Pick A or B for each question and drop your answers in the comments.
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It is called citation chaining - life changing research method
#useful
When you find one genuinely useful paper, don't just read it and move on. Do two things:
A basic search only shows what an algorithm thinks is relevant. Citation chaining shows what actual researchers in the field considered important enough to reference. Completely different quality of results.
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The research topic: One of the paramount rules. โ๏ธ
๐งฟ Artificial Intelligence
Nowadays it is thought AI and its concept are prominent everywhere. Individuals ask about AI, be taught how to manipulate it, and learn its structure. Therefore, a spectrum of investigations is written about effects of AI on numerous fields. Thus, if your research topic interact with how AI works or conceptually reflects, its necessity exponentially grows.
๐งฟ Robotics
You mustnโt make researches about this science straightforward, besides correlating it with your research area. For instance, if you are writing about literature all of a sudden, include a robotized technology thatโd resolve the problem.
๐งฟ Topic Impression
When your research topic is too common and has no association which would awaken the potential readers, then it is dull. In contrast, if it highlights something significant and deep, but emerges audience's afterthoughts, it is rather plausible to be prevalent, because this kind of the titled messages presents a space for visual interconnection ("Enlisting the Power of Youth for Climate Change" by A. Bandura delineates the role and functions of Youth to address the climate issue).
#additional
To come up with the greatest topic of yours, always mention these 3 components in your research topic to formulate it more relevant in terms of the present world.
Nowadays it is thought AI and its concept are prominent everywhere. Individuals ask about AI, be taught how to manipulate it, and learn its structure. Therefore, a spectrum of investigations is written about effects of AI on numerous fields. Thus, if your research topic interact with how AI works or conceptually reflects, its necessity exponentially grows.
You mustnโt make researches about this science straightforward, besides correlating it with your research area. For instance, if you are writing about literature all of a sudden, include a robotized technology thatโd resolve the problem.
When your research topic is too common and has no association which would awaken the potential readers, then it is dull. In contrast, if it highlights something significant and deep, but emerges audience's afterthoughts, it is rather plausible to be prevalent, because this kind of the titled messages presents a space for visual interconnection ("Enlisting the Power of Youth for Climate Change" by A. Bandura delineates the role and functions of Youth to address the climate issue).
#additional
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Conducting Research: Why is it dull? #additional
It is mistakenly perceived writing your own research work would be effortless and thought-provoking if you had already chosen an interesting topic and a relevant field to go around. However, there is the excruciating truth: unhappily, even the experienced researchers might fail in locking in and finding the impression about their hobby enthusiastic. It mostly happens, because researches demand:
๐ฑ Being meticulous and stable about the text you are writing;
๐ฑ Unstoppably thinking about complex things and keeping in-touch;
๐ฑ Hardly losing attention.
On the other hand, the promoted issue practically exasperates the solely beginners as long as the professional individuals who experienced writing the researcn at least once would understand how to deal with the presented emotions. To overcome your concentration problems and improve the stable fulfillment, consider:
๐คฉ Sleeping and eating well;
๐คฉ Making your workspace cozy and clear to prevent any visual distractions;
๐คฉ Creating a strong discipline and schedule which would provide a full engagement into the managed cycle.
Never forget about the solely fact โ research conduction is not hobby itself; it is the whole and memorable project.๐ค
It is mistakenly perceived writing your own research work would be effortless and thought-provoking if you had already chosen an interesting topic and a relevant field to go around. However, there is the excruciating truth: unhappily, even the experienced researchers might fail in locking in and finding the impression about their hobby enthusiastic. It mostly happens, because researches demand:
On the other hand, the promoted issue practically exasperates the solely beginners as long as the professional individuals who experienced writing the researcn at least once would understand how to deal with the presented emotions. To overcome your concentration problems and improve the stable fulfillment, consider:
Never forget about the solely fact โ research conduction is not hobby itself; it is the whole and memorable project.
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Forwarded from ๐
APPLICATIONS ARE NOW OPEN!
