (Sensing-based Analytics) for measuring learning-related
variables, and how SbA can help teachers in physical, blended and online contexts to
amplify their sensing about students’ states (confusion, difficulty, engagement,
cognitive load) and act upon them. Prof. Giannakos discussed the challenges and
opportunities of SbA for learning design, such as continuous monitoring to support
different and dynamic learning designs, or the opportunities of rebalancing black-box
and white-box approaches with grey-box approaches enriched with features extracted
from literature. Its ultimate goal is to build systems aware of learning states, so that
they can make interventions and make dynamic learning design a reality.
1.2</p>
    </sec>
    <sec id="sec-3">
      <title>Paper Sessions</title>
      <p>LASI 2020 also included four sessions where the research papers that were accepted
from the open call of the conference were presented and the audience could discuss
with the authors. These proceedings include the 11 contributions selected after
doubleblinded peer review. These papers adequately represent the current scope of research
in LA in Spain, as represented by a recent review done by the members of SNOLA [2].
The following sections describe them grouped by theme.</p>
      <p>Performance prediction. A number of papers dealt with the capabilities of LA to make
improved predictions about the performance of the students.</p>
      <p>The paper “An Initial Analysis of Prediction Techniques as a Support for the Flipped
Classroom” by Aarón Rubio-Fernández, Pedro Manuel Moreno-Marcos, Pedro José
Muñoz-Merino and Carlos Delgado Kloos explores these issues. Prediction techniques
that can be used in combination with Learning Analytics (LA) dashboards for the
improvement of the flipped classroom model.</p>
      <p>Identifying reasons for dropout is one of the main challenges that drive predictive
modes in LA. The paper “Looking for a dropout predictor based on the instructional
design of online courses”, by Salvador Ros and Agustín Caminero, deals with dropout.
The authors analyze four data sets with different instructional designs, identifying some
elements as risk factors, such as the result of different assessments that were planned
in the courses instructional design. Using in-depth analysis of the data, the authors
conclude that the dropout-risk group is formed by a large group of students that decided
not to take one of the proposed assessments.</p>
      <p>The paper entitled “Combining clustering and sequential pattern mining to detect
behavioral differences in log data: conceptualization and case study” by Juan Antonio
Martínez-Carrascal, Elena Valderrama and Teresa Sancho-Vinuesa proposes a method
to detect differences in the behavior of the students. They consider the data recorded in
an LMS log in the context of a blended learning course. The study shows that the
proposed method can generate meaningful sequences to detect differences in behavior
between students who passed the course and those who did not.</p>
      <p>The last paper related to prediction was inspired by the participation of the authors
in the Nation’s Report Card Data Mining Competition 2019 (NAEP Competition),
where newcomers (or experts) can train machine learning systems with a given data set
offered by the organizers of the competition. This is reported in the paper “Early
prediction of students' efficiency during online assessments using a Long-Short Term
Memory architecture” by Cristina Villa-Torrano, Miguel Bote-Lorenzo, Juan Ignacio
Asensio-Pérez and Eduardo Gómez-Sánchez. The proposed classification model is
based on the Long-Short Term Memory (LSTM) recurrent neural network architecture,
as it is capable of capturing evolutionary patterns over time. Cristina Villa-Torrano
shared her thoughts about the benefits and limitations of this kind of competitions for
getting to know the field of analytics.</p>
      <p>Visual analytics. Visual analytics is a striving area of research in Learning Analytic,
fostered by the need of helping users make sense of the large and complex data collected
by the systems. There were two papers focusing on this topic:</p>
      <p>Andrea Vázquez-Ingelmo, Francisco José García Peñalvo, Roberto Theron and
Alicia García-Holgado describe in their paper “Specifying information dashboards’
interactive features through meta-model instantiation” an approach based on
metamodels that aims to facilitate the adaptation of dashboards to the needs of different
users. This paper focuses on the definition of interaction patterns within the
metamodel. Interaction patterns allow the specification of fine-grained specification and
