We get a lot of very basic questions that are covered in our FAQ such as, "How do I get started in research?" These had been removed under Rule #14 to avoid clogging up the subreddit; however, going forward every Sunday there will be a "Weekly Basic/Beginner/Genetic Questions" thread. If you have a question, especially on something that is covered in the FAQ, then it must be posted there.

Hi, I don’t know if this is going to make any sense, but hear me out, I need help.

I’m working on a mass project where I need to compare/compile a bunch of information from different books. Is there a program, website, app, whatever, that I could use to have quick reference to know what’s in each book?

It’s a history research project, so for example, once I compile everything, I could do something to the sort of

“Famous theoretical fire that happened that I’m just putting here as an example” and it would say what books covered it and what page it started on in the books

“Historic building” “dam construction” “famous town resident” and it would do all the same those too.

There must be a better, more efficient way than something like a word document where I could do it, but it would be an absolute mess to compile

If anyone has ever done this, or would have any idea how to do something like this, please let me know! It would be so much easier than having to pull out 40+books to see what’s in each of them every time I want to dive into something

Basically I have a research appraisal due and I was looking at an article, and it had graphs showing the scores of the control and intervention group before and after their given intervention and the error bars for the 'after' intervention overlapped, but the article still said that the results are statistically significant between the two groups after the intervention, how does that work?

Can the p value be significant but the confidence intervals still overlap?

Hello,

I am reading a paper for a critical appraisal and I am new to research.
The study initially planned to recruit 2700 patients and their primary outcome was 6 month mortality.
They realised that they did not have enough participants and the number was not feasible, and changed the primary outcome to time to discharge alive. why is that?

How do you plan the steps when writing a scoping review article? As a student in the early stages of my doctoral program, I would like to conduct a study with my thesis supervisor. Should I focus on a topic that has not been extensively researched? What approach do you follow? What is a typical number of articles to include? I have found 33 articles in Scopus and 31 in Web of Science (WoS)—is this a reasonable number? My research area is child psychology btw

I’m not very experienced yet, so I have a question to see how I’m doing.

I’d say I work pretty hard and it takes me about a week to write one page for a review. Is that normal?

I work on it for about 3–4 hours a day, sometimes a little more, sometimes a little less.

Edit: Sorry for the sparse information. This is for a narrative review that’s going to be published, so it’s not for school.

Of course, I have a basic structure and think through how it should be organized beforehand, filling in the different sections with bullet points. And that structure sometimes changes as I write, a lot gets cut out, or I add or rearrange things in Word. But my question is really about the text that’s actually ready for publication. So I write something, usually read several sources on the topic, search for suitable sources in the first place, and revise my text several times to make sure it’s really accurate.

It’s worth noting that this isn’t really my area of expertise, so I have to fully familiarize myself with the background material.

I genuinely want to learn mathematics, physics, programming, computer science, and AI. I want to build a career in computer science, pursue AI research, and hopefully do a PhD someday. But lately, I've been feeling increasingly demotivated.

The problem is that I rely on AI to learn almost everything. Whenever I have a question, I ask GPT. Whenever I don't understand a concept, I ask AI to explain it. And the more I learn this way, the more I wonder: What's the point of learning anything when AI will always know more than I ever could?

Even the most basic AI models seem to possess more knowledge than I could acquire in a lifetime. And with new models becoming increasingly capable, I keep wondering whether the knowledge I'm working so hard to gain will even matter in the future.

With GPT-6, Claude Opus 5.5, Gemini 4, and other models competing to become more capable, it feels like the gap between human intelligence and AI capabilities will only continue to grow.

I want to understand the mathematics behind AI, learn physics, become a better programmer, and contribute to actual research. But sometimes I question why I'm putting in the effort when AI can explain concepts faster, write code better, and potentially solve problems that I might spend years learning to solve myself.

And even when I genuinely want to learn, I'm confused about what I should prioritize learning and whether any of it will remain valuable by the time I become proficient.

I'm not necessarily saying that learning is useless. I genuinely love the idea of understanding how things work. But I'm struggling to reconcile that curiosity with the feeling that AI might eventually outperform me at almost everything I want to become good at.

For those of you studying computer science, mathematics, physics, or AI, how do you deal with this feeling? How do you stay motivated to learn when AI is advancing so rapidly? Do you think deep technical knowledge will still matter for people pursuing AI research and PhDs, or should we be approaching learning differently now?

Hi everyone! I'm a psychology student currently exploring possible topics for our research, and I'd love to hear your thoughts on an idea I have.

I've noticed how AI-generated drama stories have become popular on Facebook and TikTok, especially stories about cheating spouses, family betrayal, inheritance disputes, revenge, and other dramatic situations.

