The FMS Workload Reporting System (WRS)

Collecting and monitoring data relating to academic workloads

managing workloads

Universities have a responsibility to ensure that the workload allocations in their units are consistent and in line with their policies on workload allocation.

To achieve this there needs to be an accessible tool that can the capture agreed academic activities carried out on behalf of the University.

The FMS Workload Recording System (WRS) has been developed to allow staff to self-report their workload through a more transparent, equitable and collaborative process.

It is anticipated that this will lead to more informed PDR conversations, improved support around career development & wellbeing issues and allow equality diversity & inclusion considerations to be part of workload planning.

So, what does the system collect?

Previous work on collecting information around teaching activities highlighted the following key points:

  • The scope of the system needs to be wider than just teaching related activities
  • The auto population of activities through mining existing data sources was not always reliable 
  • Self-reporting is essential to ensure accuracy of the data collected
  • Each activity needs to be standardised using its own tariff formulae, for example:
                tutees reported hours = no of tutees x 5
                PARTNERS summer school lead hours = (no of students x 0.1) + 10

A working group was set up to specify what activities were to be recorded, each with its own tariff formulae to convert that activity into hours. These activities when they grouped into three distinct areas:

  1. Teaching & Assessment
    • Taught Sessions
    • Assessment & Feedback
    • Tutees & Projects
    • Other
  2. Research & Innovation
    • Research Projects
    • Research Awards
    • Research Applications
    • Others
  3. Management, Administration & Citizenship
    • Unit
    • Faculty
    • University
    • External/Other

The system was developed in phases:

Phase I (4 months)

Develop the website with an individuals summary view and a collection of self-reporting forms, all driven by a database of workload questions and augmented by data from existing sources.

individual worklaod summary
workload self-reporting forms

Phase II (one month)

Release website to a small pilot group of users to collect user feedback. Development of basic reporting tools (user activities, evaluation reports and cohort workload summaries).

cohort/unit workloads

Phase III (4 months)

Refine any existing usability issues raised by pilot group and develop the advanced reporting & administration tools required for full release.

Phase IV

Full release of the system.

So where are we now ?

The FMS Workload Recording System (WRS) went live in July 2022 to a pilot group of 158 academics.

The next stage (PHASE III) is to review what additional features or changes to the system are required and then prepare the system for its release to the whole Faculty.

3D Holograms in Teaching – NULTConf

Dr Aleksey Kozikov, School of Mathematics, Statistics and Physics presented on 3D holograms and showed examples of using them in lecture theatres.

Dr Aleksey Kozikov discussed the uses of 3D holograms and showed examples, including the projection of lab equipment, objects, and presenters into lecture theatres.

In traditional teaching approaches, students are taught in a sitting and listening manner. To provide a more participatory learning experience, help students to visualise, clarify the taught concepts and enhance the way students learn, we are planning to introduce 3D “holograms” into the real space learning environment. We will discuss ideas to use holograms of research facilities and extend to any practical activities that are otherwise not possible to do in a lecture theatre

This can enhance in-person teaching and could be a resource used in FMS.

There could be live projections of speakers or leading experts in the field, who could not be there in person. They could join the conversation from abroad but look like they are physically in the room with other speakers.

Lecturers could explain a piece of equipment which was previously too cumbersome to transport to lectures. Students could see a visible representation of equipment beside them as they discuss it.

We could show experiments without the person and equipment physically being in the room. This could be done in multiple rooms simultaneously, relieving the need for large lectures halls or repeated sessions.

Resources

Faster Captioning

This post details some easy tips and tricks to speed up your caption editing process using Notepad and Word.

This post assumes users are using Panopto (ReCap), therefore Panopto guidance is linked for uploading and downloading caption files. Guidance for other products such as Streams, Vimeo and YouTube can be found on their own sites.

In FMS TEL many team members regularly work with captioning videos – whether these are our own instructional videos or webinars, or student learning materials. Recently a few of us in the team have been talking about how we caption videos – specifically, what processes we use. There are some of us in the team who use the inline caption editor in Panopto, and use speed controls to manage the flow of speech so they can correct as they go. Others prefer to download the caption files and work with them in a separate program.

