AI Discovery Zone @ EdUHK Library's Research Support

Master AI for Research This Summer & Get Your AI for Research Certificate 

This bootcamp is organised by Scite.  Throughout the bootcamp, you'll receive emails from scite including:

• Session reminders with Zoom links
• Pre-session preparation materials
• Practical exercises and resources
• Tips for maximizing your AI research skills
• Certificate completion updates

Get Your AI for Research Certificate

Remember: Attend any 3 out of 4 sessions (with one industry session mandatory) to earn your AI for Research Certificate.

Registration

CNKI has recently launched AI Academic Research Assistant, an advanced tool that leverages artificial intelligence technology to assist in scientific research. This new version is based on CNKI's vast academic resources and the intelligent technology of the HuaZhi large model, closely integrating AI large model technology, high-quality data, and research scenarios, aiming to enhance efficiency in key areas such as literature retrieval, reading, and academic writing. 

CNKI has provided a trial for the EdUHK current students and staff on the “CNKI AI” services till Oct 31 2025. The services have integrated with DeepSeek R1. Services included: 

• Chatbot grounded on CNKI contents

 • Research assistant based on single article / a collection of articles (up to 10) 

• Writing assistant 

You can test the services by visiting this URL within campus IPs: https://aismart.oversea.cnki.net/ 

You will also need to create a personal account to use the services. 

Though there is no limit on the number of accounts that can be created, each account has its own quota for various services:

Highlight Summary

EBSCO now provides a Natural Language Search mode that uses LLMS to allow you to search using everyday language. It understands what you’re looking for, even if you ask in full sentences, and it delivers better results.

How Does Natural Language Search Work?

Natural Language Search (NLS) lets you search the way you naturally speak or write—no need for special keywords or complicated search rules. No need to use the complex keywords or Boolean operators, for example, you can ask the question "What is the best education for children?" instead of using (education OR schooling) AND (child* OR kid* OR student* OR pupil*) AND (best OR optimal OR effective) AND ("academic achievement" OR outcomes OR “learning results”).

Here is the comparison table of Traditional Search vs. Natural Language Search:

How to Use Natural Language Search Mode?

STEP 1: Go to “Advanced Search Mode” from the basic search.

STEP 2: Under “Search options”, you can select “Natural language” to turn on this mode.

STEP 3:  To turn on NLS mode immediately, simply toggle the Natural Language switch in basic search.

Step 4:  Now let's test NLS mode with our sample question: “What is the best education for children?” Observe how NLS generates 810,595 comprehensive results while the traditional search generates a limited 250 records.

You'll notice that the NLS mode retrieves relevant results containing conceptually related terms, such as “teaching”, “effective”, and “students”—even though these exact words weren't included in our original search query. This demonstrates a key advantage of Natural Language Search: unlike traditional keyword-based systems, NLS leverages Large Language Models (LLMs) to interpret the semantic meaning behind your question, eliminating the need for exact keyword matching.

Recommendations from the Library:

To get the most out of EBSCO's search tools, the following strategies for combining NLS and traditional search mode are:

•  Begin with NLS to explore topics broadly using conversational queries
• Switch to traditional search to refine results using precise keywords, Boolean operators, or field tags

The Library has already subscribed to Scite, a powerful AI research tool designed to elevate your research experience. 

Our subject guide, “AI Tools for Your Research: Scite” explains its features and provides instructions for getting started. Recently Scite has launched a new feature, Tables in Scite Assistant, a major advancement that enables researchers to extract, organize and analyze data from scientific literature. 

How to Use AI Tables?
Scite's AI Tables do more than just summarize papers—they help you extract specific data points, methodologies, and outcomes directly from scientific articles.

Step 1: Go to Scite Assistant and select “Use Table Mode” for the new Table function.

Step 2: Click “Add Column” and type “name” and “instructions” for the new column. You can choose the length of the answers, from short to long.

Step 3: Continue creating new columns, such as “Methodology,” “Key Findings,” and others, to organize and analyze your data effectively.

In addition, you can export all references with all columns in various formats, such as CSV, ris and BibTeX.