Female Acumen Society ะฒ ะบะพะปะปะฐะฑะพัะฐัะธะธ ั Youth Research Accelerator ะทะฐะฟััะบะฐะตั ะฟะพะปะฝะพัััั ะะะกะะะะขะะซะ 4-ะฝะตะดะตะปัะฝัั ะบััั-ะฒะฒะตะดะตะฝะธะต ะฒ Research Projects ะดะปั ะดะตะฒะพัะตะบ ัะพ ะฒัะตะณะพ ะกะะ!๐
Application form: ััะบ
ะะพัะผะพััะตัั ะพะฟัั ััะฐััะฝะธั ั ะฟัะพัะปะพะณะพ ะฟะพัะพะบะฐ: ััะบ
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๐ THE 5 STATS CONCEPTS EVERY STUDENT RESEARCHER ACTUALLY NEEDS
#useful
1๏ธโฃ Mean, Median, Mode
When data has extreme outliers like income or housing prices, the median tells a more honest story than the mean. Always ask which one actually represents your data best rather than defaulting to mean automatically.
2๏ธโฃ Sample Size
Too small and your results can't be trusted โ you can't draw conclusions from 8 people. For survey-based student research, aim for at least 30 responses as an absolute minimum. 100 or more gives your findings real credibility.
3๏ธโฃ Correlation
Measures how strongly two variables move together. Ranges from -1 to +1. Strong positive, strong negative, or no relationship. The most important thing to remember: correlation never proves causation. Two things happening together doesn't mean one caused the other.
4๏ธโฃ P-value
Tells you whether your results are statistically significant or just random chance. Below 0.05 is the standard threshold โ meaning less than a 5% probability your results happened by coincidence. You don't need to calculate this by hand โ tools like Google Sheets, JASP, or Jamovi do it instantly.
5๏ธโฃ Standard Deviation
How spread out your data is. A low standard deviation means most responses clustered close to the average. A high one means responses were all over the place. Neither is automatically good or bad โ it depends entirely on what you're studying.
#useful
When data has extreme outliers like income or housing prices, the median tells a more honest story than the mean. Always ask which one actually represents your data best rather than defaulting to mean automatically.
Too small and your results can't be trusted โ you can't draw conclusions from 8 people. For survey-based student research, aim for at least 30 responses as an absolute minimum. 100 or more gives your findings real credibility.
Measures how strongly two variables move together. Ranges from -1 to +1. Strong positive, strong negative, or no relationship. The most important thing to remember: correlation never proves causation. Two things happening together doesn't mean one caused the other.
Tells you whether your results are statistically significant or just random chance. Below 0.05 is the standard threshold โ meaning less than a 5% probability your results happened by coincidence. You don't need to calculate this by hand โ tools like Google Sheets, JASP, or Jamovi do it instantly.
How spread out your data is. A low standard deviation means most responses clustered close to the average. A high one means responses were all over the place. Neither is automatically good or bad โ it depends entirely on what you're studying.
๐ Free tools: JASP (jasp-stats.org) and Jamovi (jamovi.org) โ both free, both beginner-friendly, both used by actual researchers.
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POPULAR METHODS IN RESEARCHES.
๐ Quantitative research:
๐ค Quantitative research focuses on numbers, measurement, and statistical analysis. It is used when you want to test a hypothesis, compare groups, or measure how strongly variables are related. Common data collection tools include surveys with fixed response options, experiments, standardized tests, and existing datasets.
๐ Qualitative research:
๐ค Qualitative research focuses on meanings, experiences, and context rather than numbers. It is used to understand how people think, feel, and interpret events, behaviors, or social situations. Common methods include interviews, focus groups, observations, document analysis, and oral histories.
๐คฉ Experimental research:
๐ค Experimental research is designed to test cause and effect. The researcher changes one variable, keeps other conditions controlled as much as possible, and then observes whether the change affects another variable. This method is common in psychology, medicine, natural sciences, and education.
