https://www.pcla.wiki/index.php?title=Native_Language_and_Dialect&feed=atom&action=history
Native Language and Dialect - Revision history
2024-03-29T12:53:32Z
Revision history for this page on the wiki
MediaWiki 1.37.1
https://www.pcla.wiki/index.php?title=Native_Language_and_Dialect&diff=393&oldid=prev
Ryan: Added Sha et al (2021)
2022-07-04T16:01:04Z
<p>Added Sha et al (2021)</p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 12:01, 4 July 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>* 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"></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>* Multiple algorithms have slightly better false positive rates for second-language speakers than native speakers, but equivalent performance on multiple other metrics.</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>* 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 colspan="2" class="diff-side-deleted"></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><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></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><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></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><ins style="font-weight: bold; text-decoration: none;">Sha et al. (2021) [https://angusglchen.github.io/files/AIED2021_Lele_Assessing.pdf pdf]</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></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><ins style="font-weight: bold; text-decoration: none;">* Models predicting a MOOC discussion forum post is content-relevant or content-irrelevant</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></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><ins style="font-weight: bold; text-decoration: none;">* MOOCs taught in English</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></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><ins style="font-weight: bold; text-decoration: none;">* ABROCA varied from 0.03 to 0.08 for non-native speakers of English versus native speakers</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></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><ins style="font-weight: bold; text-decoration: none;">* Balancing the size of each group in the training set reduced ABROCA</ins></div></td></tr>
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Ryan
https://www.pcla.wiki/index.php?title=Native_Language_and_Dialect&diff=380&oldid=prev
Ryan: added Rzepka
2022-06-21T03:01:36Z
<p>added Rzepka</p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 23:01, 20 June 2022</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l12">Line 12:</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>* L1-specific model trained on the speaker’s native language was the least fair, especially for Chinese, Japanese, and Korean speakers, but not for German speakers</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>* L1-specific model trained on the speaker’s native language was the least fair, especially for Chinese, Japanese, and Korean speakers, but not for German speakers</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>* All models (Baseline, Fair feature subset, L1-specific) performed worse for Japanese speakers</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>* All models (Baseline, Fair feature subset, L1-specific) performed worse for Japanese speakers</div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></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><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></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><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></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><ins style="font-weight: bold; text-decoration: none;">Rzepka et al. (2022) [https://www.insticc.org/node/TechnicalProgram/CSEDU/2022/presentationDetails/109621 pdf]</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></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><ins style="font-weight: bold; text-decoration: none;">* Models predicting whether student will quit spelling learning activity without completing</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></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><ins style="font-weight: bold; text-decoration: none;">* Multiple algorithms have slightly better false positive rates for second-language speakers than native speakers, but equivalent performance on multiple other metrics.</ins></div></td></tr>
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Ryan
https://www.pcla.wiki/index.php?title=Native_Language_and_Dialect&diff=312&oldid=prev
Seiyon at 12:27, 19 May 2022
2022-05-19T12:27:20Z
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 08:27, 19 May 2022</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l1">Line 1:</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>Naismith et al. (2018) [http://d-scholarship.pitt.edu/40665/1/EDM2018_paper_37.pdf 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>Naismith et al. (2018) [http://d-scholarship.pitt.edu/40665/1/EDM2018_paper_37.pdf 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>* Model that measures L2 learners’ lexical sophistication with the frequency list based on the native speaker corpora</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>* Model that measures L2 learners’ lexical sophistication with the frequency list based on the native speaker corpora</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>* Arabic-speaking learners are rated systematically lower across all levels of human-assessed English proficiency than speakers of Chinese, Japanese, Korean, and Spanish<del style="font-weight: bold; text-decoration: none;">.