http://vrl.cs.brown.edu/wiki/index.php?action=history&feed=atom&title=CS295J%2FLiterature_class_2.11CS295J/Literature class 2.11 - Revision history2026-04-20T21:55:06ZRevision history for this page on the wikiMediaWiki 1.43.1http://vrl.cs.brown.edu/wiki/index.php?title=CS295J/Literature_class_2.11&diff=5181&oldid=prevChen Xu at 16:43, 19 September 20112011-09-19T16:43:51Z<p></p>
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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>* [http://delivery.acm.org/10.1145/1130000/1125552/p454-akers.pdf?ip=138.16.160.6&CFID=41848857&CFTOKEN=88172531&__acm__=1315781624_3f3ff7dffae48746685278b9f2b7dabb Wizard of Oz for Participatory Design: Inventing a Gestural Interface for 3D Selection of Neural Pathway Estimates], Akers-2006-WOP.</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>* [http://delivery.acm.org/10.1145/1130000/1125552/p454-akers.pdf?ip=138.16.160.6&CFID=41848857&CFTOKEN=88172531&__acm__=1315781624_3f3ff7dffae48746685278b9f2b7dabb Wizard of Oz for Participatory Design: Inventing a Gestural Interface for 3D Selection of Neural Pathway Estimates], Akers-2006-WOP.</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>: The paper decribes a participatory design process which is used to invent an interface for neuroscientists to select neural pathways from existing brain images by mouse. </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>: The paper decribes a participatory design process which is used to invent an interface for neuroscientists to select neural pathways from existing brain images by mouse. <ins style="font-weight: bold; text-decoration: none;">Neuroscientists </ins>are frastrated selecting pathways. In this design process, they are asked to invite their own gestures, with a prototype including two basic gesture, which is unknown by the neuroal scientist. They use mouse to make a gesture and tell the prototype what they want to do, like drawing a circle to indicate they want pathways through the circle. The prototype achieves the goal by combining basic gesture operations, and showing the results to the scientist right away. It's better to use the prototype because people can obtain the results immediately. This design process is more productive than those not using a prototype. ( Owner:Chen, Discussant: Nathan, Discussant: Diem Tran)</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;">neuroscientists </del>are frastrated selecting pathways. In this design process, they are asked to invite their own gestures, with a prototype including two basic gesture, which is unknown by the neuroal scientist. They use mouse to make a gesture and tell the prototype what they want to do, like drawing a circle to indicate they want pathways through the circle. The prototype achieves the goal by combining basic gesture operations, and showing the results to the scientist right away. It's better to use the prototype because people can obtain the results immediately. This design process is more productive than those not using a prototype. ( Owner:Chen, Discussant: Nathan, Discussant: Diem Tran)</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;"><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>* [http://site.ebrary.com/lib/brown/docDetail.action?docID=10173678 The Laws of Simplicity] by John Maeda</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>* [http://site.ebrary.com/lib/brown/docDetail.action?docID=10173678 The Laws of Simplicity] by John Maeda</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>: An interesting work on the efficiency of minimalist design. Quick read for those interested. </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>: An interesting work on the efficiency of minimalist design. Quick read for those interested. </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 set of design guidelines some of which we may be able to build on in automating interface evaluation; will certainly apply to manual evaluations (Owner: Wenjun Wang, Discussant: [[User:Steven Gomez|Steven Gomez]], Discussant: ?)</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 set of design guidelines some of which we may be able to build on in automating interface evaluation; will certainly apply to manual evaluations (Owner: Wenjun Wang, Discussant: [[User:Steven Gomez|Steven Gomez]], Discussant: ?)</div></td></tr>
</table>Chen Xuhttp://vrl.cs.brown.edu/wiki/index.php?title=CS295J/Literature_class_2.11&diff=5180&oldid=prevChen Xu at 16:43, 19 September 20112011-09-19T16:43:24Z<p></p>
