<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-04-18T05:55:12Z</responseDate><request verb="GetRecord" identifier="oai:www.recercat.cat:20.500.14342/2867" metadataPrefix="oai_dc">https://recercat.cat/oai/request</request><GetRecord><record><header><identifier>oai:recercat.cat:20.500.14342/2867</identifier><datestamp>2025-03-15T03:36:05Z</datestamp><setSpec>com_2072_482405</setSpec><setSpec>com_2072_183628</setSpec><setSpec>col_2072_482415</setSpec></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
   <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:contributor>Universitat Ramon Llull. La Salle</dc:contributor>
   <dc:contributor>Universitat Politècnica de Catalunya</dc:contributor>
   <dc:contributor>Universidad de Salamanca</dc:contributor>
   <dc:subject>Dades massives</dc:subject>
   <dc:subject>Ensenyament -- Innovacions tecnològiques</dc:subject>
   <dc:subject>004</dc:subject>
   <dc:subject>62</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: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>© L'autor/a. Tots el drets reservats</dc:rights>
   <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
   <dc:format>9 p.</dc:format>
   <dc:publisher>Proceedings of the Learning Analytics Summer Institute, León, 18-19 June 2018</dc:publisher>
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