Advanced Research Methodology in Psychology: Syllabus and Course Introduction

Course Prerequisites and Advanced Expectations

This course is structured for advanced students who have mastered specific foundational competencies. It is an elevated research methodology course requiring a strong grasp of both statistical analysis and academic writing.

• Mandatory Prerequisites: Students must have completed elementary, introductory, or basic statistics (covering psychology or general stats). Additionally, completion of a 100W course or its equivalent is required.

• Writing Standards: While 100W equivalents in English or Literature are accepted, students must adapt from MLA to APA formatting. APA style is mandatory for all course materials. Subjective language, such as using terms like "unlikely" or "unfortunately," must be avoided in favor of objective, evidence-based writing.

• Time Commitment: Based on credit hour expectations ($3$ credits plus a lab), students should expect to dedicate at least $9$ hours per week to this course. This includes lectures, lab work, communication with teammates, and independent study.

Research Objectives and the Semester Project

The central focus of the semester is the design, execution, and presentation of an original research study.

• Elevated Methodology: Students advance from basic measurement and skills toward designing a full-scale study from start to finish. This includes designing the process, collecting data, analyzing results, and interpreting meaning.

• Statistical Interpretation: Interpretation goes beyond numerical formulas; it involves extracting meaning from sample results and extrapolating those findings to the broader population.

• Study Parameters:

  • Data Collection: Projects must be survey-based.

  • Incentives: No incentives (such as candy or vouchers) can be offered to participants.

  • Topic Selection: Students have freedom in choosing topics, ranging from social, clinical, and cognitive areas to sports, health, and developmental psychology.

  • Sampling: Participants are often San Jose State University students, providing a unique opportunity to study individuals from Silicon Valley or conduct comparative research with peer institutions across the United States.

Assessment and Grading Structures

There are no midterms or final examinations in this class. Evaluation is based on gradual development and mastery of concepts through low-stakes testing and a tiered project submission system.

• Quizzes:

  • Points: $20$ points per quiz.

  • Structure: Typically $10$ to $20$ questions.

  • Attempts: Students are allowed $3$ attempts per quiz, with the highest score being recorded.

  • Format: Open-note and no time limit. Questions are often context-specific to assess comprehension of nominal vs. ordinal variables or qualitative vs. quantitative data.

• Participation Tasks: These are primarily housing-based within lecture sessions. Each module includes participation work worth up to $10$ points.

• Lab Activities: These are hands-on tasks completed during lab sections. The goal is to start and potentially complete these activities during the scheduled lab time.

• Final Paper Milestones:

  • Module 1: Introduction Draft.

  • Module 2: Methods (Design and measurement).

  • Module 3: Results (Analysis and data cleaning).

  • Module 4: Discussion (Connecting findings back to literature).

  • Module 5: Final Paper (A polished, APA-formatted compilation of all revised sections).

Attendance and Late Work Policies

• Attendance: Lecture attendance is not strictly required, but participation points are earned during these sessions. Lab attendance is crucial for group coordination and accessing in-person instructor support.

• The 48-Hour Grace Period: All assignments have a built-in $48$-hour grace period after the Friday deadline. No justification is needed to use this time. If an assignment is submitted within this window, any automatic late markers on Canvas will be removed manually by the instructor.

• Penalties: Submissions following the grace period incur a $-10\%$ penalty per day. After $10$ days, no points remain for the assignment.

• Revisions: On a case-by-case basis, students may revise and resubmit assignments for additional points. This must be done within one week after grades are released.

Artificial Intelligence (AI) and Academic Integrity Policies

In accordance with SJSU policy, generative AI tools are generally prohibited for writing assignments unless explicitly stated in the syllabus.

• Rationale: The goal of the course is to train students to narrow general observations into researchable questions; AI should not be the primary generator of these ideas.

• Permissible Tools: Grammarly (legacy features), Zotero (reference organization), and Litmask (used with Zotero) are allowable for refining and organizing work.

• Prohibited Tools: Generative writing tools like ChatGPT, QuillBot, and Wordtune are not allowed.

• Reporting: Potential misuse of AI or copyright violations (e.g., feeding course materials into a device) are reported to the Office of CED (Student Division).

• Disclosure: If an allowed tool is used, it must be cited with a brief explanation of how it assisted the writing process.

Course Materials and Technological Resources

• Textbook: A free, open-source textbook is provided via the syllabus and Canvas. No purchase is necessary. Readings generally follow a chapter-per-week schedule (e.g., Chapter 1 in Week 2, Chapter 2 in Week 2, Chapter 3 in Week 3).

• Software:

  • SPSS: The primary statistical software for running analyses.

  • Qualtrics: Used for survey design and data collection.

• Hardware: Computer access is mandatory. Students may use the desktops in the lab (Room 236 or 136) or borrow a laptop from the library.

Laboratory Sections and Group Dynamics

• Groups: Labs involve working in teams of $3$ to $5$ peers.

• Collaboration: While students design a study together (focusing on a shared theory or construct, like attachment styles or social development), all drafts and final papers are completed and submitted individually.

• Swapping Sections: Students interested in switching lab sections (e.g., from Monday to Wednesday) should coordinate with the instructor by the end of the second week rather than dropping the course, as waitlisted students may take the vacant spot.

Instructor Background and Philosophy

Ankit Lee Gagne is a researcher and educator with a passion for psychology and systemic reform.

• Identity and Pronunciation: First name is pronounced Ankit (accent on the first syllable). Sur-name is Gagne (Lee Gagne using Spanish pronunciation). Pronouns are They/Them in English and É/Le in Spanish.

• Academic Journey:

  • Undergraduate: Studied Psychology and Gender Studies at UCLA. Conducted fellowships in clinical labs focusing on relationship science (notable influences: Dr. Benjamin Karney, Dr. Thomas Bradbury, and Dr. Lisa Neff).

  • Graduate: Holds a Master of Science ($MS$) in Developmental Psychology from the University of Utah. The $MS$ designation signifies a focus on quantitative research (numbers and statistics).

• Current Research and Interests: Specialized in gender and sexual identity development, minority health disparities, and prison education. Currently works as a data analyst for a parole lab and prison education program, focusing on transformative justice.

• Pedagogical Values:

  • Cultural Buffet vs. Melting Pot: Favoring language and identity immersion over assimilation.

  • Care Carryover: Investigating the lack of support for students after they graduate from high-pressure charter schools.

  • Academia for Survival: Using education as a path toward healing and personal advancement without succumbing to simple meritocracy.