Difference between revisions of "SOCR Events ISIS Aug2009"

From SOCR
Jump to: navigation, search
(Logistics)
Line 9: Line 9:
 
===Logistics===
 
===Logistics===
 
* Organizers: [http://www.stat.ucla.edu/~dinov Ivo Dinov] & [http://www.stat.ucla.edu/~nchristo Nicolas Christou]
 
* 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].
 
* Place: [http://www.icc.co.za Durban, SA, International Convention Center].
 
* Abstract submission and inquiries: Contact [http://www.stat.ucla.edu/~nchristo Nicolas Christou]
 
* Abstract submission and inquiries: Contact [http://www.stat.ucla.edu/~nchristo Nicolas Christou]

Revision as of 14:30, 29 June 2009

SOCR News - 2009 ISI Special Session

Interactive, Data-Driven and Technology-Enhanced Approaches for Probability and Statistics Education

In this 2-hour special session we'll select and invite 4 speakers to give 20+5 min talks presenting their novel approaches for integrating 20+technology and modern pedagogical ideas in different types of probability and statistics classes. The focus of this session will be on hands-on utilization of research-generated data, tools for statistical computing and Web-based learning resources and instructional materials.

The presenters we will discuss ideas and activities for helping students to learn fundamental concepts of statistical inference with a randomization-based curriculum rather than normal-based inference. These approaches lead to deeper conceptual understanding, make clear connections between study design and scope of conclusions, and provide powerful and generalizable analysis frameworks.

Logistics

Speakers

  • Nicolas Christou, Examples of Embedding SOCR materials in Undergraduate Statistics Curricula
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.
  • 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.
  • Paul Fields, TBD
  • 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




Translate this page:

(default)
Uk flag.gif

Deutsch
De flag.gif

Español
Es flag.gif

Français
Fr flag.gif

Italiano
It flag.gif

Português
Pt flag.gif

日本語
Jp flag.gif

България
Bg flag.gif

الامارات العربية المتحدة
Ae flag.gif

Suomi
Fi flag.gif

इस भाषा में
In flag.gif

Norge
No flag.png

한국어
Kr flag.gif

中文
Cn flag.gif

繁体中文
Cn flag.gif

Русский
Ru flag.gif

Nederlands
Nl flag.gif

Ελληνικά
Gr flag.gif

Hrvatska
Hr flag.gif

Česká republika
Cz flag.gif

Danmark
Dk flag.gif

Polska
Pl flag.png

România
Ro flag.png

Sverige
Se flag.gif