configuration of the dashboards, by allowing to customize not only the visual display,
but also the methods used to interact with the datasets.</p>
      <p>On the other hand, the paper “A proposal for the Monitoring of the Intervention
Strategy on the learning of MOOC learners” by Ruth Cobos and Juan Soberón
describes the development of a system to provide periodically MOOC learners with
visual information on a Web-based Learner Dashboard, showing them their progress
and engagement in the MOOC. This system aims to address the lack of feedback and
interaction among instructors and learners, which affect negatively learner retention
and engagement in MOOCs. The system offers MOOC instructors access to a
Webbased Instructor Dashboard that shows the interest in this service by the learners.</p>
      <p>The short paper entitled “Conceptual framework for process-oriented feedback
through Learning Analytics Dashboards” by Íñigo Arriarán Olalde and Nagore Ipiña
Larrañaga, presents and discusses the design implications for a Learning Analytics
Dashboard (LAD) inspired on the principles of self-regulated learning (SRL) processes,
thus aiming to provide pedagogically sound support to its users.</p>
      <p>Innovative and active pedagogies. How to apply LA to support innovative and active
pedagogies is an active research topic. Collaborative Learning Flow Patterns (CLFPs)
enable the translation of good practices in collaborative learning to scripts that are
interpretable by computers. The paper “Towards rewards-based gamification in
Collaborative Learning Flow Patterns based on learning analytics” by Rene Lobo,
Alejandro Ortega-Arranz and Davinia Hernández-Leo describes the first iteration for a
model to integrate the use of gamification and Learning Analytics in collaborative
learning activities structured following the Jigsaw and Pyramid CLFPs. The overall
goal of the project is to find the ways in which ways LA can support gamification
strategies in CLFP activities to foster student collaboration.</p>
      <p>The paper “Visualizing Educational Game Data: A Case Study of Visualizations to
Support Teachers” by Pedro A. Martínez, Manuel J. Gómez, José A.
RuipérezValiente, Gregorio Martínez Pérez and Yoon Jeon Kim describes a Learning Analytics
dashboard that aims to support teachers in knowing how students are using the game,
transforming clickstream data into meaningful metrics and displaying them visually.
The ultimate goal is to enable teachers to track the students and evaluate them, or act if
needed. The paper presents the work done to this end with Shadowspect, a game-based
assessment tool that provides metrics related to geometry among other math-related
contents.</p>
      <p>Finally, “Self and Peer Monitoring during Peer Feedback: The Instructor
Perspective” by Erkan Er presents the instructors’ perspectives about self and
peermonitoring enabled by Synergy, a student-oriented dashboard that supports peer
reviewing protocols, with implications for Learning Analytics design. The study is
based on an open-ended survey. The results suggest that teachers acknowledge the
benefits of this approach to enhance self- and co-regulation of learning, and they also
pose some challenges related to the extra-effort required. The paper derives
implications for the activity design and learning analytics support that could help
address these concerns.</p>
      <p>Ethics and data-privacy. The papers presented at LASI were aligned with the
challenges identified by Martínez-Monés et al. [2] for the Learning Analytics field in
both the Spanish and international contexts. One of the main challenges was related to
the consideration of ethics and data-privacy in the Learning Analytics solutions.</p>
      <p>
        Ethical issues are at the core of the paper entitled “How are Learning Analytics
Considering the Societal Values of Fairness, Accountability, Transparency and Human
Well-being? - A Literature Review” by Eyad Hakami and Davinia Hernandez-Leo. The
paper reviews the presence of the four values mentioned in the title in the full series of
LAK conferences from 201
        <xref ref-type="bibr" rid="ref1">1 to 2020</xref>
        . The authors conclude that in spite of an increasing
concern that is being observed in the LA research community, the societal values of a
responsible Artificial Intelligence have been addressed only to a limited extend. They
point out at the need of a more holistic perspective that considers not only transparency,
but also ways in which LA can contribute to diverse dimensions of human well-being.
To this end, there is a need of identifying metrics and techniques to help educators in
safeguarding these values in the lifecycle of LA tools and solutions.