#important
Here are the most common methodologies in investigations and scientific works which might introduce you with the entire world of experiments and statictics!
#important
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Youth Research Accelerator
ะัะต ััะฟะตะปะธ ะทะฐัะตะณะธัััะธัะพะฒะฐัััั? ๐ง
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We have real research questions. Think it through and share your perspective, backed by valid reasoning.
Todayโs question:
"Should AI be allowed to co-author scientific research papers?"
Some context worth considering: AI tools are already being used to analyze data, generate hypotheses, write literature reviews, and draft sections of papers.
Several major journals have banned AI authorship entirely. Others argue that if AI contributed meaningfully to the work, excluding it from authorship is intellectually dishonest. If a paper with AI co-authorship later turns out to contain errors - who exactly is accountable? -
Some say this will democratize science and help researchers in under-resourced settings. Others say it will flood journals with low-quality work.
Respectful disagreement only
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Conclusion: A novel explication! #structure
1๏ธโฃ To write your research conclusion properly, reassure yourself you have restated your main research question or goal (from introduction) to remind readers of the main purpose of the emphasised research. Besides that, it is significant not to miss the significance interpretation related to the study and be utterly realistic about the achieved results โ highlight drawbacks and plausible limitations that hindered some targets. Additionally, the end of everyone's conclusion might happen with meaningful slogan or someone's citation (but it is hardly acceptable and often inappropriate).
2๏ธโฃ When it comes to structure of the conclusion, obviously, its first sentence should reflect the identity of the held research: primary functions, goals, and hypotheses. Further 2 sentences could connect your results with your aims (also, use words like "limit", "clarify", "establish"). Afterwards, provide concisely boundaries and problems that were explained before. Ultimately, regard recommendation or brief takeaway that would form the final perception of your research. โค๏ธ
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We are currently looking for motivated people to join our team in the following roles:
If you are interested in one of the roles - fill out the form
We will be happy to welcome new people to the team
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Exactly 6 months and 1 day ago, we officially launched Youth Research Accelerator.
In just half a year, we've:
โณ๏ธ shared 280+ educational posts on our Telegram channel;
๐งโ๐งโ๐งโ๐ง built a community of 1,660 students on Telegram;
๐ค collaborated with 50+ organizations and initiatives;
๐ organized 4 competitions across different fields;
๐ค hosted 3 educational webinars.
None of this would have been possible without our incredible volunteers, whose dedication and passion helped shape YRA into what it is today.
This is only the beginning.
Onward to even bigger milestonesโค๏ธ
Support us in Linkedin๐
In just half a year, we've:
โณ๏ธ shared 280+ educational posts on our Telegram channel;
๐งโ๐งโ๐งโ๐ง built a community of 1,660 students on Telegram;
๐ค collaborated with 50+ organizations and initiatives;
๐ organized 4 competitions across different fields;
๐ค hosted 3 educational webinars.
None of this would have been possible without our incredible volunteers, whose dedication and passion helped shape YRA into what it is today.
This is only the beginning.
Onward to even bigger milestones
Support us in Linkedin
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Common mistakes in Methodologies. #additional
๐คฉ Wrong approach for the aim:
โ If your research is aimed at investigating qualitative fields, it is unreasonable to make interviews with casual or generalised questions. Unless your controversial methods are not proven anywhere of the research, it would pretty be inexplicable to incorporate the contradictory strategy.
๐คฉ Weak measurement tools:
โ Tools you have been using must be accountable for their reliance and validity. As long as the undisclosed questionnaires capture erroneous type of individuals or include non-neutral questions, they are unable to guarantee reliable outcomes and perform for the fair conclusion.
๐คฉ Missing fundamental definitions:
โ Most studies (of students) consider extremely common terms which are both fundamental and vague. Hence, the problem hinders to understand what is studied exactly. For example, "academic success" is general and vague, because it does not contain any spare of ideas.
Methodology must be dedicated to provide a meticulous description of how your research was organized and, afterwards, managed, while the part can include specific superiorities of the methods you used.
