If you are in the world of research, there is no doubt that you haven’t yet heard of R and R Studio.
These programming languages are emerging as some of the most popular tools in data science for data exploration (with graphics) and statistical computing. I’m thinking you’ve come to this page because your time to learn R is now!
Some people can be totally freaked by the idea of coding, but programs such as R help science become more transparent and actually help you to keep track of your analysis process.
Why learn R?
Having all your data processes written in code from the very first step, means if anything goes wrong at any stage, you’ll always have the script of exactly what you did.
If at some stage some sorted or edited data files go missing, you can easily re-run your code to create everything again from scratch. Compared to working with data in excel – if your spreadsheet is suddenly deleted – there’s no way you’d be able to create means, delete columns and add rows from the raw data again, simply with one keyboard shortcut.
You can also see exactly what you did at every step of your analyses. If you ever get six months down the track and wonder why a certain participants’ data looks like this and not that, you’ll likely have written exactly what transformations you did to it in your code (aka script).
Using code also helps to be open about data analysis, and sharing it can lead to more reproducible research and greater scientific integrity! Research techniques can be shared, discussed and tweaked by multiple scientists across different disciplines to produce better quality research outcomes.
For someone like me (who spent an entire undergraduate degree working with SPSS), it didn’t take long to get hooked on programming in R.
The neuroscience lab that I work in is particularly obsessed with R as a platform for statistical analyses of experiments and creating beautiful graphs for theses and scientific journal article submissions.
It’s not hard to see why!
Before you learn R: Get R and R Studio
The best part about R is that it is all free and open source. Open source refers to programs that are publicly accessible and publicly modifiable – and this also means that learning to code in R also comes with a huge community of people interested in making it more practical, useful and accessible in the widest range of contexts possible.
R is the programming language itself, while R Studio provides an interface to work with R.
When you need some datasets to play around with, look no further then the Tidy Tuesday repository on Github. If you don’t know what a repository is, its just a place to upload code online! It simply means that things can be shared around.
Tidy Tuesdays is run by the R for Data Science community – and involves weekly uploads of new datasets to be explored. You’ll get a fancy new dataset to explore, introductions on its contents and some example code as to how others have played around with it!
As I said before, R is a open-source program, and therefore has a huge community of people behind it, always trying to make it better and share any struggles they’ve faced.
You will be able to find heaps of resources on how to learn R by jumping on to twitter and doing a quick search! It is the after all, the preferred social media of researchers and scientists, so it’s where you’ll find lots of discussion and sharing!
This is by no means an extensive compilation of free online resources to learn R. The community of researchers on R are only a google away, so don’t be scared to delve into the world of coding.
But mindfulness can do more than just make you relaxed.
Those calming few silent moments alone could actually make you a better learner, more focused and prevent age-related cognitive decline.
The Rise of Mindfulness
The sudden interest in meditation and mindfulness has been encouraged largely by the growing body of scientific evidence suggesting its benefits for overall wellbeing, particularly for coping with stress and anxiety management.
In the year 2000, only 10 articles about mindfulness were published in scientific journals. Since then, this number has been steadily increasing every year.
In 2016, a total of 667 articles were published.
Nowadays, apps like Headspace are making mindfulness techniques accessible to the everyday individual.
You don’t need classes and you don’t need weekend retreats anymore. These techniques are easily accessible to anyone who can jump onto the internet.
Even Spotify has series of podcasts dedicated to guided meditations (my favourite is Meditation Minis!).
You know that meditation and mindfulness can promote relaxation and lower your stress levels.
But here are 5 reasons you need to start using mindfulness meditation (other than relaxation) that you probably don’t know!
5 Benefits of Mindfulness Beyond Relaxation
1. Improve Your Attention
This study by van der Hurk and Gielen looked at experienced mindfulness meditators to determine whether the practice was related to increases in attentional ability.
Experienced meditators and a group of non-meditators were tested on the Attention Network Task.
This test measures someone’s ability to react and orient themselves to different targets on a screen, and correctly respond (usually by pressing different keyboard buttons when cued).
The researchers found that those with mindfulness experience were significantly better at orienting their attention (moving it from one thing to another).
This means that meditators were better at disengaging from one task, to quickly move to another target task when cued.
They concluded that mindfulness meditation develops a more flexible attention network, as a typical session usually involves shifting of attention from one thing to the next, successively.
But these were experienced mindfulness meditators… can these effects be mirrored in shorter time frames?
As the following studies show, improvements can also be immediate, with benefits following only short sessions of mindfulness.
This study by Ainsworth and other researchers looked at two kinds of meditation: focused attention (where people focus their mind on one thing, usually the breath) or open-monitoring (where people ‘open up’ their attentional circle to expand their observed sensations).
After either meditation session, or a purely ‘relaxation session,’ people were also tested on the Attention Network Test.
