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! ​

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. ​

References
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.
Veselá, Z. (2003) Czech Republic’s unrivalled system of marked walking trails. Radio Prague International, 5.12.2003.

It is obvious when you put it like that. To ask if there are more meanings than words begs several more questions. We could start with: what is a word and what is meaning? Then we could ask how the numbers of these things are counted. We might even wonder who wants to know. Or as my grandmother used to provoke: how will knowing this change my life?

Let’s start by appeasing my long-passed grandmother. To be honest, I am not sure that being aware of the fact that there are more meanings than words in a language (spoiler alert) would have changed her life as she was not a linguist in any sense of the word: she didn’t study languages and she didn’t study language. Bingo! Right there in that very statement the question manifests. Are the countable and uncountable forms of language one word or two?

An orthographic word is a string of letters that has a space before and after it. This applies to the written word, obviously. Spaces in the spoken language do not separate words. When software counts words, this is the definition of word that it uses. But no one would argue that a text that contained a thousand words expressed a thousand units of meaning. No one is two othographic words but one lexeme. Lexeme is the term for a unit of meaning and while most meanings are expressed by orthographic words, very many are expressed by compound nouns, compound adjectives, compound prepositions, phrasal verbs, idioms, fixed phrases and chunks of various kinds. The day before yesterday is one lexeme made up of four orthogrpahic words. Made up of is a phrasal verb consisting of three words expressing one meaning in this context. The words that compose these multi-word lexemes are used in many others.
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Is there a difference in meaning between participate and take part in? In many languages, the day before yesterday is one word. A linguist in the old-fashioned sense meaning polyglot and the modern sense of language researcher have their own words in other languages. German has Sprachkundige for polyglot and Sprachforscher for the academician. Even without any knowledge of German, the interested reader will notice that the first syllable of these two words is the same and will therefore conclude that these are compound nouns without a space between the orthographic words that they consist of. Spaces and hyphens also confound the definition of word: in English, we write hobby horse, hobby-horse and hobbyhorse. This word also has very different literal and figurative meanings.

Every dictionary has a different number of meanings for make. Some dictionaries lump together similar meanings and uses, while others split them into separate sub-entries. Lexicographers thus accuse each other of being lumpers and splitters. In fact, they are not alone. Lumping and splitting occurs in many fields wherever things are being categorised. But I digress. In delexical verbs, make doesn’t mean much at all: make a decision, make a comment, make a plan, make a promise, make a suggestion. In fact, in these cases, there are single word verbs that have the same meaning even though they are syntactically different. Compare: someone makes a plan and someone plans something. Delexical verbs are quite different from phrasal verbs as the latter contains only a verb + particle (prepositions and adverbs) and the meaning of many phrasal verbs results from the interaction of the verb with the functions of the particles. For example, one of the functions of up in phrasal verbs expresses completion e.g., clean up, wrap up. Another function expresses change, e.g. grow up, break up.
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Make up is two orthographic words and one lexeme. But the Collins COBUILD lists eight meanings of make up. These meanings result from the different functions of up. The Collins lists three meanings of the hyphenated noun form make-up.

In the iconic expression of the 1960s peace movement, Make love not war, the denotation of make love is have sex. But the connotation carries more intimacy than the physical act. The 1960s protest movement was advocating warmth, harmony and love between people, not a biblical “go forth and multiply”. I often wonder why the hippies didn’t perform more music by Bach, after all he had 20 children with his two wives. Making war is something that politicians ultimately do. The military doesn’t make war. The military goes to war, wages war, fights battles. Anyone chanting Make love not war must have been directing the slogan at politicians. They wanted them to promote harmony between people instead of sending them to war.
On a lighter note, in an old pun on the word make, one guy says, My mother made me a homosexual (make = cause) and his friend replies, Would she make me one too (make = create)? Many words form phrases and idioms, and express jokes, puns and cultural references. Some words have shades of meanings that cause lumpers and splitters sleepless nights.

Not every word is as polysemous as make, but many of the high frequency words in the language do have multiple meanings. Many of them also undergo conversion, that is, they function in more than one part of speech. How many parts of the body are both nouns and verbs, for example? And don't think that parts of the body and body parts are synonymous. Speaking of verbs that parts of the body do, consider the similarities and differences between these troponyms of 'go on foot': amble, stroll, wander, meander, saunter. And these troponyms of 'eat': nibble, devour, swallow, feed, consume. These words are not synonyms either.

