2020 Learning Technologist of the Year Awards

Celebrating excellent research and practice in Learning Technology

The ALT Learning Technologist of the Year Awards celebrate and reward excellent research and practice and outstanding achievement in Learning Technology. Established in 2007, the Awards have established a benchmark for outstanding achievement in Learning Technology on a national scale and attract competitive entries from the UK and internationally. All entries are reviewed by an independent judging panel chaired by the President of ALT.  

The Awards continue to be open for entries until Wednesday 2 September 2020.  We are contacting everyone who has made an entry before 11 May to offer the opportunity to update their entry in light of the extended deadline.
 
The Learning Technologist of the Year Awards Ceremony will take place on 26 November 2020 as part of ALT’s Online Winter Conference. 
 

About the Awards

Award categories

The following award categories were awarded:

  1. Learning Technologist of the Year (individual)
  2. Learning Technologist of the Year (team)
  3. Learning Technology Research Project of the Year

Judging panel

The expert panel of judges is chaired by Martin Weller, President of ALT. The panel represents expertise from different sectors and countries, bringing together a wealth of experience in Learning Technology. The 2020 judging panel are:

Team & Individual Award Judges:

  • Martin Weller - President of ALT 
  • Matt Cornock - Online CPD Coordinator, STEM Learning
  • Lizzie Seymour - Learning Technlogy Officer, The Royal Zoological Society of Scotland
  • Sharon Flynn - Project Manager Enhancing Digital Teaching & Learning, Irish Universities Association
  • Peter Bryant - Associate Dean (Education) and Associate Professor of Business, University of Sydney
  • Karen Howie - Head of Digital Learning Applications & Media, University of Edinburgh

Research Project Award Judges:

  • Michael Flavin - Senior Lecturer in Global Education, Kings College London
  • Gail Wilson - Associate Professor, Southern Cross University, Australia
  • Yi-Shan Tsai  - Research Associate, University of Edinburgh
  • Richard Walker -  Head of the Programme Design and Learning Technology Team, University of York

Community Choice Award

All short-listed entries are asked to supply a short video (with subtitles, no longer than 3 minutes) and supporting information for the public vote deciding the Community Choice Award. The public vote will be open from 2 November. If you are looking for inspiration, have a look at the entries from last year's finalists and the recordings from last years webinar series

Award Ceremony

The Awards will be presented during the ALT Online Winter Conference, 25-26 November 2020. The judging panel will make the following awards: First, second and third prize as follows: 1st prize £1000; 2nd prize £500; 3rd prize £250. The Community Choice Award, voted for openly in November, is also awarded. Finalists (up to two for teams) will be invited to attend the Online Winter Conference to receive their awards. 

Winners of the Awards

You can find out more about the winners of the Awards from previous years here

Winner of the Awards from previous years

How to enter

The awards are free to enter and are open to individuals and teams based anywhere in the world. If you'd like to see what it takes to win, have a look at the entries from last year's finalists and the recordings from last years webinar series. Entries are open until 2 September 2020.  

Entry form

You need to complete all sections of the appropriate online entry form. Entries will be judged on the basis of the information you provide and the evidence you refer to. We acknowledge all entries via email. 

  • Entry Form A: Learning Technologist of the Year (individual or teams)
  • Entry Form B: Learning Technology Research Project of the Year

Short-list

The judging panel reviews all entries and the highest scoring entries in each category are short-listed. All entries will be notified whether they have been short-listed.

Interviews for short-listed entries

All short-listed entries will be invited for an interview (provisionally scheduled for 8 October), online. Interviews will be 25 min long, and you will be asked to give a 10 min presentation followed by questions from the judging panel. 

Finalists

Following the interviews all short-listed entries will be notified and Finalists invited to the Award Ceremony. Finalists will be asked to supply a short video (under 3 minutes with subtitles) and supporting information for the public vote deciding the Community Choice Award. The public vote takes place in November. 

Judging criteria

Entries are judged (from the completed entry form, and, if short-listed, at interview) in answer to the following criteria and questions:

Learning Technologist of the Year

Learning Technology Research Project of the Year

The judging criteria are informed by the CMALT principles. We include these here for information: 

What makes your work THIS YEAR an outstanding achievement in Learning Technology? 

('this year' refers to the 12 months prior to submitting your entry)

What makes this research project THIS YEAR an outstanding achievement in Learning Technology?

('this year' refers to the 12 months prior to submitting your entry)

 
What makes your/your team's work excellent? What makes this research project excellent? A commitment to exploring and understanding the interplay between technology and learning
How did you develop and support this achievement? A clear, credible statement of what methodological approach was taken and which, if any, ethical implications were considered A commitment to keep up to date with new technologies
Strong evidence that your work has made a significant impact on practices within the your or your team's organisation, community, or sphere of influence Strong evidence that the project made a significant contribution to Learning Technology, including evidence of its impact A commitment to communicate and disseminate effective practice
Clear explanation of how others may learn from your work and what have you done to enable others to do so

Clear explanation of how others may learn from this research project and what have you done to enable others to do so

An empathy with and willingness to learn from colleagues from different backgrounds and specialism