To learn more about the newest version of the software and its algorithms, an article will be accessible by Summer 2018!
The newest Incremental Thesaurus for Assessing Causal Maps
(ITACMv2) supports modelers and educators in assessing models for complex, open-ended questions. As such questions do not have a small set of "correct" answers, the assessment of one's model is done with respect to the model developed by a field expert. Our software focuses on this comparison. Our key innovation is our intelligent system to align maps, as two people may use different terms but refer to the same concept. Without assistance, alignment can be an extremely time-consuming task, as the term used in one model may be equivalent to any of the terms used in another model. Our intelligent system re-uses the alignments from previous users to identify the most relevant terms and provides suggestions. Our software is designed to be user-friendly, with most tasks feasible in only a few clicks, and interactive visualizations providing a clear feedback. The software is a collaboration between Drs. Giabbanelli and Tawfik, and this second version is managed by Vishrant Krishna Gupta as part of his thesis work. The software is built on a client/server model. All the data resides on the server, such that our intelligent system can use it to make an informed recommendation. Users access the software by logging in through their client:
Signing up for an account is quick and free. As educators are the primary target for this work (since their students generate many maps that need to be assessed), we include several fields for educators:
After logging in, the user has access to all of his/her "assignments", and can create new ones. An assignment is simply a way to gather all the maps that were collected under one project. Assignments can be shared with other users, but only the person who created the assignment "owns" it. Users with whom the assignment is shared can analyze it, but they cannot edit it or delete it.
The analysis provides access to our complete suite of intelligent tools. The first one is our intelligent system to align the terms used in maps. The student's terms will show on the left, and recommendations will be provided on the most relevant expert terms on the right. Recommendations appear in red as "possibilities", and once the user clicks on one term, it confirms it and turns blue.
Our solution is built on Neo4J, SQL, and D3 technologies to provide a responsive and modern environment. This allows to benefit from state-of-the-art algorithms and provides a satisfactory user experience. In particular, we use visualizations (in the form of node-link diagrams) to easily explore and contrast two maps.
To learn more about the software and its algorithms, please refer to our publication in the journal Technology, Knowledge and Learning
Download ITACM Software (Java)
The ZIP file includes all the files required to run the program.Download
The Incremental Thesaurus for Assessing Causal Maps
(ITACM) is a tool built for educators. When students work on ill-structured problems, it is difficult to evaluate their results. One way is to compare their work with an expert's solution. However, current solutions for comparison tend to remain labor intensive. ITACM partially automates the process. It takes in as input two causal maps (the student's and the expert's), which are represented as directed networks. In the download section at the bottom, you will find both the software and two sample maps. Then, ITACM helps educator to visually compare and manually align the maps. The process of aligning the map incrementally builds a thesaurus, that is, a list of all alignments. The more maps are aligned, and the larger the thesaurus, thus helping to align additional maps faster. In other words, the process of aligning the map creates an understanding of the problem space as a by-product, which can be shared among educators and used to speed-up the intensive alignment task. The software was programmed by Dr. Philippe Giabbanelli in a joint project with Dr. Andrew Tawfik, from Northern Illinois University's Department of Educational Technology, Research & Assessment.