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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>* [http://delivery.acm.org/10.1145/1130000/1125552/p454-akers.pdf?ip=138.16.160.6&CFID=41848857&CFTOKEN=88172531&__acm__=1315781624_3f3ff7dffae48746685278b9f2b7dabb Wizard of Oz for Participatory Design: Inventing a Gestural Interface for 3D Selection of Neural Pathway Estimates], Akers-2006-WOP.</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>* [http://delivery.acm.org/10.1145/1130000/1125552/p454-akers.pdf?ip=138.16.160.6&CFID=41848857&CFTOKEN=88172531&__acm__=1315781624_3f3ff7dffae48746685278b9f2b7dabb Wizard of Oz for Participatory Design: Inventing a Gestural Interface for 3D Selection of Neural Pathway Estimates], Akers-2006-WOP.</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;">Designs </del>an <del style="font-weight: bold; text-decoration: none;">interactive visualization </del>interface for <del style="font-weight: bold; text-decoration: none;">3D selection of </del>neural pathways <del style="font-weight: bold; text-decoration: none;">of human brains</del>. <del style="font-weight: bold; text-decoration: none;">The </del>mouse <del style="font-weight: bold; text-decoration: none;">based interface helps neuroscientists </del>to <del style="font-weight: bold; text-decoration: none;">select neural </del>pathways more <del style="font-weight: bold; text-decoration: none;">efficiently and intuitively</del>.( Owner:Chen, Discussant: Nathan, Discussant: Diem Tran)</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;">The paper decribes a participatory design process which is used to invent </ins>an interface for <ins style="font-weight: bold; text-decoration: none;">neuroscientists to select </ins>neural pathways <ins style="font-weight: bold; text-decoration: none;">from existing brain images by mouse. </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;">neuroscientists are frastrated selecting pathways. In this design process, they are asked to invite their own gestures, with a prototype including two basic gesture, which is unknown by the neuroal scientist</ins>. <ins style="font-weight: bold; text-decoration: none;">They use </ins>mouse to <ins style="font-weight: bold; text-decoration: none;">make a gesture and tell the prototype what they want to do, like drawing a circle to indicate they want </ins>pathways <ins style="font-weight: bold; text-decoration: none;">through the circle. The prototype achieves the goal by combining basic gesture operations, and showing the results to the scientist right away. It's better to use the prototype because people can obtain the results immediately. This design process is </ins>more <ins style="font-weight: bold; text-decoration: none;">productive than those not using a prototype</ins>. ( Owner:Chen, Discussant: Nathan, Discussant: Diem Tran)</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>* [http://site.ebrary.com/lib/brown/docDetail.action?docID=10173678 The Laws of Simplicity] by John Maeda</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>* [http://site.ebrary.com/lib/brown/docDetail.action?docID=10173678 The Laws of Simplicity] by John Maeda</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>: An interesting work on the efficiency of minimalist design. Quick read for those interested. </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>: An interesting work on the efficiency of minimalist design. Quick read for those interested. </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 set of design guidelines some of which we may be able to build on in automating interface evaluation; will certainly apply to manual evaluations (Owner: Wenjun Wang, Discussant: [[User:Steven Gomez|Steven Gomez]], Discussant: ?)</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 set of design guidelines some of which we may be able to build on in automating interface evaluation; will certainly apply to manual evaluations (Owner: Wenjun Wang, Discussant: [[User:Steven Gomez|Steven Gomez]], Discussant: ?)</div></td></tr>
</table>Chen Xuhttp://vrl.cs.brown.edu/wiki/index.php?title=CS295J/Literature_class_2.11&diff=5126&oldid=prevHua Guo at 16:52, 15 September 20112011-09-15T16:52:50Z<p></p>
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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>: Some thought about how this paper relates to our proposal:</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>: Some thought about how this paper relates to our proposal:</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># "Mental effort" is a good indicator for visualization effectiveness, if combined properly with other indicators and measured accurately.</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># "Mental effort" is a good indicator for visualization effectiveness, if combined properly with other indicators and measured accurately.</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># The author mentioned, though now fully expanded, in the paper that when considering cognitive load, we may want to distinguish between "useful cognitive load" which either contributes positively to user reasoning or is inevitable, such as data complexity and task complexity, and "wasted cognitive load" which is unnecessary for problem solving, such as visual complexity. This can be further explored to be incorporated into future cognitive modeling, or serve as design guidelines (Owner: Hua Guo, Discussant: Clara Kliman-Silver, Discussant: Jenna Zeigen)</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># The author mentioned, though now fully expanded, in the paper that when considering cognitive load, we may want to distinguish between "useful cognitive load" which either contributes positively to user reasoning or is inevitable, such as data complexity and task complexity, and "wasted cognitive load" which is unnecessary for problem solving, such as visual complexity. This can be further explored to be incorporated into future cognitive modeling, or serve as design guidelines <ins style="font-weight: bold; text-decoration: none;">: </ins>(Owner: Hua Guo, Discussant: Clara Kliman-Silver, Discussant: Jenna Zeigen)</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>* [http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.123.3761&rep=rep1&type=pdf Could I have the Menu Please? An Eye Tracking Study of Design Conventions] McCarthy-2003-CMP</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>* [http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.123.3761&rep=rep1&type=pdf Could I have the Menu Please? An Eye Tracking Study of Design Conventions] McCarthy-2003-CMP</div></td></tr>
