July 21, 2021 Conference paper Open Access

Chiodini Luca

MARC21 XML Export

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    <subfield code="a">Wrong Answers for Wrong Reasons: The Risks of Ad Hoc Instruments</subfield>
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    <subfield code="a">&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;
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