At the end of the new edition of Discovering English with VersaText, published yesterday, there is a list of 22 takeaways. These are the points that I hope I have instilled in the readers. They embrace teaching, learning, creativity, metalinguistics, metacognition (all things meta TBH), guided discovery, text, grammar, vocabulary, pronunciation, depth, respect and colour.

Here they are.

1. Text is the starting point.
2. The multiple affordances of texts and tasks.
3. The Six Pillars of Vocabulary – the properties of words.
4. All properties of words beget language learning tasks.
5. The task activates learning.
6. Relationships between words carry meaning.
7. Relationships between words and grammar carry meaning.
8. Disabuse students of the idea that vocabulary is random.
9. Reveal the visible patterns in language – patterns of normal usage.
10. Respect students' intelligence.
11. Students benefit from guided discovery.
12. Flatter students' intelligence by introducing terminology and its etymology.
13. Tell students the truth or lead them to discover it.
14. Train students in the art and science of observation and pattern hunting.
15. Take students on the journey from analysis to synthesis.
16. Prepare students to become lifelong learners.
17. Let them bask in the wonder of meaning creation.
18. Demystify English at all levels of the Hierarchy of Language.
19. Accept that students have to do the learning and teachers have to lead them to finding their own optimal paths.
20. Equip students with the information and skills they need to make guided discovery work for them.
21. Don't accept students' narrow view of language as a foundation for their wish list when asked what they would like to do or like to learn.
22. Never stop asking students, HDYK.

Originally, a Kindle only, it is now also a print book with white space for readers' answers, notes, comments. The new edition reflects all the updates we have made to the free, online software, and AI appears at pertinent moments.
The Kindle and book are available from Amazon.

​Should you be interested in all things VersaText, or even some of them, feel free to join the Facebook group too.

Language learners benefit greatly from example sentences, since it is an opportunity to learn language from language, my big thing. For this reason, I devoted a considerable amount of my teaching, training and writing to helping students gain the maximum benefit from illustrative sentences.

In the early 2000s, I attended my first Teaching and Language Corpora conference in Bertinoro, a beautiful hilltop town near Bologna, and presented my incipient formula for computationally selecting the most useful sentences from corpora to present to students. I programmed a tool that allocated the frequency of every word in a sentence and average it. Sentence length was also a criterion.

As mentioned in previous posts, the great English lexiocagrapher, Patrick Hanks was my colleague at this time and I asked him what criteria his kind used when selecting sentences to include in their dictionaries. He said there was no list.

I worked on this further and came up with a list of ten criteria that I discussed with Patrick and he added one more. I gave this list to Pavel Rychlý, who was developing Sketch Engine and his team used these criteria as a basis for their GDEX algorithm, i.e. good example sentences. It is now a standard part of SkELL and Sketch Engine. My criteria are listed on this 2006 webpage.

So, it’s a good thing that corpora can select illustrative sentences, but can students? And should they? In short, yes and yes. But then what? How does a learner know what they can learn from an illustrative sentence apart from it being a targeted piece of input which they might soak in, as they do from any input they are exposed to. The answer lies in knowing the properties of the target word that are necessary to shift it from active to passive use.

I am a strong advocate of the Collins COBUILD Advanced Learner’s Dictionary because it even presents its definitions in full sentences. Full sentence definitions are goldmines. From the sentence defintion, you can easily extract concept checking questions (CCQs). For example,

Collins: A wildcard is a symbol such as * or ? which is used in some computing commands or searches in order to represent any character or range of characters.

• What is a wildcard? A symbol
• What are some examples of wildcard? * or ?
• Where is it used? In computing commands
• What is its function? to represent any character …

Collins: An aphorism is a short witty sentence which expresses a general truth or comment.

• What is an aphorism? a short witty sentence.
• What does it do? it expresses a general truth or comment.

