MSLT prepares graduate students to improve the learning and instruction of Science, Technology, Engineering, and Mathematics (STEM) disciplines. To achieve that goal, we are deeply committed to research and scholarship, using both basic and applied research.
We put a premium on developing principled approaches to affect educational practice and pursuing rigorous theory building about educational phenomena. We apply such knowledge in developing state of the art instructional designs. These efforts grow from an understanding of educational practice and close work with practitioners in both formal and informal learning settings.
Importantly we recognized that certain social groups have been historically marginalized from STEM disciplines, education, and work. We seek to understand the processes and structures contributing to the systematic exclusion of these groups and to actively contribute to correcting such inequities. Our work draws from a variety of disciplines including cognitive science, sociology, anthropology, the learning sciences, psychology, and computer science.
The Program of Study for theMathematics, Science and Learning Technology Education Doctoral Concentration consists of the following.
Eleven (11) required courses totaling 33 credits:
Two (2) required elective courses totaling 6 credits.
With the required eighteen (18) dissertation credits, the total number of required credits is 57.
The courses that are eligible to fulfill these doctoral requirements can be found at the following link: Mathematics, Science and Learning Technology Graduate Program Curriculum Outline.
Doctoral students are encouraged to work closely with their advisor on developing a program of study that is aligned with the student's interests and background and MSLT faculty's research expertise. Such a program of study will include various research methods courses (qualitative, quantitative and/or mixed methods) as well as topic-specific courses within the department, across the College of Education or the University.
Doctoral students are additionally encouraged to seek out opportunities to work closely with MSLT faculty on their research projects and/or teaching assignments in order to develop insights and skills in research and teaching in academia.
Coordinator: John Francisco (Associate Professor)
Elementary Science Teacher Education: Kathy Davis (Associate Professor)
Learning Technologies (Doctoral): Florence Sullivan (Associate Professor) and Torrey Trust (Assistant Professor)
Mathematics Education (Master's/Licensure and Doctoral): John Francisco (Associate Professor) and Sandra Madden (Associate Professor)
Science Education (Master's/Licensure and Doctoral): Martina Nieswandt (Associate Professor)
John J. Clement (Professor Emeritus), Kathleen S. Davis (Associate Professor), John M. Francisco (Associate Professor), John Kudukey (Lecturer), Sandra Madden (Associate Professor), Martina Nieswandt (Associate Professor), Howard A. Peelle (Professor), Florence Sullivan (Associate Professor)