Both methods have their pros and cons. Working within the online editor is often best for short videos, or those with very few corrections to be made. Sometimes, though, it is easier to manage longer or more error-prone caption files in their own window. This gives more space to see what you’re doing – as long as you can avoid messing up the file structure. You can also use proofing tools in Word to speed things along or cut out repeated mistakes.

The rest of this post details some tips you can try to speed up your own process if not using the online editor.

You may find that for the bulk of the editing you don’t even need to be listening to the video – the errors can sometimes be evident just from text.

To work with captions outside of Panopto, you’ll first need to download the caption file. If there is no file to download, you’ll need to request automatic captions first. The caption file can be opened in Notepad. From there, you can edit each line of text separately. You must not change the file structure – so do not edit any of the other lines in the file, even the empty ones.

The file repeats in structure every 4 lines. The first is the sequence number of the caption, the second is the timestamp displayed in hours, minutes, seconds and milliseconds, the third is the spoken text and the fourth is an empty line.

Then, save the Notepad file. In its folder, right-click the file, select ‘rename’ and edit the file extension to .vtt instead of .txt (you may need to change your folder settings to view file extensions first). Then, upload your caption file.

Deciding WHAT to edit is a whole separate issue, but once you’ve made those decisions, Word’s proofing tools can help you target certain things more efficiently.

If you want to take advantage of some more proofing tools, try copy and pasting your entire file into Word. This will allow you to use tools such as Spelling and Grammar check to remove duplicate words or transcribed stuttering sounds, and can also draw your attention to other oddities. The Spelling and Grammar tool automatically moves you through your document, saving time scrolling and searching. As well as checking spelling, this can also help trim unnecessary words from the text, making it faster to read.

Find and Replace is useful, and can help…

  • If a name has been consistently misspelled – for example Jo/Joe.
  • If the speaker has a filler word that can be removed (I say “kind of” as filler so always search for and remove it from the captions!).
  • To replace key numbers or years that have been spelled out with their numerical representations (e.g. ninety-nine percent -> 99%).
  • Filtering out inappropriate language if it has been misheard by the auto software – if you see it once you can search the whole document quickly.
  • Filtering out colloquial spellings (gonna -> going to).

A good tip to ensure you only find whole words is to search them with spaces before and after the word itself. You can also use the ‘more’ option dialog and check the ‘whole words only’ box.

These extra options can help speed things up.

If you have been deleting a lot of items and adding spaces in their place, you might also want to do a find and replace for two spaces together and replace with one space. Run this a few times until there are no results. Similarly, you could look for comma-space-comma if you have removed a lot of filler.

These steps won’t fix everything, but can cut out some of the bulk and help speed up your process. After using these tools, read through the captions carefully again to fix any leftover errors.

Our team is growing!

Last month we welcomed Michael Hughes to the FMS TEL team, as Learning Technologies Developer.

Michael is one of six Web Developers within the team who create and maintain Web-based systems which support learning and teaching across the Faculty, University and beyond. He brings with him great enthusiasm and experience of developing innovative systems. One of his first projects is to work with the RolePlayNorth team to redevelop an old, but business-critical, system that has reached end of life. He will be co-developing this with Dan Plummer (FMS TEL systems usually have a least two developers, to help ensure nothing is one person deep!) and collaborating with the wider team in other activities.

“Coming from a manual labour background and specifically working in the Traffic management and Utilities industry for the past 8 years. Seeing a lack of development and online tools to help assist doing the job led me to learning how to code.

Industries like those are the backbone of the economy and the lack of basic tech was eye opening. Working one day I asked one of my more experienced co workers about the marker post locations (white sticks 100 meters apart on the motorway) which we used everyday to plan out roadworks. Finding out that most workers didn’t have the information where they are and if your traveling from say A69 or the A66 coming to the A1 you have no idea if you have to travel south or north to come south as to not miss your starting location for roadworks or even worse a car crash which could mean a 30 minute turn around if guessed incorrectly.

This idea pushed me to working on the project that got me the learning technologies position here at Newcastle University.”

Michael Hughes

We are excited to have Michael on the team and cannot wait to see what he will accomplish!