These sentences typically start with a hypernym, here symbol, which immediately limits what it is and is not. Their definitions progress with the target word’s features, functions, etc. Each of these is encapsulated in a phrase or clause in the sentence definition. They are the properties of the word. The Collins then provides example sentences in which the abstract properties are made concrete. If students know what they can learn from full sentence definitions, they can see how the meanings of words manifest in authentic sentences.

I’m writing a student workbook at the moment which will probably be called Discovering Phrasal Verbs, in which students are repeatedly tasked with finding example sentences in corpora. The book explains the importance of the semantics of the phrasal verb particles (prepositions and adverbs) and the importance of the subjects and objects of the verbs. These properties are the most important contributors to the meanings of the otherwise opaque, or at best translucent, phrasal verbs.

When you search corpora for a phrasal verb, the sheer volume of data can be overwhelming. Fortunately, SkELL uses GDEX, so the 40 sentences it presents are manageable. The other tool I recommend is CorpusMate because it is very fast, it enables searches with wildcards, and the cotext is colour-coded using the same colours for parts of speech as VersaText. The wildcard searches are necessary when the phrasal verb is separable, e.g. tear .* away, keep .* .* away.
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AI is another source of illustrative sentences. In ChatGPT's own words, "The sentences generated by AI are original constructs, created using the language patterns learned during training." They are by definition inauthentic sentences, which means they were not motivated by any communicative impetus, hence they lack real-world contexts. These sentences often resemble those made up by textbook authors and test creators. It is reasonable to ask if the trade-off between authentic and inauthentic example sentences in terms of learnability is worth it. Do students really benefit more from authentic than inauthentic sentences?
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Like all good questions in ELT, the answer starts with, it depends. My it depends revolves around what the students are tasked with. If the textbook provides made-up example sentences without any task other than perhaps read, read aloud, translate or memorise some sentences, the students will function at the bottom of Bloom's Taxonomy. Garbage in, garbage out.

​But if the tasks involve higher order thinking skills in which the students skim and scan multiple examples of authentic language in search of specific properties to which they have been alerted, they develop a better understanding of the properties of the target word, and ultimately a more sophisticated understanding of language per se emerges. Like all good citizen-scientists, students engaged in “extreme noticing” need systems to record their findings that will in turn deepen their conceptual grasp of the target language and prepare them to use it confidently.

It is well-known that guided discovery is not for everyone. I was a school music teacher in my 20s and one would occasionally hear, Never try to teach a pig to sing: it wastes your time and annoys the pig. This is yet another aphorism attributed to Mark Twain, but who knows?
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Guided discovery demands a strong rationale, clear instructions, the right tools and an understanding that the students are going to benefit from the multiple affordances of the tasks. It is important that students are made aware of the multiplicity of these learning experiences in the process of acquiring words and their properties. No reflection, no connection.

​Hoey in fact studied foreign languages so that he could experience the processes of language learning and the practical applications of linguistic and pedagogical theory. When he was observing language in context, that is by reading and listening, he would notice certain collocations but he needed proof of their typicality before he could consider them worth learning. Just because someone has combined a pair of words does not mean that this combination is a typical formulation in the language. The lexicographer, Patrick Hanks (1940–2024) felt the same: Authenticity alone is not enough. Evidence of conventionality is also needed (2013:5).

Some years before these two Englishman made these pronouncements, Aristotle (384–322 BC) observed that one swallow does not a summer make. Other languages have their own version of this proverb, sometimes using quite different metaphors, but all making the same point.

​In order to ascertain that an observed collocation is natural, typical, characteristic or conventional, it is necessary to hunt it down, and there is no better hunting ground for linguistic features than databases containing large samples of the language, a.k.a corpora. In the second paragraph, Hoey experienced the processes … Is experience a process a typical collocation? This is the data that CorpusMate yields:

In the same paragraph, we have the following collocation candidates:

• study language
• foreign language
• apply theory
• observe language
• notice collocation
• combine words
• typical formulation

Here is some more data from CorpusMate.

In the following example, we have a wildcard which allows for one element to appear between the two words of the collocation. Even in these first 12 of the 59 results, other patterns are evident.

