1. Empirical evaluation of internet-enabled intelligent argumentation for collaborative decision making
Student: Ravi Arvapally, Computer Science Department
Faculty Advisor(s): Dr. Frank Liu , Computer Science Department and Dr.Shun Takai , Mechanical and Aerospace Engineering
OBJECTIVES
The objective of this project is to conduct an empirical evaluation of a Web-based intelligent argumentation system.
To evaluate effectiveness of the argumentation system in collaborative decision making empirically.
Compare it with other e-communication tools such as , Web-logs, etc.
Develop a set of evaluation metrics.
INTELLIGENT ARGUMENTATION SYSTEM
Intelligent Argumentation tool is a Web-based application, and it is based on the Client – Server Architecture.
Participants can post their arguments using any Web browser.
The Server runs three different fuzzy inference engines for the reduction of arguments, reassessment of argument weights and for the dynamic priority assessment.
The Server takes issues, alternatives, arguments, and evidences as inputs and manages them in the argumentation tree by using the fuzzy inference engines.
WEB-BASED INTELLIGENT ARGUMENTATION
SYSTEM
ARGUMENTATION DIALOG GRAPH
FRAMEWORK FOR ASSESSMENT
CASE STUDY AND ISSUE
Issue: Select a software process model for a hypothetical education organization
Target system: A Web oriented educational ERP system for students, Instructors and staff.
Issue
Waterfall Model Agile Process Model Unified Process Model
METRICS FOR WEB-BASED INTELLIGENT ARGUMENTATION SYSTEM
The criterion set that is considered during the decision making process using an Web-based intelligent argumentation system.
Change in the opinion of participants after the argumentation process.
The growth of support for a rationale in the argumentation process and survey.
The average number of arguments posted by participants in the argumentation tree.
Number of self-conflicts and conflicts among participants.
METRICS FOR BASED ARGUMENTATION
Number of -based argumentation threads.
Ratio of argumentation-related threads to non- argumentation threads.
Average length of threads in -based argumentation.
The criterion set that is considered during a decision making process using an based argumentation system.
Number of s exchanged on each criteria.
Average number of responses in -based argumentation from a participant.
ANTICIPATED RESULTS & FUTURE WORK
Conduct empirical studies to evaluate how effective the intelligent argumentation system compared with other mass communication tools.
Collect empirical data based on the metrics.
Analyze collected empirical data and compare our system with s, blogs, and other mass communication tools.