With a reliable internet connection comes access to the enormous World Wide Web. Being so large, we rely on tools like Google to search and filter all this information. Additional filters can be found in sites like Wikipedia, offering a library style access to curated knowledge, but it too is enormous. In more recent years, open online courses has rapidly become a highly popular method of gaining easy access to curated, high quality, as well as pre-packaged knowledge. A particularly popular variety is the Massive Open Online Course, or MOOC, which are found on platforms like Coursera and edX. The promise – global and free access to high quality education – has often been applauded. Some have heralded the age of the MOOC as the death of campus based teaching. Others are more critical, often citing the high drop-out rates as a sign of failure, or argue that MOOCs do not or cannot foster ‘real’ learning (e.g., Zemsky, 2014; Pope, 2014). Continue reading
R is a statistical programming language whose popularity is quickly overtaking SPSS and other “traditional” point-and-click software packages (Muenchen, 2015). But why would anyone use a programming language, instead of point-and-click applications, for data analysis? An important reason is that data analysis rarely consists of simply running a statistical test. Instead, many small steps, such as cleaning and visualizing data, are usually repeated many times, and computers are much faster at doing repetitive tasks than humans are. Using a point-and-click interface for these “data cleaning” operations is laborious and unnecessarily slow: Continue reading
Last summer saw the publication of the most important work in psychology in decades: the Reproducibility Project (Open Science Collaboration, 2015; see here and here for context). It stirred up the community, resulting in many constructive discussions but also in verbally violent disagreement. What unites all parties, however, is the call for more transparency and openness in research.
Eric-Jan “EJ” Wagenmakers has argued for pre-registration of research (Wagenmakers et al., 2012; see also here) and direct replications (e.g., Boekel et al., 2015; Wagenmakers et al., 2015), for a clearer demarcation of exploratory and confirmatory research (de Groot, 1954/2013), and for a change in the way we analyze our data (Wagenmakers et al., 2011; Wagenmakers et al., in press). Continue reading
Registered Reports (RRs) are a new publishing format pioneered by the journal Cortex (Chambers 2013). This publication format emphasises the process of rigorous research, rather than the results, in an attempt to avoid questionable research practices such as p-hacking and HARK-ing, which ultimately reduce the reproducibility of research and contribute to publication bias in cognitive science (Chambers et al. 2014). A recent JEPS post by Dablander (2016) and JEPS’ own editorial for adopting RRs (King et al. 2016) have given a detailed explanation of the RR process. However, you may have thought that publishing a RR is reserved for only senior scientists, and is not a viable option for a postgraduate student. In fact, 5 out of 6 of the first RRs published by Cortex have had post-graduate students as authors, and publishing by RR offers postgraduates and early career researchers many unique benefits. Continue reading
When you think of a smoker, it is likely that you are imagining someone who goes through a pack of cigarettes per day and can often be found running to the nearest store to maintain their supply. Perhaps you amuse yourself watching your friend conspicuously leaving work to stand outside and huddle around their cigarette in the rain. Your assumption would often be correct as the majority of smokers are dependent on nicotine and smoke throughout the day. These daily smokers account for approximately 89% of current smokers in the UK (Herbec, Brown and West 2014), and between 67%-75% of smokers in the USA (Coggins, Murrelle and Carchman 2009). However, what about this missing proportion of smokers? Continue reading
Programming is a skill that all psychology students should learn. I can think of so many reasons on why, including automating boring stuff, and practicing problem solving skills through learning to code and programming. In this post I will focus on two more immediate ways that may be relevant for a Psychology student, particularly during data collection and data analysis. For a more elaborated discussion on the topic read the post on my personal blog: Every Psychologist Should Learn Programming.
Here is what we will do in this post:
- Basic Python by example (i.e., a t-test for paired samples)
- Program a Flanker task using the Python library Expyriment
- Visualise and analyse data Continue reading
Does the mention of the word “statistics” strike fear into your heart and send shivers down your spine? The results section of your thesis seeming like that dark place one should avoid at all cost? Heteroscedasticity gives you nightmares? You dread having to explain to someone what degrees of freedom are? What is the point of using ANOVA if we can do a series of t-tests? If any of these remind you of the pain of understanding statistics, or the dread of how much more lies ahead during your studies, when all you really want is someone to explain it in a humanly understandable way—look no further. Quite a few fellow students might tell you “You should go and look at Andy Field’s books. Now, at least, I understand stats”. The “Discovering statistics using …” is a gentle, student friendly introduction to statistics. Principles are introduced at a slow pace, with plenty of workable examples so that anyone with basic maths skills will be able to digest it. Now add a lens of humor and sarcasm that will have you giggling about statistics in no time! Continue reading
There used to be a time when students could attend classes at their university or in their vicinity – and that was it. Lately, the geospatial restriction has vanished with the introduction of massive open online courses (MOOC’s). This format of online courses are part of the “open education” idea, offering everyone with an internet connection an opportunity to participate in various courses, presented by more and less known institutions and universities. The concept is more or less similar for all courses: anyone can join, and lectures are available in form of a video and as lecture notes. During the course, whether it is a fixed-date or self-paced (as in you deciding when to complete tasks), you will need to take quizzes, exams, and/or written projects if you wish to complete the course. In less than 10 years, this idea has grown to include millions of users, hundreds of countries and more than a dozen universities around the world, while continuing to grow. Continue reading
For more than six years, JEPS has been publishing student research, both in the form of classic Research Articles as well as Literature Reviews. As of April 2016, JEPS offers another publishing format: Registered Reports. In this blog post we explain what Registered Reports are, why they could be interesting for you as a student, and how the review process works. Continue reading
Last summer saw the publication of a monumental piece of work: the reproducibility project (Open Science Collaboration, 2015). In a huge community effort, over 250 researchers directly replicated 100 experiments initially conducted in 2008. Only 39% of the replications were significant at the 5% level. Average effect size estimates were halved. The study design itself—conducting direct replications on a large scale—as well as its outcome are game-changing to the way we view our discipline, but students might wonder: what game were we playing before, and how did we get here? Continue reading