New Improvements to Scite Assistant

OpenAI o3 mini + Reasoning

A new AI model, OpenAI o3 mini, now integrates advanced reasoning capabilities and is being utilized by Scite. Scite enhances its platform by combining its own datasets and access to scholarly content with powerful AI models, offering researchers tools for analysis and discovery.

What is “Reasoning”?

Reasoning Models: These are advanced AI systems that go beyond simple pattern recognition (which is what most standard AI models do). Instead, they are designed to:

1. Think through problems internally before answering.
2. Consider multiple approaches to solving a question.
3. Evaluate the accuracy of different possible answers. 
4. Plan structured and coherent responses.
5. Solve multi-step problems methodically.

Covidence = “Collaboration” + “Evidence”, is a powerful web-based platform designed to simplify and accelerate the systematic review process. Researchers and students may feel the systematic review workload is overwhelming, from screening thousands of articles to extracting data and resolving conflicts. 

What can Covidence do?

Covidence can support key stages of the review process, including:

• Importing references from databases

  How to import references

• Screening titles and abstracts to identify relevant studies

  How to screen by title and abstract

• Full-text review to assess eligibility

  How to screen by full text

• Data extraction and quality assessment of included studies

  Data Extraction

  Quality Assessment

• Collaboration with team members, including conflict resolution

  How to invite a team member to a review

   

Get Started with Covidence

While the library does not currently have a subscription to Covidence, a trial has been established for all EdUHK members until April 15, 2025. Trial accounts can only be created by invitation. If you are interested in trying it out, please inform us at myhyiu@eduhk.hk, and the library will send you an invitation as below:

Invitation

Note: When you fill in the required information to complete the registration, remember to use your EdUHK email.

Training Resources from Covidence

Covidence has its own YouTube channel with video tutorials to to guide you through the main features of the system. 

Useful Resources from Covidence

• Quick Step-by-Step Guide
• Data Extraction for Intervention Systematic Reviews
• Covidence blog - Follow Covidence's blog to find helpful resources, insights and product updates
• Covidence Webinar - Attend the next live session or watch the latest recording

Conducting a literature review can feel overwhelming. With so many research papers published yearly, finding the most important and relevant studies can be tough. That's where Litmaps comes in. This article will show you how to use Litmaps for an efficient literature review.

Note that EdUHK Library does not currently have a subscription to Litmaps. This introduction to the tool is solely for educational and research purposes.

What is Litmaps?

Litmaps is an AI-powered research discovery tool that creates interactive visual maps of academic literature. By analyzing citation networks, Litmaps can help you: 

• See how literature connects
• Find relevant articles
• Not miss important papers
• Get updated on changing literature

• Stay organized

   

Visualize Your Research with Litmaps

Step 1: Go to Litmaps and set up a free account. We start by looking for just one paper on your topic. Our research topic is “The Impact of Virtual Reality on Learning Outcomes in Higher Education”.

Tip: Look for articles with more citations. This will make it easier to find more related literature in the next step.

Step 2:  Select one article as your starting article and click “Explore Related Articles” 

Step 3: The initial Litmap provides a foundational overview of the scientific literature connected to your starting article, but it’s only the beginning. To explore more topics, click "More like this" for articles that interest you.  Then, you can click "Refresh" to see new recommendations.

Step 4: Tag articles by assigning them different keywords and color codes. Over time, this will help you create a map similar to the one shown below. What's more, Litmaps offers multiple options for sharing your visualization map with others.

Monitor Your Map to Stay Up-To-Date

After completing a literature review, it can take months or years for works to be published. To stay up to date, the best approach is to enable the ongoing monitoring of your map. Simply go to the map’s homepage and click “Enable Automatic Monitoring”. Once activated, Litmaps will automatically run your map through its search algorithm every week and notify you if any newly published articles match or connect to your research.

Summary

A successful literature review tells a concise story about the topic, leaving the reader satisfied with the field's current state while addressing gaps and framing new research.

Litmaps displays the most relevant papers in batches of 10, organized in a unique graph format. This graph highlights highly cited papers (top) and recent publications (right), making identifying influential and up-to-date research easy.