Meaning needs and features of a good research problem / design
Needs:
1. Clear significance: The research should address a significant problem or knowledge gap, with potential to:
- Contribute to theory or practice
- Improve understanding or outcomes
- Address a practical issue or concern
2. Specific objectives: Clear, concise, and measurable goals, including:
- Research questions or hypotheses
- Expected outcomes or findings
- Methodological approaches
3. Relevance: Alignment with the research area and potential impact, considering:
- Theoretical frameworks and concepts
- Practical applications and implications
- Emerging trends and issues
4. Feasibility: Access to resources, data, and participants, including:
- Availability of data or samples
- Access to participants or settings
- Adequate funding and support
Features:
1. Specificity: Well-defined and focused research question or hypothesis, avoiding:
- Vague or broad questions
- Multiple unrelated questions
- Unclear or ambiguous language
2. Originality: Unique contribution to existing knowledge or theory, considering:
- Novel research questions or approaches
- Innovative methods or techniques
- Unexplored populations or contexts
3. Measurability: Quantifiable outcomes or observable phenomena, using:
- Reliable and valid measures
- Appropriate data analysis techniques
- Clear and concise reporting
4. Achievability: Realistic expectations and timelines, considering:
- Available resources and support
- Researcher's expertise and experience
- Potential obstacles or challenges
5. Relevance: Connection to practical applications or theoretical frameworks, including:
- Implications for policy or practice
- Contribution to existing theories or models
- Potential for generalization or transferability
6. Ethical considerations: Respect for participants' rights, privacy, and confidentiality, adhering to:
- Ethical guidelines and regulations
- Informed consent and participation
- Confidentiality and anonymity
7. Methodological soundness: Appropriate research design, sampling, and data analysis techniques, considering:
- Research approach and methodology
- Sampling strategy and sample size
- Data collection and analysis methods
8. Potential impact: Contribution to knowledge, practice, or policy, with potential to:
- Improve understanding or outcomes
- Inform decision-making or practice
- Address social or economic issues
9. Interest and motivation: Researcher's passion and investment in the project, ensuring:
- Sustained interest and engagement
- Motivation to overcome challenges
- Commitment to quality and rigor
10. Clarity and concision: Easy to understand and communicate, using:
- Clear and concise language
- Simple and intuitive design
- Effective visualization and presentation
Additionally, a good research problem and design should also consider:
Theoretical framework: Connection to existing theories or concepts
Literature review: Understanding of previous research and knowledge gaps
Methodological flexibility: Adaptability and adjustment as needed
Interdisciplinary approach: Integration of multiple perspectives or disciplines
Collaboration and teamwork: Involvement of experts or stakeholders
Ethical approval and compliance: Adherence to ethical guidelines and regulations