Search across guide titles, topics, keywords, and content throughout the Researcher's Field Guide.
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A contribution claim can fail because it says too little or claims too much. Learn how to recognize weak, vague, and overly broad contributions and recalibrate them to what the study actually adds.
Read Guide →A strong contribution claim does not need inflated language. Learn how to make the most defensible claim your evidence supports without exaggerating novelty, generalizability, theoretical importance, or practical implications.
Read Guide →Research does not always make the contribution you originally expected. Learn how to reassess the evidence, identify what the study actually contributes, and revise the manuscript without rewriting the history of the research.
Read Guide →A research problem and research question can each sound convincing while still pointing in different directions. Learn how to test whether the question actually investigates the problem your study claims to address.
Read Guide →Participatory research changes who contributes to producing knowledge and how influence is distributed across the research process. It does not abandon research rigor or require every decision to be made collectively.
Read Guide →Communities can help identify, develop, refine, and prioritize research questions, particularly when lived or local knowledge is important to deciding what deserves investigation. Community priorities still need to be translated into feasible, ethical, and scientifically answerable research questions.
Read Guide →Research protocols and research proposals often contain similar material, but the terms are not always interchangeable. The clearest distinction is usually their function: a proposal seeks authorization or support for a study, while a protocol specifies how the study will be conducted.
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 →Generative AI can help researchers notice possible problems, tensions, contradictions, and unexplained phenomena worth investigating. It cannot establish from plausible language alone that a research problem genuinely exists or deserves study.
Read Guide →Generative AI can make research-topic brainstorming faster and more varied, especially when you give it meaningful constraints. The strongest approach is not to ask for a long list of titles, but to use AI to explore different directions before selecting and validating a topic yourself.
Read Guide →Do not search only the exact wording of an AI-generated research question. Break it into concepts, relationships, populations, and contexts, then search the literature broadly enough to discover substantively equivalent questions.
Read Guide →Generative AI can help researchers interrogate why a research question might matter, compare possible contributions, and expose weak rationales. It cannot independently determine scientific importance without reliable evidence and disciplinary context.
Read Guide →Generative AI can help researchers expose assumptions hidden in a research idea, from presumed causal relationships to definitions, populations, methods, and claims of significance. The researcher must still determine which critiques are substantively valid.
Read Guide →Generative AI can make a familiar research idea sound unusually innovative by changing its framing, terminology, and claims of contribution. Rhetorical novelty should never be confused with novelty demonstrated against the literature.
Read Guide →There is no single universal rule saying that whoever receives an AI-generated research idea automatically “owns” it. Copyright, patent law, contracts, institutional rules, confidentiality, and scholarly credit address different aspects of ownership and may lead to different answers.
Read Guide →A research topic identifies what interests you, but a researchable question establishes what you intend to investigate. Learn how generative AI can help bridge that gap without inventing a research problem or assuming an unverified knowledge gap.
Read Guide →A study can have well-written research questions, objectives, hypotheses, and methods that do not actually fit together. Learn how generative AI can help identify conceptual and methodological inconsistencies before they compromise the evidence your study can produce.
Read Guide →Generative AI can help researchers plan, organize, synthesize, and draft literature reviews, but fluent writing does not guarantee an accurate representation of the evidence. Learn which tasks AI can reasonably support, where errors arise, and how to retain control over the scholarly argument.
Read Guide →Generative AI can help identify relationships across research papers and draft an integrated synthesis, but combining findings requires more than summarizing individual studies. Learn how to preserve methodological differences, conflicting evidence, and source traceability.
Read Guide →Generative AI can help identify recurring research designs, sampling approaches, instruments, and analytical methods across studies. However, methodological patterns must be verified against original publications, and frequently used methods are not necessarily the most appropriate or reliable.
Read Guide →Generative AI can help create a literature review matrix by extracting and organizing information from research papers. However, a complete-looking table may contain incorrect findings, invented methodological details, or misleading comparisons. Learn how to build a verifiable matrix that supports genuine research synthesis.
Read Guide →Generative AI can help connect concepts, theoretical perspectives, and findings across research studies. However, plausible conceptual relationships are not necessarily supported by evidence. Learn how to build a defensible conceptual synthesis while distinguishing established relationships from interpretive proposals.
Read Guide →An AI-generated literature synthesis may contain genuine citations without accurately representing the studies behind its claims. Learn how to build claim-to-source maps, preserve evidence locations, document interpretive decisions, and make AI-assisted research synthesis independently verifiable.
Read Guide →Generative AI can support different sections of a research manuscript, but the appropriate level of assistance varies. Compare what AI can help with in the introduction, methods, results, discussion, conclusion, and abstract, and identify the scientific decisions that must remain under researcher control.
Read Guide →Generative AI can help organize and draft a research paper introduction, but it cannot independently establish the research gap or verify the literature. Learn how to use AI for introduction writing while preserving source accuracy, scholarly reasoning, and the study's intellectual justification.
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