Projects are all in the general area of educational media. Keywords are artificial intelligence, multi-user environments, virtual environments, MUDs and MOOs, educational games, distance education, VRML, role-playing, software agents, software tutors, assessment, software tools.
For details, write firstname.lastname@example.org
|Geology Explorer Project|
|Planet Oit Content Development||Dr. Schwert, Dr. Saini-Eidukat, Dean Vestal|
|Planet Oit Assessment Studies||Dr. Schwert, Dr. Saini-Eidukat, Ned Kruger, Elizabeth Smith|
|Planet Oit Graphical Java-MOO Client||John Bauer|
|Planet Oit Graphics||Rebecca Potter, Acey Olson|
|Planet Oit GUI Design||Dr. Schwert, Dr. Saini-Eidukat, Dean Vestal, Rebecca Potter, Acey Olson, John Bauer, James Shimer|
|Planet Oit Software Tutors||Krista Dauner|
|Planet Oit Water Processes||Rahul Devabhaktuni|
|Planet Oit Environmental Effects||James Shimer|
|Crystal Formation Agents in VRML||<volunteer needed>|
|NLP-based Conversational Concept Agents||<volunteer needed> (was Brad Vender)|
|Geology Explorer Workbooks||<volunteer needed>|
|Retail Education Project|
|Retailer Game Graphical Java-MOO Client||Brad Vender|
|Retailer Game Graphics||Josh Stompro, Matt Carlson, Brad Corradi|
|Retailer Game Agent-based Economic Simulation||Golam Farooque|
|Retailer Game Economic Forcasting||Hong Wu|
|Retailer Game Market Research||Jun Zhou|
|Retailer Game Employee Agents||<volunteer needed>|
|Retailer Game Case-based Tutoring||Kishore Peravali|
|Restauranter Free Text Query Interface||Atif Majeed|
|Virtual Cell Project|
|Protein/Receptor/Inhibitor Agents in VRML||Dr. McClean, Dr. White, Brad Vender, Yihe Wu|
|Virtual Cell Graphical/VRML Java-MOO Client||Brad Vender|
|Virtual Cell Graphical/VRML User Interface||Aaron Bergstrom, Mark Rose|
|Organelle and Instrument MOO Simulation||Dr. McClean, Dr. White, Faye Erickson, Lance Holden|
|Organelle and Instrument Agents in VRML||<volunteer needed>|
|Transporter Proteins in VRML||<volunteer needed>|
|Virtual World Building Tools Project|
|Integrated Virtual World Building Tool||Kuo-Di Jian, John Bauer|
|Virtual Abstraction Tool||Yongxin "George" Jia (with Kuo-Di Jian)|
|Virtual Entity Tool||Vidyalatha Nagareddy (with Kuo-Di Jian)|
|Virtual Map Building Tool||Umesh Kedla (with Kuo-Di Jian, was Brad Vender)|
|SLATE Subjective Assessment Tool||Atif Majeed, Ned Kruger|
|Deductive Tutoring Agent Tool||<volunteer needed>|
|LambdaCore Upgrade Engine||<volunteer needed> (was Brad Vender)|
|Visual/Virtual Computer Science Project|
|The Visual Computer Program||Dr. Juell, Srinivas Kolipaka, Srinivas Kanala|
|Machines in a Virtual Museum for Computer Science Education||Curt Hill|
This project, still in the design stages, is intended to teach college level geology students how to act like geologists. We plan to develop an earthlike planet in a synthetic environment and dispatch small teams of geology students to the surface in search evidence that the planet will support colonization. The first module will involve oil exploration, where students will be expected to plan an expidition, locate and assess potential oil deposits, and survive the somewhat hostile environment in order to report on it.
An existing synthetic environment, designed to teach micro-economics and currently populated by a few human players and an army of extremely simple software agents, will be entirely re-developed with a new set of highly interactive software agents in order to create, for the first time, an interesting environment of "atmosphere", "infrastructure", and "tutorial" agents.