The process of validating your findings through multiple sources or methods is known as triangulation, and it is an essential stage in most research. When we train students to triangulate their linguistic observations, it is quite likely that they are familiar with this process from their other school subjects.

This is not just a quantitative observation, i.e. this collocation occurs X times in the corpus. It is qualitative as well: the students observe other elements of the cotext, such as the use of other words and grammar structures that the collocation occurs in. They might also observe contextual features that relate to the genres and registers in which the target structure occurs.

They are being trained in task-based linguistics as citizen scientists, engaging their higher order thinking skills as pattern hunters. This metacognitive training is a skill for life that will extend far beyond the life of any language course they are undertaking.

Triangulation does not apply only to collocation. Any aspect of language can be explored in this way. You may have noticed the word order in the idiom: does not a summer make. Many people have run with this curious word order and exploited it creatively. It is thus a snowclone. Here are some examples from SkELL.

Respect our students' intelligence and ​equip them to learn language from language.

Croswaithe, P. & Baisa, V. (2024) A user-friendly corpus tool for disciplinary data-driven learning: Introducing CorpusMate International Journal of Corpus Linguistics.
    
Hanks, P. (2013) Lexical Analysis: Norms and Exploitations. MIT.
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Hoey, M. (2000) A world beyond collocation: new perspectives on vocabulary teaching. Teaching Collocation. Further Developments in the Lexical Approach. LTP (ed. Lewis, M.)

How often have you seen claims like these?

• Speak like a native in no time!
• Effortless fluency guaranteed!
• Learn a language in your spare time with no effort!
• Language fluency made simple and quick!
• Master any language with this one simple trick!
• Learning a new language is a breeze!
• Fluency in just 10 days!
• Master a language while you sleep!

Who would make such claims? Certainly not someone who has achieved a high level of competence in a foreign language. As an eternal language student, and a language teacher and a teacher of teachers, I am pretty certain that you and I have worked hard to get to where we are in our foreign languages. It was not effortless, it wasn’t a breeze and no progress was made while we were asleep. I was so desperate to improve my vocabulary, that I used to sleep with my dictionary under my pillow. No I didn’t, but that is the impression you get from some of these slogans.

Learning a language is hard work and there ain’t nothin’ wrong with hard work. Never confuse hard work with hard labour. Hard doesn’t mean boring and monotonous and it doesn’t mean frustrating and unrewarding.

The hard work we do when learning a language involves planning, monitoring and revising. It involves understanding what we are learning, which in turn involves connecting what we already know with what is new to us. Hard work involves practising what we have learnt so that it becomes automatic. Hard work involves using our time efficiently, choosing approaches that work for us. This requires us to assess or critique the approaches to language study that are introduced to us if we are fortunate enough to have various approaches. It is worth reflecting on how many different learning experiences we are having while studying – the learning #affordances of an activity.
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For example, if we are learning a set of English words with their first language equivalents, whether in written lists, on paper or electronic flashcards, in a computer game or being tested by our study buddy, the only connection we make is between the L1 and L2 word. We do not learn how the word is used. This leads us to assume that the L2 word is used in the same way as it used in L1 and this is okay when it works. It is not okay the rest of the time. Psycholinguists refer to this assumption as the semantic equivalence hypothesis (Ijaz 1986, Ringbom 2007).

Another issue with learning L1–L2 pairs is the mental processing of the L2 word: what is your mind doing whilst trying to remember a word? Lower order thinking does not make for a rich learning experience. When we are critiquing our approaches to vocabulary study, we need to consider how many different features of words we are learning at the same time.
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However, when we study the vocabulary of a text in a text, we see how keywords are used differently each time they are used. Yes, their different uses create different messages which means that the author is telling us something new about the keyword each time it is used. These different messages involve different words, which means we can make a diagram of a keyword as it is used in a text. I call these diagrams Word Constellations.