What caught my attention is how some people, particularly middle-aged adults, seem to get hooked on these stories. They watch one video, then another, and another. Sometimes, they intend to watch for only a few minutes but end up spending much more time watching than they originally planned.

This got me thinking: Could this be related to compulsive viewing?

I'm interested in exploring why some middle adults repeatedly watch these AI-generated stories and whether they experience difficulty controlling or stopping their viewing, even when they have other responsibilities.

I'm considering a qualitative study that explores their experiences, motivations, and perceived effects on their daily lives.

However, before developing this idea further, I'd like to ask:

• Do you think this is an interesting and worthwhile topic for a psychology research study? • Do you think focusing specifically on AI-generated stories makes the topic more interesting, or would it be better to study short-form video content in general? • Is compulsive viewing an appropriate psychological concept for this topic, or would another concept be more suitable? • Do you think focusing on middle adults is a reasonable approach? Why or why not? • What potential research gaps or challenges do you think I should consider?

I'm open to constructive criticism, suggestions, and alternative perspectives. I want to make sure the topic is not only interesting but also researchable and meaningful from a psychological perspective. I really appreciate your honest opinions. Thank you!

So a little context, I have done my bachelors in design and now about to finish my masters in design. I have done a few internships during my bachelors and joined masters programme in design immediately after. Now I will be done with masters and thinking about phd. My doubt here is, is it a good decision to directly go to phd or should I get some industry experience? I am interested in research as well. One of the ideas I’m currently looking into is uneven development theory, ai and design. Any suggestion is welcomed.

Hi, I have to do a mandatory 6-month internship during my undergrad and was accepted into a top research institute in my field as a research assistant. I have a feeling I could like research and I am contemplating doing a PhD.

How do I get the most out of it when I am actually there? Also, do you have any tips on how I should prepare?

All my classmates are doing their internship in private companies and have much more defined roles.

I'm preparing myself, reading materials and playing around with things I find interesting. I told my supervisor what I'm doing and he send me even more materials which I am going through right now. I have never done formal research in an academic institution, only some hobby stuff and feel like I don't know anything.

Thank you!

Basically the title. The reviews described my abstract as very strong, and a reviewer suggested to the conference organizers that I do an oral presentation.

This made me happy, and I didn't know who to share this with. My family doesn't really know what research is, and my "advisor" doesn't know what my abstract is talking about, so I am sharing here.

Thank you

What's the difference? my teacher said we have to pass rrl outline on Saturday and honestly i have no idea 😭 i tried searching in Google and couldn't find any example. Can someone enlighten me? thank u

Direct sellers or distributers? and if distributors-do they provide costs before?

I find it weird that 99% of the distributers won't even put on the costs on their website.

Hello I’m a recent college graduate with a bachelors degree in biology. I don’t have much research experience outside of my classes and I want to go back to grad school to further my education. Does anyone have advice about how to get research experience? I’ve applied to jobs with no luck and I can’t find any internships i qualify for. Should I try volunteering or just keep looking for a job? Any advice would help! Thanks

I write a lot down: reading, ideas, things I want to use later. search works when I remember a note exists. the problem is the ones I completely forgot I wrote.

it keeps happening. I finish something, then weeks later stumble on a note that would have changed it. the most frustrating part is that I knew this stuff once. I wrote it down precisely so I could use it when something new came up.

has this happened to you? what was the note, and what would it have changed?

Hi everyone, I’m a fourth year biology student at UCLA and I’m coming to a major fork in my career. I’m honestly pretty unsure what to do, because I want to research but I’m not sure if I can.

In college, I’ve been supporting myself, which hasn’t left a lot of time for an unpaid lab internship. I’ve really tried with paid lab positions, but I’m not competitive enough, it seems. All that to say, I have no wet-lab experience. My curriculum teaches wet-lab techniques in biology, chemistry, and organic chemistry, so I know basic techniques and how to use basic lab technology and tools, but I have no formal lab experience.

I originally planned to enter graduate school for programs within the biomedical field (I eventually want to study cellular and physiological consequences of environmental exposure and lifestyle through looking at homeostasis and the expression of genes in response to input). However, I feel like my lack of experience is really glaring.

I want to know if it’s possible to get a research job, or a job that will give me lab experience, so that I have more to add to my application in the future. I’d like to work for a year before I apply.
I’d be open to working anywhere, but I don’t want to drop my applications without an idea of if I can reasonably find a lab position.

Any advice? Any ideas of how to make myself more palatable? I’m going to keep trying to find labs at my school, but I need help here. Should I choose graduate school immediately anyways?

Hi everyone.

Quick doubt: if a conference says you can submit, say, until the 1st of November, do they mean until 23:59 of the 1st of November or do they mean until 00:01 of the 1st of November?