      </p>
      <p>Privacy was also a hot topic of discussion in the paper “Tracking the Students'
Learning Behavior for Cybersecurity Scenarios” by Antonio Uzal, Llanos Tobarra,
Alejandro Utrilla, Antonio Robles-Gómez, Rafael Pastor-Vargas and Roberto
Hernández. They presented how they had implemented privacy issues that satisfy
Spanish and European standards in a platform, which includes gamification
mechanisms in a system oriented to cybersecurity learning that enables monitoring of
the players’ performance by the teaching team.</p>
    </sec>
    <sec id="sec-4">
      <title>Doctoral Consortium</title>
      <p>For the first time in the LASI Spain series of conferences, we had a Doctoral
Consortium, where four PhD candidates working on topics related to Learning
Analytics presented their PhD projects, and had the opportunity to discuss them with
four senior researchers that volunteered to act as mentors and provide feedback. These
experts were Teresa Sancho-Vinuesa, Yannis Dimitriadis, Manuel Caeiro, and Pedro
Muñoz-Merino, all of whom participated actively in the session, giving the students
advice based on their long-lasting experience as mentors within the LA field.</p>
      <p>Two of the works presented delved around the idea of self-regulated learning, which
is gaining importance as a fundamental skill. The work entitled “Contributions to
realtime monitoring and analysis of heterogeneous learning environments”, by Lucía
Uguina-Gadella proposes a system to detect students at risk on a real-time basis, using
for it data from the system logs, enhanced with self-regulation learning information
obtained from tests and mid-term exams.</p>
      <p>Cristina Villa-Torrano in her PhD project “Detecting patterns of Socially Shared
Regulation of Learning in Smart Learning Environments”, proposes the extension of
the idea of self-regulated learning to the support of collaboration, by detecting patterns
of social shared regulation of learning (SSRL) using data from the learning
environment.</p>
      <p>The session was complemented with two more works, which were presented orally:
“Design of gameful learning activities across social planes using analytics”, by René
Lobo, and “Assessing wellbeing impacts of Learning Analytics systems” by Eyad
Hakami. The proposal by Lobo is related to the use of learning analytics and
gamification to foster collaborative learning activities, while the proposal by Hakami
revolves around the work also presented as a paper in the conference, related to the
analysis of the treatment of of Fairness, Accountability, Transparency and Well-being
in the field of LA.
1.4</p>
    </sec>
    <sec id="sec-5">
      <title>Panel “Learning analytics in Latin America”</title>
      <p>One of the main consequences of the transition to an online event was that LASI Spain
2020 could more easily welcome contributions and participation from the Latin
America LA research community. A panel was set up to let prominent researchers in
the area share their experiences related to LA adoption in Latin America. This panel
nicely closed the conference, with relevant examples of the challenges met in practice
when proposing Learning Analytics tools for adoption at different scales.</p>
      <p>Ronald Pérez presented the LALA project, and its continuation through the LALA
community and SIG; and the Observatory of Learning Analytics initiatives in Latin
America. He discussed the boost of research in Latin America in recent years, as
described by Cechinel et al. [2]. Finally, as a particular example of research done in
Latin America related to LA, he described his work on the NoteMyProgress tool, which
supports self-regulation strategies of students in on-line learning settings.</p>
      <p>Margarita Ortiz-Rojas, with her talk “Does one size fit all? The experience of
implementing an academic counseling system in system of academic counselling in
three Latin American universities”, presented the experience of adapting a tool, initially
developed for KU Leuven, for counselling in three Latin-American universities. Six
thousand students and teachers were involved overall in the project. This work is clear
example of how the context of each University influenced the adaptation of the
dashboard, showing a nice case of how the “commons” mentioned by Abelardo Pardo
in his opening keynote can be put into action.</p>
      <p>The last intervention was related to the paper entitled “Design of a tool of learning
analytics to support continuous curriculum improvement” by Isabel Hilliger. She
described another project where adoption was a major issue, in the context of
continuous curriculum improvement. The work was framed within a grid that
conceptualizes the adoption of Learning Analytics with respect to different kinds of
leadership (bottom-up and top-downs) and levels of maturity. She described the needs
analysis they performed with the involved stakeholders (students, teaching staff, and
managers). The study findings highlight areas of interest in LA applied to curriculum
improvement, including quality feedback and timely data-driven support for students.</p>
    </sec>
    <sec id="sec-6">
      <title>Acknowledgements</title>
      <p>The authors want to thank the financial support provided by the National Research
Agency of the Spanish Ministry of Science, Innovation and Universities and the
Structural Funds (FSE and FEDER) under project grant RED2018-102725-T. We also
thank the members of the Organizing and Scientific Committees for their dedication
and knowledge, as well as all the authors, who submitted their valuable contributions
to LASI Spain 2020.</p>
      <p>LASI Spain 2020 Committees
Alejandra Martínez Monés (University of Valladolid, UVa)
• Ainhoa Álvarez Arana (University of the Basque Country, UPV/EHU)
• Manuel Caeiro Rodríguez (University of Vigo, UVigo)
• Yannis Dimitriadis (University of Valladolid, UVa)</p>
    </sec>
    <sec id="sec-7">
      <title>Scientific Committee</title>
    </sec>
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