**Research Integrity and Open Science II (PSYC124)** **Overview** How do we determine what is true in science? How do we know which theories are well supported by evidence and which ones are not? How can we tell if researchers are trying to pull the wool over our eyes? The module focuses on the research process, and in particular, learning how to spot and avoid questionable research practices, in favour of practices that are open, transparent and reproducible. The course builds on PSYC123 and considers some of the problems faced by researchers (e.g., bias, flexibility in reporting outcomes), and how we can assess research findings in the face of such problems. The module will show how scientific practices in the field have changed rapidly in recent years, with renewed interested in openness and transparency. Students will focus on a range of problems that impact our interpretation of research findings (false- positive results, questionable research practices, fraud), and develop an understanding of tools that can help overcome and prevent these issues from arising (pre-registration of studies, sharing of data, meta-analyses). This course was developed jointly by [Dr. Dermot Lynott][1] and [Dr. Marina Bazhydai][2], and first delivered at Lancaster University in 2020-2021. It is suitable for delivery at First Year undergraduate level. **A note for Instructors** Lectures are about 50 minutes in duration, and the labs can be completed in around 50 minutes, although some will take a bit longer. There is some flexibility in the order that topics can be delivered. For example, Meta-Analysis is a standalone topic that could be moved later in the course. For instructors, answer sheets are available for the lab exercises. Please just email if you'd like a copy (dermot.lynott@mu.ie). **Files** PSYC124 Syllabus - https://osf.io/4jmyq/ **Lectures** 1 - [Introduction to False positive psychology][3] (lab: https://osf.io/yrk4q/) 2 - [Questionable Research Practices][4] (Lab: https://osf.io/urg4e/) 3 - [Biases and incentive structures][5] (Lab: https://osf.io/xzp4j/) [Combined Lecture 2 and 3][6] 4 - [Introduction to meta-analysis][7] (Lab: https://osf.io/96t7a/) 5 - [Scientific Fraud][8] (Lab: https://osf.io/he593/ ) 6 - [Errors and error detection][9] (Lab: https://osf.io/dbpqr/) 7 - [Principles of Open Data Sharing][10] (Lab: https://osf.io/crvtj/) 8 - [Spotlight on Developmental Science][11] (Lab: https://osf.io/nu5kz/) [1]: http://osf.io/hkw4x [2]: https://osf.io/2hn9y/ [3]: https://osf.io/d8nze/ [4]: https://osf.io/qbsh3/ [5]: https://osf.io/vnpzk/ [6]: https://osf.io/54edx/ [7]: https://osf.io/syq2e/ [8]: https://osf.io/pc96s/ [9]: https://osf.io/qz3c4/ [10]: https://osf.io/hpfb6/ [11]: https://osf.io/h4nfu/