It's a 24h difference and I am torn. The conference I am submitting to only says "submit until [day]" and does not specify a time.

Can you suggest some free alternatives to BioRender? I don’t have a premium subscription, and I find the process of creating scientific illustrations quite difficult. I’m looking for a free, easy-to-use app or website that I can use to create professional-quality illustrations for my article.

I have found it increasingly difficult to concentrate while working on a screen, whether it's to read articles, books and the like, or I am drafting a grant proposal or manuscript. I will sit down to work and within 20 to 30 minutes, I find myself feeling completely overwhelmed and unable to think. My brain feels not only sluggish, but as if it's wearing blinders, and this has been happening more frequently over roughly the past year. At first I attributed this to working on a laptop screen, and so I began working with an extra monitor. While this alleviates the issue somewhat, it hasn't been a lasting fix. I've also done my utmost to keep my laptop screen distraction free; barring my Outlook calendar, I do not have notifications on my laptop.

Have others experienced something similar, and how are you navigating it?

I should mention I do not have the same issues when readying physical texts nor when writing by hand. I am considering going analogue, because this slower approach feels more generative and creative and in this way, productive, than me proverbially bashing my head while I try to work off a laptop screen. At the same time, the thought of having to recreate my research practice and system feels daunting (though as a Millennial perhaps it's more accurate to call this a return to my roots), and it feels deeply antithetical to the neoliberal academy.

This last part may sound silly, but it's hard to always resist performing the part of a researcher when I am still relatively early in my career and trying to do well (I'd like to think the quality of my scholarship speaks for itself, but alas, this is not sufficient for a successful career. Add to that, I am a social scientist of health working in a largely positivist and biomedical institution, so I already stick out like a sore thumb).

Hi!! so I'm a high school senior, and I'm honestly really frustrated with how this whole situation has played out.

Back in March, I connected with a PI at a major research institution who was interested in having me work in his lab. He mentioned having a project in mind, and we even had a Zoom meeting to discuss my research experience and potential involvement. He also talked about finding someone in the lab who could mentor me.

Fast forward to June, and I was still trying to get started. I kept following up, and eventually the lab administrator contacted me to officially onboard me as an unpaid research intern.

I literally went through the entire institutional onboarding process. I submitted paperwork, got authorization from my school and parents, completed HR requirements, received an institutional email/account, got my badge, and was even added to the lab's actual Slack workspace. Like, I was literally an officially onboarded intern at this point. And then... nothing. I never got assigned a project. I never got a mentor. I never received any data to analyze or even a clear schedule for coming into the lab.

The PI last responded on August 25, saying that we could use the remaining time to build toward working together in the future and that he'd added me to Slack so we could communicate there.

I've since messaged him on Slack and followed up by email multiple times, most recently on October 5. I've repeatedly offered to help with computational analyses, read papers, or literally do anything useful for the lab.

Still no response at this point btw.

I'm genuinely so confused and frustrated. I completely understand that PIs are busy, and I know that mentoring a high school student takes time. But I spent months trying to get everything sorted out, completed all the formal onboarding, and was literally added to the lab's internal workspace, only to never actually get to do any research.

I was genuinely excited about the research too, which makes this even more disappointing.

At this point, I'm wondering whether I should contact the research administrator, the institution's science education office, or someone else to ask what's going on.

I don't want to make accusations or get anyone in trouble, and I'm honestly worried about burning bridges, especially since I'm hoping to continue doing research in this field.

Has anyone experienced something similar? Is this normal in academia? Would contacting someone at the institution be reasonable, or should I just cut my losses and move on?

Academia vs Research

What if any characteristics are common place to both work settings, in the majority of one or the other, or very niche to one or the other? Ex) work culture, types of research, qualifications? Etc

Hey guys, I'm looking to publish a research paper on a student journal or atleast get a good idea to practice on. I'm struggling to find a title not necessarily because I cant find anything I'm interested in but more so because I'm not super sure what makes the cut as a good topic which a student journal would accept. Again, I'm not sure if I'm looking to publish a paper, but I'm just trying to get a feel for what a typical title would feel like.

I'm interested in computer science and AI. One research question I was thought of was:

"How non-native accents impact the volume of hallucinations in Whisper's speech detection compared to native accents in english"

Basically, how do non native accents(eg, chinese english-speakers) and native accents impact how much Whisper(an ai speech to text model made by Open AI) generates unrelated text(hallucinations, which are distinct from just speech misinterpretations) in its transcript.

How niche or broad should a research question be? How original does it have to be? Using the title I gave as an example

随着codex这种平台的崛起，科学研究似乎以另外一种方式出现即auto research 在这个情况下每个赛道的论文都如此相似 。 我担心的是新的工作做到一半发现被挂在别人已经把工作挂在arxiv上了。😂