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                     <mods:roleTerm type="text">author</mods:roleTerm>
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                  <mods:namePart>Casanova de Vilalta, Lydia</mods:namePart>
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                  <mods:dateIssued encoding="iso8601">2021-01-26T10:21:34Z2021-01-26T10:21:34Z2020-07</mods:dateIssued>
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               <mods:abstract>Treball fi de màster de: Master in Cognitive Systems and Interactive MediaDirectors: Patricia Santos, Marc BeardsleyApplied cognitive psychology has been a center topic for a number of research works&#xd;
in last decades. In particular, there are studies conducted on memory, cognition&#xd;
and on the science of learning. The latter are meant to find new methods in order&#xd;
to improve the process of learning. The use of the Retrieval Practice (RP) and&#xd;
Distributed Learning (DL) has been proved to be improving the efficiency of learning&#xd;
when compared to Massive Learning (ML) practices (which is the most used method&#xd;
in formal education). Even though there are studies which proved the advantages&#xd;
of using DL, different patterns can be found and it is not clear which one is the best&#xd;
to apply to get the best students’ results.&#xd;
This study was conducted in the last 3 courses of primary education and the learning&#xd;
topic was Computational Thinking (CT). CT is one of the 21st century skills that&#xd;
gained more attention and it is progressively being incorporated in formal learning&#xd;
since the early stages of education. CT refers to understanding how to develop stepby-step solutions of problems, helping students to use and improve logical thinking,&#xd;
pattern recognition and decomposition skills. New generations are likely to live in&#xd;
a technologically integrated society, hence, CT might become an essential skill that&#xd;
will enable them to understand and manipulate the technology that surrounds them.&#xd;
Thus, the main goal of this project is to find out how the learning process is affected&#xd;
by different patterns of distributed practice and discover which is the distribution&#xd;
that leads to a better performance in the latter, as well as being suitable to apply&#xd;
in formal learning contexts. In order to do that, two different patterns of DL and&#xd;
a ML group (as a control group) will be compared with the aim to find which one&#xd;
of the two reaches the best performance using RP as a constant in all groups. As&#xd;
a result, I expect that DL groups will perform better than the ML groups, and I&#xd;
forsee to find out whether there is a significant difference in performance between&#xd;
the two DL patterns tested.</mods:abstract>
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               <mods:accessCondition type="useAndReproduction">This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License http://creativecommons.org/licenses/by-nc-nd/4.0 info:eu-repo/semantics/openAccess</mods:accessCondition>
               <mods:subject>
                  <mods:topic>Distributed Learning</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Computational Thinking</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Massive Learning</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Retrieval Practice</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Formal Education</mods:topic>
               </mods:subject>
               <mods:titleInfo>
                  <mods:title>Effects of distributed learning patterns on elementary student learning of computational thinking</mods:title>
               </mods:titleInfo>
               <mods:genre>info:eu-repo/semantics/masterThesis</mods:genre>
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