</del></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>* Arabic-speaking learners are rated systematically lower across all levels of human-assessed English proficiency than speakers of Chinese, Japanese, Korean, and Spanish</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>* Level 5 Arabic-speaking learners are inaccurately evaluated to have similar level of lexical sophistication as Level 4 learners from China, Japan, Korean and Spain <del style="font-weight: bold; text-decoration: none;">.</del></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>* Level 5 Arabic-speaking learners are inaccurately evaluated to have similar level of lexical sophistication as Level 4 learners from China, Japan, Korean and Spain</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>* When used on the ETS corpus, essays by Japanese-speaking learners with higher human-rated lexical sophistication are rated significantly lower in lexical sophistication than Arabic, Japanese, Korean and Spanish peers<del style="font-weight: bold; text-decoration: none;">.</del></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>* When used on the ETS corpus, essays by Japanese-speaking learners with higher human-rated lexical sophistication are rated significantly lower in lexical sophistication than Arabic, Japanese, Korean and Spanish peers</div></td></tr>
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Seiyon
https://www.pcla.wiki/index.php?title=Native_Language_and_Dialect&diff=311&oldid=prev
Seiyon at 12:26, 19 May 2022
2022-05-19T12:26:51Z
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 08:26, 19 May 2022</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l1">Line 1:</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>Naismith et al. (2018) [http://d-scholarship.pitt.edu/40665/1/EDM2018_paper_37.pdf 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>Naismith et al. (2018) [http://d-scholarship.pitt.edu/40665/1/EDM2018_paper_37.pdf pdf]</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>* <del style="font-weight: bold; text-decoration: none;">a model </del>that measures L2 learners’ lexical sophistication with the frequency list based on the native speaker corpora</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>* <ins style="font-weight: bold; text-decoration: none;">Model </ins>that measures L2 learners’ lexical sophistication with the frequency list based on the native speaker corpora</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>* Arabic-speaking learners are rated systematically lower across all levels of human-assessed English proficiency than speakers of Chinese, Japanese, Korean, and Spanish.</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>* Arabic-speaking learners are rated systematically lower across all levels of human-assessed English proficiency than speakers of Chinese, Japanese, Korean, and Spanish.</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>* Level 5 Arabic-speaking learners are inaccurately evaluated to have similar level of lexical sophistication as Level 4 learners from China, Japan, Korean and Spain .</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>* Level 5 Arabic-speaking learners are inaccurately evaluated to have similar level of lexical sophistication as Level 4 learners from China, Japan, Korean and Spain .</div></td></tr>
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Seiyon
https://www.pcla.wiki/index.php?title=Native_Language_and_Dialect&diff=250&oldid=prev
Seiyon at 00:41, 18 May 2022
2022-05-18T00:41:27Z
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 20:41, 17 May 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>* L1-specific model trained on the speaker’s native language was the least fair, especially for Chinese, Japanese, and Korean speakers, but not for German speakers</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>* L1-specific model trained on the speaker’s native language was the least fair, especially for Chinese, Japanese, and Korean speakers, but not for German speakers</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>* All models (Baseline, Fair feature subset, L1-specific) performed <del style="font-weight: bold; text-decoration: none;">disadvantageously </del>for Japanese 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>* All models (Baseline, Fair feature subset, L1-specific) performed <ins style="font-weight: bold; text-decoration: none;">worse </ins>for Japanese speakers</div></td></tr>
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Seiyon
https://www.pcla.wiki/index.php?title=Native_Language_and_Dialect&diff=241&oldid=prev
Seiyon at 00:56, 17 May 2022
2022-05-17T00:56:59Z
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 20:56, 16 May 2022</td>
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<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>Naismith et al. (2018) <del style="font-weight: bold; text-decoration: none;">[</del>[http://d-scholarship.pitt.edu/40665/1/EDM2018_paper_37.pdf pdf<del style="font-weight: bold; text-decoration: none;">]</del>]</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>Naismith et al. (2018) [http://d-scholarship.pitt.edu/40665/1/EDM2018_paper_37.pdf 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>* a model that measures L2 learners’ lexical sophistication with the frequency list based on the native speaker corpora</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>* a model that measures L2 learners’ lexical sophistication with the frequency list based on the native speaker corpora</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>* Arabic-speaking learners are rated systematically lower across all levels of human-assessed English proficiency than speakers of Chinese, Japanese, Korean, and Spanish.</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>* Arabic-speaking learners are rated systematically lower across all levels of human-assessed English proficiency than speakers of Chinese, Japanese, Korean, and Spanish.</div></td></tr>