To borrow an analogy from database design, words and meanings have a "many-to-many" relationship. This is the  type of relationship between two entities where each element of one entity can be associated with many elements of another entity, and vice versa. Many words, though not all, have many meanings, and many meanings are expressed by orthographic words and by multi-word lexemes.

​This knowledge about language (KAL) would not have been of much use to my grandmother but for the billions of people who are both Sprachkundige and Sprachforscher in the modern world, being equipped with concepts about vocabulary enables them to systematise their study. It makes learning visible. It is not necessary to second-guess things. Knowledge is power. ​

This slideshow has a few examples from my ever-expanding a slide show, which I would watch to revise my word notes. This often me prompted me to link a previously studied word to a new one. And as we all know, the relationships between words is crucial to understanding, choosing and using them. Relationships between people are also crucial, which makes the shareability (no, it’s not a nonce word) of Google slides a godsend to anyone studying with a study buddy or when a student wants to show their teacher their efforts.

This is about studying vocabulary, not teaching it. As teachers, we can offer our students ways of studying vocabulary, but they have to do the work. One slide a day is quite a commitment when you fill it with all the features listed above. It is better to add new word data to existing slides. In fact, we are constantly and subconsciously adding to our dossiers on words when we are listening, watching and reading. One word a day may seem a tortoisly (yes, that’s a nonce word) slow march towards developing vocabulary breadth (size). And it would be if size were the only gain. However, to create a slide, the student engages in a lot of language and in the process, develops vocabulary depth. The tortoise always wins.

​Yesterday, I read two current academic papers by esteemed colleagues. Is DDL dead?  by Dr. Peter Crosthwaite and Prof. Alex Boulton. I co-edited a book of conference papers with Alex in 2012 and I presented my Discovering Academic English (2022) work in one of Pete's webinar series last year. The second paper, Generative AI and the end of DDL was written by the same Peter and Dr. Vit Baisa. I have been working with Vit for many years – he programs my VersaText and Pete's CorpusMate. The full titles of these works are in the references below.
 
Data-driven learning (DDL) is an approach to studying language through treating language as data. Just as journalists, scientists and spies seek patterns in data so as to understand their subjects better and be able to make predictions, linguists including budding linguists, make and record their observations of features of language that they observe in authentic data. Being a discovery-based and inductive approach to language learning means that it is not suitable for every learning context, which is equally true of drilling, gap filling and using flashcards. DDL is one of many acronyms used in this article. They are listed at the end.
 
Is DDL dead? reports very positive findings by researchers working in all corners of the globe over the last thirty years. Nevertheless, the authors identified a number of problems in the theoretical underpinnings of DDL, and with the actual corpus tools, and in the lack of cognitive studies, and even with the conduct of the research. They mention other drawbacks of DDL such as the technical knowledge required to use the tools, the fact that search tools work differently from other search engines, and that some corpus data is unsuitable for some learners.  
 
The second paper suggests that AI could potentially contribute to DDL but it is too soon to say. They argue that corpora still have a role to play in data-driven learning because corpus tools show where the data came from. Also, the data is authentic, unlike AI generated texts. The authors refer to them as hallucinations. They also point out that the inductive work done by students when working with corpora is actually done by ChatGPT, and not by the students.  
 
I have been immersed in DDL since the late 1990s, working with teachers and trainees and with students of academic writing. I have created e-learning courses, worksheets, books and have presented this work at conferences, some of which I have hosted and been on committees for. In the process, I have read many research papers and books on corpora and also on grammar, vocabulary and everything in between.
 
So, I feel their pain. Many of the researchers cited in these two papers, and many more besides, regret that DDL has not become a standard modus operandi among internet savvy students and teachers in internet-wired homes and schools. The findings of these researchers has empirical credibility, but there are other issues that need to be addressed in order to alleviate the pain. And this is what I would like to focus on in this article and in several that will follow it.
 
DDL focusses largely on the minutiae of language. The students are tasked with identifying patterns in the language by exploring the data. So far so good. But it is important that the students also learn how to record their findings, as they do in science experiments, for example. If they do not integrate their findings into previous schemata, much of the value of the task is lost. My Versatile Blank Book provides students with approaches to recording their findings systematically, intelligently, graphically and creatively.
 