</table>Hua Guohttp://vrl.cs.brown.edu/wiki/index.php?title=CS295J/Literature_class_2.11&diff=5125&oldid=prevHua Guo at 16:52, 15 September 20112011-09-15T16:52:18Z<p></p>
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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># The formulation that "visualization efficiency" can be measured in terms of cognitive gain and cognitive loss, where cognitive gain is reflected through response accuracy, and cognitive cost is reflected through response time and mental effort.</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># The formulation that "visualization efficiency" can be measured in terms of cognitive gain and cognitive loss, where cognitive gain is reflected through response accuracy, and cognitive cost is reflected through response time and mental effort.</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 of factors related to cognitive load. In this model, domain complexity, data complexity, task complexity, visual complexity, demographics complexity, time complexity and between-factors complexity are considered as casual factors of cognitive load, and mental effort, response time and response accuracy are considered as assessment factors of cognitive load.</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 of factors related to cognitive load. In this model, domain complexity, data complexity, task complexity, visual complexity, demographics complexity, time complexity and between-factors complexity are considered as casual factors of cognitive load, and mental effort, response time and response accuracy are considered as assessment factors of cognitive load.</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;"># A model of the relationship between task performance, mental effort and cognitive load.</ins></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>: The formula for visualization efficiency intends to put more emphasis on "how much cognitive load is required when working with a certain visualization" in addition to the traditional emphasis on user performance. Taking cognitive load into account helps distinguish the effectiveness of two visualizations where the user performance is roughly equal, but the required cognitive workload is different when working with the two visualizations.</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>: The formula for visualization efficiency intends to put more emphasis on "how much cognitive load is required when working with a certain visualization" in addition to the traditional emphasis on user performance. Taking cognitive load into account helps distinguish the effectiveness of two visualizations where the user performance is roughly equal, but the required cognitive workload is different when working with the two visualizations.</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 user study is performed to (in)validate whether the proposed casual factors are significantly correlated with the proposed assessment factors.</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 user study is performed to (in)validate whether the proposed casual factors are significantly correlated with the proposed assessment factors.</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>(Owner: Hua Guo, Discussant: Clara Kliman-Silver, Discussant: Jenna Zeigen)</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;">: Some thought about how this paper relates to our proposal:</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;"># "Mental effort" is a good indicator for visualization effectiveness, if combined properly with other indicators and measured accurately.</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;"># The author mentioned, though now fully expanded, in the paper that when considering cognitive load, we may want to distinguish between "useful cognitive load" which either contributes positively to user reasoning or is inevitable, such as data complexity and task complexity, and "wasted cognitive load" which is unnecessary for problem solving, such as visual complexity. This can be further explored to be incorporated into future cognitive modeling, or serve as design guidelines </ins>(Owner: Hua Guo, Discussant: Clara Kliman-Silver, Discussant: Jenna Zeigen)</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>* [http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.123.3761&rep=rep1&type=pdf Could I have the Menu Please? An Eye Tracking Study of Design Conventions] McCarthy-2003-CMP</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>* [http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.123.3761&rep=rep1&type=pdf Could I have the Menu Please? An Eye Tracking Study of Design Conventions] McCarthy-2003-CMP</div></td></tr>