We can identify a key word and highlight all of its occurrences in the text, then highlight the words that are used with it. I prefer to do this with #VersaText because it is easy to see the left and right cotexts of keywords in a concordance. You can do this with at least several key words in the text. ​

In critiquing this approach, we need to consider how much the students learnt during the time spent.

• Did the knowledge gained empower them to use the keyword and its cotextual words better than learning such combinations from flashcards or bilingual lists?
• Did they meet any combinations of words that were new and useful?
• Did they have to check their dictionary for anything?
• Did they notice anything about the distribution of the keyword through the text?
• Did the process heighten their understanding of the text?
• Did drawing the word constellations feel like a strong learning experience?
• Was it an enjoyable process?
• Can they imagine their vocabulary notebooks full of word constellations?
• Are they likely to refer to them again? And again?

If they didn't create a word constellation of a key word in a text, what did they do? How did they spend their time? What learning took place? 

Once we have a keyword in its multiple cotexts, we can use them as the bases of our own sentences. We might like to use them to form questions to discuss with our study buddy or our favourite AI tool. Here are some simple examples of a chat with Perplexity.ai.

Hi. I'm a B1 student of English. Will you be my study buddy today?
Of course! I'd be happy to help you with your English studies.

• Are Czech walking trails a complex system?
• Are they connected together?
• Do they run through the whole country?

Is this time-consuming? Is it a good use of our time? Are we having strong learning experiences? Are connections forming in our minds that have a high chance of becoming permanent?

I used bilingual lists for many years, long after I needed to. I think that if I were to start another foreign language, I would need them as a beginner. But applying what I have actually known for a long time, I would move as quickly as possible to studying words with their natural cotexts.

It may be the case that people who make claims like those at the top of this article do actually teach vocabulary in cotext, but from the courses and resources that I have seen over the years, this does not seem very likely.

If you or your students ever create word constellations, I’d love to see them. And I would love to know what the process led to.

Feel free to join the VersaText Facebook Group where you can share your experiences and learn from others.
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Ijaz, I. H. (1986). Linguistic and cognitive determinants of lexical acquisition in a second language. Language Learning, 36(4): 401-451

Ringbom, H. (2007). Cross-linguistic similarity in foreign language learning (Vol. 21). Multilingual Matters.
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Veselá, Z. (2003) Czech Republic’s unrivalled system of marked walking trails. Radio Prague International, 5.12.2003.

I had an email from a teacher who loves using my VersaText tool with his students. In addition to the very welcome and rarely received praise for VersaText, he was enquiring into the possibility of adding a collocation feature. As you know, VersaText works with single texts, its slogan being, “learning language from language, one text at a time”, collocations are vanishingly rare. In fact, “vanishingly rare” is a strong collocation in English. Check out the examples in #SkELL.

#Collocation is defined variously. First and foremost, collocation consists of two content words of different parts of speech. Compound nouns and adjectives, phrasal and delexical verbs are not collocations. And neither are words that combine with that/ -ing / inf / wh-/prepostions. These are colligations and offer very little choice, if any. You’ve all seen gap fills in coursebooks and exams that test this. Collocation does permit some variation, but within limits of acceptability if you are going to use the patterns of normal usage of the language.

One category of definitions of collocation revolves around statistical frequency. These definitions rely on the number of times words occur in close proximity to each other. The verb collocates of trouble, for example, occur frequently within four words before and/or after the noun in SkELL's huge sample of English.

Other definitions of collocation are phraseological: cause trouble is the core of a clause, which is the essential structure that creates Messages, which in turn constitutes text. Up the Hierarchy of Language we go! 

Most key words in most texts collocate with different items because the author is telling us something new about the word. And this is why a collocation tool in VersaText would be by and large redundant.
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One thing we can be sure of in a text is that the author is not going to repeat the same message repeatedly, again and again, over and over, unless they have some rhetorical reason for doing so.  Here is an example. In VersaText’s sample text, Learning Zone (a transcript of a TED Talk), we see that the verb spend is frequently used with time, and with other time words, e.g. minutes, hours, our lives. It occurs 13 times in the text. Time occurs 28 times in the text and is used thus: ​

Go to VersaText, select the Learning Zone text from the list, then click Wordcloud at the top. If you want the lemma of improve, for example, choose the lemma radio button under the word cloud. Click on any word to see its concordance in this text. This motivates many discovery learning tasks for the students.

