Difference between revisions of "SOCR Events CAUSE TL Spring2010"
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* Meeting: [http://www.causeweb.org/webinar/teaching/ CAUSE Teaching and Learning (T&L) Webinar]. | * Meeting: [http://www.causeweb.org/webinar/teaching/ CAUSE Teaching and Learning (T&L) Webinar]. | ||
* Organizers: Jackie Miller, Dennis Pearl. | * Organizers: Jackie Miller, Dennis Pearl. | ||
| − | * Date/Time: Tuesday, May 11, 2010, 11:00-11:30 AM (Pacific Time). | + | * Date/Time: Tuesday, May 11, 2010, 11:00-11:30 AM (Pacific Time). |
| − | * Place: Virtual Meeting/Webinar using ReadyTalk. | + | * Place: [http://www.causeweb.org/webinar/teaching/2010-05/ Virtual Meeting/Webinar using ReadyTalk]. |
| + | * Presenter: [http://www.stat.ucla.edu/%7Edinov/ Ivo D. Dinov] | ||
===SOCR Presentation=== | ===SOCR Presentation=== | ||
| Line 11: | Line 12: | ||
* '''Title''': ''Interactive Statistics Education using Web-based SOCR Data, Tools, Activities, and Resources''. | * '''Title''': ''Interactive Statistics Education using Web-based SOCR Data, Tools, Activities, and Resources''. | ||
* '''Abstract''': This webinar will present data, tools, materials and the pedagogical approach of the Statistics Online Computational Resource (SOCR) for technology-enhanced probability and statistics education. Following a review of the different types of SOCR online resources, we will go over two specific classroom utilization examples. The first one provides a hands-on demonstration of a statistical concept ([[AP_Statistics_Curriculum_2007_Limits_CLT |CLT]]) using interactive virtual experiments and simulations. The second example will showcase the use of SOCR resources to address interesting social, health, environmental, scientific, and engineering challenges. In this case, we'll focus on the [[SOCR_MotionCharts_CAOzoneData |Ozone pollution in California]], formulate health-related hypotheses, identify appropriate data and employ web-based exploratory and statistical data analysis tools. | * '''Abstract''': This webinar will present data, tools, materials and the pedagogical approach of the Statistics Online Computational Resource (SOCR) for technology-enhanced probability and statistics education. Following a review of the different types of SOCR online resources, we will go over two specific classroom utilization examples. The first one provides a hands-on demonstration of a statistical concept ([[AP_Statistics_Curriculum_2007_Limits_CLT |CLT]]) using interactive virtual experiments and simulations. The second example will showcase the use of SOCR resources to address interesting social, health, environmental, scientific, and engineering challenges. In this case, we'll focus on the [[SOCR_MotionCharts_CAOzoneData |Ozone pollution in California]], formulate health-related hypotheses, identify appropriate data and employ web-based exploratory and statistical data analysis tools. | ||
| − | + | ||
| − | + | * '''What is [http://www.SOCR.ucla.edu www.SOCR.ucla.edu]?''' | |
| − | + | ** The [http://www.SOCR.ucla.edu Statistics Online Computational Resource] provides portable online aids for probability and statistics education, technology based instruction and statistical computing. SOCR tools and resources include a repository of interactive applets, computational and graphing tools, instructional and course materials. | |
| − | + | ** SOCR aims to develop new Java applets, design diverse extensible SOCR learning activities, develop XML/HTML navigation/search tools for interactive materials, and validate and assess technology-enhances pedagogical techniques. | |
| − | + | *'''SOCR Products''' | |
| − | + | ** Tools/Applets: [http://socr.ucla.edu/htmls/dist/Normal_Distribution.html Distributions], [http://socr.ucla.edu/htmls/exp Experiments], [http://socr.ucla.edu/htmls/ana Analyses], [http://socr.ucla.edu/htmls/game Games], [http://socr.ucla.edu/htmls/mod Modeler] & [http://socr.ucla.edu/htmls/chart Graphs]. | |