</table>Hua Guohttp://vrl.cs.brown.edu/wiki/index.php?title=CS295J/Literature_class_2.11&diff=5124&oldid=prevHua Guo at 16:34, 15 September 20112011-09-15T16:34:15Z<p></p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 16:34, 15 September 2011</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># The formulation that "visualization efficiency" can be measured in terms of cognitive gain and cognitive loss, where cognitive gain is reflected through response accuracy, and cognitive cost is reflected through response time and mental effort.</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># The formulation that "visualization efficiency" can be measured in terms of cognitive gain and cognitive loss, where cognitive gain is reflected through response accuracy, and cognitive cost is reflected through response time and mental effort.</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 of factors related to cognitive load. In this model, domain complexity, data complexity, task complexity, visual complexity, demographics complexity, time complexity and between-factors complexity are considered as casual factors of cognitive load, and mental effort, response time and response accuracy are considered as assessment factors of cognitive load.</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 of factors related to cognitive load. In this model, domain complexity, data complexity, task complexity, visual complexity, demographics complexity, time complexity and between-factors complexity are considered as casual factors of cognitive load, and mental effort, response time and response accuracy are considered as assessment factors of cognitive load.</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>The formula for visualization efficiency intends to put more emphasis on "how much cognitive load is required when working with a certain visualization" in addition to the traditional emphasis on user performance. Taking cognitive load into account helps distinguish the effectiveness of two visualizations where the user performance is roughly equal, but the required cognitive workload is different when working with the two visualizations.</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;">: </ins>The formula for visualization efficiency intends to put more emphasis on "how much cognitive load is required when working with a certain visualization" in addition to the traditional emphasis on user performance. Taking cognitive load into account helps distinguish the effectiveness of two visualizations where the user performance is roughly equal, but the required cognitive workload is different when working with the two visualizations.</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>A user study is performed to (in)validate whether the proposed casual factors are significantly correlated with the proposed assessment factors.</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;">: </ins>A user study is performed to (in)validate whether the proposed casual factors are significantly correlated with the proposed assessment factors.</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>(Owner: Hua Guo, Discussant: Clara Kliman-Silver, Discussant: Jenna Zeigen)</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>(Owner: Hua Guo, Discussant: Clara Kliman-Silver, Discussant: Jenna Zeigen)</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>
</table>Hua Guohttp://vrl.cs.brown.edu/wiki/index.php?title=CS295J/Literature_class_2.11&diff=5123&oldid=prevHua Guo at 16:33, 15 September 20112011-09-15T16:33:38Z<p></p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 16:33, 15 September 2011</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>* [http://rp-www.cs.usyd.edu.au/~whua5569/papers/infovis09.pdf Measuring effectiveness of graph visualizations: a cognitive load perspective] Huang-2009-JIV</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>* [http://rp-www.cs.usyd.edu.au/~whua5569/papers/infovis09.pdf Measuring effectiveness of graph visualizations: a cognitive load perspective] Huang-2009-JIV</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>: This paper has proposed the following three items: </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>: This paper has proposed the following three items: </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;"> 1) </del>The concept of "mental effort" as a measurement for effectiveness of visualization,</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;"># </ins>The concept of "mental effort" as a measurement for effectiveness of visualization,</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;"> 2) </del>The formulation that "visualization efficiency" can be measured in terms of cognitive gain and cognitive loss, where cognitive gain is reflected through response accuracy, and cognitive cost is reflected through response time and mental effort.