July 21, 2021 Conference paper Open Access

Chiodini Luca

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  <identifier identifierType="DOI">10.5281/zenodo.5118719</identifier>
  <creators>
    <creator>
      <creatorName>Chiodini Luca</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-2712-9248</nameIdentifier>
      <affiliation>Software Institute - USI</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Wrong Answers for Wrong Reasons: The Risks of Ad Hoc Instruments</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2021</publicationYear>
  <dates>
    <date dateType="Issued">2021-07-21</date>
  </dates>
  <resourceType resourceTypeGeneral="ConferencePaper"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/5118719</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.5118718</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;This folder contains anonymized data from the experiment described in the paper &amp;quot;Wrong Answers for Wrong Reasons: The Risks of Ad Hoc Instruments&amp;quot;.&lt;/p&gt;

&lt;ul&gt;
	&lt;li&gt;&lt;code&gt;questions.md&lt;/code&gt;&amp;nbsp;contains the 14 questions used as pre/post-test&lt;/li&gt;
	&lt;li&gt;Participants are identified using numeric identifiers (from 1 to 40).&lt;/li&gt;
	&lt;li&gt;&lt;code&gt;conditions.csv&lt;/code&gt; contains the mapping between participants identifiers and their condition&lt;/li&gt;
	&lt;li&gt;
	&lt;p&gt;&lt;code&gt;{test}_{assessment_type}_anon.csv&lt;/code&gt; contains data for a given test (&lt;code&gt;pretest&lt;/code&gt; or &lt;code&gt;posttest&lt;/code&gt;) using a certain assessment type. Two assessment types are used:&lt;/p&gt;

	&lt;ul&gt;
		&lt;li&gt;&lt;code&gt;mc&lt;/code&gt; (multiple choice as assessed by Moodle: &lt;code&gt;0&lt;/code&gt; means wrong, &lt;code&gt;1&lt;/code&gt; means correct, &lt;code&gt;-&lt;/code&gt; means missing)&lt;/li&gt;
		&lt;li&gt;&lt;code&gt;revised&lt;/code&gt; (human revision after reading the explanation: the judgment is either a &lt;code&gt;0&lt;/code&gt; or a &lt;code&gt;1&lt;/code&gt; following what presented in the paper)&lt;/li&gt;
	&lt;/ul&gt;
	&lt;/li&gt;
	&lt;li&gt;
	&lt;p&gt;Statistics are computed with Python and SciPy. You can execute the script by running:&lt;/p&gt;

	&lt;pre&gt;&lt;code&gt;python3 main.py
&lt;/code&gt;&lt;/pre&gt;

	&lt;p&gt;and you should get this output:&lt;/p&gt;

	&lt;pre&gt;&lt;code&gt;=== Analyzing answers using mc as assessment type ===
Results on pretest - Condition Text: N: 21, mean ± std: 9.81 ± 3.03
Results on pretest - Condition Graphic: N: 19, mean ± std: 9.68 ± 2.11
Mann Whitney U on pretest scores: U=184.0, p=0.3406

Results on posttest - Condition Text: N: 21, mean ± std: 11.19 ± 2.75
Results on posttest - Condition Graphic: N: 19, mean ± std: 10.74 ± 2.23
Mann Whitney U on posttest scores: U=164.0, p=0.1681

=== Analyzing answers using revised as assessment type ===
Results on pretest - Condition Text: N: 20, mean ± std: 9.15 ± 3.10
Results on pretest - Condition Graphic: N: 19, mean ± std: 7.89 ± 3.16
Mann Whitney U on pretest scores: U=150.5, p=0.1344

Results on posttest - Condition Text: N: 20, mean ± std: 11.15 ± 2.39
Results on posttest - Condition Graphic: N: 19, mean ± std: 9.42 ± 3.11
Mann Whitney U on posttest scores: U=123.0, p=0.0299
&lt;/code&gt;&lt;/pre&gt;

	&lt;p&gt;You might need to install &lt;code&gt;scipy&lt;/code&gt; (e.g., depending on your setup, &lt;code&gt;pip install scipy&lt;/code&gt;).&lt;/p&gt;
	&lt;/li&gt;
&lt;/ul&gt;</description>
  </descriptions>
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