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Table of English Tenses


tense Affirmative/Negative/Question Use Signal Words
Simple Present A: He speaks.
N: He does not speak.
Q: Does he speak?
  • action in the present taking place once, never or several times
  • facts
  • actions taking place one after another
  • action set by a timetable or schedule
always, every …, never, normally, often, seldom, sometimes, usually
if sentences type I (If I talk, …)
Present Progressive A: He is speaking.
N: He is not speaking.
Q: Is he speaking?
  • action taking place in the moment of speaking
  • action taking place only for a limited period of time
  • action arranged for the future
at the moment, just, just now, Listen!, Look!, now, right now
Simple Past A: He spoke.
N: He did not speak.
Q: Did he speak?
  • action in the past taking place once, never or several times
  • actions taking place one after another
  • action taking place in the middle of another action
yesterday, 2 minutes ago, in 1990, the other day, last Friday
if sentence type II (If I talked, …)
Past Progressive A: He was speaking.
N: He was not speaking.
Q: Was he speaking?
  • action going on at a certain time in the past
  • actions taking place at the same time
  • action in the past that is interrupted by another action
when, while, as long as
Present Perfect Simple A: He has spoken.
N: He has not spoken.
Q: Has he spoken?
  • putting emphasis on the result
  • action that is still going on
  • action that stopped recently
  • finished action that has an influence on the present
  • action that has taken place once, never or several times before the moment of speaking
already, ever, just, never, not yet, so far, till now, up to now
Present Perfect Progressive A: He has been speaking.
N: He has not been speaking.
Q: Has he been speaking?
  • putting emphasis on the course or duration (not the result)
  • action that recently stopped or is still going on
  • finished action that influenced the present
all day, for 4 years, since 1993, how long?, the whole week
Past Perfect Simple A: He had spoken.
N: He had not spoken.
Q: Had he spoken?
  • action taking place before a certain time in the past
  • sometimes interchangeable with past perfect progressive
  • putting emphasis only on the fact (not the duration)
already, just, never, not yet, once, until that day
if sentence type III (If I had talked, …)
Past Perfect Progressive A: He had been speaking.
N: He had not been speaking.
Q: Had he been speaking?
  • action taking place before a certain time in the past
  • sometimes interchangeable with past perfect simple
  • putting emphasis on the duration or course of an action
for, since, the whole day, all day
Future I Simple A: He will speak.
N: He will not speak.
Q: Will he speak?
  • action in the future that cannot be influenced
  • spontaneous decision
  • assumption with regard to the future
in a year, next …, tomorrow
If-Satz Typ I (If you ask her, she will help you.)
assumption: I think, probably, perhaps
Future I Simple (going to) A: He is going to speak.
N: He is not going to speak.
Q: Is he going to speak?
  • decision made for the future
  • conclusion with regard to the future
in one year, next week, tomorrow
Future I Progressive A: He will be speaking.
N: He will not be speaking.
Q: Will he be speaking?
  • action that is going on at a certain time in the future
  • action that is sure to happen in the near future
in one year, next week, tomorrow
Future II Simple A: He will have spoken.
N: He will not have spoken.
Q: Will he have spoken?
  • action that will be finished at a certain time in the future
by Monday, in a week
Future II Progressive A: He will have been speaking.
N: He will not have been speaking.
Q: Will he have been speaking?
  • action taking place before a certain time in the future
  • putting emphasis on the course of an action
for …, the last couple of hours, all day long
Conditional I Simple A: He would speak.
N: He would not speak.
Q: Would he speak?
  • action that might take place
if sentences type II
(If I were you, I would go home.)
Conditional I Progressive A: He would be speaking.
N: He would not be speaking.
Q: Would he be speaking?
  • action that might take place
  • putting emphasis on the course / duration of the action
Conditional II Simple A: He would have spoken.
N: He would not have spoken.
Q: Would he have spoken?
  • action that might have taken place in the past
if sentences type III
(If I had seen that, I would have helped.)
Conditional II Progressive A: He would have been speaking.
N: He would not have been speaking.
Q: Would he have been speaking?
  • action that might have taken place in the past
  • puts emphasis on the course / duration of the action
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How to Be a Good Master of Ceremonies

