A research methods and data analysis book for quantitative studies. A research design management tools. A perpetually developed resource.
A web-based educational and research tool for numerical assessment of structural knowledge using constrained and unconstrained concept maps.
A suite of web application for education and research in women’s health. Designed and developed for the University of Kansas School of Medicine.
Causality is pervasive and ubiquitous. It helps build intellectual understanding, supports deliberations, is involved in planning, in technology, and even in language. Its understanding is critical to cognition and learning. I am interested in learning more about how we can help people reason and learn in causal contexts.
Today’s world produces ever increasing amounts of data which, when used properly, can provide insights that were not possible before. I believe that quantitative analysis and statistics should be approachable. The book and the associated resources are developed from the point of view that the use of statical methods to understand a quantifiable phenomena does not have to be overwhelming.
Concept maps are phenomenal tools for assessing structural knowledge of a domain or around a concept. Nevertheless, when it comes to use them for assessment, the come with a significant disadvantage because the best way to assess them is by hand. Today's technology offers us affordances that were limited in the past, both in constructing concept maps and analyzing them. This line of research attempts to study how the assessment of structural knowledge can be automated.