Core capabilities: What research tasks does the tool support? (e.g., literature review, data analysis, visualization, coding, writing assistance).
Data sources and coverage: What data sources can the tool access? (e.g., academic databases, web, specific datasets). Does it handle paywalled information?
Accuracy and reliability: How accurate and reliable are the tool's outputs? Can information be verified? Does it cite sources, and are those citations accurate ("hallucinations" are a concern)?
Non-English Languages: If applicable, how well does the tool process and generate content in languages other than English? What is the quality of translations?
Integration with other tools: Can the tool integrate with other research software you use (e.g., reference managers like Zotero)?
Reproducibility: Can the tool produce consistent results under the same conditions?
Scalability: Can the tool handle increasing amounts of data or more complex tasks as your research evolves?
Customization and fine-tuning: Can you customize the tool's parameters or fine-tune its models for your specific research needs?
Ease of use: How intuitive and user-friendly is the interface?
Accessibility: How accessible is the tool for users with disabilities (e.g., screen reader compatibility, adherence to web accessibility standards)?
Support & resources: What kind of support is available (e.g., documentation, tutorials, customer support)? How responsive and helpful is the support team?
Bias: Does the tool exhibit or mitigate biases in its training data and outputs? Are there efforts to ensure fairness and equity?
Transparency and explainability: Can you understand how the tool works and why it produces certain results? Is the decision-making process transparent?
Privacy and data security: How does the tool handle your data? What are its privacy policies? Are there any FERPA concerns for educational use?
Copyright and intellectual property: Does the tool comply with copyright laws? Is the training data properly sourced and cited? What are the implications for the ownership of AI-generated content?
Ethical Implications: What are the broader ethical considerations of using this tool in your research area? Does it raise concerns about misuse or unintended consequences?
Pricing model: What is the cost structure (e.g., subscription, one-time purchase, freemium)? Is it affordable for your budget?
Licensing terms: What are the licensing terms and restrictions? Are they suitable for your intended use (e.g., academic, commercial)?
Vendor reputation and reliability: What is the reputation of the company or institution behind the tool?
Update schedule & maintenance: How frequently is the tool updated? Is there ongoing maintenance and development?
Roadmap and scalability: What are the future development plans for the tool? Will it continue to evolve to meet future research needs?
Financial stability: Is the vendor financially stable, suggesting long-term support for the tool?