If you want to learn more about studying and teaching English with VersaText, click the Course button at the top of the VersaText pages.

My phraseological approach to collocations in single texts is the Word Constellation. See my blog post linked below. 

Like all linguistic phenomena, snowclones have been in existence much longer than the term coined to describe them. A term endows a phenomenon not only with a certain gravitas but a recognition that it has a set of features that an entity needs to be worthy of the name. If it has all of the required features it is a prototype (Rosch). ​

Another fine example is the English language: which features of English do spoken Texan, Irish football journalese, and academic written English all possess? This makes for an interesting Venn diagram and it leads to a description of “core” English. A nice activity, by the way! 

​Terms are of much use to language students and misuse impedes their progress. We are all familiar with the misnomers, past tense and past participle. As Michael Lewis convincingly conveyed, the past tense is actually about remoteness – in time, in reality, and in social distance. The past participle is a non-finite form and by definition cannot express time. 

​Compound nouns and phrasal verbs are not collocations, and delexical verb structures are neither collocations nor phrasal verbs. Restaurant, bistro and canteen are co-hyponyms, not synonyms. The use of by in passive structures is not a preposition but a particle. 

When you know the defining features of linguistic phenomena, you can observe them, study them, learn them and use them with confidence. Our English students who also study maths, science, biology, sport, history, geography, literature and the rest, understand very well that their success depends on a profound understanding of the terminology of their field(s). They also know that their professional success demands a professional level of English. Our students deserve as accurate a description of the language as we can provide them.

Until you know that snowclones are an identified and labelled feature of the language, you can’t look them up, talk about them, research them, or tag the next one you hear as one. But now you can. 

Ask not what students can do for you—ask what you can do for your students!
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If you have any other favourite, shareworthy snowclones, please add them in the comments below. It would be great to develop this. ​

Every layer of the hierarchy of language can be explored by students in a text. The exploration of Texts as Linguistic Objects (TALO) reveals how an author has used words and word forms, combined them as collocations and colligations, formed phrases and clauses that are linked with metadiscourse chunks to ultimately form texts. This is the bottom-up process that we employ both subconsciously and consciously when we speak and write. ​

As well as being linguistic objects, Texts are also Vehicles of Information (TAVI) which invoke top-down processes as we combine the content of the text with what we know about the world through schemata, general knowledge and our expectations of text types. In this way, readers and listeners are engaged in their own personal knowledge creation. 

Thirdly, Texts are Springboards for Production (TASP). We respond to texts by combining several texts on the same topic, by critiquing aspects of the text, and by discussing the potential impact of this new knowledge, for example.

To put texts under the microscope, VersaText is an open access, web-based resource that allows teachers and students to paste in a single text. The program provides several tools that foster discovery learning. The first tool is the word cloud, which depicts not only the relative frequencies of words in a text, but it colour-codes part of speech. The word cloud is highly customisable: the number of words, the choice of words vs. lemmas, which parts of speech to show. The relative sizes of words in the word cloud illustrate the extent of repetition in a text and repetition is the most commonly used resource to create lexical cohesion in text (Halliday & Hasan, 1976).​

The opportunity to put the language of a single text under such a microscope is invaluable to students of CLIL, EMI and ESP, as the texts are models of the language of subjects and fields that the students need to have a productive knowledge of, if they are to be acculturated into their subject disciplines. This is essential for TASP. 
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Halliday, M.A.K. & Hasan, R. (1976) Cohesion in English.  Longman
Hoey, M. (1991) Patterns of Lexis in Text. OUP.
Johns, T., Davies, F. (1983) Text as a vehicle for information: the classroom use of written texts in teaching reading in a foreign language. Reading in a Foreign Language, 1 (1)
Partington, A. (1998) Patterns and Meanings: Using Corpora for English Language Research and Teaching.    John Benjamins.