People who participated in the 3 hours of mindfulness practice – both focused attention and open-monitoring – performed better on the attention task when compared to a group that only engaged in a purely ‘relaxation’.
Improvements in performance occurred even when people could not report feeling any differences themselves.
So you’re ready to learn how to read a scientific journal article? You’re ready to tackle the big bad world of science? You might want to read the latest research and get your head around rapidly evolving scientific developments.
Or, you might also just be here to get on top of your university assignments.
As I mentioned in my essay writing tips, it can be super daunting jumping into your first year at university and being told you can no longer use any old websites as references in your essays.
You have to use scientific journal articles (or scientific literature) to back up statements that you make.
You need to learn – very quickly! – how to navigate and understand a scientific journal article.
For some reason though, this is never taught in undergraduate courses – you are instead just thrown in the deep end.
And on top of this, you will probably have to start writing up your research reports in a similar format (if you’re in a scientific discipline).
So today, let’s talk about how to read a scientific journal article, section by section.
What is a Journal Article?
A scientific journal article is a piece of writing by a group of scientists, which tells you about specific experiments or research they have completed.
These articles can be found in Google Scholar, or any other scientific database that your discipline likes most (like PubMed or ScienceDirect).
Journal articles undergo a rigorous (and very lengthy!) submission process before being published. Articles are only accepted into a journal when they met specific standards and pass a peer-review process (where other scientists critique the work and make comments/suggestions).
Because of this process, they are one of the most highly regarded sources of information.
Journal Articles can take a few forms.
A typical research article will explain and document a particular experiment (or series of experiments), in a way that any scientist can replicate it. There is usually an introduction to the experiment (with all background information), a very detailed procedure, results of the experiment, and what it means for outside in the real world.
A review article is a recap of previously completed research, and doesn’t include a new experiment in itself. These articles collate and organise old research in the aim of answering a specific research question. They often include an introduction to the problem, and multiple paragraphs with subheadings to explore different aspects of the problem.
Case Studies look over one particular instance of an event, disease, or person in order to better understand and document one specific phenomenon.
Typically, you will be most likely met with experiment or review articles.
As a Psychology and Cognitive Neuroscience major, I am most familiar with the format of articles in these fields, but there is typically a standard structure in which most articles follows: abstract, introduction, method, results and discussion.
I will take you through each section so that next time, you know exactly how to read a scientific journal article.
So what’s included in each section?
How to read a scientific journal article: section-by-section.
Research articles can sometimes be very long – so it’s important to know what you’re looking for and what you need when you are researching.
Each section of the research article will tell you something specific about the work, and sometimes you won’t need to read all of it, so it’s important that you know where to look.
The abstract sits at the top of the article and will give you a run down of the entire paper in less than 300 words.
It is basically a very condensed version of the entire research article, with a sentence summarising each sub-section of the report. It will give you a super speedy overview of the background of the project, the method and all of the results.
If you are searching on Google Scholar or other databases, this is the part of the research article that you will be able to read before downloading the whole thing.
It gives you an insight into the rest of the article.
Reading the abstract will let you know whether the research article has what you are looking for, and whether a full-length read will be worth your time.
If you are unfamiliar with the topic of the research article, the introduction is where you need to be.
These first few paragraphs will give you background information about the experiment.
Here, the researchers tell you why they decided to create their experiment.
The introduction often explains other research work, in order to create a basis for the current experiment. They talk about what has previously been found, and what is missing from knowledge.
This section will also likely explain why the research is important to society – how would the world benefit from this experiment?
It also often gives the rationale for the way in which the experiment was conducted.
The introduction should be written in a way that seems almost like the first chapter of a novel, setting up the scenes and the context for what is to come.
After reading this section, you will have a better understanding of the larger field in which this research is based, but you can also use other work that the researcher has referenced here to expand your knowledge.
This (often short) paragraph let’s you know who was involved in the study, how many, where they were recruited, their ages, gender, and any other criteria that was important for the study.
How participants are included/excluded is very important to the results, and heavily influences what conclusions and generalisations can be drawn from the research.
Participant numbers are also very important in making sure that you can make larger, over-arching conclusions from research.
Materials and Design
This section is the recipe for the experiment!
It lets you know what materials were used (questionnaires, EEG, computer paradigms) and what you might need to replicate the experiment.
It is important that scientists document exactly every little detail of their experiments, in order for others to critically evaluate their work.
While scientific journal articles are rigorously reviewed before publication, some methods or ways of working may be more ‘correct’ than others.
It is important for this information to be shared, so that people can make informed decisions about the results.
It also makes it easier for other scientists to build on past experiments, or tweak certain aspects to answer new questions.
Here is the exact step-by-step for the experiment.
This is what the researchers did, and when, and how far apart, and on what day, and with which piece of equipment.
