Full Abstract Details

The Probability Distributome Project: Interactive Teaching of Probability Distributions Theory and Applications using Data, Mode

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Project TypePhase 2/Type 2 - Expansion
Target DisciplineMathematics
Project FocusCreating Learning Materials and Teaching Strategies
NameSiegrist, Kyle
InstitutionUniversity of Alabama in Huntsville
DepartmentMathematics
Phone Number256-824-6486
E-mail Addresssiegrist@math.uah.edu
 
Goals & Intended Outcome

The Probability Distributome Project aims to introduce, validate and openly disseminate knowledge in the STEM sciences. The Distributome resources include portable online tools for probability and statistics education, technology based instruction and scientific computing.

 
Methods & Strategies

The Distributome infrastructure utilizes modern information, technology, networking and pedagogical resources to create, validate, and broadly distribute web-based learning materials, interactive applets, computational and graphing tools, instructional and course materials to enhance undergraduate studies of probability and its applications.

 
Evaluation Methods & Results

All Distributome web resources are pedagogically evaluated for their factual accuracy, learning usability, interoperability with external hardware and software, as well as their ability to facilitate and enhance the learning experiences. Field testing in classrooms at five universities using validated instruments is planned. In addition, the Distributome project uses a rigorous mechanism for open, community-based review and improvement of the underlying database and computational libraries.

 
Dissemination

The entire Distributome project is open-source and open-utilization. All Distributome learning materials, and resources are openly accessible via the main Distributome server (www.Distributome.org), We organize virtual and face-to-face workshops and presentations; participate in National meetings and train students (http://www.distributome.org/meetings/).

 
Impact

The Distributome resources are developed by faculty, researchers and scientists, including supervised students, to address their specific needs of improving student motivation, enhancing learning experiences and providing lasting understanding of probability theory and applications. We are currently in the process of evaluating the efficacy of the Distributome resources in classroom settings at several US universities.

 
Challenges

There were two types of challenges we encountered. The first one was resource-development related to the need for rapid, agile and efficient webapp design and development. The second challenge was tied to the need to introduce integrated learning materials, computational libraries and user-friendly web-navigation of all Distributome resources. We consulted graphics and web-development experts and cognitive scientists to solicit ideas about the most efficient and intuitive traversal and utilization of the Distributome webapps and learning materials.

 
Expected Outcomes

1. Increased student comprehension (validated by control-based experimental studies).2.Increased utilization of Distributome learning materials in the classroom.3. Improved motivation and interactive hands-on engagement of all learners.4. A diverse, extensible, collaborative, open-source development and open-dissemination computational libraries (http://Distributome.googlecode.com).5. Interactive graphical web-navigation of all Distributome resources

 
Data Impact

1. Number of users 2. Number of (known) Distributome-supported courses3. Number of Distributome Publications and citations

 
Collection Methods

1. IRB approved treatment-control studies of student comprehension and knowledge retention 2. Anonymous surveys3. Peer reviews4. Student evaluations5. Standard quantitative assessment (exams, quizzes, homeworks)

 
Key Findings

We are in the process of investigating the effects of the Distributome-resource-treatment on improving student’s quantitative performance, enhancing the students’ experiences, and exploring attitudes toward the discipline of probability and statistics education.

 
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