</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;"># </ins>The formulation that "visualization efficiency" can be measured in terms of cognitive gain and cognitive loss, where cognitive gain is reflected through response accuracy, and cognitive cost is reflected through response time and mental effort.</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;"> 3) </del>A model of factors related to cognitive load. In this model, domain complexity, data complexity, task complexity, visual complexity, demographics complexity, time complexity and between-factors complexity are considered as casual factors of cognitive load, and mental effort, response time and response accuracy are considered as assessment factors of cognitive load.</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;"># </ins>A model of factors related to cognitive load. In this model, domain complexity, data complexity, task complexity, visual complexity, demographics complexity, time complexity and between-factors complexity are considered as casual factors of cognitive load, and mental effort, response time and response accuracy are considered as assessment factors of cognitive load.</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>The formula for visualization efficiency intends to put more emphasis on "how much cognitive load is required when working with a certain visualization" in addition to the traditional emphasis on user performance. Taking cognitive load into account helps distinguish the effectiveness of two visualizations where the user performance is roughly equal, but the required cognitive workload is different when working with the two visualizations.</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>The formula for visualization efficiency intends to put more emphasis on "how much cognitive load is required when working with a certain visualization" in addition to the traditional emphasis on user performance. Taking cognitive load into account helps distinguish the effectiveness of two visualizations where the user performance is roughly equal, but the required cognitive workload is different when working with the two visualizations.</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>A user study is performed to (in)validate whether the proposed casual factors are significantly correlated with the proposed assessment factors.</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>A user study is performed to (in)validate whether the proposed casual factors are significantly correlated with the proposed assessment factors.</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>(Owner: Hua Guo, Discussant: Clara Kliman-Silver, Discussant: Jenna Zeigen)</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>(Owner: Hua Guo, Discussant: Clara Kliman-Silver, Discussant: Jenna Zeigen)</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>
</table>Hua Guohttp://vrl.cs.brown.edu/wiki/index.php?title=CS295J/Literature_class_2.11&diff=5122&oldid=prevHua Guo at 16:32, 15 September 20112011-09-15T16:32:50Z<p></p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 16:32, 15 September 2011</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>* [http://rp-www.cs.usyd.edu.au/~whua5569/papers/infovis09.pdf Measuring effectiveness of graph visualizations: a cognitive load perspective] Huang-2009-JIV</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>* [http://rp-www.cs.usyd.edu.au/~whua5569/papers/infovis09.pdf Measuring effectiveness of graph visualizations: a cognitive load perspective] Huang-2009-JIV</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>: This paper has proposed the following three items: </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>: This paper has proposed the following three items: </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>1) The concept of "mental effort" as a measurement for effectiveness of visualization,</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;"> </ins>1) The concept of "mental effort" as a measurement for effectiveness of visualization,</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>2) The formulation that "visualization efficiency" can be measured in terms of cognitive gain and cognitive loss, where cognitive gain is reflected through response accuracy, and cognitive cost is reflected through response time and mental effort.</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;"> </ins>2) The formulation that "visualization efficiency" can be measured in terms of cognitive gain and cognitive loss, where cognitive gain is reflected through response accuracy, and cognitive cost is reflected through response time and mental effort.</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>3) A model of factors related to cognitive load. In this model, domain complexity, data complexity, task complexity, visual complexity, demographics complexity, time complexity and between-factors complexity are considered as casual factors of cognitive load, and mental effort, response time and response accuracy are considered as assessment factors of cognitive load.</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;"> </ins>3) A model of factors related to cognitive load. In this model, domain complexity, data complexity, task complexity, visual complexity, demographics complexity, time complexity and between-factors complexity are considered as casual factors of cognitive load, and mental effort, response time and response accuracy are considered as assessment factors of cognitive load.