This part will be important for you if you’re looking to replicate the experiment for yourself.
It’ll also be the place to be if you need to critically evlauate the experiment (say, for an assignment) as you’ll need to pick apart exactly what was done.
If you’re reading an article for the results, this isn’t the section you need.
Finally, something new and exciting!
The results section gives you the numbers.
After the scientists ran all of their experiments, and crunched the numbers, this is what they got. It might also show you some pretty pictures (figures and tables).
It does little to explain why, and simply presents all the statistics and calculations that were done. If you like maths, it’s where you want to be.
If you are unfamiliar with statistics, this section can be very overwhelming.
It contains the results of t-tests, ANOVAs, means, standard deviations, effect sizes and p-values.
If you want to learn more about statistics in science, have a look at my blog post here.
Otherwise for now, just know that all the heavy numbers are here. While you might need them to break down the experiment and truly assess it’s validity, often times you can be safe just skimming this area, if you are simply looking for the meaning behind it all!
If you are just starting your psychology degree, rest assured that as you continue through, you will become more familiar with these terms.
The results section often includes figures.
Figures are diagrams, graphs or schematics of the results or are sometimes also included in the methods section to better explain how to run a procedure.
A figure should convey a maximal amount of information using the smallest amount of ink, and give readers an opportunity to see the data in a different way.
Figures are often referred to in the paragraphs, but allow researchers to show their results in a more straight-forward way.
Tables may also appear here!
These allow researchers to present a large array of numbers, percentages or measurements in as few lines as possible.
They are often included as additional information as they show means, observations or values from a larger number of individuals or show all results when only a few are meaningful or important.
In many cases, these are ‘read more’ options, and not compulsory to forming a basic understanding the research article as a whole.
Ahhh, finally the good stuff!
The discussion is where it’s at.
Time to learn what the results actually were (aside from the maths), and get a deeper understanding of what they mean for the world outside.
The discussion section usually starts with an overview of the results (in normal non-number talk).
“The study showed that this was higher than that… these people scored better than this… this chemical was better at doing that….”
The researchers will explain whether their findings are similar or in opposition to previous research that has been conducted.
If their findings are contrasting, they can often try to explain why this might be the case.
Whether consistent or contrasting results are encountered, researchers will explain what these mean for the wider community.
Do the results have negative or positive impacts… and what should be done because of the findings?
For example this might include: how do the results change any of our previous beliefs about the world? How should they change treatment choices? How should they direct government funding? How do they change health recommendations?
Each study may have numerous effects on the world outside the lab.
In this section, researchers will also explain any short-comings in their experiment. Nothing is ever perfect. Things can always be improved.
Researchers may also give recommendations for future research and questions still unanswered. They could also suggest ways in which their study could be built upon.
The discussion will also conclude with a sweet little paragraph summarising the whole article. This last paragraph will sum up exactly what the researchers want you to take away from their work.
As I previously mentioned, scientists may reference other scientists when introducing you to their project, or when attempting to explain their results.
An experiment may also have used questionnaires, paradigms or equipment created by other people (that requires referencing!).
That is why all scientific articles will conclude with a reference list. This gives readers easy access to other sources of information, which they can fall down the rabbit hole with!
The scientific world is a constant state of iteration.
Developing new ideas and building upon old work involves the constant sharing of information, and by allowing people to explore every old idea and building block themselves, it is hoped that articles can spark new ideas in budding researchers.
If you haven’t, make sure to look at my referencing guide to learn the best way to create your own reference list for essays. It will make your assignment writing a breeze!
And that’s it! You’ve made it.
Now you know how to read a scientific journal article.
It can be at first be a tricky maze to tackle.
But as you continue on, you will find yourself becoming a more experienced explorer. You will very quickly develop a better understanding of which sections are important for you and your own research.
There is no doubt if you have ever Googled “best study techniques”, you will have been bombarded by people talking about active recall
But what does active recall actually mean? What is the testing effect? And how will it make you better at remembering stuff?
Today, let’s talk about the neuroscience of active recall.
What is active recall and the testing effect?
It is highly likely that someone on the internet (probably Ali Abdahl) has already told you to use active recall to enhance your exam grades.
Active recall is a process of learning.
Often, students like to re-read course materials, highlight or summarise class notes when preparing for exams.
However, none of these are truly effective ways to get material into your brain.
Active recall means asking yourself questions, testing yourself and prompting you to think about the concepts on your own.
Testing yourself encourages your brain to recall information from the dark corners of your mind.
And essentially, this process of testing allows you to practice exactly what you need to do in an exam, recall information.
Compare to other study methods…
Studies have shown time and time again that active recall leads to better learning and retention of information compared to any other study technique.
This review by Roediger and Butler, shows how researchers since 1909 have shown that active recall out-performs all other study methods.