Steps

  1. Be a Good Master of Ceremonies Step 1 Version 3.jpg
    1
    Know your event. These instructions apply to all types of ceremonies, from graduations to bar mitzvahs to celebrity roasts. The key to being a good MC is confidence. Knowing what's going on (and thus what you should talk about) is everything. There's nothing more embarrassing than announcing to 100 people that Joe Blow is about to juggle bowling balls, only to have Jane Doe come out singing a song.
    Ad
  2. Be a Good Master of Ceremonies Step 2 Version 3.jpg
    2
    Establish your contact well in advance of the event day. Your contact will tell you the schedule and order of events, allowing you to be prepared. Your preparation will let you focus on interacting with the crowd, instead of trying to be entertaining, and figure out what's going on at the same time.
  3. Be a Good Master of Ceremonies Step 3 Version 3.jpg
    3
    Smile constantly. Smiling shows the crowd that you're at ease and having a good time. You want them to be at ease and have a good time, so you've got to set the example. If need be, imagine in advance several happy or funny scenarios. Play out these scenarios in your head while you're talking to the crowd. Remember the old speech class advice - imagine everyone in the crowd is in their underwear. Your light-heartedness is sure to rub off.
  4. Be a Good Master of Ceremonies Step 4 Version 3.jpg
    4
    Don't forget your main job is to talk to the crowd. You're keeping them informed about the ceremony, and giving the talent or featured individual time to prepare to go onstage.
  5. Be a Good Master of Ceremonies Step 5 Version 3.jpg
    5
    Study your lines. Usually people have lines before they do the actual thing. So study them so your mind won't go blank during the show.
  6. Be a Good Master of Ceremonies Step 6 Version 3.jpg
    6
    Don't stop when you mess up. Sometimes people say the wrong things when they're talking because they're nervous. Don't stress and move on.
  7. Be a Good Master of Ceremonies Step 7 Version 3.jpg
    7
    Try to be funny. Nobody likes a dull host! Try to laugh sometimes and crack a joke once in a while.
  8. Be a Good Master of Ceremonies Step 8 Version 3.jpg
    8
    Stare at something or think of something that makes you "less" nervous. Stare at the wall or a clock and talk to them to make you less nervous.
  9. Be a Good Master of Ceremonies Step 9 Version 3.jpg
    9
    Slow down with your words. If you talk too fast it can lead to stuttering and people watching you can't understand what you say. So slow down when you are talking
  10. Be a Good Master of Ceremonies Step 10 Version 3.jpg
    10
    Ask questions that people might answer. Especially younger crowds with answer "yes" or "no" if you ask a question. It keeps them focused and they won't get distracted. 
Source : http://www.wikihow.com/Be-a-Good-Master-of-Ceremonies
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Statistika


Statistika adalah ilmu yang mempelajari bagaimana merencanakan, mengumpulkan, menganalisis, menginterpretasi, dan mempresentasikan data. Singkatnya, statistika adalah ilmu yang berkenaan dengan data. Istilah 'statistika' (bahasa Inggris: statistics) berbeda dengan 'statistik' (statistic). Statistika merupakan ilmu yang berkenaan dengan data, sedang statistik adalah data, informasi, atau hasil penerapan algoritma statistika pada suatu data. Dari kumpulan data, statistika dapat digunakan untuk menyimpulkan atau mendeskripsikan data; ini dinamakan statistika deskriptif. Sebagian besar konsep dasar statistika mengasumsikan teori probabilitas. Beberapa istilah statistika antara lain: populasi, sampel, unit sampel, dan probabilitas.
Statistika banyak diterapkan dalam berbagai disiplin ilmu, baik ilmu-ilmu alam (misalnya astronomi dan biologi maupun ilmu-ilmu sosial (termasuk sosiologi dan psikologi), maupun di bidang bisnis, ekonomi, dan industri. Statistika juga digunakan dalam pemerintahan untuk berbagai macam tujuan; sensus penduduk merupakan salah satu prosedur yang paling dikenal. Aplikasi statistika lainnya yang sekarang popular adalah prosedur jajak pendapat atau polling (misalnya dilakukan sebelum pemilihan umum), serta hitung cepat (perhitungan cepat hasil pemilu) atau quick count. Di bidang komputasi, statistika dapat pula diterapkan dalam pengenalan pola maupun kecerdasan buatan.