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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;"><br/></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;"><br/></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>Loukina et al. (2019) <del style="font-weight: bold; text-decoration: none;">[</del>[https://aclanthology.org/W19-4401.pdf pdf<del style="font-weight: bold; text-decoration: none;">]</del>]</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>Loukina et al. (2019) [https://aclanthology.org/W19-4401.pdf 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;"><br/></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;"><br/></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 providing automated speech scores on English language proficiency assessment</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 providing automated speech scores on English language proficiency assessment</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>* L1-specific model trained on the speaker’s native language was the least fair, especially for Chinese, Japanese, and Korean speakers, but not for German speakers</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>* L1-specific model trained on the speaker’s native language was the least fair, especially for Chinese, Japanese, and Korean speakers, but not for German speakers</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>* All models (Baseline, Fair feature subset, L1-specific) performed disadvantageously for Japanese speakers</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>* All models (Baseline, Fair feature subset, L1-specific) performed disadvantageously for Japanese speakers</div></td></tr>
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Seiyon
https://www.pcla.wiki/index.php?title=Native_Language_and_Dialect&diff=179&oldid=prev
Ryan at 16:44, 28 March 2022
2022-03-28T16:44:50Z
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 12:44, 28 March 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>Naismith et al. (2018) [[http://d-scholarship.pitt.edu/40665/1/EDM2018_paper_37.pdf 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>Naismith et al. (2018) [[http://d-scholarship.pitt.edu/40665/1/EDM2018_paper_37.pdf 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>* a model that measures L2 learners’ lexical sophistication with the frequency list based on the native speaker corpora</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>* a model that measures L2 learners’ lexical sophistication with the frequency list based on the native speaker corpora</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>* Arabic-speaking learners are rated systematically lower across all levels of English proficiency than speakers of Chinese, Japanese, Korean, and Spanish.</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>* Arabic-speaking learners are rated systematically lower across all levels of <ins style="font-weight: bold; text-decoration: none;">human-assessed </ins>English proficiency than speakers of Chinese, Japanese, Korean, and Spanish.</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>* Level 5 Arabic-speaking learners are <del style="font-weight: bold; text-decoration: none;">unfairly </del>evaluated to have similar level of lexical sophistication as Level 4 learners from China, Japan, Korean and Spain .</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>* Level 5 Arabic-speaking learners are <ins style="font-weight: bold; text-decoration: none;">inaccurately </ins>evaluated to have similar level of lexical sophistication as Level 4 learners from China, Japan, Korean and Spain .</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>* When used on ETS corpus, <del style="font-weight: bold; text-decoration: none;">“high”-labeled </del>essays by Japanese-speaking learners are rated significantly lower in lexical sophistication than Arabic, Japanese, Korean and Spanish peers.</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>* When used on <ins style="font-weight: bold; text-decoration: none;">the </ins>ETS corpus, essays by Japanese-speaking learners <ins style="font-weight: bold; text-decoration: none;">with higher human-rated lexical sophistication </ins>are rated significantly lower in lexical sophistication than Arabic, Japanese, Korean and Spanish peers.</div></td></tr>
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Ryan
https://www.pcla.wiki/index.php?title=Native_Language_and_Dialect&diff=132&oldid=prev
Seiyon: 93
2022-02-17T13:38:19Z
<p>93</p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 09:38, 17 February 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;"><br/></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;"><br/></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>Loukina et al. (2019) [[https://<del style="font-weight: bold; text-decoration: none;">onlinelibrary</del>.<del style="font-weight: bold; text-decoration: none;">wiley.com/doi/pdfdirect</del>/<del style="font-weight: bold; text-decoration: none;">10</del>.<del style="font-weight: bold; text-decoration: none;">1002/ets2.12170 </del>pdf]]</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>Loukina et al. (2019) [[https://<ins style="font-weight: bold; text-decoration: none;">aclanthology</ins>.<ins style="font-weight: bold; text-decoration: none;">org</ins>/<ins style="font-weight: bold; text-decoration: none;">W19-4401</ins>.<ins style="font-weight: bold; text-decoration: none;">pdf </ins>pdf]]</div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></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> </div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></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><ins style="font-weight: bold; text-decoration: none;">* Models providing automated speech scores on English language proficiency assessment</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></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><ins style="font-weight: bold; text-decoration: none;">* L1-specific model trained on the speaker’s native language was the least fair, especially for Chinese, Japanese, and Korean speakers, but not for German speakers</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></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><ins style="font-weight: bold; text-decoration: none;">* All models (Baseline, Fair feature subset, L1-specific) performed disadvantageously for Japanese speakers</ins></div></td></tr>
