SOCR Events ISIS Aug2009 - Revision history

IvoDinov at 00:38, 12 August 2009

2009-08-12T00:38:19Z

IvoDinov: /* Speakers */ added PJF abstract/title

2009-07-15T18:49:21Z

‎Speakers: added PJF abstract/title

IvoDinov: /* Logistics */

2009-06-29T19:30:47Z

‎Logistics

IvoDinov at 19:29, 29 June 2009

2009-06-29T19:29:25Z

IvoDinov: /* Speakers */

2009-05-26T20:24:26Z

‎Speakers

IvoDinov: /* Speakers */ added abstracts

2009-05-26T20:02:42Z

‎Speakers: added abstracts

IvoDinov: /* Speakers */

2009-05-26T19:52:43Z

‎Speakers

IvoDinov at 19:52, 26 May 2009

2009-05-26T19:52:21Z

IvoDinov: /* Speakers */

2009-04-01T23:18:21Z

‎Speakers

IvoDinov at 23:17, 1 April 2009

2009-04-01T23:17:54Z

@@ Line 25: / Line 25: @@
 ===See also===
-* [http://www.statssa.gov.za/isi2009/ 2009 ISI Conference Page]
+* [http://www.statssa.gov.za/isi2009/ 2009 ISI Conference Page] & [http://www.globalconf.co.za/ISI2009/ISI%202009%20Scientific%20Programme.pdf ISI 2009 Program].
 <hr>

@@ Line 19: / Line 19: @@
 * [http://statweb.calpoly.edu/arossman/ Allan Rossman], Concepts of Statistical Inference: A Randomization-Based Curriculum
 :  We will present ideas and activities for helping students to learn fundamental concepts of statistical inference with a randomization-based curriculum rather than normal-based inference. We propose that this approach leads to deeper conceptual understanding, makes a clear connection between study design and scope of conclusions, and provides a powerful and generalizable analysis framework. We will present arguments in favor of such a curriculum, demonstrate some activities through which students can investigate these concepts, highlight some difficulties with implementing this approach, and discuss ideas for assessing student understanding of inference concepts and randomization procedures.
-* [http://statweb.byu.edu/faculty/faculty.php?person_id=80 Paul Fields], TBD
+* [http://statweb.byu.edu/faculty/faculty.php?person_id=80 Paul Fields], Teaching and Assessing Statistics Education using Technology
 * [http://www.stat.ucla.edu/~dinov Ivo Dinov], Quantitative and Qualitative Assessment of Technology-Enhanced Probability and Statistics Education
 : Modern technological advances have direct impact on the format, style and efficacy of delivery and consumption of educational content. For example, various novel networking and information technology tools and resources enable efficient, timely, interactive and graphical demonstrations of diverse scientific concepts. In this presentation, we will report on a meta-study of 3 controlled experiments of using the Statistics Online Computational Resources (www.SOCR.ucla.edu) in probability and statistics courses. Web-accessible SOCR applets, demonstrations, simulations and virtual experiments were used in different courses as treatment and compared to matched control classes utilizing traditional pedagogical approaches. Qualitative and quantitative data we collected from all courses included Felder-Silverman-Soloman index of learning styles, quantitative background assessment, pre and post surveys of attitude towards the subject, end-point satisfaction survey, and varieties of examination, quiz and laboratory test scores. Our findings indicate that students’ learning styles and attitudes towards a discipline are important confounds of their final quantitative performance. We also identified a weak effect (within each study), but very consistent (across all studies) of the technology-enhanced curricula to increase student satisfaction (measured by post surveys) and improve quantitative performance (measured by standard assessment instruments). The observed positive effects of integrating information technology with established pedagogical techniques may be valid across disciplines within the broader spectrum courses in the science education curriculum. The two critical components of improving science education via blended instruction include instructor training, and the development of appropriate curriculum- and audience-specific activities, simulations and interactive resources for data understanding.

@@ Line 9: / Line 9: @@
 ===Logistics===
 * Organizers: [http://www.stat.ucla.edu/~dinov Ivo Dinov] & [http://www.stat.ucla.edu/~nchristo Nicolas Christou]
-* Date: [http://www.statssa.gov.za/isi2009/STCPM_List.pdf STCPM 27, Mon. 17, 2009]
+* Date/Time: [http://www.statssa.gov.za/isi2009/STCPM_List.pdf STCPM 27, Mon. 17, 2009], 15:30 - 17:45
 * Place: [http://www.icc.co.za Durban, SA, International Convention Center].
 * Abstract submission and inquiries: Contact [http://www.stat.ucla.edu/~nchristo Nicolas Christou]