Penggunaan istilah statistika berakar dari istilah istilah dalam bahasa latin modern statisticum collegium ("dewan negara") dan bahasa Italia statista ("negarawan" atau "politikus").
Gottfried Achenwall (1749) menggunakan Statistik dalam bahasa Jerman untuk pertama kalinya sebagai nama bagi kegiatan analisis data kenegaraan, dengan mengartikannya sebagai "ilmu tentang negara (state)". Pada awal abad ke-19 telah terjadi pergeseran arti menjadi "ilmu mengenai pengumpulan dan klasifikasi data". Sir John Sinclair memperkenalkan nama (Statistics) dan pengertian ini ke dalam bahasa Inggris. Jadi, statistika secara prinsip mula-mula hanya mengurus data yang dipakai lembaga-lembaga administratif dan pemerintahan. Pengumpulan data terus berlanjut, khususnya melalui sensus yang dilakukan secara teratur untuk memberi informasi kependudukan yang berubah setiap saat.
Pada abad ke-19 dan awal abad ke-20 statistika mulai banyak menggunakan bidang-bidang dalam matematika, terutama peluang. Cabang statistika yang pada saat ini sangat luas digunakan untuk mendukung metode ilmiah, statistika inferensi, dikembangkan pada paruh kedua abad ke-19 dan awal abad ke-20 oleh Ronald Fisher (peletak dasar statistika inferensi), Karl Pearson (metode regresi linear), dan William Sealey Gosset (meneliti problem sampel berukuran kecil). Penggunaan statistika pada masa sekarang dapat dikatakan telah menyentuh semua bidang ilmu pengetahuan, mulai dari astronomi hingga linguistika. Bidang-bidang ekonomi, biologi dan cabang-cabang terapannya, serta psikologi banyak dipengaruhi oleh statistika dalam metodologinya. Akibatnya lahirlah ilmu-ilmu gabungan seperti ekonometrika, biometrika (atau biostatistika), dan psikometrika.
Meskipun ada pihak yang menganggap statistika sebagai cabang dari matematika, tetapi sebagian pihak lainnya menganggap statistika sebagai bidang yang banyak terkait dengan matematika melihat dari sejarah dan aplikasinya. Di Indonesia, kajian statistika sebagian besar masuk dalam fakultas matematika dan ilmu pengetahuan alam, baik di dalam departemen tersendiri maupun tergabung dengan matematika.

Beberapa kontributor statistika

Konsep dasar

Terdapat bermacam-macam teknik statistik yang digunakan dalam penelitian khususnya dlam pengujian hipotesis.[1] Dalam mengaplikasikan statistika terhadap permasalahan sains, industri, atau sosial, pertama-tama dimulai dari mempelajari populasi. Makna populasi dalam statistika dapat berarti populasi benda hidup, benda mati, ataupun benda abstrak. Populasi juga dapat berupa pengukuran sebuah proses dalam waktu yang berbeda-beda, yakni dikenal dengan istilah deret waktu.
Melakukan pendataan (pengumpulan data) seluruh populasi dinamakan sensus. Sebuah sensus tentu memerlukan waktu dan biaya yang tinggi. Untuk itu, dalam statistika seringkali dilakukan pengambilan sampel (sampling), yakni sebagian kecil dari populasi, yang dapat mewakili seluruh populasi. Analisis data dari sampel nantinya digunakan untuk menggeneralisasi seluruh populasi.
Jika sampel yang diambil cukup representatif, inferensial (pengambilan keputusan) dan simpulan yang dibuat dari sampel dapat digunakan untuk menggambarkan populasi secara keseluruhan. Metode statistika tentang bagaimana cara mengambil sampel yang tepat dinamakan teknik sampling.
Analisis statistik banyak menggunakan probabilitas sebagai konsep dasarnya hal terlihat banyak digunakannya uji statistika yang mengambil dasar pada sebaran peluang. Sedangkan matematika statistika merupakan cabang dari matematika terapan yang menggunakan teori probabilitas dan analisis matematika untuk mendapatkan dasar-dasar teori statistika.
Ada dua macam statistika, yaitu statistika deskriptif dan statistika inferensial. Statistika deskriptif berkenaan dengan deskripsi data, misalnya dari menghitung rata-rata dan varians dari data mentah; mendeksripsikan menggunakan tabel-tabel atau grafik sehingga data mentah lebih mudah “dibaca” dan lebih bermakna. Sedangkan statistika inferensial lebih dari itu, misalnya melakukan pengujian hipotesis, melakukan prediksi observasi masa depan, atau membuat model regresi.
  • Statistika deskriptif berkenaan dengan bagaimana data dapat digambarkan dideskripsikan) atau disimpulkan, baik secara numerik (misalnya menghitung rata-rata dan deviasi standar) atau secara grafis (dalam bentuk tabel atau grafik), untuk mendapatkan gambaran sekilas mengenai data tersebut, sehingga lebih mudah dibaca dan bermakna.
  • Statistika inferensial berkenaan dengan permodelan data dan melakukan pengambilan keputusan berdasarkan analisis data, misalnya melakukan pengujian hipotesis, melakukan estimasi pengamatan masa mendatang (estimasi atau prediksi), membuat permodelan hubungan (korelasi, regresi, ANOVA, deret waktu), dan sebagainya.