This project will also involve graphical client software development.
Starting with the published definition of Memory Organization Packets (MOPs) published in Inside Case-based Reasoning (Riesbeck and Schank, 1989), which is a frame language written in Common Lisp, define the equivalent frame language in C/C++ such that it is complete and platform independent (capable of executing on both IBM compatible and PowerMac).
The language must support all the functions for creating new MOPs, creating and storing links between MOPs, and creating hierarchies and ordered sequences of MOPs with branches and loops. Functions must also be provided to save a file of MOPs in compiled form, to load a compiled file of MOPs, and write an equivalent ASCII file of readable MOP definitions.
The language should be developed in such a way that the indexing tools, described below, can create, delete, and modify files of MOP definitions.
Develop a protocol and transport mechanism for storing and retrieving MOPs in a conventional (or object-oriented) multi-user database.
The challenge is that MOPs are hierarchical and dynamic data structures, and the MOP knowledge base (sometimes called a "memory") will be accessed by multiple tools and applications at the same time.
The server-side implementation must be platform independent, there must be client software capable of executing on both IBM compatible and PowerMac.
All tools must save and load network structures from both local MOP files and remote MOP databases.
The tool must allow the user to "partition" their view of the knowledge base so that multiple users can simultaneously create MOPs, and so that a user can concentrate on the part of memory relevant to them without being overwhelmed by the knowledge base as a whole.
The tool must have access to a lexically sound concept library so that new concepts can be related to and defined in terms of previously existing concepts by integrating MOP memory with the structure of a machine-readable dictionary.
The links will be of four types:
The tool must have a monitoring and matching function that notices patterns in user defined MOPs and retrieves similar, relevant MOPs for the user's benefit. The user will use the retrieved MOPs to make compare and contrast decisions in order to assist in indexing their case.
The tool must have a graphical user interface and interview-based MOP editing tools for defining the concepts and features of a domain. The user will be a subject matter expert or knowledge engineer who will be defining a domain of knowledge both by cases and by domain feature.
The tool must permit nodes to be linked into abstraction hierarchies and must provide the user with lists of possible follow-up MOPs using simple rules of inference.
The tool must maintain a library of abstract tasks and plans so the user can choose a relevant, similar task structure and modify it to their own purposes. Similarly, the tool must have a monitoring and matching function that notices patterns in user defined task structures and retrieves past cases of task structures for the user's benefit.
The tool must support multiple views of the task: flow charts, lists, timelines, etc.
The user will also be able to define objects in the environment, and will be able to link these objects to the concepts in a MOP memory.
Tutor building tools will include a graphical user interface to a platform-independent client that allows a user to define rules of inference and a case-based matcher and retrieval mechanism.
An outcome-based simulation is a network representation of a task environment. Nodes in the network represent states, places and objects, and links represent events that transition between nodes. In this way, suficiently rich problem spaces are defined that challenge a dweller to achieve some goal, while at the same time constraining the dweller to a finite, albeit large, set of possible actions at any given state.
Hooks must also be provided to the tools and other resources available in each state of the simulation.
Hooks must also be provided to the tools and other resources available in each step of the task.
The Polymer Tutor is a performance support system to assist "formulators" in using the "Formulation Expert" system. This system is for choosing ingredients for highly resistant coatings. The domain is Polymer Chemistry, and it requires highly specialized expertise to successfully create new coatings that are durable and cost-effective. The Formulation Expert system itself requires considerable expertise to use.
The Polymer Tutor is intended to assist specialists in the use of the Formulation Expert system by providing context-sensitive help and advice at every step along the (quite complex) process of formulation, and to provide case-based remindings of relevant stories of success and failure, to assist the formulators in their work.
A text-base synthetic environment was initiated in cooperation with the (now defunct) NDSU Anthropology Club. The ideawas to take the approach of first designing and creating an exploratory text-based world, in order to simulate the experiences of a working anthropologist, and then later augmenting that with a graphical user interface.