<?xml version="1.0" encoding="utf-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.0 20120330//EN" "JATS-journalpublishing1.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="article">
<front>
    <journal-meta>
        <journal-id journal-id-type="publisher-id">INFEDU</journal-id>
        <journal-title-group>
            <journal-title>Informatics in Education</journal-title>
        </journal-title-group>
        <issn pub-type="epub">1648-5831</issn>
        <issn pub-type="ppub">1648-5831</issn>
        <publisher>
            <publisher-name>VU</publisher-name>
        </publisher>
    </journal-meta>
    <article-meta>
                <article-id pub-id-type="publisher-id">INFEDU.2018.20</article-id>
                        <article-id pub-id-type="doi">10.15388/infedu.2018.20</article-id>
                        <article-categories>
            <subj-group subj-group-type="heading">
                <subject>Article</subject>
            </subj-group>
        </article-categories>
                        <title-group>
            <article-title>An Adaptive Test Analysis Based on Students&#039; Motivation</article-title>
        </title-group>
                        <contrib-group>
                                        <contrib contrib-type="author">
                                                <name>
                    <surname>YOSHIOKA</surname>
                    <given-names>Sérgio R. I.</given-names>
                </name>
                                <email xlink:href="mailto:sergio.yoshioka@sga.pucminas.br">sergio.yoshioka@sga.pucminas.br</email>
                                                <xref ref-type="aff" rid="j_INFEDU_aff_000"/>
                                            </contrib>
                        <aff id="j_INFEDU_aff_000">Graduate Program in Informatics, Pontifical Catholic University of Minas Gerais (PUC Minas)</aff>
                                                    <contrib contrib-type="author">
                                                <name>
                    <surname>ISHITANI</surname>
                    <given-names>Lucila</given-names>
                </name>
                                <email xlink:href="mailto:lucila@pucminas.br">lucila@pucminas.br</email>
                                                <xref ref-type="aff" rid="j_INFEDU_aff_001"/>
                                            </contrib>
                        <aff id="j_INFEDU_aff_001">Graduate Program in Informatics, Pontifical Catholic University of Minas Gerais (PUC Minas)</aff>
                                </contrib-group>
                                                                                                        <volume>17</volume>
                                <issue>2</issue>
                                    <fpage>381</fpage>
                        <lpage>404</lpage>
                                <pub-date pub-type="epub">
                        <day>13</day>
                                    <month>10</month>
                        <year>2018</year>
        </pub-date>
                                        <abstract>
                        <p>Computerized Adaptive Testing (CAT) is now widely used. However, inserting new items into the question bank of a CAT requires a great effort that makes impractical the wide application of CAT in classroom teaching. One solution would be to use the tacit knowledge of the teachers or experts for a pre-classification and calibrate during the execution of tests with these items. Thus, this research consists of a comparative case study between a Stratified Adaptive Test (SAT), based on the tacit knowledge of a teacher, and a CAT based on Item Response Theory (IRT). The tests were applied in seven Computer Networks courses. The results indicate that levels of anxiety expressed in the use of the SAT were better than those using the CAT, in addition to being simpler to implement. In this way, it is recommended the implementation of a SAT, where the strata are initially based on the tacit knowledge of the teacher and later, as a result of an IRT calibration.</p>
                    </abstract>
                <kwd-group>
            <label>Keywords</label>
                        <kwd>computerized adaptive test</kwd>
                        <kwd>stratified adaptive test</kwd>
                        <kwd>item response theory</kwd>
                        <kwd>motivation</kwd>
                        <kwd>anxiety</kwd>
                        <kwd>evaluation methodologies</kwd>
                        <kwd>teaching/learning strategies</kwd>
                        <kwd>improving classroom teaching</kwd>
                    </kwd-group>
    </article-meta>
</front>
</article>
