Developing Effective Research Questions

How to actually use ChatGPT as a Tool rather than a Co-author in the research process. 4️⃣ practical ways. ✔ Truth be told, AI tools, including ChatGPT, have cemented their place in the research workflow. ✔ There are practical ways researchers can enhance their work without compromising on quality or ethical standards. *************************** ✅ Refine Your Questions or Prompts to Be as Specific as Possible ✔ The quality of ChatGPT's responses heavily relies on the clarity and specificity of the input it receives ✅ Use ChatGPT's Outputs as a Starting Point, Not the Final Product ✔ View ChatGPT's contributions as preliminary drafts or initial insights rather than conclusive findings is important. ✅ Engage in an Iterative Process, Refining Your Queries Based on Previous Responses ✔ Interaction with ChatGPT should be viewed as an iterative dialogue rather than a one-off query. ✅ Combine ChatGPT's Insights with Expert Knowledge and Critical Analysis ✔ The most effective use of ChatGPT in research involves synthesizing its outputs with your own knowledge and analytical skills. ************************** ✔ The ultimate goal is to foster innovation and efficiency in research methodologies while upholding the principles of academic rigor and integrity. #academia #research #phd #graduateschool #mentoring

When I first heard about SciSpace’s new feature, Deep Review, I assumed it was just another AI tool among many. I casually gave it a try, but to my surprise, it turned out to be incredibly helpful. Here’s how: ✅ Intelligent Query Enhancement – Optimizes searches with better keywords and context. ➡ For example, if I search for "drought resistance genes," it automatically suggests more precise keywords like "drought-tolerance QTLs in maize." ✅ Precision-Based Questioning – Helps refine queries by prompting you to be more specific. ➡ For instance, when I searched for markers for anthracnose resistance in peppers, it asked if I needed species-specific or marker-type-specific results (e.g., SSR, SNP, QTLs). ✅ Query Transformation – Runs multiple refined searches to improve accuracy. ➡ Instead of a single broad search, it automatically breaks down queries into smaller, more effective searches, ensuring better coverage. ✅ Citations & References Traversal – Identifies hidden yet relevant research papers. ➡ If an important paper isn't directly in the top results, it traces citations and references to surface highly relevant but less obvious papers. ✅ Smart Filtering – Ensures only the most relevant papers are included, with the top 20 papers listed first. ➡ For example, if a query retrieves 200+ results, it prioritizes the most cited and contextually relevant studies instead of listing everything indiscriminately. ✅ Structured Insights – Categorizes papers for clarity. It also includes additional sections like methods studied or markers used or species studied for better organization. ➡ For instance, it groups studies based on experimental approaches, such as genome-wide association studies (GWAS) vs. linkage mapping. For me, this serves as a quick reference tool to identify markers linked to specific diseases. It not only saves time but also provides precise results. The curated list includes SSR, SNP, and QTL markers, which would otherwise take weeks to compile manually. Definitely a must-try for literature searches! 🎥 Check out my demo video here!👇🏻 Additionally, SciSpace is launching a new feature—SciSpace Browser Control, an AI-powered research assistant that helps you find and access papers beyond SciSpace. With Browser Control, you can search across multiple databases, including Google Scholar, PubMed, ScienceDirect, and more. This feature is coming soon! Useful links to access these features: Deep Review UTM link: https://lnkd.in/gUBWfjZG Browser control waitlist link: https://lnkd.in/ghfhf5qD Use these referral codes for discounted subscription: Other countries: DEEPDR40 — offers 40% off on advanced annual plan DEEPDR20 — offers 20% off on advanced monthly plan India: JAGDR20 — offers 20% off on both advanced monthly and annual plan #SciSpaceDeepReview #SciSpaceAIResearchAgent #SystematicLiteratureReview #AIinresearch

Crafting Qualitative Research Questions: The Key to Your Study 🎯 Your qualitative research question is the compass 🧭 of your study. It guides every aspect—from data collection to analysis—and ensures your findings address the core phenomenon you're exploring. Here’s a breakdown of how to design effective qualitative research questions: 1. Purpose-Driven Questions ✨ Start with the intent of your study. Qualitative research seeks to explore, understand, or describe experiences, processes, or phenomena. Use open-ended phrases like: "What are the experiences of..." 🗣️ "How do individuals perceive..." 👀 "Why do people engage in..." ❓ 2. Key Characteristics 🗝️ Open-Ended: Avoid yes/no formats to enable depth. Exploratory: Focus on understanding rather than measuring. Contextual: Embed questions within the specific cultural, social, or situational settings of your study. 3. Common Frameworks 🏗️ Qualitative research questions often align with methodological traditions: Phenomenology: "What is the lived experience of [X]?" 🌅 Grounded Theory: "How do [participants] navigate [phenomenon]?" 🛤️ Ethnography: "What are the cultural practices of [group] in [context]?" 🏘️ Narrative: "How do individuals construct stories about [experience]?" 📖 4. Examples 💡 "What are the factors influencing community trust in healthcare systems? 🏥" "How do teachers adapt to online learning in resource-limited settings? 💻" "What strategies do caregivers use to manage stress? 💆♀️" 5. Iterative Refinement 🔄 As you immerse yourself in the research, refine your questions to reflect new insights and ensure they remain aligned with your study's purpose. 🛠️ Whether you're embarking on your first study or honing expertise, mastering research questions ensures clarity and focus. What qualitative inquiry will you design next? 🤔

