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Full Day Tutorial

Sunday 25th June 2006, 11.00 am - 6.30 pm

T1: Teaching Introductory Programming with ALICE

Not yet confirmed.

Presenters: Charles W. Herbert (Community College of Philadelphia - USA) and Charles B. McGinley (Community College of Philadelphia - USA)

Description: Learning to write computer programs can be difficult because of two major problems faced by novice programmers: language and visualization. The language problem occurs when people trying to learn about programming concepts must also learn a new programming language at the same time. The visualization problem occurs when people try to think about all the changes that will happen inside a computer when a program runs. They find it hard to visualize what happens when a program runs.

Carnegie Mellon University has developed a system called Alice, to make programming easier to learn by minimizing the problems of language and visualization. The Alice programming language has a grammar and syntax like other modern programming languages, and is both object-oriented and event driven.

This tutorial is intended for educators who teach introductory computer programming, and others interested in computer science education who have some knowledge of the topics covered in a modern object-oriented programming course.

Please note: Participants must bring their own laptop computer.

Half Day Tutorials

Sunday 25th June 2006, 2.30 pm - 6.00 pm (Ranzani Building)

T2: An introduction to the WEKA Data Mining System

Presenters: Zdravko Markov (of Central Connecticut State University - USA) and Ingrid Russell (of University of Hartford - USA)

Description: This half day tutorial on Weka, an open source data mining software will introduce faculty to the package (which is freely available) and to the pedagogical possibilities for its use in the undergraduate computer science and engineering curricula. The Weka system provides a rich set of powerful Machine Learning algorithms for Data Mining tasks, some not found in commercial data mining systems. These include the basic statistics and visualization tools, as well as tools fro pre-processing, classification, and clustering, all available through an easy to use graphical interface.

The purpose of this tutorial is to present an introduction to the Weka system and outline major approaches to using Weka for teaching Machine Learning, data and Web Mining. No background in machine learning or data mining is needed.

T3: Addressing the Risks in Class Software projects: a hands on approach to ethics and professionalism

Not yet confirmed.

Presenter: Don Gotterbarn (of Eastern Tennessee State University - USA) and Simon Rogerson (of De Montfort University - UK)

Description: This tutorial will address two problems. First all of us teach our students how to avoid the technical risks of developing software. However, student projects frequently fail because they underestimate or ignore the risks related to the delivery and the use of the product in their design and development. Second, discussion of computer science professional issues is often left to philosophers who have difficulty making philosophical theories relevant to technical computer science decisions.

This tutorial will introduce faculty to a technique for a hands-on introduction of professional and ethical risk analysis in any courses doing software development, provide them with experience using the Software Development Impact Statement Inspection process that has been used in universities in Australia, England, New Zealand and the USA. Participants will be able to apply this process to their class's software development projects, and they will learn how to integrate the ACM Code of Ethics in the risk analysis process. Participants will be provided with distributable copies of the SoDIS Inspection Case tool and an automated tutorial for their students to use in learning the process.