Even Artistotle mentioned that “Exercise in repeatedly recalling a thing strengthens the memory.”
Six classic studies by Gates, Jones, Spitzer, Tulvig, Glover and Carrier and Pashler demonstrate how students (from school-aged to college) are able to perform better, recall more information and forget less by intermittent re-testing before a final exam.
They concluded that active recall provides a much better basis for remembering information than other forms of passive studying.
The students were split into two groups: one that re-read the cognitive psychology information after initial learning, and a second group that was tested on the material six different times (with feedback).
After this, a final test showed that students who were previously tested on the material scored significantly better than those who simply re-read the information.
On top of this, the researchers found that a person’s general working memory ability (how well you can hold information in your mind short-term) didn’t change the beneficial effects of active recall during study.
This study by Karpicke & Blunt examined students’ learning across three different study methods: re-reading, concept mapping and retrieval.
While those who produced concept maps did perform better than those who simply re-read their notes, students who used active recall methods performed up to 50% better in the final test! (Time to throw away your mind maps).
This study by Karpicke & Roediger showed that you can even get these benefits by testing yourself only on things you couldn’t initially recall correctly.
They taught college students lists of foreign word pairs.
Different groups participated in different re-test conditions. Some were re-tested on all word-pairs, whereas other students had words dropped from their subsequent practice tests when they were correctly recalled.
Interestingly, there wasn’t any difference between the different conditions.
Repeated studying of material didn’t improve performance later on.
So how does it work?
In 2015, Broek and other researchers reviewed studies of active recall to uncover how the testing effect actually helps to improve memory.
They found that active recall is thought to improve learning through several different mechanisms.
Firstly, testing yourself and retrieving information is thought to change semantic networks in your brain (connections between meaningful stored information).
By activating these pathways when testing yourself, you are strengthening their connections by creating additional associations (as you are re-thinking of this information in a new context).
On top of this, testing yourself can also promote more streamlined thinking.
Practicing to answer a certain question with a specific target response, allows other irrelevant information to be set aside (that time you talked with your class mate about how it would be funny if ethanol was created when we did anaerobic exercise? Gone! You don’t need that information for the exam).
Further, instead of the textbook or class notes ‘cueing’ your remembering of the content, you are practicing using the question as a cue for your brain to remember the information.
Exactly what you need to do in an exam!
Overall, it seems that active recall helps to strengthen memory representations (and get rid of irrelevant stuff!).
How to Use Active Recall: What you Should Do
Think about it, at the end of the day, you are studying for an exam. You are studying to retrieve answers from your brain when you are presented with a question.
You are not studying to retrieve answers from your brain while reading class notes.
Stop re-reading your notes. Get rid of your mind maps.
While you can still gain benefits from simply attempting to retrieve the information, feedback can further improve performance! Knowing what is right and wrong can help you to correct your responses or maintain ones that are already right.
Slowly increase time-lengths between testing.
Testing yourself every 30 minutes everyday will not necessarily improve the amount of exam information you retain.
The best way to use the testing effect is to first, check something is correctly ‘encoded’ (memorised) by testing yourself shortly after initial learning.
This might be a quiz after reading a textbook chapter.
Then, give yourself another test the next day.
After that, test again in another 3 days.
Studies show that consistent, shorter intervals between testing don’t actually further improve test performance. You can slowly give yourself longer and longer intervals between testing, and you will still see the benefits.
If I told you that the best thing you could do for your upcoming exams was to take a nap – you probably wouldn’t believe me, right?
You’ve heard it all before: the Cornell method, active recall, spaced repetition.
But sleep may be one of the most important things you need to add into your study schedule.
I can see you rolling your eyes – but seriously, you want to read this.
Anyone can tell you that you are likely to perform better if you are awake, alert and feeling great after a good night’s sleep.
But that’s not all.
Sleeping may actually be the difference between you remembering an answer or being lost for words on exam day.
Read more to learn why sleep is the best study technique.
How Sleep Improves Learning
Studies have shown that sleeping after periods of learning improves later test performance later on.
One of the earliest studies in this area, run in 1924, taught people a list of nonsense words (words that look and sound like English words but aren’t actually).
People were better at remembering the nonsense words when tested after sleeping, compared to those that stayed awake for the same length of time.
Even with just one hour of sleep, people could recall 7 nonsense words compared to 4.5 if they spent the same time awake.
This effect is increased as the time of sleep lengthens.
With an eight hour sleep opportunity after initial learning, an average of 5.6 words were correctly remembered.
However, if staying awake for eight hours after learning, it was rare that even one was recalled correctly.
That’s a big difference!
These first results have been replicated again and again in sleep research.
This study taught native English speakers a list of 24 German words and found that those who slept immediately after learning could remember more words 48 hours later when compared to those who were sleep-deprived.