Metode Statistika

Dua jenis penelitian: eksperimen dan survai

Terdapat dua jenis utama penelitian: eksperimen dan survei. Keduanya sama-sama mendalami pengaruh perubahan pada peubah penjelas dan perilaku peubah respon akibat perubahan itu. Beda keduanya terletak pada bagaimana kajiannya dilakukan.
Suatu eksperimen melibatkan pengukuran terhadap sistem yang dikaji, memberi perlakuan terhadap sistem, dan kemudian melakukan pengukuran (lagi) dengan cara yang sama terhadap sistem yang telah diperlakukan untuk mengetahui apakah perlakuan mengubah nilai pengukuran. Bisa juga perlakuan diberikan secara simultan dan pengaruhnya diukur dalam waktu yang bersamaan pula. Metode statistika yang berkaitan dengan pelaksanaan suatu eksperimen dipelajari dalam rancangan percobaan (desain eksperimen).
Dalam survey, di sisi lain, tidak dilakukan manipulasi terhadap sistem yang dikaji. Data dikumpulkan dan hubungan (korelasi) antara berbagai peubah diselidiki untuk memberi gambaran terhadap objek penelitian. Teknik-teknik survai dipelajari dalam metode survei.
Penelitian tipe eksperimen banyak dilakukan pada ilmu-ilmu rekayasa, misalnya teknik, ilmu pangan, agronomi, farmasi, pemasaran (marketing), dan psikologi eksperimen.
Penelitian tipe observasi paling sering dilakukan di bidang ilmu-ilmu sosial atau berkaitan dengan perilaku sehari-hari, misalnya ekonomi, psikologi dan pedagogi, kedokteran masyarakat, dan industri.

Tipe pengukuran

Ada empat tipe skala pengukuran yang digunakan di dalam statistika, yaitu nominal, ordinal, interval, dan rasio. Keempat skala pengukuran tersebut memiliki tingkat penggunaan yang berbeda dalam pengolahan statistiknya.
  • Skala nominal hanya bisa membedakan sesuatu yang bersifat kualitatif atau kategoris, misalnya jenis kelamin, agama, dan warna kulit.
  • Skala ordinal selain membedakan sesuatu juga menunjukkan tingkatan, misalnya pendidikan dan tingkat kepuasan pengguna.
  • Skala interval berupa angka kuantitatif namun tidak memiliki nilai nol mutlak sehingga titik nol dapat digeser sesuka orang yang mengukur, misalnya tahun dan suhu dalam Celcius.
  • Skala rasio berupa angka kuantitatif yang memiliki nilai nol mutlak dan tidak dapat digeser sesukanya, misalnya adalah suhu dalam Kelvin, panjang, dan massa.

Teknik-teknik statistika

Beberapa pengujian dan prosedur yang banyak digunakan dalam penelitian antara lain:

Statistika Terapan

Bebebarapa ilmu pengetahuan menggunakan statistika terapan sehingga mereka memiliki terminologi yang khusus. Disiplin ilmu tersebut antara lain:
Statistika memberikan alat analisis data bagi berbagai bidang ilmu. Kegunaannya bermacam-macam: mempelajari keragaman akibat pengukuran, mengendalikan proses, merumuskan informasi dari data, dan membantu pengambilan keputusan berdasarkan data. Statistika, karena sifatnya yang objektif, sering kali merupakan satu-satunya alat yang bisa diandalkan untuk keperluan-keperluan di atas.

source : http://id.wikipedia.org/wiki/Statistika
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How to improve vocabulary


Improving your vocabulary in English - or any language - requires commitment. Writing long lists of new words is not really an efficient way to improve your vocabulary. The technics described in this article will help you improve your vocabulary, but you will need to dedicate yourself to researching and broadening your vocabulary. There are many ways to improve your vocabulary. When working to improve your vocabulary it's important to know your goals in order to best choose the way in which you want to learn. Reading can be a great way to improve your vocabulary. However, it won't be much help on a vocabulary test next week. Here are a number of methods to help you improve, and expand, your English vocabulary.
Difficulty: Average
Time Required: from 30 minutes to 3 or more hours

Here's How:

