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               <dc:title>Learning Analytics to Assess Students’ Behavior With Scratch Through Clickstream</dc:title>
               <dc:creator>Amo Filvà, Daniel</dc:creator>
               <dc:creator>Alier, Marc</dc:creator>
               <dc:creator>GARCÍA-PEÑALVO, Francisco José</dc:creator>
               <dc:creator>Fonseca, David</dc:creator>
               <dc:creator>Casany, María José</dc:creator>
               <dc:subject>Dades massives</dc:subject>
               <dc:subject>Ensenyament -- Innovacions tecnològiques</dc:subject>
               <dc:description>The construction of knowledge through computational practice requires to teachers a substantial amount of time and effort to evaluate programming skills, to understand and to glimpse the evolution of the students and finally&#xd;
to state a quantitative judgment in learning assessment. This suposes a huge problem of time and no adecuate intime feedback to students while practicing programming activities.&#xd;
The field of learning analytics has been a common practice in research since&#xd;
last years due their great possibilities in terms of learning improvement. Such&#xd;
possibilities can be a strong positive contribution in the field of computational&#xd;
practice such as programming.&#xd;
In this work we attempt to use learning analytics to ensure intime and quality&#xd;
feedback through the analysis of students behavior in programming practice.&#xd;
Hence, in order to help teachers in their assessments we propose a solution to&#xd;
categorize and understand students’ behavior in programming activities using&#xd;
business technics such as web clickstream.&#xd;
Clickstream is a technique that consists in the collection and analysis of data&#xd;
generated by users. We applied it in learning programming environments to study&#xd;
students behavior to enhance students learning and programming skills.&#xd;
The results of the work supports this business technique as useful and adequate in programming practice. The main finding showns a first taxonomy of&#xd;
programming behaviors that can easily be used in a classroom. This will help&#xd;
teachers to understand how students behave in their practice and consequently&#xd;
enhance assessment and students’ following-up to avoid examination failures.</dc:description>
               <dc:date>2018-06</dc:date>
               <dc:date>2018-06</dc:date>
               <dc:type>info:eu-repo/semantics/conferenceObject</dc:type>
               <dc:identifier>http://hdl.handle.net/20.500.14342/2867</dc:identifier>
               <dc:language>eng</dc:language>
               <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
               <dc:rights>© L'autor/a. Tots el drets reservats</dc:rights>
               <dc:publisher>Proceedings of the Learning Analytics Summer Institute, León, 18-19 June 2018</dc:publisher>
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