LJMU Events and Appointments

Discover: Getting the most out of library resources 

Are you searching on Google and getting overwhelmed with the amount of information you are getting back?  How do you know what you are finding is the right type and quality for your assignment?  

Discover, the library search tool, is the simple way to search for relevant books, e-books, journal articles, databases and more.  

This session will show you how to access a range of resources and make the best use of the features of Discover, including advanced search, saving searches and items and creating search alerts.

So, if you are not sure how or where to start, or if you want to learn how to get better search results then this is the session for you.  

There will be opportunities to ask questions throughout the session.

This class will take place in Teams and a link will be sent out to attendees on the day of the event.  

Drop by and ask our Maths & Stats tutors for advice on topics in mathematics, statistics, or data analysis — quantitative or qualitative — including use of software, e.g. Excel, R, SPSS, NVivo, Matlab, Python,... Just remember to bring your maths, statistics, or data analysis query with you, as well as any relevant course materials or data.

You may also like to enrol on the Maths & Statistics Canvas NCSKI02 module to find resources and recordings of classes.

This session will be an introduction to the Declaration on Research Assessment (DORA). It will explain the principles within DORA and how researchers can think more responsibly in terms of their work, from research to supervision, hiring to giving appropriate credit. .

During this workshop we will discuss and demonstrate examples of DORA principles in practice, show where you can get more information, with lots of opportunities for questions.

Enrol on our Library Researcher Engagement Canvas page to access slides, recording and notes.

In qualitative research your data are words, pictures, audio or video, rather than the numbers used in quantitative research. NVivo is a program which helps researchers to organise their sources, and help with the coding and analysis of the data.

This session will provide a first introduction to NVivo, including:

• Getting data into NVivo
• Basics of coding
• Simple queries

Note: If you are using your own laptop, please install NVivo in advance from the student and staff download page

Further information will be posted on the Maths & Statistics Canvas module before the class.

This session will cover:

• the key features of literature reviews in different types of assignment

• how to prepare and plan one

• techniques for writing one 

This comprehensive session brings together best practices in online student engagement, focusing on both discussion board activities and social engagement tools within Canvas. The session aims to provide practical insights into designing engaging online activities, rooted in the experiences of LJMU staff and established distance learning practices.

Designing Interactive Discussion Boards: Learn how to create simple yet effective discussion board activities on Canvas. This includes sharing these activities with students, encouraging participation, and monitoring engagement.

Hands-On Experience: Get practical exposure by trying out various discussion board activities, enhancing your understanding of the tool's functionality and potential in engaging students.

Social Engagement in Blended Learning: Explore how to use existing Canvas tools to foster online social engagement, crucial for active blended learning environments. This segment is developed in response to the Academy's recent staff survey, highlighting the need for enhanced guidance in this area.

Practical Examples and Idea Sharing: We'll provide numerous examples of social engagement activities. There will also be opportunities to discuss and share ideas on how these can be integrated into your teaching practices.

Note: The Teaching and Learning Academy reserves the right to cancel the session if there are insufficient attendees.