Language Teacher Toolkit: Steve Smith's blog

Questions in French are a tricky area to teach for several reasons and it's tempting to just let students pick them up over time through input and repeated use. Some students will be able to do this, though few will figure out how to use the subject/verb inverted forms. They are formal and hard to learn..Most students will be able to use a limited range of high frequency questions hey have heard and used many times over ( Qu'est-ce que tu fais? Comment t'appelles-tu? Quel âge as-tu? Qu'est-ce que tu as visité? — that sort of thing.  In this post I'm going to share my tips for teaching questions to students of varying aptitude First, a quick reminder why questions are are a challenge. I think first of two types of questions: yes/no ( elle est grande? est-ce que'elle est grande? est elle grande? )  and open-ended question word questions ( qu'est-ce qu'elle fait. elle fait quoi, que fait-elle ). I then think of the structure of questions taking four form...

Multi-choice questions (MCQs) have long been a staple in language resources and exams, and with AI making them easier to produce than ever, I've been making growing use of them in my frenchteacher resources. In the past, I avoided them since they took so long to write. But while technology has simplified their creation, the art of designing  effective MCQs — whether for assessment or practice —still requires thought and precision. Here are some issues to consider when writing and using MCQs. Assessment 1. Objectivity One of the greatest strengths of MCQs is their objectivity . Unlike level-based mark schemes (or "rubrics" in the USA), where subjectivity can creep in, MCQs provide reliable scores, an important aspect of assessment. When designed well, they should offer a reliable snapshot of student listening and reading comprehension, or sometimes lexical and grammatical knowledge. 2. The three-option rule  Research and practice show that three options are statistically ...

 I'm not sure who first coined the terms fine-tuning and rough-tuning of input, but they have certainly become associated with the work of Stephen Krashen. In this post, I'll explain what the terms refer to and what they might mean for language teacher practice. We all know that a prequisite for first and additional language acquisition is input students can understand ( comprehensible input , to use Krashen's familar term). Krashen used the formula i + 1 to describe input which is at or just above the learner's current level. This would imply giving students aural and written texts, dialogues, etc, which contain a large majority of vocabulary students already know (Paul Nation and others write about 95-98% knowledge), using grammatical constructions which students are already familiar with. This is where the distinction between fine-tuning and rough-tuning of input comes in. There is no precise definition of this, but essentially if you finely tune the input you go out...

 I used the AI tools Deepseek and Le Chat (Mistral AI) to help me write this - a great example of cognitive offloading, as you'll see. So what is cognitive offloading and what implications are there for our work as language teachers and teacher educators? Cognitive offloading  is the process of using physical actions or external tools to reduce the immediate cognitive demand of a task. It's the act of shifting the burden of mental processing from your brain onto the environment to free up mental resources. A simple everyday example would be to use a calculator to do simple arithmetic. I've also come across the term auxiliary memory, to describe tools like phones and notebooks where we can store information so we don't hae to worry about holding it in memopry. Call it freeing up cognitive space, if you like, or "letting tools do the work for you". Everyday examples include: Writing a list:  Instead of trying to remember 10 grocery items, you write them down. Yo...

 Always remember how good information gap tasks are! This one generates listening, reading, speaking and factual, cultiral knowledge for the A-level exam. Just sit back and watch your B1/2 level students (Y13 in England) listen and speak! I used Le Chat (Mistral AI) to generate the texts and questions, just doing a few vocab glosses if words were likley not to be understood. I asked for level B1. le Chat works as well as Chat GPT for this sort of resource creation and comes with less political baggage. The topic is how French charities support migrants and I would have very happily set this as a task for an A-level (Y13) class. If you have an odd number in the group, just create one group of three where two students share the same text and take tuns asking the questions. This is a sort of variation on my 'Ask the Experts' tasks on the site, but this has the advantage that you can do it with a very samll group — as few as two! Here is my resource — you could get AI to create si...

 A few weeks ago I was in Brussels visiting an old friend, Jonathan, who is retired but does voluntary work including teaching English to teenage students who have dropped out of school for various reasons. These students attend a school run by ABER . Their website states that their aim is to help 15-21 year-olds get back into school by offering a personal education programme. This includes English lessons. Most of the class were of Moroccan descent, all had fluent French. The class had various levels of English ranging from A! (very little) to A2/B1 - a certain degree of fluency. My friend asked me if I would like to come along and join in with an English lesson, which I was very happy to do. Now Jonathan is not a trained teacher and he was pleased to let me take over the class of about 12 students. We had been given a somewhat dated article to use whose main aim was to get students using the future tense. To play along, I got the students to do some choral reading, pronunciation ...