| − | + | ** Multilingual instructional resources: [[EBook | EBooks]], [[SOCR_News | continuing statistics education workshops/seminars]] | |
| − | + | ** Learning activities: [[SOCR_EduMaterials |interactive, data-driven and technology-enhanced learning activities]] | |
| − | + | ** Examples: | |
| − | + | *** [[SOCR_EduMaterials_Activities_GeneralCentralLimitTheorem | Central Limit Theorem]] | |
| − | + | *** [[SOCR_MotionCharts_CAOzoneData | Hands-on California Ozone Data Activity]] | |
| − | + | ** Data: [[SOCR_Data | Diverse publicly accessible datasets for copy-paste/download utilization]] | |
| − | + | *** Example: [[SOCR_LetterFrequencyData | Latin Letters Frequency Distribution]] | |
| − | + | ** Dissemination: [http://www.socr.ucla.edu/htmls/SOCR_References.html papers], [[SOCR_News | conferences, workshops, etc.]] | |
| − | + | * '''SOCR Evaluation and Efficacy''': We have conducted several control-based studies of the efficacy of technology-enhanced statistics education. Using IRB-approved studies, quantitative and qualitative measures of student performance were recorded in classes using traditional (control) instruction (R or Stata based) and classes using SOCR resources and tools. Non-parametric analyses of the data showed very statistically significant (SOCR) treatment effects (<math>p<10^{-4}</math>) on student performance and perception of the material. The practical significance of these treatment effects were more modulated. [http://www.socr.ucla.edu/htmls/SOCR_References.html More details about these studies are available here]. | |
| + | |||
* '''Summary''': | * '''Summary''': | ||
** [http://www.SOCR.ucla.edu Main SOCR server, applets]. | ** [http://www.SOCR.ucla.edu Main SOCR server, applets]. | ||
** [http://wiki.stat.ucla.edu/socr Data, activities and EBooks]. | ** [http://wiki.stat.ucla.edu/socr Data, activities and EBooks]. | ||
| − | ** http://forums.stat.ucla.edu/socr Feedback and Forum]. | + | ** [http://forums.stat.ucla.edu/socr Feedback and Forum]. |
** [http://socr.ucla.edu/SOCR_HT_ResourceViewer.html Graphical SOCR Navigator]. | ** [http://socr.ucla.edu/SOCR_HT_ResourceViewer.html Graphical SOCR Navigator]. | ||
| + | |||
| + | ===Participants=== | ||
| + | <center> | ||
| + | {| class="wikitable" style="text-align:center; width:75%" border="1" | ||
| + | ! Name || Institution | ||
| + | |- | ||
| + | | Danny Kaplan || Macalester College | ||
| + | |- | ||
| + | | Michael Bulmer || University of Queensland | ||
| + | |- | ||
| + | | Radoslav Nickolov || Fayetteville State University | ||
| + | |- | ||
| + | | Scott Millis || Wayne State University | ||
| + | |- | ||
| + | | Vanessa Miller || Southwestern IL College | ||
| + | |- | ||
| + | | Sharon Fronheiser || Rochester City School District | ||
| + | |- | ||
| + | | Jadwiga Domino || Medaille College | ||
| + | |- | ||
| + | | Herle McGowan || North Carolina State University | ||
| + | |- | ||
| + | | Joni Torsella || University of Cincinnati | ||
| + | |- | ||
| + | | James Regenfusz || Cincinnati State TCC | ||
| + | |- | ||
| + | | Todd Schwartz || UNC-Chapel Hill | ||
| + | |- | ||
| + | | Benjamin V.C. Collins || Univ of Wisconsin-Platteville | ||
| + | |- | ||
| + | | Kathy Mowers || Owensboro CTC | ||
| + | |- | ||
| + | | David Gurney || Southeastern Louisiana University | ||
| + | |- | ||
| + | | Rob Weitz || Seton Hall University | ||
| + | |- | ||
| + | | Nicholas Horton || Smith College | ||
| + | |- | ||
| + | | Bill Davis || CTC | ||
| + | |- | ||
| + | | Kalpana Pai || Texas Wesleyan University | ||
| + | |- | ||
| + | | Jackie Miller (Host) || Ohio State University | ||
| + | |}</center> | ||
===See also=== | ===See also=== | ||
Latest revision as of 10:34, 12 May 2010
Contents
SOCR News - 2010 SOCR Presentation at the Spring 2010 CAUSE T&L Webinar Series
Logistics
- Meeting: CAUSE Teaching and Learning (T&L) Webinar.