</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>The formula for visualization efficiency intends to put more emphasis on "how much cognitive load is required when working with a certain visualization" in addition to the traditional emphasis on user performance. Taking cognitive load into account helps distinguish the effectiveness of two visualizations where the user performance is roughly equal, but the required cognitive workload is different when working with the two visualizations.</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;"> </ins>The formula for visualization efficiency intends to put more emphasis on "how much cognitive load is required when working with a certain visualization" in addition to the traditional emphasis on user performance. Taking cognitive load into account helps distinguish the effectiveness of two visualizations where the user performance is roughly equal, but the required cognitive workload is different when working with the two visualizations.</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>A user study is performed to (in)validate whether the proposed casual factors are significantly correlated with the proposed assessment factors.</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;"> </ins>A user study is performed to (in)validate whether the proposed casual factors are significantly correlated with the proposed assessment factors.</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>(Owner: Hua Guo, Discussant: Clara Kliman-Silver, Discussant: Jenna Zeigen)</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>(Owner: Hua Guo, Discussant: Clara Kliman-Silver, Discussant: Jenna Zeigen)</div></td></tr>
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</table>Hua Guohttp://vrl.cs.brown.edu/wiki/index.php?title=CS295J/Literature_class_2.11&diff=5121&oldid=prevHua Guo at 16:32, 15 September 20112011-09-15T16:32:04Z<p></p>
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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>* [http://rp-www.cs.usyd.edu.au/~whua5569/papers/infovis09.pdf Measuring effectiveness of graph visualizations: a cognitive load perspective] Huang-2009-JIV</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>* [http://rp-www.cs.usyd.edu.au/~whua5569/papers/infovis09.pdf Measuring effectiveness of graph visualizations: a cognitive load perspective] Huang-2009-JIV</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>: This paper <del style="font-weight: bold; text-decoration: none;">discusses </del>the <del style="font-weight: bold; text-decoration: none;">cognitive load theory and its application in measuring </del>effectiveness of <del style="font-weight: bold; text-decoration: none;">graph </del>visualization. A model of <del style="font-weight: bold; text-decoration: none;">user </del>task <del style="font-weight: bold; text-decoration: none;">performance</del>, mental effort and cognitive load <del style="font-weight: bold; text-decoration: none;">has been proposed and experiments have been conducted </del>to <del style="font-weight: bold; text-decoration: none;">refine </del>the <del style="font-weight: bold; text-decoration: none;">model</del>. <del style="font-weight: bold; text-decoration: none;">This seems to be an attempt along </del>the <del style="font-weight: bold; text-decoration: none;">line </del>of <del style="font-weight: bold; text-decoration: none;">defining quality metrics for visualization through </del>cognitive <del style="font-weight: bold; text-decoration: none;">modeling, which then closely relates </del>to <del style="font-weight: bold; text-decoration: none;">our proposal</del>. (Owner: Hua Guo, Discussant: Clara Kliman-Silver, Discussant: Jenna Zeigen)</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>: This paper <ins style="font-weight: bold; text-decoration: none;">has proposed </ins>the <ins style="font-weight: bold; text-decoration: none;">following three items: </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;">1) The concept of "mental effort" as a measurement for </ins>effectiveness of visualization<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;">2) The formulation that "visualization efficiency" can be measured in terms of cognitive gain and cognitive loss, where cognitive gain is reflected through response accuracy, and cognitive cost is reflected through response time and mental effort</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;">3) </ins>A model of <ins style="font-weight: bold; text-decoration: none;">factors related to cognitive load. In this model, domain complexity, data complexity, </ins>task <ins style="font-weight: bold; text-decoration: none;">complexity, visual complexity, demographics complexity, time complexity and between-factors complexity are considered as casual factors of cognitive load</ins>, <ins style="font-weight: bold; text-decoration: none;">and </ins>mental effort<ins style="font-weight: bold; text-decoration: none;">, response time </ins>and <ins style="font-weight: bold; text-decoration: none;">response accuracy are considered as