76% of workers know they need AI skills to stay competitive. Yet most UX professionals are still creating personas manually, writing research questions from scratch, and spending hours on wireframe specs. Listen, if you're a UX professional in 2025: Stop: - Treating AI as a threat to your job - Writing every research question manually - Spending hours on repetitive documentation - Waiting for "the perfect time" to learn AI Instead: - Master prompt engineering frameworks (it takes 30 days) - Use the REFINE method for every AI interaction - Build a library of reusable prompt templates - Save 40% of your time on routine tasks Here's my battle-tested prompt framework for UX research: The REFINE Framework: - Role: "You are a senior UX researcher specializing in [industry]" - Expectations: Clearly state your desired outcome - Format: Specify exact output structure - Iterate: Plan to refine based on results - Nuance: Add project-specific context - Example: Provide concrete samples Real example that saved me 3 hours: "You are an experienced UX researcher conducting user interviews for a telehealth platform. Create 8-10 open-ended interview questions that will help uncover: - User motivations and pain points - Current workflows and processes - Feature preferences and expectations Format: Present as a bulleted list with follow-up probes for each main question. Context: Users are 55+ seniors new to digital health Target Users: Medicare patients managing chronic conditions" The AI generated better questions than my manual brainstorming - in 30 seconds. Why this matters to you: AI skills are demanded in 1 in 4 new tech jobs. UX professionals who master prompt engineering aren't just surviving - they're becoming the most valuable players on their teams. You already have the core skills: understanding user needs, clear communication, and iterative problem-solving. Prompt engineering just amplifies them. --- PS: What are your go-to prompts? 🤔 Follow me, John Balboa. I swear I'm friendly and I won't detach your components.

On problematization as a research method (or a guide for early career scholars). Problematization is one of the most challenging things a scholar must learn to do. Why? Because it requires us, as scholars, to question everything that we know. Doing it well, requires us to constructively identify and articulate issues or inconsistencies in established knowledge, frameworks, or practices to open new avenues for inquiry and understanding. Being constructive is important because if we become too critical, problematization becomes a nihilistic exercise - with scant useful outcomes. But how to do it? In a constructive way? Brahim Hinda just published a framework that walks you through five approaches to problematization, offers guidance on how to pursue them, and grounds them in the appropriate literatures. What I like about the paper, is Hinda does not suggest that one or another approach to problematization is superior, rather, it advocates for using several approaches in concert - to really sort out the issues. Give it a look! Citation: Hiba, B. (2025). If you don't problematize it, you won't see it, and you won't understand it. New Ideas in Psychology, 77, 101141. Link: https://lnkd.in/eWtXs3YS Abstract: This paper critically redefines problematization as both a research method and a transformative approach to critical thinking, positioning it as a pivotal modus operandi that transcends the limitations of conventional research practices. Diverging from traditional established research methods focused on gap-spotting and incremental contributions, this paper underscores problematization's unique capacity to interrogate and disrupt the foundational assumptions underpinning existing knowledge structures. By doing so, it drives researchers to reimagine and expand the horizons of scholarly inquiry. Grounded in the intellectual contributions of Nietzsche, Foucault, Marx, Heidegger, Deleuze, and Lacan, this paper addresses the theoretical limitations of the discourse about problematization, often clouded by complex philosophical jargon, while dismantling misconceptions about its nature and application. Beyond theoretical exploration, this paper introduces a practical framework that integrates innovative metaphors, discursive clarity, and actionable strategies. This framework is tailored to empower doctoral students and early-career researchers, equipping them with a taxonomy of epistemological and critical questions for effectively problematizing research problems. The research questions guiding this paper investigate how problematization can be reinterpreted and operationalized to challenge the ideological and power dynamics within dominant research paradigms. Furthermore, this paper explores how a multi-modal approach—combining rhizomatic, genealogical, visual, metaphorical, and ecological thinking—can deepen the practice of problematization.