In my last blog post, "…", I wrote:

• When we search a corpus for "does not a .* make", it is clear that this is a systematic linguistic exploitation, as the great British lexicographer, Patrick Hanks refers to such creative uses of language. 

Since I wrote this, this great British lexicographer has passed away.
 
Patrick's theory was articulated in his unputdownable book Lexical Analysis: Norms and Exploitations (2013). It is an empirical investigation into how words go together in collocation patterns and constructions to make meanings. In the book he writes extensively about patterns of normal usage and then demonstrates how a great deal of creative language use is also patterned, albeit differently. By the time Lexical Analysis was published, I had known Patrick for quite a while during our overlapping years at the Faculty of Computer Science (FI MU Brno). Our offices were on opposite sides of a corridor across which we'd often call to each other.

​Patrick had not been fully apprised of the doctoral defence procedure. Czech doctoral defences are preceded by an oral exam and he more or less delivered his inspired defence during the exam. We had to wait outside the exam room while the committee determined his exam result before allowing him to give his defence, which turned into a grand round table discussion. I remember James Pustejovsky, who'd been flown from the USA for the defence, ramping up Patrick's interrogation by claiming that he was getting off a little bit lightly. He passed.

Before the New Oxford, there was the COBUILD project at Birmingham University in the 1980s. Patrick was the managing editor of the COBUILD Dictionary. I distinctly remember the day he strode the metre and a half from his office to mine to tell me that he'd just learnt of the death of his dear friend and colleague, John Sinclair. Sinclair had run the highly innovative COBUILD project for a decade. Patrick would often relate the day Sinclair announced to his team of lexicographers that all of the dictionary's definitions would be written in full sentences unlike the standard practice of providing synonyms and snippets to express a word's meaning. These sentence definitions are built up of chunks of information that explain what and why and how something means what it means. This aspect of the COBUILD dictionary is why I recommend it to students and teachers in all my training and writing. I shall wax lyrical on this in another post.
 
One Friday afternoon, Patrick drove around the corner from the faculty to the bank, unnecessarily and lamentably. He came back from the bank on foot, his car having been stolen. Unfortunately, he hadn't finished unloading boxes of rare and specialist books from his car into the flat that a friend of mine let to him. The police came and drove Patrick and me around the neighbourhood for quite some time before they took us to the police station where we spent hours answering questions for the policeman to fill in forms. I was interpreting for him and I had to keep asking if cars really have all of these features he was being asked to say yea or nay to. It had been well over 20 years since I had owned a car and half of the features sounded indulgent and verging on sci-fi. He never got his car back let alone the books. But we did spend that Friday evening washing down a hefty steak with a fine Czech brew or two.
 
While still in Brno Patrick started a project that he pursued to the end of his working life. It is the Pattern Dictionary of English Verbs (PDEV), publicly available as an online database. He and his team studied concordances of verbs, tagging their grammatical and lexical features. They used Sketch Engine of course, since it was born and thrives to this day in the faculty where we were working. Sketch Engine achieved an international reach when the philosopher-linguist, Adam Kilgarriff, bought into it through a university–enterprise agreement. Adam died of cancer at the age of 55. In fact, the last time I saw Patrick was at Adam's funeral in Brighton.
 
Here is the entry for adapt in PDEV.

Every meaning/use of a verb has a unique pattern, which is why we know which meaning of a verb is meant when we read or hear it. And we use this information when we write and speak. Native speakers do this subconsciously while non-native speakers learn this, although to the best of my knowledge, there are no vocabulary teaching resources that employ this user-friendly description of meaning. I'm working on it! Watch this space. While an entry does not employ terminology such as valency, complementation or transitivity, it does use semantic types which are indicated in square brackets. The PDEV entry for answer has 14 entries, two of which are tagged phrasal: answer back and answer for and two are tagged idiom: have a lot to answer for and answer call of nature.
 
