https://www.pcla.wiki/index.php?title=Task/Activity_Quit_Prediction&feed=atom&action=history
Task/Activity Quit Prediction - Revision history
2024-03-28T22:48:53Z
Revision history for this page on the wiki
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https://www.pcla.wiki/index.php?title=Task/Activity_Quit_Prediction&diff=379&oldid=prev
Ryan at 03:00, 21 June 2022
2022-06-21T03:00:33Z
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">← Older revision</td>
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 23:00, 20 June 2022</td>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Rzepka et al. (2022) [https://www.insticc.org/node/TechnicalProgram/CSEDU/2022/presentationDetails/109621 pdf]</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Rzepka et al. (2022) [https://www.insticc.org/node/TechnicalProgram/CSEDU/2022/presentationDetails/109621 pdf]</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Models predicting whether student will quit spelling learning activity without completing</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Models predicting whether student will quit spelling learning activity without completing</div></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>* Multiple algorithms have slightly better false positive rates for second-language speakers than native speakers,</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>* Multiple algorithms have slightly better false positive rates for second-language speakers than native speakers, but equivalent performance on multiple other metrics.</div></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>but equivalent performance on multiple other metrics.</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>* Multiple algorithms have slightly better false positive rates and AUC ROC for students with at least one parent who graduated high school, but equivalent performance on multiple other metrics.</div></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>* Multiple algorithms have slightly better false positive rates and AUC ROC for students with at least one parent who graduated</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>* Multiple algorithms have slightly better false positive rates and AUC ROC for male students than female students, but equivalent performance on multiple other metrics.</div></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>high school, but equivalent performance on multiple other metrics.</div></td><td colspan="2" class="diff-side-added"></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>* Multiple algorithms have slightly better false positive rates and AUC ROC for male students than female students, </div></td><td colspan="2" class="diff-side-added"></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>but equivalent performance on multiple other metrics.</div></td><td colspan="2" class="diff-side-added"></td></tr>
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Ryan
https://www.pcla.wiki/index.php?title=Task/Activity_Quit_Prediction&diff=378&oldid=prev
Ryan: first entry
2022-06-21T02:58:32Z
<p>first entry</p>
<p><b>New page</b></p><div>Rzepka et al. (2022) [https://www.insticc.org/node/TechnicalProgram/CSEDU/2022/presentationDetails/109621 pdf]<br />
* Models predicting whether student will quit spelling learning activity without completing<br />
* Multiple algorithms have slightly better false positive rates for second-language speakers than native speakers,<br />
but equivalent performance on multiple other metrics.<br />
* Multiple algorithms have slightly better false positive rates and AUC ROC for students with at least one parent who graduated<br />
high school, but equivalent performance on multiple other metrics.<br />
* Multiple algorithms have slightly better false positive rates and AUC ROC for male students than female students, <br />
but equivalent performance on multiple other metrics.</div>
Ryan