💡 Clinical research starts with the right question—but coming up with one can feel impossible. If you’re stuck trying to create a research question from scratch, stop. ❇️Great questions don’t come out of nowhere.❇️ The best research questions start with context. Look at your daily work, identify gaps, and build from there. Here’s how to turn your observations into meaningful clinical research. 👇 A FRAMEWORK FOR CRAFTING IMPACT RESEARCH QUESTIONS 1️⃣ Start Where You Are The best research questions aren’t created in isolation—they’re grounded in context. Ask yourself: - What are the recurring pain points in your daily work? - Are there inefficiencies in processes like hospital discharge, patient education, or workflows? - Who is your focus population? (e.g., patients, caregivers, medical students, or providers) By reflecting on these, you’ll uncover meaningful questions rooted in real-world challenges. 2️⃣ Conduct a Literature Review - Start with a recent, highly cited review article to get a sense of the broader landscape. - Then, dive deeper into original research referenced in that article. - This will help you identify gaps and refine your focus. 3️⃣ Narrow Your Angle If everything feels “already done,” here’s how to narrow your focus: - Population: Could you study a subgroup or demographic that hasn’t been explored? - Context: Can you apply findings to a new setting, like outpatient vs. inpatient care? - Methodology: What about using a different study design? 4️⃣ Use a Framework Structuring your research question makes it clearer and actionable. Here are three popular frameworks to consider: ✅ PICO (Population, Intervention, Comparison, Outcome): Best for intervention studies. 🖋️ Example: Does a new telehealth program (Intervention) improve medication adherence (Outcome) in rural diabetes patients (Population) compared to in-person visits (Comparison)? ✅ PEO (Population, Exposure, Outcome): Ideal for prognosis or outcome research. 🖋️ Example: What is the long-term impact (Outcome) of early-life antibiotic exposure (Exposure) on pediatric gut health (Population)? ✅ PIC (Population, Interest, Context): Perfect for prevalence/incidence studies. 🖋️Example: What is the prevalence of physician burnout (Interest) among emergency room attendings (Population) in urban hospitals (Context)? 5️⃣ Pass the "So What?" Test Before finalizing your question, ask yourself: - Why does this question matter? - Will the findings help guide patient care, education, or policy? - Bounce your idea off colleagues or mentors—they can offer fresh perspectives to ensure your question is meaningful. 🗝The Key Takeaway🗝 You don’t need to "discover" a research question out of thin air. Start where you are. Look at your daily work, identify challenges, and build from there. With the right context and a clear framework, impactful research questions will follow.

The image outlines the seven types of research gaps, which can be described as follows: 1. Evidence Gap: This refers to a lack of empirical data or research to support a hypothesis or theory. For example, if there's a claim that a certain teaching method improves student engagement but there's no concrete data to prove this, there's an evidence gap. 2. Knowledge Gap: This is when there's a lack of understanding or information about a particular area. An example might be the long-term effects of a new medication, which have not yet been studied or understood. 3. Practical-Knowledge Gap: This exists when there's a disconnect between theoretical knowledge and its application in real-world scenarios. For instance, engineers may understand the physics behind a new material but don't know how to use it effectively in construction. 4. Methodology Gap: This occurs when current research methods are inadequate to explore a particular question. For example, existing surveys may not capture the full range of attitudes toward telecommuting, indicating a need for new research techniques. 5. Empirical Gap: This gap is present when there's a lack of empirical evidence or research on a particular question or phenomenon. For example, there might be very few studies on the effects of social media usage on the elderly, creating an empirical gap. 6. Theoretical Gap: This refers to the absence of theories or models that can explain certain observations or phenomena. An example could be the lack of a unifying theory to explain the different patterns of social behavior observed in online communities. 7. Population Gap: This gap exists when research has not included certain groups or populations, which may lead to results that are not generalizable. For instance, if clinical trials of a drug have only been conducted on adults, there's a population gap regarding its effects on children. These gaps often highlight areas where further research is necessary to advance knowledge, improve practice, or refine theoretical models. Identifying and addressing these gaps is a crucial part of the research process in any field.

👩🏫 Coaching doctoral students through research question (RQ) revision is one of the most rewarding and revealing jobs I have. Recently, I was working with a grad student whose interview-based study explored how high school English teachers experience writing instruction. Her RQs were thoughtful, but one of them risked nudging participants toward a particular kind of answer, a “leading question,” in qualitative terms. We discussed ways to reframe it: Instead of “What training do teachers need...,” try “How do teachers talk about the training that supports...” In that moment, we weren't changing the content of the question but rather exploring different ways to shape its meaning, tone, and implications by expanding her expressive toolkit. 🤖 She asked whether using ChatGPT or Claude might help with that kind of rewording. My response: Absolutely BUT only with a critical mindset. Language models can offer an amazing range of linguistic options. They’re great for brainstorming alternate phrasings or surfacing patterns we might not have seen. Here's what I told her: 🪞 Language models can be valuable tools for expanding our expressive range once we have clarity of communicative intent and conceptual stance. 🪞 Because language is never neutral, these tools can subtly redirect our ideas under the guise of 'wordsmithing.' We have to treat their outputs as ideologically loaded options to be critically sifted. And this is true whether we’re writing a research question, a mission statement, or a LinkedIn post. Words aren’t just words. They’re meaning-making tools. 🧭 Let the thinking lead the language, not the other way around. 🧭