I participated in the PDEV corpus work for a short time. I was convinced that the searches could be partially automated as I had developed database scripts for automating Sketch Engine CQL searches for verbs in their known grammar patterns as part of my MA dissertation research. But Patrick preferred to work from raw data without skewing observations towards predetermined patterns. He also rejected intuition. There were times when I pointed out that the data did not show something about a verb that should be part of its description.
 
While his interest was in verbs, mine lay in nouns as the primary carriers of meaning in message clauses. I posited applying the PDEV approach to nouns, but Patrick had a completely different methodology for this part of speech. The cognitive profile, as he called it, consists of a set of short, objective sentences each sentence revolving around a collocation of the noun. For example, his spider profile includes these sentences:

• Some species of spiders hunt prey.
• Spiders lurk in the centres of their webs.
• Spiders have eight legs.
• Many people have a dread of or are frightened of spiders.

 
I have adapted this for teaching purposes, preferring the more student-friendly term, word profile. In pedagogical circles, a cognitive profile is more likely to pertain to a student than a word. I'll elaborate in another post.
 
I took him a couple of times to visit the old folks in Mikulov, a beautiful Moravian town on the Austrian border. The old folks were my dear friends, a Czech man and his South African wife, who had lived in my town, Sydney, for 15 years before moving to Czechia after the fall of the wall. We used to chat at the bar in their house, drink carafes of Moravian wine, play Noel and Cole on June's Steinway and stumble home the following day.
 
Patrick did invite me to stay with him for a few days in Bristol during which time he was frantically busy, but we did manage to talk about pattern descriptions of nouns, about his loneliness, his depressive moods, his ex-wife and his beloved daughter.
 
I can't imagine where my thinking about language would be had I not spent this time with Patrick. They were pivotal years for me, and it is a great honour to have been in his presence. You are very well-remembered, dear friend.

The title of this post is a sentence in a book I don’t seem to be able to finish: Grammar, Vocabulary and Everything in Between (GVEB). It’s a book full of language learning tasks on whose cover I would like to plaster “More fun than Murphy". Better not :-).

But what is holding me up at the moment is the writing of another task book called After IELTS (and e-course), which is for students who have passed the Academic IELTS and will soon start their university studies in English, perhaps in the belief that IELTS prepared them for university level work. This belief was at least partly engendered by the low IELTS score that the university declared adequate for this level of study. I witnessed many hundreds of students in exactly this situation being seriously ill-prepared. So, when I finish writing After IELTS, I will finally finalise the final version of GVEB. Watch this space!
 
In the context of GVEB, "casual encounters rarely lead to life-long relationships” refers to the lack of long-term impact that a meeting with a word whilst reading, listening and watching has. It’s like being in your local shopping mall or at a reception with hundreds of people milling about. They all share the properties of [HUMAN] – walking upright, head, body, four limbs, clothed, a sense of purpose. There will be some outliers – very tall, blue hair, in a wheelchair, atypically dressed, looking lost and confused. Some people look very familiar, some less familiar, and others not at all.  It will be clear that some people are there with another person, and others are functioning in small groups. Some people will be helping others and some people will be performing their roles in their milieu independently.
 
If we don’t stop and get to know someone in a crowd or a word in a text, they are not going to enter into our consciousness or become a part of our understanding of the world. They are just going to be a part of “the general mush of goings on”, to quote J. R. Firth, whom some regard as the founding father of British linguistics. People do stop, even crouch, to pat someone’s dog or goo-gah someone’s child as a coy excuse to talk to the accompanying adult. At a reception, people have the shared context of the event itself to thaw the ice. When I was teacher training for the BC in Tashkent, the British Ambassador held occasional garden parties. At one such event, I walked up to two women nursing wines and announced that I didn’t know anyone there. They said they didn’t either. We got chatting and ended up Sunday lunching together for the next few months till COVID put paid to that. And a few other social niceties and professional MOs. We three have a Telegram group and stay in touch. I’ve met them both once since. They have most definitely become a part of my worldview.
 