  1. Vocabulary Trees Vocabulary trees help provide context. Once you've mapped out a few vocabulary trees, you'll discover yourself thinking in vocabulary groups. When you see a cup your mind will quickly relate such words as knife, fork, late, dishes, etc. This overview to vocabulary trees provides will help you get started. Here is an example of a vocabulary tree.
  2. Create Vocabulary Themes Create a list of vocabulary themes, include the vocabulary, a definition and an example sentence for each new item. Here is an example of a household appliance vocabulary theme sheet.
  3. Use Technology to Help You Watching DVDs is a great way to help you understand native speakers of English. Using all the fancy options watching individual scenes can help make DVD use into a vocabulary learning exercise.
  4. Specific Vocabulary Lists Rather than studying a long list of unrelated vocabulary, use specific vocabulary lists to help you prepare for the type of vocabulary you need for work, school or hobbies. These business vocabulary word lists are great for industry specific vocabulary items.
  5. Word Formation Charts Word formation is one of the keys to success for advanced level ESL learners. Advanced level English exams such as the TOEFL, First Certificate CAE and Proficiency use word formation as one of the key testing elements. These word formation charts provide the concept noun, personal noun, adjective and verb forms of key vocabulary listed in alphabetical order.
  6. Visual Dictionaries A picture is worth a thousand words. It's also very helpful for learning precise vocabulary. There are a number of excellent English learner visual dictionaries for sale. Here is an online version of a visual dictionary dedicated to jobs.
  7. Learn Collocations Collocations refer to words that often or always go together. A good example of a collocation is to do your homework. These lists of important verb + noun collocations will help your learn some of the most important.
  8. Use a Corpus Corpora are huge collections of documents that can track the number of times a word is used. By using a corpora, you can find which words are often used together with target vocabulary words. Combining corpora use with vocabulary trees is a great way to learn key vocabulary for specific vocabulary target areas. You can get started by visiting the British National Corpus.

Tips:

  1. Use vocabulary learning methods to focus quickly on the vocabulary YOU need to study.
  2. Don't make random lists of new words. Try to group words in themes. This will help you memorize new words more quickly.
  3. If you have the time, and even if you think you don't have the time, try to add context. Writing a few example sentences using new vocabulary will help you remember the words in context.
  4. Keep a vocabulary notepad at hand whenever you are reading in English. 

  5. Source : http://esl.about.com/od/engilshvocabulary/ht/htvocab.htm
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Definition of Lexical Semantics in General


Lexical semantics could be defined as the ‘study of word meaning’, but in practice it is often more specifically concerned with the study of lexical (i.e. content) word meaning, as opposed to the meanings of grammatical (or function) words. This means that lexical semanticists are most interested in the open classes of noun, verb and adjective and with more ‘contentful’ members of the adverb and preposition classes (for instance over but not of). Lexical semantics is thus mostly exempt from considering issues that arise from the use of grammatical words, such as definiteness and modality.
But while lexical semantics focuses on content words, such words cannot be studied in an agrammatical vacuum. Some lexical properties, like Aktionsart (lexical aspect) have effects throughout the sentence. So, for instance, a difference between the verbs spot and see can be described in terms of aspectual properties of the verbs: spot describes a punctual event, while see does not. This in turn affects which tense and aspect markers can be present in the same clause and how such markers are interpreted. So, I saw the bird all day long can describe a continuous seeing event, while I spotted the bird all day long must be interpreted as repeated instances of spotting events. Because of the effects of the verbs’ semantics on other elements in the sentence, Aktionsart (and other topics, like thematic role assignment) is often presented as ‘semantics’ in textbooks, rather than as ‘lexical semantics’. This can create problems both for students’ understanding of lexical semantics and for instructors’ planning of a lexical semantics course that complements a general semantics course. The approach taken below is to offer a broad range of lexical semantic topics.