assessment factors of </ins>cognitive load<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;">The formula for visualization efficiency intends to put more emphasis on "how much cognitive load is required when working with a certain visualization" in addition </ins>to the <ins style="font-weight: bold; text-decoration: none;">traditional emphasis on user performance</ins>. <ins style="font-weight: bold; text-decoration: none;">Taking cognitive load into account helps distinguish </ins>the <ins style="font-weight: bold; text-decoration: none;">effectiveness </ins>of <ins style="font-weight: bold; text-decoration: none;">two visualizations where the user performance is roughly equal, but the required </ins>cognitive <ins style="font-weight: bold; text-decoration: none;">workload is different when working with the two visualizations.</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;">A user study is performed </ins>to <ins style="font-weight: bold; text-decoration: none;">(in)validate whether the proposed casual factors are significantly correlated with the proposed assessment factors</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>(Owner: Hua Guo, Discussant: Clara Kliman-Silver, Discussant: Jenna Zeigen)</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>* [http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.123.3761&rep=rep1&type=pdf Could I have the Menu Please? An Eye Tracking Study of Design Conventions] McCarthy-2003-CMP</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>* [http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.123.3761&rep=rep1&type=pdf Could I have the Menu Please? An Eye Tracking Study of Design Conventions] McCarthy-2003-CMP</div></td></tr>
</table>Hua Guohttp://vrl.cs.brown.edu/wiki/index.php?title=CS295J/Literature_class_2.11&diff=5120&oldid=prevNathan Malkin: summary description2011-09-15T16:15:10Z<p>summary description</p>
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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>* [http://dl.acm.org/citation.cfm?id=1658355 Computational visual attention systems and their cognitive foundations: A survey] Frintrop-2010-CVA</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>* [http://dl.acm.org/citation.cfm?id=1658355 Computational visual attention systems and their cognitive foundations: A survey] Frintrop-2010-CVA</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>: This paper "provides an extensive survey of the grounding psychological and biological research on visual attention as well as the current state of the art of computational systems". It <del style="font-weight: bold; text-decoration: none;">should make </del>for <del style="font-weight: bold; text-decoration: none;">good background reading if we want </del>to <del style="font-weight: bold; text-decoration: none;">work with visual attention (detecting </del>regions of interest <del style="font-weight: bold; text-decoration: none;">in images)</del>. <del style="font-weight: bold; text-decoration: none;">([[User:Nathan Malkin|Nathan Malkin]]</del>, <del style="font-weight: bold; text-decoration: none;">12 September 2011)</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>: This paper "provides an extensive survey of the grounding psychological and biological research on visual attention as well as the current state of the art of computational systems".</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;">: Specifically, it:</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;"># Provides a brief overview of the human visual system and the concept of visual attention</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;"># Presents and discusses a number of different psychological and cognitive models of attention</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;"># Reports on the most common approaches to visual attention used by computational systems</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;"># Discusses the evaluation of these systems, their applications in computer vision and robotics, and open questions in the field</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;">: This relates to our project in that:</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>It <ins style="font-weight: bold; text-decoration: none;">provides an overview, and lots of references, to models of attention, which is generally useful </ins>for <ins style="font-weight: bold; text-decoration: none;">understanding human-computer interaction.</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;"># More specifically, predictive models could be used </ins>to <ins style="font-weight: bold; text-decoration: none;">identify </ins>regions of <ins style="font-weight: bold; text-decoration: none;">(particular) </ins>interest <ins style="font-weight: bold; text-decoration: none;">to users of the software, for example to provide additional details, auto-focus, or auto-select</ins>. <ins style="font-weight: bold; text-decoration: none;">These models, and their predictions</ins>, <ins style="font-weight: bold; text-decoration: none;">could be verified and compared with eye-tracking data.</ins></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>: <span style="color: green">(Owner: [[User:Nathan Malkin|Nathan Malkin]], Discussant: Hua Guo , Discussant: Wenjun Wang)</span></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>: <span style="color: green">(Owner: [[User:Nathan Malkin|Nathan Malkin]], Discussant: Hua Guo , Discussant: Wenjun Wang)</span></div></td></tr>
