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I am responsible for providing vision, direction, planning and implementation regarding the use of technology in instruction of mathematics and science.
My
research interests are in theories of cognition, how these theories inform
the design of instruction, how we might best design instructional
technology within those frameworks, and how the research and development of
instructional technologies can inform our theories of cognition. I am
also interested in the role of technology in educational improvement and
reform.
Some of my current research projects
- EEES: Engaging Early Engineering Students to Expand Numbers of Degree Recipients
The focus of EEES is to improve retention and completion rates among engineering students. To do so, EEES will develop: (a) cross linkages between basic math/science courses and first year engineering courses, (b) a suite of diagnostics-driven intervention methods to help first and second year engineering students survive and thrive in their early years, (c) a core of upper division students who will act to supply "Supplemental Instruction" to lower division students for key technical courses, and (d) sound and long term faculty connections with first and second year students.
- FIRST Database
To support data-driven instructional decision making, we are building a database for storing, searching and supporting a wide variety of analyses of assessment data from undergraduate science courses.
- CPACE: A Collaborative Process to Align Computing Education with Engineering Workforce Needs
CPACE will develop, implement, and evaluate a process to create an academic/industry community as a lynchpin of curricular change. The specific project goal is to demonstrate the process in the context of meeting industrial needs for computational problem solving in engineering.
- Problem-Based Learning Project for Teachers
On this project, teachers and researchers work together to develop, implement and study the impact of a subject matter-focused, Problem-Based Learning (PBL) professional development model for preservice and inservice science teachers.
- Diagnostic Question Clusters (DQC) and Data Analysis Group (DAG)
We are developing
questions to diagnose common student misconceptions in biology (DQC) and evaluating instructional interventions to address those (DAG)
- LON-CAPA
Free open-source distributed learning content management and assessment system
- Animal Behavior & Welfare Group
Our research aims to improve the quality of life for animals and provide a scientific foundation for animal welfare standards. The online animal welfare course allows interaction between students and instructors from many different institutions and provides students with access to a broad network of animal welfare professionals and researchers as well as opportunities for dialogue and future collaboration.
Teaching & Mentoring
Prior to joining the DSME, I
was in the Department of Computer Science where I was part of a team that developed several introductory computer
science courses for non-computer science students. The most recent course
is Computing Concepts and Competencies, offered as
CSE 101 here at MSU.
About me
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