Yesterday I wrote about the many different ways I use AI to enhance my geography lessons.

However, I as well as being Head of Geography in my school, I also have a number of whole-school roles, so using AI to work more efficiently has become a complete lifesaver for me!

Here are some examples of the ways in which I use AI to manage my workload...

Writing letters for trips

• Add a few simple details such as time, location, clothing, purpose of the day, food etc, and AI will create you a warm and professional letter to send to parents/carers
• Improves your grammar, spelling and punctuation – beware of Americanisms and ask it to use English spellings

Step-by step instructions

When I can’t remember short-cuts or need to edit and can’t work out how, I now ask AI to give me step-by-step instructions. It covers a wide range of Microsoft applications e.g. Word and Excel but also can often answer my questions on ARCGIS when I can’t remember how to add a layer or manipulate data sets.

Filtering spreadsheets

I use AI to filter large Excel sheets to focus in on what is important to me. Large organisations often send out Excel spreadsheets, for example, invigilation for summer exams or roles and times for sports day. Trawling through to find where I need to be and what I need to be doing is now far simpler as I pop the spreadsheet into AI and ask it to produce my timetable of dates, times and where I need to be.

Summarising the key points in documents or academic articles

This is particularly useful at A Level! With the vast amount of information online, it can be overwhelming trying to find what you need. I use Microsoft Copilot to upload a document for example the IPCC sixth report and asked it to create a summary how tropical storms are expected to change in the future. It creates a 3-section summary on Observed and current trends, Projected future trends, and regional impacts. These are presented in short bullet point form, so the key information is quick and easy to read and then used to update my lesson.

Creating student feedback

This has been a game-changer for me! I have started using audio voice notes into text as I flick through each student’s book, identifying specific ‘what went well’ and ‘even better if’ for a specific piece of work or for looking over a couple of lessons work. The brief text can be added to AI and with a short prompt will create a more fluent feedback response per student which can be printed off and shared. It halves the time it takes to mark books, and the feedback is personalised providing pupils with feedback to feedforward.

Diagnostic testing feedback

I have used Microsoft Copilot for diagnostic testing feedback. I have designed a series of MS Forms which test specific geographical skills and students complete these alongside their regular written exam paper questions. I use these as formative assessments to identify specific weaknesses in individual students but also across the whole class/ year group, so I can adapt lessons accordingly including more of certain skills or supporting specific students to mastery. To do this, the MS Form questions are categorised and then a prompt written describing which question is assigned to which column and then asking for an overview for each student creating personalised feedback.

GCSE and A-level results scrutiny

This is vital as a Head of Department and this year my task was successfully assisted by AI adding the Enhanced Results Analysis (with names removed), it was able to home in on specific trends and offer really precise advice on areas to target this coming year. The level of detail was really helpful as a HoD, to identify some clear priorities and adaptations to our current Year 11 curriculum to address those weaker areas whilst allowing me to reflect on the strengths and think about the strategies we had used which had led to this success.

Creating personalised mock feedback

I use AI to create these for students and parents which highlighted weaker areas and set targets for further improvement with tasks to bridge the gap. Last year, after marking the mock papers, I created short note-form sentences on strengths and weaknesses (this can be done using audio notes to text) and the sections they scored more highly on. Each paper took a couple of minutes each. I then put the notes into ChatGPT (names removed), prompted it with a range of statements, some suggestions of the types of tasks which could be set as a target and then added brief audio notes per student. This allowed me to give individualised detailed feedback which students and parents found very useful in our post-mock parents evening. It provided a clear focus and concrete activities for students to focus post-mocks.

I am going to talk about this last one in more detail in a blog tomorrow.