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</table>Nathan Malkinhttp://vrl.cs.brown.edu/wiki/index.php?title=CS295J/Literature_class_2.11&diff=5119&oldid=prevCaroline Ziemkiewicz at 16:12, 15 September 20112011-09-15T16:12:26Z<p></p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 16:12, 15 September 2011</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>: This article discusses search performance strategies in user interfaces per the results of an eye-tracking study. Specific attention is given to menu organization in the context of Web interfaces; the study asks whether people can learn to navigate menu environments that differ from standard layouts. Results show that there able to adapt to new layouts, even they violate previous expectations. Although substantial progress has been made in the past decade, the article draws attention to relevant design issues and concepts, especially as eye tracking methodologies continue continue to grow and improve. It also serves to reinforce the importance of eye tracking in HCI research and how exactly people analyze the data, techniques we can take into account as we seek new approaches for our own HCI research. (Owner: Clara Kliman-Silver, Discussant: Michael Spector, Discussant: Wenjun Wang)</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>: This article discusses search performance strategies in user interfaces per the results of an eye-tracking study. Specific attention is given to menu organization in the context of Web interfaces; the study asks whether people can learn to navigate menu environments that differ from standard layouts. Results show that there able to adapt to new layouts, even they violate previous expectations. Although substantial progress has been made in the past decade, the article draws attention to relevant design issues and concepts, especially as eye tracking methodologies continue continue to grow and improve. It also serves to reinforce the importance of eye tracking in HCI research and how exactly people analyze the data, techniques we can take into account as we seek new approaches for our own HCI research. (Owner: Clara Kliman-Silver, Discussant: Michael Spector, Discussant: Wenjun Wang)</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" 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>*[http://<del style="font-weight: bold; text-decoration: none;">ejournals</del>.<del style="font-weight: bold; text-decoration: none;">ebsco</del>.com<del style="font-weight: bold; text-decoration: none;">.revproxy.brown.edu</del>/<del style="font-weight: bold; text-decoration: none;">Direct</del>.<del style="font-weight: bold; text-decoration: none;">asp?AccessToken=6VFL2LL89KIIOIXL2I3O9IOHVIC28L2MMF&Show=Object </del>Cognitive Models of the Influence of Color Scale on Data Visualization Tasks] -Breslow-2009-CMI</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>*[http://<ins style="font-weight: bold; text-decoration: none;">www</ins>.<ins style="font-weight: bold; text-decoration: none;">sagepub</ins>.com/<ins style="font-weight: bold; text-decoration: none;">mcbridestudysite/study/Chapters/articles/Ch11_Breslow_Article</ins>.<ins style="font-weight: bold; text-decoration: none;">pdf </ins>Cognitive Models of the Influence of Color Scale on Data Visualization Tasks] -Breslow-2009-CMI</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>: Discusses the ways color scales and differences can be influential in the optimization of data visualization and analysis. Discusses the differences between absolute identification and relative comparison tasks and the implications of different types of color scales on the performance of such tasks. The authors create computational models of the processes and then compare their predictions to the results of two experiments. This paper is relevant because the visualizations we create probably will involve color scales, and the analysis of our visualizations probably will involve both types of tasks described. (Owner: Jenna Zeigen, Discussant: [[User:Steven Gomez|Steven Gomez]], Discussant: Stephen Brawner)</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>: Discusses the ways color scales and differences can be influential in the optimization of data visualization and analysis. Discusses the differences between absolute identification and relative comparison tasks and the implications of different types of color scales on the performance of such tasks. The authors create computational models of the processes and then compare their predictions to the results of two experiments. This paper is relevant because the visualizations we create probably will involve color scales, and the analysis of our visualizations probably will involve both types of tasks described. (Owner: Jenna Zeigen, Discussant: [[User:Steven Gomez|Steven Gomez]], Discussant: Stephen Brawner)</div></td></tr>
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</table>Caroline Ziemkiewicz