If we want new words to become part of our "wordview", a fleeting meeting ain’t gonna cut it. We can read and listen and watch till the cows come home, but if we don’t devote some attention to the desirably unfamiliar, they will remain unfamiliar and the desire will remain unquenched. If you have never seen the word unquenched before, be not surprised. In the 52 billion (sic) word corpus, EnTenTen (Sketch Engine), it occurs a paltry 1,292 times. By comparison, desire occurs 5 million times in said corpus. Even the lemma of quench only occurs 112,342 times. The lemma includes quench, quenched, quenching. Does quench typically keep company with desire? Yes, 821 times. It more typically keeps company with thirst, hunger, craving and curiosity. The words that typically come between quench and one of these objects are my, your, etc., In the chunk, quench the thirst of (3,105 times), thirst is mainly used metaphorically, e.g. the thirst of millions. Quench also collocates with fire, flame, furnace.

Following on from my previous post about constellations, in this post I'm looking at the asterisk, which some of my students refer to as a star. I admit that that's a pretty tenuous connection and I apologise whole-heartedly. But the universe does get a mention here, so bear with me.

I'm drafting a vocabulary workbook at the moment, or should I say yet another vocabulary workbook. In this one, the students are often tasked with discovering how words work in grammar patterns. They mainly use CorpusMate. This is quite a new, free, open-access and superfast corpus tool that was designed by Peter Croswaithe and programmed by Vit Baisa, who also programmed my VersaText and was instrumental in the development of SkELL.

The CorpusMate corpus does not have part of speech tagging, which means that you can't search for a pattern such as Verb + noun + v-ing and there are hundreds of verbs in English that function in this pattern, e.g. remember, picture, catch, tolerate, leave. There are not only hundreds of words, but there are also hundreds of patterns that nouns, verbs and adjectives function in. My current vocabulary book revolves around the COBUILD grammar pattern reference books from the late 1990s. In fact, I wrote my masters dissertation on the grammar patterns of the verbs in the then new Academic Wordlist (2000) that Averil Coxhead had created for her masters dissertation.

It is always interesting to see how much can be gleaned about the grammar pattern of a word without part of speech tags. The asterisk is mighty. In fact, it holds the secret to the meaning of life, the universe and everything. Read on!

A supercomputer called Deep Thought was asked what the meaning of life, the universe and everything was. It calculated that it was 42. See the announcement in this extract from the film. Douglas Adams, the author of The Hitchhiker's Guide to the Galaxy, the cult 1979 novel from which this comes, always claimed that he chose the number 42 randomly. But 42 is the ASCII code for the asterisk, which in computer searches means anything and everything. Did Deep Thought calculate that the meaning of life, the universe and everything is anything and everything?
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This search uses two asterisks. The first has spaces before and after it, which makes the program search the corpus for all of the words in between the items to the left and the right of it. The second asterisk is used with a dot and is attached to ing. Dot-star, as my students call it. This makes the program search for words ending with ing. While this might include words such as thing and during, the fact is that the -ing word that follows remember followed by another word tends to be an -ing verb. This is the reality of pattern grammar.

As mentioned, Verb + noun + -ing is one of hundreds of grammar patterns of words that the COBUILD team uncovered. They were not the first to identify this or many other patterns, but they were able to demonstrate with large corpora the semantic relationships between words that function in the same pattern. This means that the words in a grammar pattern are related in meaning. Important and interesting.

Chunks
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Now back to our mighty asterisk! With queries such as these, you can find the frequent chunks that a target word is used in. The concordance extract below shows some things that people are "in search of a". ​

I'm hoping that a vocabulary workbook that has students learning about the patterns that words function in and the words that go in these patterns through tasking them with discovering these properties of words for themselves using CorpusMate and other tools will be a stimulating voyage of discovery which will add a layer of systematicity to their vocabulary study which will in turn lead to them using words with more confidence and fewer hesitations. Think fluency. They might become stars themselves! ​