Search

8661 results for: ‘global learning outcomes’

  • Professional Development

    Module code: NU1020 This module is facilitated using a range of approaches delivered in the main in multi-professional groups that include students from Physiotherapy, Midwifery and Nursing as well as single profession groups.

  • Professional Development

    This module is facilitated using a range of approaches delivered in the main in multi-professional groups that include students from Physiotherapy, Midwifery and Nursing as well as single-profession groups.

  • Course documentation

    Browse programme specifications for courses for each year of entry for the last five years.

  • Research archive

    Information about all past RCMG research projects and events can be found here

  • Research shows human impact forms striking new pattern in Earths global energy flow

    The impact humans have made on Earth in terms of how we produce and consume resources has formed a ‘striking new pattern’ in the planet’s global energy flow, according to research led by Professors Mark Williams and Jan Zalasiewicz from the Department of Geology.

  • Regulations governing professional Doctorate programmes: Specific learning difficulties, disability, and long-term medical conditions

    .

  • Access to facilities and what's included

    The University of Leicester’s on-campus facilities are available to all AIOU course delegates and postgraduate students.

  • Quizzes in Reflect recordings

    Posted by mmobbs in Leicester Learning Institute: Enhancing learning and teaching on November 13, 2018 Did you know you that you can add quizzes to your Reflect recordings? This feature can add a level of interactivity to recordings and presents a number of learning and...

  • Leicester Lecture to examine profound impact of current global trends on future health and medical care

    Our prestigious Frank May Clinical Sciences Lecture series will feature the forthcoming lecture 'How health in the U.K. will change over the next 20 years; the good and the bad' on 23 October.

  • Machine learning reveals clues to improved weather forecasting in our atmosphere

    Inspired by statistical mechanics, scientists co-led by University of Leicester applied algorithms designed to study molecules to atmospheric data and identified patterns in atmospheric fields that give clues to when weather variations will occur

Back to top
MENU