AI Discovery Zone @ EdUHK Library's Research Support - Guides at The Education University of Hong Kong

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

Recent Posts

EBSCO's Natural Language Search mode: No More Keywords to Discover Research

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:Traditional SearchNatural Language SearchRequires keywordsAccepts complete questionsNeeds Boolean operatorsUnderstands natural phrasingOften needs multiple attemptsFrequently succeeds on first try 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 queriesSwitch to traditional search to refine results using precise keywords, Boolean operators, or field tags...

Explore Scite Assistant’s New AI-Powered Tables

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 AssistantOpenAI o3 mini + ReasoningA 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:Think through problems internally before answering.Consider multiple approaches to solving a question.Evaluate the accuracy of different possible answers. Plan structured and coherent responses.Solve multi-step problems methodically....

What is Covidence? - A Smart Way to Manage Your Systematic Reviews

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 databasesHow to import referencesScreening titles and abstracts to identify relevant studiesHow to screen by title and abstractFull-text review to assess eligibilityHow to screen by full textData extraction and quality assessment of included studiesData ExtractionQuality AssessmentCollaboration with team members, including conflict resolutionHow to invite a team member to a review Get Started with CovidenceWhile 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:InvitationNote: When you fill in the required information to complete the registration, remember to use your EdUHK email. Training Resources from CovidenceCovidence has its own YouTube channel with video tutorials to to guide you through the main features of the system. Useful Resources from CovidenceQuick Step-by-Step GuideData Extraction for Intervention Systematic ReviewsCovidence blog - Follow Covidence's blog to find helpful resources, insights and product updatesCovidence Webinar - Attend the next live session or watch the latest recording...

Litmaps: Visualizing Connections in Research Literature Review

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 connectsFind relevant articlesNot miss important papersGet updated on changing literatureStay 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. ...