Being an A Level English Language teacher, my life revolves around unseen data of all types. Consequently, I spend a significant amount of my time thinking about how I can encourage students to engage with this in a meaningful way, and in a way which not only gives them confidence but also a structure to approach this data without becoming constrained and formulaic.
There is much debate in our household about the use of PEA / PEAL / SQUID or any other framework used by students to structure a response. As is very often the case, I had my instinctive thinking illuminated to me earlier this evening when with the usual clarity, the point was made that responding to a text in an initial interpretative way was a very different kind of reading to how we then subsequently write about that reading in an analytical response. I have had two great lessons this week – the kind of lessons which remind me why I love teaching so much – and what I had experienced, absolutely made clear the reality of this distinction.
How do you approach unseen data?
I have written before about how my biggest frustration as an English teacher is seeing analysis of a text devoid of any context – the kind of feature spotting approach which is mechanical at best, superficial and speculative at worst.
I have long trained students to think about the following in this order when they respond to a text:
- Ideas / Concepts
- Linguistic Methods
This approach ensures that they think about a text as existing, in what elsewhere I describe as a magical space, between producer and receiver. No text just exists. Both producer and receiver negotiate meanings based on all kinds of contextual information including the prior experiences and knowledge of those engaging with the text. This has to be the starting point of a response to a text, otherwise it simply becomes a case of what feature can be named, or how might this feature be artificially linked to why it has been used. It is also useful for students to think about the bigger ideas and concepts which are embodied within a text because of the contextual factors relating to that text. Once armed with that knowledge, students can then select and consider which linguistic methods have been used BECAUSE of these factors, not in spite of.
My students have become pretty good at training themselves to have the discipline to think like this and override their natural instincts to look for linguistic methods that they feel comfortable or familiar with. However, this isn’t always enough and I have plenty of students who when faced with an extract of data struggle to know where to start with engaging with it.
Ask questions, rather than look for answers
About a year ago, I was looking at some data with my students and thought to myself I wonder what would happen if instead of trying to look for answers within the text, they just asked questions. It was one of those great teaching moments. Suddenly there was no panic about what they should say, no worry about how they were going to respond, and no attempt to try to fit preconceived answers into the data. Instead, with an open mind and lack of pressure, they simply engaged with the text. I have repeated the activity many times since then but during my lesson on Monday, it naturally developed further.
Students still started by just asking questions. I asked them to think about questions in relation to context, ideas and concepts, and linguistic methods. There was no right or wrong question and it didn’t matter if they knew the answer or not. They had 10 minutes to do this and they had to keep going. Making them continue to ask questions for the full amount of time elicited some thoughtful questions that had far more depth than the initial ones.
Interrogating the questions
Once questions had been generated, we went through the process of determining which were irrelevant / or less important and which were more key. This was a good way for students to think about the issues with some of the questions they had asked – which ones would lead them to make speculative comments or guesses for example. It also got them to think about which were most useful or interesting.
Following this, students were asked to create chains between the three columns. Again, there was no right or wrong answer – the only stipulation was that a link had to be made across all three. Once this had been done, students then looked at the nature of their links. It very clearly allowed them to see where they had used the same linguistic methods to support their points which they, quite rightly, said would lead to repetition and a lack of range. They revisited this column and saw whether some would be better suited to support another point.
It became a very messy diagram:
but the thought process we went through led to some of the best responses I have seen from my students in relation to their response to data.
What did the students think?
At the end of the lesson I asked them to reflect on what they had found difficult or helpful about the approach. They made the following observations:
- It helped them to think first of questions as they knew the answers but the questions helped them to retrieve these.
- It encouraged them to engage more deeply with the text as they had to keep asking questions until the time was up.
- It enabled them to see that they had even coverage across the AOs.
- It provided a clear plan of the most interesting and important aspects of the data.
- The steps meant they did not jump straight to their initial thoughts, and the process of sorting and refining these sometimes elicited more useful analysis.
- Some raised concerns about the time the process took, but acknowledged it meant much of the hard work of their responses had been done for them when they came to write up their analysis.
What it has absolutely confirmed for me is that in our desire to help students respond well in exams to any text, fiction or non-fiction, by getting them to skip straight to the step where they write up their response to a text, we deny them the thinking that will get them there.