In addition, students need to apply their findings to their own language output. The students didn't discover the most frequent preposition that follows a particular adjective just to answer that guided discovery question. They discovered this to use the adjective confidently, to learn that different prepositions are used with different adjectives in patterned ways, and to learn how to observe such features of language. These affordances of DDL need to be articulated.
 
The course books I have worked with over the years and seen at recent conference stands, and the resources which well-meaning teachers share in their Facebook and Pinterest groups, are not rich in opportunities for students to treat language as data or to exercise their intelligence and creativity. I remember my heart sinking when I once walked into Foyles bookshop on Charing Cross Road (London) to see "Celebrating 25 years of the world's best-selling grammar book", which many a reader of this post possibly also celebrated along with the author, Raymond Murphy. 

Such resources do not engage students in knowledge creation, rather they feed students a diet of matching activities and gap fills regardless of the age, level or motivation of the student. By the way, these are testing not teaching procedures. Grammar, vocabulary and everything in between are mostly poured into students' heads as information that can be presented and tested. This deprives students of the reality of language, namely the patterns and relationships that permeate everything we know about language. And we know a lot more about language than we did 50 years ago thanks largely to corpus studies. This diet of lower order thinking  (LOTS) skills work deprives students of the opportunity to develop their knowledge about language (KAL) and the skill of learning language from language.
 
It would be interesting to read the aims and objectives atop the lesson plans which DDL researchers have been studying. By the end of this lesson, the students will be able to … It would be equally interesting to read what the students write in their reflections on these lessons. From what I remember of the papers I read and edited quite some years ago, the research is mostly conducted under research conditions, not in classes led by teachers who are committed to this mode of language teaching and study. For the VersaText e-course I have just finished writing and which is currently being piloted by a few kind individuals, I created the taxonomy below. It will undergo some revision as it matures, but it nevertheless attempts to show what language students can learn from guided discovery tasks that require them to explore discrete aspects of language. It helps formulate aims and objectives, even though this linguistic minutiae is only a stepping stone to improved competence in the four skills. It also contributes to the development of their metacognitive competence. I suspect that any student or teacher of IELTS, TKT or DELTA could derive some benefit from this. 

​Every feature of language begets a language learning task. For example, if we corpus aficionados want to study phrasal verbs and teach students how to study phrasal verbs, we need a clear definition of ‘phrasal verb’ and we need discovery tasks that can be solved through corpus consultation, and students need to be trained in reporting and applying their findings, just as any research scientist needs to do. One of the interesting things I have found in my EMI training is that university teachers of STEM and MBA subjects readily grasp how language can be treated as data and how patterns and relationships can be extrapolated. They just need to be told. In fact, one professor of horse surgery, upon his first introduction to corpus work, thanked me for making myself redundant (as a language teacher). He got it immediately. Many of our students major in STEM, MBA and medical subjects and do have the required mindset to learn language from language.
 
Another issue besetting ELT is that KAL is not a high priority. No other subject so readily dismisses the theoretical foundation on which it is built (Marr and English, 2019). People place a lot of faith in osmosis, i.e., learners will acquire the language through vast exposure and by being required to do activities that will exercise what they know and force them to struggle to express ideas that they don't have the language for. Mind the gap! A considerable body of research supports my anecdotal experience that osmosis does not work for many people (Hinkel, 2006). For any learner who requires a professional level of a foreign language, attention to detail is essential. This may not be obvious to anyone who has never aspired to learn a foreign language to a high level.
 
Language teaching seems to have leapfrogged language and is nowadays preoccupied with inclusion, empowerment, digital literacy, creativity, learner autonomy, gamification, global issues, critical thinking and soft skills (Kerr 2022). On a casual stroll through the list of topics that conferences cover, you will be unlikely to bump into many language topics. However, in order to pursue any of these worthy passions in a foreign language and with any degree of sophistication and nuance, the students need the principle resource for the job, namely a sophisticated and nuanced level of English. To facilitate this, double processing is recommended. This involves using the associated reading and listening for language as well as for content – explore the linguistic features of the key words and then use them in the writing and speaking tasks that follow.
 
One of the reasons I created VersaText was to facilitate the study of the language of single texts. In this concordance of sheep from an article about BSE, we can see what the text is saying about the target word as well as how the author has said it. The aim is not to infer the meaning of sheep!