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Seiyon
https://www.pcla.wiki/index.php?title=Native_Language_and_Dialect&diff=97&oldid=prev
Seiyon at 09:21, 3 February 2022
2022-02-03T09:21:16Z
<p></p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 05:21, 3 February 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>Naismith et al. (2018) [[http://d-scholarship.pitt.edu/40665/1/EDM2018_paper_37.pdf 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>Naismith et al. (2018) [[http://d-scholarship.pitt.edu/40665/1/EDM2018_paper_37.pdf pdf]]</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><del style="font-weight: bold; text-decoration: none;"></del></div></td><td colspan="2" class="diff-side-added"></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>* a model that measures L2 learners’ lexical sophistication with the frequency list based on the native speaker corpora</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>* a model that measures L2 learners’ lexical sophistication with the frequency list based on the native speaker corpora</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>* Arabic-speaking learners are rated systematically lower across all levels of English proficiency than speakers of Chinese, Japanese, Korean, and Spanish.</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>* Arabic-speaking learners are rated systematically lower across all levels of English proficiency than speakers of Chinese, Japanese, Korean, and Spanish.</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>* <del style="font-weight: bold; text-decoration: none;">When New General Service List(NGSL) is used on Pitt English Language Institute Corpus(PELIC), </del>Level 5 Arabic-speaking learners are unfairly evaluated to have similar level of lexical sophistication as Level 4 learners from China, Japan, Korean and Spain .</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>* Level 5 Arabic-speaking learners are unfairly evaluated to have similar level of lexical sophistication as Level 4 learners from China, Japan, Korean and Spain .</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>* When used on ETS corpus, “high”-labeled essays by Japanese-speaking learners are <del style="font-weight: bold; text-decoration: none;">rater </del>significantly lower in lexical sophistication than Arabic, Japanese, Korean and Spanish peers.</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>* When used on ETS corpus, “high”-labeled essays by Japanese-speaking learners are <ins style="font-weight: bold; text-decoration: none;">rated </ins>significantly lower in lexical sophistication than Arabic, Japanese, Korean and Spanish peers.</div></td></tr>
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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>Loukina et al. (2019) [[https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/ets2.12170 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>Loukina et al. (2019) [[https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/ets2.12170 pdf]]</div></td></tr>
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Seiyon
https://www.pcla.wiki/index.php?title=Native_Language_and_Dialect&diff=94&oldid=prev
Seiyon at 08:51, 3 February 2022
2022-02-03T08:51:17Z
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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 04:51, 3 February 2022</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l5">Line 5:</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>* When New General Service List(NGSL) is used on Pitt English Language Institute Corpus(PELIC), Level 5 Arabic-speaking learners are unfairly evaluated to have similar level of lexical sophistication as Level 4 learners from China, Japan, Korean and Spain .</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>* When New General Service List(NGSL) is used on Pitt English Language Institute Corpus(PELIC), Level 5 Arabic-speaking learners are unfairly evaluated to have similar level of lexical sophistication as Level 4 learners from China, Japan, Korean and Spain .</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>* When used on ETS corpus, “high”-labeled essays by Japanese-speaking learners are rater significantly lower in lexical sophistication than Arabic, Japanese, Korean and Spanish peers.</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>* When used on ETS corpus, “high”-labeled essays by Japanese-speaking learners are rater significantly lower in lexical sophistication than Arabic, Japanese, Korean and Spanish peers.</div></td></tr>
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<tr><td colspan="2" class="diff-side-deleted"></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><ins style="font-weight: bold; text-decoration: none;">Loukina et al. (2019) [[https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/ets2.12170 pdf]]</ins></div></td></tr>
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Seiyon