- Organizers: Jackie Miller, Dennis Pearl.
- Date/Time: Tuesday, May 11, 2010, 11:00-11:30 AM (Pacific Time).
- Place: Virtual Meeting/Webinar using ReadyTalk.
- Presenter: Ivo D. Dinov
SOCR Presentation
- Title: Interactive Statistics Education using Web-based SOCR Data, Tools, Activities, and Resources.
- Abstract: This webinar will present data, tools, materials and the pedagogical approach of the Statistics Online Computational Resource (SOCR) for technology-enhanced probability and statistics education. Following a review of the different types of SOCR online resources, we will go over two specific classroom utilization examples. The first one provides a hands-on demonstration of a statistical concept (CLT) using interactive virtual experiments and simulations. The second example will showcase the use of SOCR resources to address interesting social, health, environmental, scientific, and engineering challenges. In this case, we'll focus on the Ozone pollution in California, formulate health-related hypotheses, identify appropriate data and employ web-based exploratory and statistical data analysis tools.
- What is www.SOCR.ucla.edu?
- The Statistics Online Computational Resource provides portable online aids for probability and statistics education, technology based instruction and statistical computing. SOCR tools and resources include a repository of interactive applets, computational and graphing tools, instructional and course materials.
- SOCR aims to develop new Java applets, design diverse extensible SOCR learning activities, develop XML/HTML navigation/search tools for interactive materials, and validate and assess technology-enhances pedagogical techniques.
- SOCR Products
- Tools/Applets: Distributions, Experiments, Analyses, Games, Modeler & Graphs.
- Multilingual instructional resources: EBooks, continuing statistics education workshops/seminars
- Learning activities: interactive, data-driven and technology-enhanced learning activities
- Examples:
- Data: Diverse publicly accessible datasets for copy-paste/download utilization
- Example: Latin Letters Frequency Distribution
- Dissemination: papers, conferences, workshops, etc.
- SOCR Evaluation and Efficacy: We have conducted several control-based studies of the efficacy of technology-enhanced statistics education. Using IRB-approved studies, quantitative and qualitative measures of student performance were recorded in classes using traditional (control) instruction (R or Stata based) and classes using SOCR resources and tools. Non-parametric analyses of the data showed very statistically significant (SOCR) treatment effects (\(p<10^{-4}\)) on student performance and perception of the material. The practical significance of these treatment effects were more modulated. More details about these studies are available here.
- Summary:
Participants
| Name | Institution |
|---|---|
| Danny Kaplan | Macalester College |
| Michael Bulmer | University of Queensland |
| Radoslav Nickolov | Fayetteville State University |
| Scott Millis | Wayne State University |
| Vanessa Miller | Southwestern IL College |
| Sharon Fronheiser | Rochester City School District |
| Jadwiga Domino | Medaille College |
| Herle McGowan | North Carolina State University |
| Joni Torsella | University of Cincinnati |
| James Regenfusz | Cincinnati State TCC |
| Todd Schwartz | UNC-Chapel Hill |
| Benjamin V.C. Collins | Univ of Wisconsin-Platteville |
| Kathy Mowers | Owensboro CTC |
| David Gurney | Southeastern Louisiana University |
| Rob Weitz | Seton Hall University |
| Nicholas Horton | Smith College |
| Bill Davis | CTC |
| Kalpana Pai | Texas Wesleyan University |
| Jackie Miller (Host) | Ohio State University |
See also
- SOCR Home page: http://www.socr.ucla.edu
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