CUIN 520: Methods in Educational Research

Class Program
Credits 3
Catalog
Graduate
CIP Code
13.0501

The course exposes learners to various primary education research methods and scientific paradigms. The course introduces several themes and topics to the learners that include research strategies and designs, the nature of quantitative/qualitative research, quantitative/qualitative data collection and analysis. Conducting literature reviews, critiquing research, and designing a research proposal will be emphasized.

Course Outcomes

After successfully completing the course, the learner will be able to:

  • Apply multiple learning hierarchies to teaching and assessment of student progress.
  • Demonstrate a comprehensive understanding of program theory and its articulation;
  • Demonstrate a basic understanding of the uses and utilization of program theory and its application for evaluation planning and decision-making;
  • Discuss and apply the criteria by which instruments are designed and assessed;
  • Demonstrate a basic understanding of various concerns in testing and measurement.
  • Discuss and apply ways in which reliability and validity are established;
  • Explain the range of testing issues that educators confront and describe sound ways to handle those issues effectively.
  • Design classroom-based tests that meet standards for the sound administration of assessment and testing.
  • Explain how data from multiple frameworks are applied to inform decision-making about learning and teaching.
  • Clarify the cognitive bases for learning and their connections to various forms of assessments of learning and learning activities.
  • Analyze learning artifacts such as lesson plans, assessment reports, and others regarding their cognitive demands and determine the appropriate assessment of students’ expectations.
  • Describe the differences between the conceptual frameworks underlying classroom and system-level assessment data.
  • Discuss and apply the use of criteria utilized in data collection procedures and how they are planned and assessed;
  • Identify how data-driven decision-making is implied or made explicit in federal statutes and state assessment programs, particularly for the state where employed.