The following professional development courses are open to all graduate students across campus:
BIO_SC 8060: Ethical Conduct of Research (1 credit hour.) (same as BIOCHM 8060). Discussion of ethical issues in biological research, including the rules and conventions for appropriate research conduct. Graded on S/U basis only.
ED LPA 9409: Introduction to Research Design (3 credit hours.) This course provides an introduction to quantitative, qualitative, and mixed methods research, with an emphasis on the epistemological and ontological issues that inform our choice of research methods. This course is intended for first year doctoral students. Graded on A-F basis only.
ED LPA 8955: Discourse Analysis (3 credit hours) (same as LTC 8955). This course introduces the theories and methods of discourse analysis, including conversation, critical discourse, and multimodal. Students will analyze the role of context and ethics, as they transcribe and analyze discourse, especially from analytical settings. Graded on A-F basis only.
ED LPA 9465: Policy Analysis/Large Databases (3 credit hours.) Intends to develop students' capacity to process national level large databases and to conduct policy-related research.
ED_LPA 9620: Qualitative Methods in Educational Research II (3 credit hours.) (same as ESC_PS 9620 and LTC 9620). This course constructs a conceptual and methodological bridge between the understandings of qualitative research developed in Qualitative Methods I and more advanced study of theories, designs, and methods. The focus is on theory, approaches to data analysis, and interpretation. Graded on A-F basis only.
JOURN 9087: Professional Seminar on Research Ethics (1 credit hour.) Weekly discussion session for doctoral students. Required of all doctoral students. Graded on S/U basis only.
JOURN 9087: Professional Seminar on Scholarly Integrity (1 credit hour.) Weekly discussion session for doctoral students. Required of all doctoral students. Graded on S/U basis only.
LTC 8900: Contemporary Challenges and Methodologies of Qualitative Research (1-3 hrs) This course surveys a range of non-traditional and/or disruptive approaches to qualitative research. Possible methodologies include: crystallization, performance ethnography, CRiT Walking (critical race theory), poststructural feminist policy analysis, and a/r/t/ography. Students will also read and discuss politics at the macro, meso, and mirco levels of doing inquiry within academia. Students will think about the politics of disrupting traditional ways of dissertating and thinking ahead for tenure/promotion.
MANGMT 7429: Managerial Statistics (1.5 credit hours).
N9550 Meta-Analysis Research (same as HDFS 9550). Prerequisites: 6 credits graduate statistics and graduate level quantitative methods course.
N9560 Qualitative Systematic Reviews (3 credit hours.) (Same as SOC_WK 9560 and H_ D_FS 9560) Examine and carry out elements of qualitative systematic reviews: topic/problem identification, data collection, and analysis. Understand how to limit threats to validity and maximize generalizability.
PSYCH-8910: Responsible Conduct of Research (1 credit hour.) This course exposes students to important concepts in the responsible conduct of research. Graded on A-F basis only.
VP-BIO 8641-01 Introduction to Research Ethics (1 credit hour). This course provides students with a brief overview of many of the ethical issues that confront today's scientist. It is important that scientist think about and develop their abilities to make well-reasoned responses to ethical problems.
VMS 8431: Research Methods and Data Analysis (2-4 credit hours.) A consideration of research methods, data analysis, and practical approaches to analyzing data sets derived from veterinary and biomedical studies.
VMS 8432: Applied Statistics and Informatics (2 credit hours.) Educate students in the practical application of statistics and information research tools. Students will learn about application of statistical modeling to biomedical research. They will be trained to use statistical software programs and then use those skills to analyze data sets. Additionally, students will learn about the use of informatics systems for researching scientific questions, data searching, and data dissemination. At the end of the course successful students should be able to develop and perform statistical analyses appropriate for most basic research study designs. Recommended: Successful completion of a general statistics course is highly recommended prior to taking this course. Graded A/F.