HIMATT is an integrated set of assessment tools for knowledge elicitation. It was developed by an international research team and has been implemented in various settings above all educational and work place sectors. It is based on empirical research and mainly concentrates on graph theory. So far, HIMATT integrates 3 research technologies: DEEP, SMD, and T-Mitocar.
Methodologically, the tools integrated into HIMATT touch the boundaries of qualitative and quantitative research methods and provide bridges between them. On the one hand, text can be analyzed very quickly without loosening the associative strength of natural language (MITOCAR and T-MITOCAR). Furthermore, conceptual graphs can be annotated by experts (DEEP). All of the data, regardless of how it is assessed, can be analyzed quantitatively with the same comparison functions for all built-in tools without further manual effort or recoding. Additionally, HIMATT generates standardized images of text and graphical representations.
The HIMATT architecture consists of two major platforms: a) HIMATT Research Engine and b) HIMATT Subject Environment. Functions for conducting and analyzing experiments are implemented within the HIMATT Research Engine. These functions include 1) Experiment Management, 2) Researcher Management, 3) Subjects Management, 4) View Function, and 5) Analysis and Compare Function. The HIMATT Subject Environment dynamically provides assigned experiments to individual subjects.
HIMATT has been implemented and runs on a Web server using Apache, MySQL (MY Sequential Query Language), and PERL (Practical Extraction and Report Language), plus additional packages, e.g. GraphViz (Ellson, Gansner, Koutsofios, North, & Woodhull, 2003).
We encourage and support researchers in using HIMATT, and we especially hope that our colleagues will contribute to its further development. Progress in the design of instruction for complex task requires tools such as HIMATT. Progress in developing personalized learning systems requires an extended version of HIMATT that can support formative feedback and self-regulatory behaviours. We hope that HIMATT will change and evolve into an even more powerful set of tools to support learning, performance and instruction.
Please refer to the following works when using HIMATT:
Ifenthaler, D. (2010). Scope of graphical indices in educational diagnostics. In D. Ifenthaler, P. Pirnay-Dummer & N. M. Seel (Eds.), Computer-based diagnostics and systematic analysis of knowledge (pp. 213-234). New York: Springer.
Ifenthaler, D. (2010). Relational, structural, and semantic analysis of graphical representations and concept maps. Educational Technology Research and Development, 58(1), 81-97. doi: 10.1007/s11423-008-9087-4
Ifenthaler, D., Pirnay-Dummer, P., & Seel, N. M. (Eds.). (2010). Computer-based diagnostics and systematic analysis of knowledge. New York: Springer.
Pirnay-Dummer, P., Ifenthaler, D., & Spector, J. M. (2010). Highly integrated model assessment technology and tools. Educational Technology Research and Development, 58(1), 3-18. doi: 10.1007/s11423-009-9119-8