​I hope to finish in 2024 a B1 and a B2 activity books, both of which I would like to subtitle, More fun than Murphy, but better not. These books teach students language, about language and about language learning, using tools such as SkELL, VersaText and CorpusMate. The students will be doing “task-based linguistics” from the first to the last pages. AI was not integrated into these books when they were being drafted, but it would be profligate to ignore the opportunity that this new technology affords. If you would be interested in piloting these books with your students, please message me.
 
I will say more about the pitfalls and potential of DDL in follow up posts. Thanks for reading and I look forward to your comments.

DDL: data-driven learning coined by Tim Johns (1990)
AI: artificial intelligence
LOTS: lower order thinking skills (cf. HOTS)
IELTS: International English language testing system
TKT: teachers knowledge test (a Cambridge exam)
DELTA: diploma in English language teaching to adults
EMI: English as a medium of instruction (university teachers teach their subject in English)
STEM: science, technology, engineering, mathematics – a class of school subjects
MBA: masters in business administration
ELT: English language teaching
KAL: knowledge about language
BSE: Bovine spongiform encephalopathy a.k.a. mad cows disease
a.k.a.: also known as

Crosthwaite, P. & Boulton, A. (2022). DDL is dead? Long live DDL! Expanding the boundaries of data-driven learning. In H. Tyne, M. Bilger, L. Buscail, M. Leray, N. Curry & C. Pérez-Sabater (Dir.), Discovering language: Learning and affordance. Peter Lang.
 
Crosthwaite, P. & Baisa, V. (2023) Generative AI and the end of corpus-assisted data-driven learning? Not so fast! Applied Corpus Linguistics. Vol. 3 Issue 3.
 
Hinkel, E. (2006) Current Perspectives on Teaching the Four Skills. TESOL QUARTERLY Vol. 40, No. 1.

Kerr,  P. (2022) 30 Trends in ELT. CUP.
 
Marr, T, and English, F. (2019) Rethinking TESOL in diverse global settings: The language and the Teacher in a Time of Change. Bloomsbury Academic.

Thomas, J, & Boulton, A. (2012) Input, Process and Product: Developments in Teaching and Language Corpora. Masaryk University Press.

Thomas, J. (forthcoming) Discovering Academic English.
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Thomas, J. (2022) Versatile Blank Book. Versatile Publisher.

I’ve spent too much of the last forty years of my life learning foreign language vocabulary, as well as quite a lot of new words and concepts in my native English but this was through different means for different ends. Most of my early foreign language vocabulary study involved learning from bilingual lists or flashcards, labelling pictures, matching foreign words with pictures or English words, and filling in gaps in strings of unrelated sentences. Having no reason to believe that my teachers or course books had set out to hinder my progress or waste my time, I kept plodding along at first in Italian, then German and later Czech. And some Russian.

By the time I started studying Czech, I had also become an ELT teacher around the golden eras of the COBUILD project and the Lexical Approach. Corpora were also peeking their heads above the parapet (data driven learning). This was the early 1990s and it promised great things for a more sophisticated approach to vocabulary study, one in which we would study and teach the properties of words, their internal and external relationships with other words, their roles in creating meaning. It was a time when “learning to learn” and discovery learning were establishing themselves in ELT. Empowerment through linguistic competence was in the air. 

It took me some time to absorb and apply these new trends to my self-study of Czech, but I’m glad I did. It was more difficult to squeeze into my English teaching as we had to turn the pages of course books in lockstep with external syllabuses.
A few weeks ago I was at IATELF Poland, where I picked up a sample course book, fresh off the press from one of the Big 4 publishers. Having been a teacher trainer for 25 years, it came as little surprise that the approach to studying and teaching vocabulary espoused in this brand new course book has no made no headway since the Headways I was teaching from 30 years ago.

In my teacher training, I always offer teachers vocabulary teaching activities that engage higher order thinking skills, creativity, discovery learning, metacognitive strategies, the double processing of texts and negotiating meaning. Many of the activities derive from contemporary findings in linguistics, such as grammar patterns as properties of words, and the role of collocation in creating meaning.

​In the books I have published in the last ten years, I have also provided teachers with lesson plans, activities and resources that elevate the status of vocabulary to its rightful place, that prevent teachers from hindering students’ vocabulary development and that provide students with rewarding self-study procedures. Teachers want their students to be more fluent, accurate, sophisticated and idiomatic (FASI) and a solid grasp of vocabulary is an essential ingredient.