@@ Line 9: / Line 9: @@
 ===Logistics===
 * Organizers: [http://www.stat.ucla.edu/~dinov Ivo Dinov] & [http://www.stat.ucla.edu/~nchristo Nicolas Christou]
-* Date: TBD
+* Date: [http://www.statssa.gov.za/isi2009/STCPM_List.pdf STCPM 27, Mon. 17, 2009]
-* Place: TBD
+* Place: [http://www.icc.co.za Durban, SA, International Convention Center].
 * Abstract submission and inquiries: Contact [http://www.stat.ucla.edu/~nchristo Nicolas Christou]
@@ Line 19: / Line 19: @@
 * [http://statweb.calpoly.edu/arossman/ Allan Rossman], Concepts of Statistical Inference: A Randomization-Based Curriculum
 :  We will present ideas and activities for helping students to learn fundamental concepts of statistical inference with a randomization-based curriculum rather than normal-based inference. We propose that this approach leads to deeper conceptual understanding, makes a clear connection between study design and scope of conclusions, and provides a powerful and generalizable analysis framework. We will present arguments in favor of such a curriculum, demonstrate some activities through which students can investigate these concepts, highlight some difficulties with implementing this approach, and discuss ideas for assessing student understanding of inference concepts and randomization procedures.
-* TBD, TBD
+* [http://statweb.byu.edu/faculty/faculty.php?person_id=80 Paul Fields], TBD
 * [http://www.stat.ucla.edu/~dinov Ivo Dinov], Quantitative and Qualitative Assessment of Technology-Enhanced Probability and Statistics Education
 : Modern technological advances have direct impact on the format, style and efficacy of delivery and consumption of educational content. For example, various novel networking and information technology tools and resources enable efficient, timely, interactive and graphical demonstrations of diverse scientific concepts. In this presentation, we will report on a meta-study of 3 controlled experiments of using the Statistics Online Computational Resources (www.SOCR.ucla.edu) in probability and statistics courses. Web-accessible SOCR applets, demonstrations, simulations and virtual experiments were used in different courses as treatment and compared to matched control classes utilizing traditional pedagogical approaches. Qualitative and quantitative data we collected from all courses included Felder-Silverman-Soloman index of learning styles, quantitative background assessment, pre and post surveys of attitude towards the subject, end-point satisfaction survey, and varieties of examination, quiz and laboratory test scores. Our findings indicate that students’ learning styles and attitudes towards a discipline are important confounds of their final quantitative performance. We also identified a weak effect (within each study), but very consistent (across all studies) of the technology-enhanced curricula to increase student satisfaction (measured by post surveys) and improve quantitative performance (measured by standard assessment instruments). The observed positive effects of integrating information technology with established pedagogical techniques may be valid across disciplines within the broader spectrum courses in the science education curriculum. The two critical components of improving science education via blended instruction include instructor training, and the development of appropriate curriculum- and audience-specific activities, simulations and interactive resources for data understanding.
 ===See also===
-* [http://www.statssa.gov.za/isi2009/index.aspx 2009 ISI Conference Page]
+* [http://www.statssa.gov.za/isi2009/ 2009 ISI Conference Page]
 <hr>

@@ Line 15: / Line 15: @@
 ===Speakers===
 * [http://www.stat.ucla.edu/~nchristo Nicolas Christou], Examples of Embedding SOCR materials in Undergraduate Statistics Curricula
-: In this interactive demonstration, I will show the functionality, utilization and assessment of the current SOCR resources in probability and statistics courses at different levels. All SOCR tools, activities and materials are freely available over the Internet to the entire community. Specific probability and statistics resources that will be demonstrated include data (simulated, observational and research acquired) and tools for exploratory data analysis, virtual computer experiments, distribution modeling and data analysis. This will be an interactive hands-on discussion where participants are encouraged to bring in their Wi-Fi enabled laptops and try these resources directly during the presentation.
+: In this interactive demonstration, we will show the functionality, utilization and assessment of the current SOCR resources in probability and statistics courses at different levels. All SOCR tools, activities and materials are freely available over the Internet to the entire community. Specific probability and statistics resources that will be demonstrated include data (simulated, observational and research acquired) and tools for exploratory data analysis, virtual computer experiments, distribution modeling and data analysis. This will be an interactive hands-on discussion where participants are encouraged to bring in their Wi-Fi enabled laptops and try these resources directly during the presentation.
 * [http://statweb.calpoly.edu/arossman/ Allan Rossman], Concepts of Statistical Inference: A Randomization-Based Curriculum
-:  I will present ideas and activities for helping students to learn fundamental concepts of statistical inference with a randomization-based curriculum rather than normal-based inference. I propose that this approach leads to deeper conceptual understanding, makes a clear connection between study design and scope of conclusions, and provides a powerful and generalizable analysis framework. I present arguments in favor of such a curriculum, demonstrate some activities through which students can investigate these concepts, highlight some difficulties with implementing this approach, and discuss ideas for assessing student understanding of inference concepts and randomization procedures.
+:  We will present ideas and activities for helping students to learn fundamental concepts of statistical inference with a randomization-based curriculum rather than normal-based inference. We propose that this approach leads to deeper conceptual understanding, makes a clear connection between study design and scope of conclusions, and provides a powerful and generalizable analysis framework. We will present arguments in favor of such a curriculum, demonstrate some activities through which students can investigate these concepts, highlight some difficulties with implementing this approach, and discuss ideas for assessing student understanding of inference concepts and randomization procedures.
 * TBD, TBD
 * [http://www.stat.ucla.edu/~dinov Ivo Dinov], Quantitative and Qualitative Assessment of Technology-Enhanced Probability and Statistics Education