2.1 Topics in lexical semantics

Lexical semantics fits into linguistics curricula in various ways. Some of the most common ways are:
  • as a sub-module in a semantics course (often lower-mid level in degree)
  • as part of a course on vocabulary/lexicology—including morphology, etymology, lexicography as well as semantics (often lower-mid level)
  • as a free-standing course (often upper level)
Plainly, what one covers is determined by the type of course, the number of sessions devoted to lexical semantics, the level of the students and what has been presented already in other courses. The following table presents an outline of key topics in lexical semantics. The rightmost column suggests issues that could be studied in more depth in courses that can presuppose or develop more background information. This is not intended as a week-by-week syllabus, but as a list of major concepts and areas of investigation, which may be presented in a different order, different combinations and different levels of depth than presented here.
  • Topics 1-4 (basic issues) should be covered in any linguistics degree, and may be covered in courses other than lexical semantics.
  • Topics 3-4 and 6 are covered in most short lexical semantics modules (e.g. within a general semantics course).
  • Coverage of topics 5 and 7-9 is more uneven across departments, but at least some aspects of these would normally be covered in an upper-level lexical semantics course.
The sources cited below are useful places to start in thinking about issues to raise in the classroom.
Table 1. Teachable issues in lexical semantics
General Topic Basic issues to discuss and useful resources Taking it further
What is a lexicon?
  • key terms: lexicon, mental lexicon, lexis, lexeme/lexical item, lexical entry
  • lexicon/grammar (idiosyncrasy of lexical information)
  • Does the lexicon include only arbitrary information? (Bybee 1998)
What is a word?
  • definitions of word/lexeme (Trask 2003b)
  • word classes (Internet Grammar of English; Trask 2003a)
What is meaning?
  • aspects of meaning: denotation, connotation, social meaning (Leech 1981, Allan 2002)
  • semantics/pragmatics
  • sense/reference
  • ambiguity/vagueness, polysemy/homonymy
Meaning components: basics
  • ‘Classical’ theory of meaning (covered well in most semantics texts)
  • Problems with classical theory (e.g. prototype effects) (Taylor 2003)
Alternatives to ‘Classical Theory’ Some selection of the following (covered briefly in Löbner 2002, Saeed 2003—more specific textbooks listed below):
  • modern componential approaches, e.g.: Conceptual Semantics (Jackendoff 2002), Natural Semantic Metalanguage (Goddard 1998)
  • ‘schematic’ approaches from Cognitive Linguistics (Croft and Cruse 2004; Evans and Green 2006)
Primary theory sources:
Semantic relations
  • synonymy, antonymy, hyponymy, (meronymy, others) (Cruse 2000b)
  • semantic fields (Lehrer 1974)
  • Classical theory approach
  • relation to propositional relations (entailment, contradiction)
  • How are these relations represented in the lexicon? (Murphy 2003, forthcoming.)
  • Are the relations semantic or also lexical? (Murphy 2003, forthcoming.)
Topics in verb meaning
  • Ontological categories: event, state (Frawley 1992)
  • Aspectual classes/Aktionsarten (Hofmann 1993; some basic coverage in Saeed 2003)
Topics in noun meaning [basic issues generally raised under topics 4/5]
Topics in adjective meaning

2.2 Approaching lexical semantics from other angles

Stand-alone lexical semantics courses are fairly unusual, but aspects of lexical semantics can be taught within a range of other disciplinary and cross-disciplinary courses. As already mentioned, this most commonly happens in general semantics courses, and can also be part of lexicography or lexicology courses. The latter, under various names, have become more common lately, particularly as introductory linguistics courses—as words provide an accessible gateway to many linguistic concepts.
Lexical semantics courses can incorporate other (inter-)disciplinary interests. Courses in other (sub-)disciplines, including the following, can benefit from inclusion of some lexical semantic topics:
Pragmatics – No semantics course can help but to tread on the toes of pragmatics, and some theoretical approaches (particularly Cognitive Linguistics) have done away with the distinction between semantic and pragmatic competence. Still, one of the first challenges in learning about lexical semantics is to be able to make the distinction between a word’s contribution to the meaning of an utterance and the contributions of context (pragmatics) and co-text (the phrasal context). Pragmatic accounts have been proposed for many lexical semantic issues, such as polysemy (e.g. Nunberg 1979, Blutner 1998) and semantic relations (Murphy 2003).
Morphology – Just as there are many interfaces between syntax and sentential semantics, so there are between morphology and lexical semantics. One is the question of whether word class is semantically determined (see Table 1, topic 2). The semantics of derivational morphemes and derived words also provides fertile thinking ground. Kreidler’s Introducing English semantics (1998) has an accessible chapter for beginners, while Lieber (2004) provides a theoretical account that fits with Jackendoff’s Conceptual Semantics.
Psycholinguistics – Most lexical semantic issues can be addressed from a psycholinguistic perspective, and psycholinguistic methods offer evidence concerning how words and meanings are organised in the mind. Aitchison (2002) provides an introduction to many of these issues. Reeves et al. (1998) outline some of the experimental methods used in investigating the mental lexicon, some of which can be replicated in the classroom.
Language acquisition – Unlike grammar, vocabulary is acquired throughout life, so some of the issues in lexical acquisition can be addressed from an adult first- or second-language angle. An appreciation for some basic issues in semantics—such as the arbtrariness of the sign and how we solve Quine’s (1960) gavagai problem (discerning the meanings of words in context) can be gained through consideration of how one initially discovers that bits of sound have meaning. Most child language textbooks include sections on lexical acquisition. Clark (1993) and Bloom (2000) take particular perspectives on some of these issues. In second language acquisition, Carter (1998) introduces many of the relevant issues, and the recent influence of lexical teaching/learning strategies provides another point of engagement with the lexicon.
Anthropological linguistics, field linguistics, typology – Cross-linguistic lexical comparison has a long history in anthropology, particularly with reference to kinship terms, biological classification and colour (Berlin and Kay 1969). Lexical-semantic typology (e.g. Talmy 1985) and contrastive lexical semantics (e.g. Weigand 1998) raise issues that are relevant to language courses as well. Linguistic relativity, the idea that the language one knows can affect one’s means of thinking, is enjoying some reconsideration (e.g. Gumperz & Levinson 1996). Some of the more promising avenues for such study involve morphological categories, such as gender. The converse idea, that lexis is affected by culture, has been explored in depth in Anna Wierzbicka’s work (particularly 1992 and 1997). These issues are usually very popular with students.
Computational linguistics – Much lexical semantic work nowadays is done in computational linguistics/natural language processing (NLP), including much work on polysemy/ambiguity resolution and the development of semantic networks. WordNet (Fellbaum 1998) has enjoyed particular success as an NLP tool and model of lexical structure. There is a large body of work on ambiguity resolution, and Pustejovsky’s (1995) Generative Lexicon Theory (see below) has arisen though and been applied to such NLP concerns.

