Difference between revisions of "SOCR Events ISIS Aug2009"
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===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: | + | * Date/Time: [http://www.statssa.gov.za/isi2009/STCPM_List.pdf STCPM 27, Mon. 17, 2009], 15:30 - 17:45 |
| − | * Place: | + | * 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] | ||
===Speakers=== | ===Speakers=== | ||
* [http://www.stat.ucla.edu/~nchristo Nicolas Christou], Examples of Embedding SOCR materials in Undergraduate Statistics Curricula | * [http://www.stat.ucla.edu/~nchristo 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. | ||
| + | |||
* [http://statweb.calpoly.edu/arossman/ Allan Rossman], Concepts of Statistical Inference: A Randomization-Based Curriculum | * [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], Teaching and Assessing Statistics Education using Technology | ||
| + | : Modern technology enables novel pedagogical approached for teaching and learning assessment in introductory statistics. Students and instructors have varieties of choices with respect to course content, type of technological enhancement and learning styles. We will review varieties of pedagogically, cost and knowledge-retention effective strategies. Student curricular placement, a pre- and post-assessments and synchronization of teaching vs. learning styles significantly affect the outcomes of college statistics courses. | ||
* [http://www.stat.ucla.edu/~dinov Ivo Dinov], Quantitative and Qualitative Assessment of Technology-Enhanced Probability and Statistics Education | * [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=== | ===See also=== | ||
| − | * [http://www.statssa.gov.za/isi2009/ | + | * [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> | <hr> | ||
Latest revision as of 19:38, 11 August 2009
Contents
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
- Organizers: Ivo Dinov & Nicolas Christou
- Date/Time: STCPM 27, Mon. 17, 2009, 15:30 - 17:45
- Place: Durban, SA, International Convention Center.
- Abstract submission and inquiries: Contact Nicolas Christou
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, Teaching and Assessing Statistics Education using Technology
- Modern technology enables novel pedagogical approached for teaching and learning assessment in introductory statistics. Students and instructors have varieties of choices with respect to course content, type of technological enhancement and learning styles. We will review varieties of pedagogically, cost and knowledge-retention effective strategies. Student curricular placement, a pre- and post-assessments and synchronization of teaching vs. learning styles significantly affect the outcomes of college statistics courses.
- 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
- SOCR Home page: http://www.socr.ucla.edu
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