Constructing Research Questions: Doing Interesting Research" 🎓🔍 OnlineClassHelp.Net This article explores the art of crafting compelling research questions and how they shape the quality and impact of academic inquiry. It emphasizes that strong research questions drive innovative, relevant, and thought-provoking studies. The text also highlights how researchers can formulate engaging and significant questions to contribute meaningful insights to their fields. 🧐 Key Insights ✅ Why Research Questions Matter in Academic Research A well-constructed research question guides the entire study 📚 It defines the research focus, scope, and relevance 🎯 Strong questions lead to theoretical advancements and real-world applications 🌍 ✅ Characteristics of a Good Research Question Interesting: Sparks curiosity and contributes to the field 🧠 Original: Addresses a gap in knowledge or challenges assumptions 🔄 Clear & Focused: Avoids ambiguity and broadness ✍️ Feasible: Can be researched with available data and methods 📊 ✅ Strategies for Constructing Strong Research Questions Problem Identification: Finding a gap in existing literature 📖 Reframing the Question: Looking at issues from different perspectives 🔄 Using Conceptual Frameworks: Structuring the question with clear variables 📊 Engaging in Peer Discussions: Refining ideas through scholarly debate 🗣️ ✅ Common Pitfalls to Avoid Overly Broad or Vague Questions: Leads to unfocused research ❌ Unanswerable Questions: Lacks empirical foundation or feasibility 🚧 Ignoring Context & Relevance: Disconnects research from real-world applications 🌎 ✅ Best Practices for Interesting Research Ask "Why?" and "How?" to uncover deeper insights 🔎 Challenge existing assumptions and theories 🏗️ Connect research to current societal or academic debates 🎭 Seek interdisciplinary perspectives for richer inquiry 🌐 📢 Final Thought: 🔹 Crafting a strong research question is essential for producing impactful research. 🔹 Engaging, well-structured questions drive meaningful contributions to academic and professional fields. 🔹 Innovative thinking and structured methodologies help create research that stands out and influences change. 🚀📚 #ResearchQuestions #AcademicWriting #ScientificInquiry #ResearchMethods #CriticalThinking #HigherEducation #PhDResearch #ThesisDevelopment #ScholarlyWriting #KnowledgeCreation #InnovativeResearch #LiteratureReview #InterdisciplinaryResearch #ScientificDiscovery #StudyDesign #CuriosityDrivenResearch #EmpiricalStudies #QualitativeResearch #QuantitativeResearch #ResearchImpact

96% of our knowledge of humans comes from 12% of the world's cultural contexts. Our understanding of humans needs to stop being so WEIRD. Western. Educated. Industrialized. Rich. Democratic. The study of human development specifically has a representation crisis: A 2023 study found that 84% of studies relied exclusively on data from geographical regions inhabited by less than 7% of the world’s population. This is more than just bad science. These biases in our research directly shape how we define “good” babies/parents: ⇢ Attachment measures standardized on Western families pathologize cultural caregiving practices around the world ⇢ Developmental assessments fail to account for cultural variation in milestones ⇢ Mental health screening tools assume nuclear families and individualistic values Here's your action item. First, ask yourself: Leaders: Do your policies account for diverse family structures and ways of learning? Maternal care providers: How are your assessment tools validated across cultures? Policymakers: Whose development is centered in your early childhood initiatives? Researchers: Who designs your research questions and methods? Now, apply 5 ways to combat these biases: 1. Re-examine your measurement tools - Validate assessments across cultures - let cultural experts lead tool development - Question Western-centric assumptions 2. Challenge your frameworks - Question "universal" theories - Consider cultural epistemologies - Recognize multiple pathways 3. Transform your training - Include cultural humility education - Center diverse family structures - Challenge deficit-based perspectives 4. Adjust your implementation - Allow flexible delivery methods - Adapt to local caregiving practices - Support indigenous knowledge systems 5. Share power - Let communities lead research design - Support community-led initiatives - Redistribute research resources Remember: Good science requires representation. Better representation creates better science. ↓ What’s an example from your work that made you question whether an approach was actually inclusive? How have you overcome cultural biases? - • • • • • • • • • • • • • • • • • • • • • • • • • • • For more on research + babies ↓ Follow Emily Little, PhD Join my newsletter: https://lnkd.in/gCJa6pM5