2.3 Lexical semantic theories

Whether to teach a particular theoretical perspective on lexical semantics is a tricky question, since in a sense, there’s no such thing as a free-standing ‘lexical semantic theory’, but instead there are semantic theories that pay more or less attention to representation at the lexical level. If one were to try to cover the topics listed in Table 1 with reference to a single theory, it is unlikely that even coverage of the topics would be possible, since different theoretical perspectives have taken different starting points.
For first-year courses, a pre-theoretical approach is usually most attractive. This can be done, for instance, by taking a lexicographical approach—i.e. what are the issues that one needs to understand in order to write dictionary entries? Jackson’s textbook Words and their meaning (1988) took this kind of approach. Hudson’s workbook Word meaning (1995) introduces basic lexical semantic concepts with minimal theoretical discussion, and Cruse’s Meaning in language (2000b) is heavily focused on lexical issues. In addition, there are lexicology textbooks (Jackson and Zé Amvela 2000, Singleton 2000) that are suitable for lower-level courses. These are generally more suitable for courses that intend an ‘introduction to linguistics through words’, since their treatments of basic semantic issues, such as polysemy, are rather cursory.
In more advanced courses, theoretical approaches are appropriate, but which ones should be tackled is to some degree a matter of taste and of the rest of the curriculum—in that it could be confusing to teach a theory for lexical semantics that is incompatible with the theories taught in the department for general semantics and grammar. That said, while general semantics courses are often taught from a formal, model-theoretic perspective, lexical semantics teaching is generally approached from non-formal stances.
My own preference is to contrast different theoretical approaches to a particular topic (without presenting formalisms that require knowledge of particular logical languages)—but this presents particular challenges. First, the approaches to be contrasted may have very different basic assumptions about the nature of meaning or the lexicon, and thus a fair amount of background to the theories must be presented. Second, they may not be trying to answer exactly the same questions or to cover the same set of phenomena.
There are at least three ways of getting around these issues. One is to present from the beginning two general types of approach (e.g., componential vs image-schematic), examining in detail first their basic assumptions, and then investigating how the contrasting theories have (or would) approach particular phenomena. We can call this the ‘comparative approach’. Because one is dealing with ‘families’ of theories in this way, it can be possible to examine a range of problems from contrasting perspectives. Still, it does require some theoretical juggling. (This is the approach of Murphy, forthcoming.) Another possibility is to take an ‘envelope-pushing’ approach, in which a particular theory is taken as a starting point, but then challenged to account for issues that have been discussed from purely descriptive or other theoretical approaches. This is most suitable to upper-level courses, in which the students are ready to develop their own theoretical accounts. The final option is to simply teach a theory as it is presented in its fundamental literature. However, while this last option may be appealingly straightforward, it is the least promising for instilling critical thinking skills or a broad perspective on the field. The comparative and envelope-pushing approaches can also be valuable for inspiring further research projects, for example in a final-year dissertation.
One of the greatest challenges for teaching semantics from a theoretical standpoint is the lack of theory-specific textbooks for the undergraduate level. The only current texts in this vein that I am aware of are Goddard’s Semantic Analysis (1998), which introduces mostly lexical issues in the Natural Semantic Metalanguage framework, and Cognitive Linguistics texts (most of which are not limited to lexical semantic issues). Some general semantics textbooks (e.g. Löbner 2002, Saeed 2003) give comparative overviews of some theoretical approaches, but for the most part, it can be difficult to find textbooks that are suitable to non-formal theories. Frawley’s Linguistic Semantics (1992) covers many issues of lexical interest at some level of comparative theoretical detail. Another option is to develop a reading pack, based on shorter primary materials, including book chapters, journal articles and encyclopedic overviews.
Some relevant, mostly current theoretical approaches are listed below, with citation of their foundational literature or (where possible) textbooks—marked here by T. In general, they can be divided into two types: componential and schematic. Componential approaches rely on a language-like system of meaning representation involving a limited number of primitive symbols in some kind of grammar—the classic example being the model in Katz and Fodor 1963. Schematic approaches take the position that word meaning must be approached within more complex conceptual structures, often relying on a more image-driven representational form, such as the ‘image schemas’ of Lakoff 1987. Componential approaches are more generally associated with the goals of generative linguistics, and schematic ones with cognitive linguistics, although there is a wide range of variation among all these approaches.
Table 2. Some theories of (lexical) semantics
Theory Characteristics Starting point references
Cognitive Semantics
  • family of theoretical approaches
  • schematic
Conceptual Semantics
  • componential
  • not strictly lexical
  • strong on argument structure and other interfaces between semantics and grammar
Frame Semantics
  • schematic
  • links to lexicographical and machine translation projects
  • FrameNet website
    [no real overview text]
Generative Lexicon
  • componential; qualia structure
  • strong on meaning variation in context; argument structure
Natural Semantic Metalanguage
  • componential; universal primes; non-formal structure
  • strong on names of abstract entities; cross-cultural comparison


