Debating Curricular Strategies for Teaching Statistics and Research Methods

Abstract

Coursework in statistics and research methods is a core requirement in most undergraduate psychology programs. However, is there an optimal way to structure and sequence methodology courses to facilitate student learning? For example, should statistics be required before research methods, should research methods be required before statistics, or should statistics and research methods be taught in a combined, integrated fashion? In this article, we first review the current empirical evidence on whether there is a preferred format and sequencing of methodology courses to enhance student learning outcomes. Then we summarize an assessment study conducted at our own institution comparing a nonintegrated, two-course sequence that required statistics before research methods and an integrated, two-course sequence in which students shifted in an out of research methods and statistics units during each semester on short-term and long-term student outcomes. Our results revealed that students enrolled in the integrated sequence not only earned higher course grades in each of their initial methodology courses but also scored higher on senior exit assessments of their methodology skills taken at the end of their undergraduate careers.

Predicting Performance in Upper Division Psychology Classes: Are Enrollment Timing and Performance in Statistics and Research Methods Important?

“…Scholarship in teaching and learning examines students’ characteristics, qualities of teachers, and specific teaching techniques to identify factors that promote student success. However, relatively little research has examined optimal sequencing of courses within the psychology major (but see Barron & Apple, 2014; Betancur et al, 2018; Freng et al, 2011). Enrollment timing of research methods, in particular, predicts the success of psychology majors, but several questions remain.…”

Active Learning Strategies and Competency-Based Design in Research Education: a Longitudinal Review

“…The design, structure, content, and delivery are in alignment with the course's RMS consumer purpose, which now clearly differentiates this course from the other core courses in the RMS curriculum. The current and similar designs can also be used to address issues of abstract and generic presentation (Barr, 2014), sequencing within a course (Barron & Apple, 2014), and perhaps begin to tackle students' research and statistics apprehension (Coleman & Conrad, 2007;Cook, 1998;Davis, 2003;Huang, 2018;Rodriguez & Toews, 2005;Shenk et al, 2001;Smith & Martinez-Moyano, 2012). The current competency-based design and assessments are also in alignment with master's degree-level preparation (CoRE Project Team, 2010;ESG, 2025;Lumina, 2014) including preparation for practitioners to be informed RMS consumers in a variety of settings and disciplines (Katzer, Cook, & Crouch, 1998;Okahana, Augustine, & Zhou, 2018;McMillan, 2012;Rodriquez & Toews, 2005;Smith & Martinez-Moyano, 2012).…”

“…The following six design and satisfaction statements were included across the 8-year period: 1. value of assignments, 2. clarity of course objectives, 3. weights of assignments, 4. grading criteria, 5. whether the course increase knowledge, and 6. whether the course would be recommended. Statements 1 through 4 were used to gauge design decisions such as sequencing and the concreteness of the content (Barr, 2014;Barron & Apple, 2014), statements 1 and 5 gauged relevance, and statement gauged overall satisfaction (Shenk et al, 2001;Davis, 2003;Rodriguez & Toews, 2005). Qualitative comments were also used to inform design decisions, gauge relevance and satisfaction, and provide a window into possible anxiety and other negative feelings (Coleman & Conrad, 2007;Davis, 2003;Huang, 2018).…”

From the Classroom to the Lab: How Faculty Can Extend Curriculum Oriented Research Experiences to Publish With Undergraduates

“…During the first 2 years of the major, our declared students take a year-long sequence of Research Design and Statistical Analysis (RDSA). Rather than splitting the topics into separate semesters, we find that this integrative approach better synthesizes the theoretical and practical aspects of research, thereby making the material more accessible to students (see Barron and Apple, 2014). Within the lecture-based portion of the class, students learn about ethical responsibilities, sampling techniques, measurement, and study design, as well as practice reading, summarizing, and critiquing research.…”