โ If your research is aimed at investigating qualitative fields, it is unreasonable to make interviews with casual or generalised questions. Unless your controversial methods are not proven anywhere of the research, it would pretty be inexplicable to incorporate the contradictory strategy.
โ Tools you have been using must be accountable for their reliance and validity. As long as the undisclosed questionnaires capture erroneous type of individuals or include non-neutral questions, they are unable to guarantee reliable outcomes and perform for the fair conclusion.
โ Most studies (of students) consider extremely common terms which are both fundamental and vague. Hence, the problem hinders to understand what is studied exactly. For example, "academic success" is general and vague, because it does not contain any spare of ideas.
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Each scenario below has at least one serious problem. Read each one carefully and comment what you think is wrong ๐
Scenario 1: A student wants to study whether listening to classical music improves memory. They test 10 of their close friends, all from the same school and the same grade. Their conclusion: "Classical music improves memory in teenagers."
Scenario 2: A researcher surveys students about their daily screen time and their grades. Students who use their phone more than 4 hours a day tend to have lower grades. The conclusion: "Excessive screen time causes lower academic performance."
Scenario 3: A student studies stress levels among students at their school. They send a survey to 200 students but only 8 respond. They analyze those 8 responses and write up their findings as representative of the school.
Scenario 4: A researcher tests whether a new study technique improves grades. They teach the technique to students who voluntarily signed up for the program, then compare their grades to students who didn't join. The volunteers' grades go up.
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The modern world of researchers: Primary Issues. ๐ #additional
1๏ธโฃ Hollow Projects.
Even though a comprehensive involvement of various explorations might sound pretty progressive, in the reality it underrates actual standards of them, because the more researches are manufactured, the more their difficulty is diminished and limited for students and other individuals. The referenced issue has already occupied most of youth journals, because the selection criteria have negatively reconsidered. In the past, researchers were given a certain amount of time and financial support to conduct a very research, whilst nowadays it has been accepted as a beautiful combination of questionnaires, narrow field to observe, and academic style. The primary reminder is that it is not the problem yet, but it would definitely lead to some potential misguidance in the future.
2๏ธโฃ Academic overwhelming.
As a result of the sharp enlightenment, a misconception of academic content of the provided text became widespread. There is the conventional bottleneck in the rapid progress which has led to researches being academically overwhelmed in last days. The volume of published work makes it hard to find a clear gap and keep a review focused and critical rather than just descriptive. Consequently, investigations have been deprived of contextual clarity and specific information which used to be appropriate for the main target of the whole researchers.
Even though a comprehensive involvement of various explorations might sound pretty progressive, in the reality it underrates actual standards of them, because the more researches are manufactured, the more their difficulty is diminished and limited for students and other individuals. The referenced issue has already occupied most of youth journals, because the selection criteria have negatively reconsidered. In the past, researchers were given a certain amount of time and financial support to conduct a very research, whilst nowadays it has been accepted as a beautiful combination of questionnaires, narrow field to observe, and academic style. The primary reminder is that it is not the problem yet, but it would definitely lead to some potential misguidance in the future.
As a result of the sharp enlightenment, a misconception of academic content of the provided text became widespread. There is the conventional bottleneck in the rapid progress which has led to researches being academically overwhelmed in last days. The volume of published work makes it hard to find a clear gap and keep a review focused and critical rather than just descriptive. Consequently, investigations have been deprived of contextual clarity and specific information which used to be appropriate for the main target of the whole researchers.
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๐ฌUpcoming Research & Innovation Competitions 2026โ2027
1. Regeneron Science Talent Search (STS) The US's oldest research competition โ individual scientific research, essays, recommendations.
๐ Application: June 1 โ Nov 5, 2026
2. Regeneron ISEF
World's largest pre-college science fair โ grades 9โ12, any country, must qualify through a Society-affiliated regional/national fair first.
