EDM 2016 Tutorial - SAS Tools for Educational Data Mining


We're so excited for EDM 2016 in Raleigh, NC this year and even more pleased to announce that we'll be hosting a tutorial on using free SAS tools for educational data mining. This tutorial will take place on June 29 and will include a hands-on* demonstration of SAS® University Edition and an overview of SAS® Enterprise Miner™ through SAS® OnDemand for Academics. We hope to see you there!

* If you intend to participate in the hands-on activities, please bring a laptop with SAS University Edition already installed. The process can take up to an hour so there will not be time for it on the day of the tutorial. The free download is available at http://www.sas.com/en_us/software/university-edition.html

Tutorial Overview

This tutorial will focus on introducing SAS to participants and guiding them through the use of the suite of tools using relevant educational data sets. The tools that will be covered include:

  • SAS® Programming Language. SAS programming language is a powerful language designed specifically for intensive data analysis. This highly flexible and extensible fourth generation programming language has a clear syntax and hundreds of language elements and functions. It supports programming everything from data extraction, formatting and cleansing to data analysis, building sophisticated models, and generating reports. The SAS programming language is at the heart of the SAS University Edition tools.
  • SAS® Studio. SAS Studio is the development environment for SAS University Edition and runs through the web browser as well as in the cloud. It offers a powerful GUI interface that allows novice programmers to interact with data and perform analyses without writing any SAS code themselves. However, the SAS code is all generated behind the scenes and is visible to help users learn.
  • SAS® Enterprise Miner™. SAS Enterprise Miner helps users streamline the data mining process to create highly accurate predictive and descriptive models based on analysis of vast amounts of data. It includes innovative algorithms in the areas of statistics and machine learning to enhance the stability and accuracy of predictions, which can be verified easily by visual model assessment and validation. Users build process flow diagrams that serve as self-documenting procedures. These diagrams can be updated easily or applied to new problems without starting over from scratch. In addition to process flow diagrams, Enterprise Miner provides a programming interface for advanced users. Enterprise Miner allows integration with open source software for data manipulation and model comparison, the open standard PMML, and databases for scoring models without data movement.

Additional SAS tools that may be covered if it is of interest to the participants include tools for time series analysis, forecasting, matrix manipulations, and advanced statistics.

Tutorial Format

This tutorial will be presented as interactive instructions where users will be guided through the tools using relevant education data with a focus on techniques that are commonly required in the EDM community. The tutorial will also include an overview of SAS and its commitment to education research by a leading SAS executive. We also seek to gain feedback from participants prior to the event so that we can tailor the sessions to specific needs or questions. A tentative schedule is below:

Session 1: Introduction and SAS University Edition

9:00-9:15    Introduction – Introduction of presenters and participants and overview of SAS Analytics U

9:15-10:30  SAS Studio and SAS Programming Language

Coffee Break

Session 2: SAS Studio

11:00-12:30   SAS Studio

Lunch Break

Session 3: SAS Enterprise Miner

14:00-15:30   SAS Enterprise Miner

Coffee Break

Session 4: Participant Requested Instruction

16:00-17:00   Additional Instruction – based on the goals of the participants we will delve deeper into aspects of the tools already presented or introduce additional tools as listed in the tutorial description.

17:00-17:30   Conclusion

In addition to the tutorial, instructional materials will be made available to participants. We will also provide guidance on avenues for further learning through online instruction.


About Author

Jen Sabourin

Jen Sabourin, Ph.D., is a Software Developer and Research Scientist as part of SAS’ Social Innovation Division. Presently, her work is focused on using SAS resources and analytic capabilities to have a positive impact on the world, with a special focus on K-12 education initiatives. Jen holds a Ph.D. in Computer Science from North Carolina State University where her research focused on artificial intelligence and data mining applications for education. She is also passionate about broadening participation in technology and data science and introducing students of all ages and backgrounds to the joys of computer science and analytics.

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