Overview

PSYC 6013: Advanced Statistics in Psychology, is a graduate-level course designed to equip students with advanced statistical skills necessary for conducting research in psychology. Covering a range of topics from statistical theory to data analysis and the application of statistical software, it is a core requirement for students pursuing a Master's degree in Psychology.

Target Students

The course is primarily targeted at graduate students who have a foundational understanding of statistics and research methods. These students come from diverse academic backgrounds and have varying levels of confidence and proficiency in statistical analysis. The course aims to enhance their statistical reasoning, critical thinking, and practical application skills to prepare them for advanced research roles.

Use of Humour and Creativity: To engage students and reduce statistics anxiety, I introduced a meme competition related to course content. This activity served as an icebreaker, stimulated interest in the subject, and set a positive tone for the course. The enthusiastic participation and positive feedback from students highlighted the effectiveness of this approach.

Multimedia Resources and Online Quizzes: Incorporating multimedia resources such as YouTube videos and online quizzes has significantly enhanced student engagement and learning. These tools cater to various learning styles and provide students with flexible, accessible means to review and understand course material.

Flipped Classrooms and Group Assignments: Flipped classrooms and group assignments foster collaboration and active learning. By presenting in groups and participating in discussions, students develop a deeper understanding of statistical concepts and improve their communication and teamwork skills.

Mini-Conferences and Guest Lectures: Transforming the Research Proposal Presentations into Mini-Conferences, and inviting guest lecturers, has provided students with practical insights and motivation. These activities mimic real-life academic and professional settings, preparing students for future roles in research and academia.

Note: During the 2020-2021 Academic year, the course was offered online via remote emergency teaching until 2022-2023. In that way, I customised my lessons to suit the online environment using Zoom to facilitate collaborative activities such as "think,group,share" and Flipped Classrooms via breakout rooms. 

See more on these innovative Strategies in Evidence of Teaching Impact. 

• Student Feedback and Performance: The success of my teaching methods is evidenced by positive feedback from my students as well as their improved performance. Students appreciated the interactive and supportive learning environment, and the course consistently achieved high pass rates with many students earning grade As.

• Professional Growth and Adaptation: Over the years, I have continuously adapted my teaching practices to meet the evolving needs of my students. Participation in professional development programmes and consultations with colleagues have enriched my teaching approach, ensuring that it remains relevant and effective.

• Commitment to Excellence: My unwavering dedication to student success and continuous improvement in teaching practices equip my students into the 21st century skills. My passion for empowering students with statistical literacy and research skills reflects my enduring contributions to the student body of the UWI and the world at large. 

The bar chart displaying the average final marks for each academic year from 2019/2020 to 2023/2024 provides several key insights:

1. Highest Average in 2020/2021:

   • The academic year 2020/2021 has the highest average final marks among the years presented. This could be due to a variety of factors, such as changes in assessment methods, the shift to virtual learning, or increased support for students during the pandemic.

2. Slight Decline in 2021/2022:

   • There is a noticeable drop in the average final marks in 2021/2022. This could be attributed to the ongoing adjustments to virtual learning environments or potential changes in course difficulty or assessment criteria.

3. Recovery in 2022/2023 and 2023/2024:

   • The average marks begin to recover in 2022/2023 and further improve in 2023/2024. This suggests that my students and I appeared to adapt better to my improved teaching and learning approaches, included more summative assessments and hands-on, interaction with datasets, leading to improved performance.

4. Variability in Averages:

   • The fluctuations in the average final marks over the years indicate that various external and internal factors likely influenced student performance. These factors could include changes in my instructional methods, variations in student cohorts, modifications in assessment techniques, and broader socio-economic influences.

5. General Performance Trends:

   • Despite the fluctuations, the overall average marks remain relatively high, suggesting that students generally performed well across the years. This consistency indicates a stable academic environment with my effective teaching and learning practices.

Overall, the bar chart reflects how different academic years have unique challenges and strengths, impacting student performance in the PSYC 6013 course. For more on these insights and how I use these metrics to measure effectiveness, see Metrics for Effective Teaching. 

Impact on my Teaching Practice 

• To engage students and reduce statistics anxiety, I introduced a meme competition related to course content. This activity served as an icebreaker, stimulated interest in the subject, and set a positive tone for the course. The enthusiastic participation and positive feedback from students highlighted the effectiveness of this approach.

• Moreover, by incorporating multimedia resources such as YouTube videos and online quizzes, this has significantly enhanced student engagement and learning. These tools catered to various learning styles and provided students with flexible, accessible means to review and understand course material.

• The inclusion of flipped classrooms and group assignments fostered collaboration and active learning. By presenting in groups and participating in discussions, students developed a deeper understanding of statistical concepts and improved their communication and teamwork skills.

• Additionally, transforming the Research Proposal Presentations into Mini-Conferences, and inviting guest lecturers, has provided students with practical insights and motivation. These activities mimic real-life academic and professional settings, preparing students for future roles in research and academia.

Student-Centered Learning through Collaboration and Mentorship  

• My teaching philosophy is deeply rooted in student-centered learning, recognizing my role as a facilitator and mentor. I strive to create an inclusive, dynamic, and supportive learning environment where students feel confident in their abilities to understand and apply statistical concepts.

• I also employ innovative strategies such as multimedia resources, online quizzes, and flipped classrooms to enhance student comprehension and participation. My teaching methods are continuously evaluated and refined through reflective lenses and tools like SWOT analysis and course reviews, reflecting my dedication to delivering high-quality education.

• Moreover, my commitment to growth and excellence is evidenced by my proactive approach to soliciting feedback from both students and colleagues, as well as my active participation in professional development activities such as the Certificate in University Teaching and Learning (CUTL) programme, as well as Teaching with AI training from Course Hero. See Professional Development and Training for more on these.