๐ Affiliated fairs run JanโApril 2027; ISEF finals May 2027 (Los Angeles)
3. Conrad Challenge Team-based (2โ5 students, 13โ18) entrepreneurship + STEM competition โ aerospace, energy, cyber, health categories. Fully international, virtual-friendly.
๐ 2026โ27 cycle not yet announced โ
4.Diamond Challenge
Global high school entrepreneurship competition (business or social innovation track), teams of 2โ4, any country, $100K prize pool.
๐ 2027 cycle dates TBA (2026 deadline was Jan 15, 2026 โ expect similar timing)
1. Regeneron Science Talent Search (STS) The US's oldest research competition โ individual scientific research, essays, recommendations.
๐ Application: June 1 โ Nov 5, 2026
2. Regeneron ISEF
World's largest pre-college science fair โ grades 9โ12, any country, must qualify through a Society-affiliated regional/national fair first.
๐ Affiliated fairs run JanโApril 2027; ISEF finals May 2027 (Los Angeles)
3. Conrad Challenge Team-based (2โ5 students, 13โ18) entrepreneurship + STEM competition โ aerospace, energy, cyber, health categories. Fully international, virtual-friendly.
๐ 2026โ27 cycle not yet announced โ
4.Diamond Challenge
Global high school entrepreneurship competition (business or social innovation track), teams of 2โ4, any country, $100K prize pool.
๐ 2027 cycle dates TBA (2026 deadline was Jan 15, 2026 โ expect similar timing)
Sometimes, researches โ evidence. But why? โ๏ธ
๐ฑ Research might not entirely reflect evidential value of even a single statement, but most beginners tend to ask theirselves how they are set to develop their idea and give evidences for their hypotheses. Publication cannot guarantee truth, it probably relies on another causation, and statistical significance is not practical validation. Additionally, bias is able to affect your references, whilst firm testimony is usually accrued from multiple lines of maintenance.
๐ฑ When scientific work encounters a shortage of sufficient sources, authors, whatsoever, reference a plethora of various investigations even if it sounds pretty contradictory. Thus, filling your referencing list is a part of all the explorations as well. Therefore, it would be controversial to enmesh the statements with the solely one publication as long as there might be 8 studies with a positive effect and 2 with no effect.
#important
#important
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Hypotheses vs. Theories
Hypotheses are testable predictions of researchers, while their primary aims are systematically to delineate a research question the investigation centred at. Noticeably, a hypothesis is predominantly more specific and narrow rather than theories, because it must be evidential within the investigation and research processes, namely questionnaires, statistics, and other categories which might prove the promoted statement.
Theories are prominently broad and general explanations of phenomena, and therefore they have been being developed by primary scientists as long as they have collected an immense list of evidences, testimonies, and arguments to unquestionably represent their own idea. Unlike the hypotheses, the theories are unable to be formulated when they are not sufficiently proven in several dogmas.
Let's enlist all the differences amongst theories and hypotheses. Of course, nothing is better, because they are by no means congruent. However, there are some deep contradictory moments to eact other. On the one hand, the theories are testified as a strctured explanatory frameworks, as well as, on the other hand, the hypotheses are basically statements or projections.
#additional
Hypotheses are testable predictions of researchers, while their primary aims are systematically to delineate a research question the investigation centred at. Noticeably, a hypothesis is predominantly more specific and narrow rather than theories, because it must be evidential within the investigation and research processes, namely questionnaires, statistics, and other categories which might prove the promoted statement.
Theories are prominently broad and general explanations of phenomena, and therefore they have been being developed by primary scientists as long as they have collected an immense list of evidences, testimonies, and arguments to unquestionably represent their own idea. Unlike the hypotheses, the theories are unable to be formulated when they are not sufficiently proven in several dogmas.
Let's enlist all the differences amongst theories and hypotheses. Of course, nothing is better, because they are by no means congruent. However, there are some deep contradictory moments to eact other. On the one hand, the theories are testified as a strctured explanatory frameworks, as well as, on the other hand, the hypotheses are basically statements or projections.
#additional
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