Research Question Refiner
Research Question Refiner
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Description
Gradually narrow broad interests, real-world phenomena, literature leads, or preliminary results into researchable, testable questions. Use an evidence ledger to identify gaps in data, mechanisms, boundaries, method comparisons, and contradiction synthesis; rank candidate questions through hard gates and sensitivity analysis; and develop a minimum viable research design for the top choice.
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WriteAcademic Research Question
• Diagnose candidate topics: Identify overly broad topics, unclear subjects, uncontrolled boundaries, and false novelty before determining whether the topic is ready to be finalized. • Narrow the research scope: Remove nonessential subjects, variables, and objectives to reduce “trying to study everything” to one central question. • Derive the core question: Identify a single research direction based on subject clarity, question sharpness, scope control, and fit with available materials. • Generate a standardized title: Produce one Chinese title aligned with the research question, with an English title and a specific contribution statement when needed. After opening, say: “I have 3 candidate topics and want to submit to a CSSCI journal. Help me finalize the topic.” It will first check the research subject, core question, scope, and practical constraints, then provide a well-supported final research question. If information is insufficient, it will ask follow-up questions instead of forcing a polished title. Suitable for: Researchers with candidate topics who are struggling to choose one / scholars who need to focus quickly before submission / anyone who does not want to be rejected by a reviewer’s one-line criticism that the research question is unclear. ✅ This version has undergone two months of refinement, testing, and iteration.
TRIZ Research Innovation Coach
TRIZ Research Innovation Coach is a system for discovering innovative research problems and generating research topics for academic work. Centered on TRIZ contradiction resolution, the nine-screen method, laws of evolution, resource analysis, and thinking-trap diagnosis, it uses a rigorous AFP-style step-by-step process to transform vague research challenges into clear scientific questions, actionable research plans, and theoretically compelling topic directions. The system also includes dual review by a thinking coach and an academic editor, assessing research subjects, theoretical mechanisms, evidence pathways, methodological fit, and degree of innovation. It helps users overcome common challenges such as “I can’t find an innovation,” “I can only compromise,” and “my methods are limiting me,” while building transferable and reusable innovative thinking skills.
TRIZ-Academic Problem Discovery v2.0
The core dilemma researchers face when selecting a topic is often not 'having no problems,' but 'not seeing the real problem.' TRIZ-Academic Problem Discovery v2.0 uses the AFP 3.1 three-layer architecture, integrating 14 core TRIZ tools to discover scientifically rigorous problems with theoretical tension from ambiguous dilemmas. Core Capabilities: 1. 1+4 Matrix Architecture — 1 router (8-signal diagnosis) + 4 execution paths (perspective expansion, conflict resolution, solution construction, thought diagnosis) 2. Discipline Adaptation — Automatically adapts TRIZ tool emphasis across three modes: STEM (technical contradictions), humanities and social sciences (social contradictions), and management (organizational contradictions). 3. In-depth Operation of 14 TRIZ Tools — Nine-screen method, laws of evolution, ideal final result, ARIZ, separation principles, STC operator, resource analysis, functional analysis, etc., each with an operational template. 4. B-Core Nine-Dimension Quantitative Audit — Structure, logic, tool accuracy, discipline fit, innovativeness, conflict resolution, anti-compromise, executability, theoretical tension; a score of ≥80 is required for delivery. 5. Three-Level Degradation Strategy — Automatically degrades to general innovation methodology when TRIZ tools are not suitable. Suitable for: PhD and master's students, early-career researchers, interdisciplinary researchers, and supervisors. Supports both Chinese and English.
Information
- Version
- v3
- Last updated
- Runtime credits
- Usage-based
- Models
- Auto
