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A good response to ethics committee comments makes it easy to see what was requested, what you changed, where you changed it, and why. Learn how to prepare a clear point-by-point response and coordinated revision package.
Read Guide →Participants need enough relevant information to understand what participation involves and why they might or might not want to take part. The exact required information varies by study and governing framework.
Read Guide →Potential participants need enough relevant information to make an informed decision, but not every detail has to appear in the first recruitment message. The amount, timing, and organization of disclosure depend on whether researchers are recruiting interest, seeking informed consent, or using an ethics-approved alteration of consent.
Read Guide →An organization cannot make voluntary research participation compulsory simply by calling it a course requirement or workplace task. The answer depends first on whether the activity is actually research, then on the applicable consent rules, alternatives, penalties, and ethics-review framework.
Read Guide →Course credit can be used as a research incentive, but students must not be placed in a position where research is effectively the only practical way to earn the credit. A comparable non-research alternative and protection against academic penalties are central to voluntariness.
Read Guide →Students offered course credit for research should have an equitable non-research way to earn the same credit. The alternative should require reasonably comparable time and effort without making research participation the easier or academically safer choice.
Read Guide →Researchers should not collect identifying information simply because it might be useful later. Each identifier should serve a defensible research or operational purpose, and the appropriate amount depends on what the study actually needs to accomplish.
Read Guide →A good research debrief does more than reveal that deception occurred. It should explain the study’s actual purpose, identify what was false or withheld, explain why the alteration was necessary, correct important misconceptions, and communicate any participant options required by the governing ethics framework.
Read Guide →Plagiarism in research is not limited to copying sentences. It can involve taking another person's words, ideas, processes, results, or other intellectual contributions without giving appropriate credit.
Read Guide →Paraphrasing usually does not remove the need to cite a source. Your wording may be new, but the idea, finding, interpretation, or information can still belong to the source you used.
Read Guide →An attribution problem does not necessarily disappear because it was accidental. Yet accidental plagiarism and a formal finding of research misconduct are not automatically the same thing, because intent and applicable policy matter.
Read Guide →A thesis can often be developed into one or more journal articles, but there is no universal percentage of acceptable overlap. What matters is the type of material reused, transparency, journal policy, copyright, and whether the article is genuinely shaped as a journal publication.
Read Guide →Developing a hypothesis after seeing your results can be scientifically useful. HARKing occurs when that post hoc hypothesis is presented as though it had been predicted before the results were known.
Read Guide →Industry sponsorship deserves attention because empirical research has found associations between sponsorship and sponsor-favorable results or conclusions in some fields. That evidence supports greater scrutiny, not automatic rejection of every industry-funded study.
Read Guide →Research assistance and ghostwriting can involve similar tasks, but they differ in how intellectual contributions, responsibility, and authorship are represented. Learn when paid writing support is legitimate, when undisclosed contributions become problematic, and how researchers can establish ethical boundaries before engaging external writers.
Read Guide →A research gap describes what existing knowledge does not adequately answer, while a research problem defines the specific issue your study will investigate. Learn how the two concepts connect without treating them as interchangeable.
Read Guide →Reference managers can do much more than generate bibliographies. Learn how to use Zotero, Mendeley, EndNote, and similar tools to capture accurate references, organize literature, manage PDFs, take useful notes, cite while writing, and protect your research library.
Read Guide →You can conduct academic research without a reference manager, but manual reference management becomes increasingly difficult as your sources, projects, and citations grow. Here is how to decide when using one is worth the effort.
Read Guide →A large language model learns statistical patterns in token sequences and uses them to generate or process language and related content. For researchers, LLMs can be versatile assistants, but fluent output should never be confused with verified evidence.
Read Guide →AI assistants, search engines, research databases, and reference managers can all help researchers work with information, but they do different jobs. Knowing whether you need generation, discovery, scholarly retrieval, or reference management helps you choose the right tool.
Read Guide →AI-assisted research uses artificial intelligence to support one or more research tasks while researchers retain responsibility for the study and its scholarly decisions. The important question is not merely whether AI was used, but what it assisted with and how its contribution was evaluated.
Read Guide →AI-assisted research uses AI to support a human-led research process, while AI-generated refers to material or outputs produced by the AI itself. A project can involve both, so researchers should describe what AI actually contributed rather than relying on either label alone.
Read Guide →Generative AI can assist with tasks across much of the research process, including exploration, literature work, coding, data preparation, analysis support, writing, and communication. Its usefulness depends on the task, the system, the evidence available for verification, and the consequences of getting the output wrong.
Read Guide →AI can assist with many demanding research tasks, but some responsibilities should remain under meaningful human control. Researchers should not completely delegate accountable scholarly judgment, ethical responsibility, authoritative verification, or final interpretation to AI.
Read Guide →Generative AI can potentially improve research quality when it helps researchers detect errors, consider alternatives, test ideas, improve reproducibility, or communicate evidence more clearly. Faster production and more polished writing, however, should not be mistaken for better research.
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