3. Teaching through student-led research

Words provide self-contained packets of language about which many types of investigation can be carried out. Teaching lexical semantics is thus particularly exciting for the opportunities that it allows for student-led, original research.

3.1 Research methods for lexical semantics

Students can research word meaning using a variety of tools, including introspection, fieldwork, dictionaries, corpora and (where appropriate) psycholinguistic experimentation, as discussed in turn below.
Introspection: Asking oneself how one uses language is the classic linguistic method, and it should be used throughout a lexical semantics course. Beginning students usually need some guidance to bring them from “what does this word mean to me?” (a question whose answer may not be reliable) to finding answers for the question “how can I test the semantic properties of this word?” For students whose native language is not the language of the course, introspection is usually not a suitable main means of discovery. I therefore allow students to treat any assignment that calls for introspection as also allowing ‘field methods’.
Field methods: Where native intuitions are not available or where they may vary, one may instead (or in addition) quiz native-speaker informants about the acceptability of a word in various contexts (or about the boundaries of the word’s sense, etc.). Here, a little more training is needed, in part to avoid wasting informants’ time and patience. This can be achieved by modelling field methods practice in the classroom and then asking the students to devise a list of questions/examples that they will ask their informants about. For any assignment that is the same for all students on the course, I enforce a rule that their informants cannot be members of the class, nor other Linguistics students, so that the ‘field methods’ cannot be mistaken for ‘collusion’.
Dictionaries: Dictionary definitions can provide a good starting point for thinking about a word’s meaning, the nature of polysemy and the relation between descriptive and prescriptive attitudes to language. Advanced learners’ dictionaries often provide more ‘grammatical’ information about words, including information about collocations and more specific grammatical categories (e.g. count/mass nouns), which can be valuable for both non-native and native speakers. The Oxford English Dictionary, on the other hand, provides plenty of etymological information and examples of usage. Both types can be valuable for different kinds of activities. Some activities using dictionaries include: using a number of dictionaries to map the sense boundaries of a particular word, comparing actual uses of words to their dictionary definitions (are their senses more fluid than the dictionary records?), and determining the principles underlying the organisation of information in a thesaurus.
Corpora: Corpus linguistics offers a means to supplement and/or challenge introspective evidence. The problem for any lexical semantics course, however, is whether the facilities and time are available to provide students with access to a corpus, corpus software and the requisite skills to use them. For my own courses, the answer has been ‘no’, but it is still possible to introduce corpus analysis. A basic way is to provide students with printouts or word-processor/pdf files of pre-prepared concordances. Once students know a bit about corpora, they can have a hand in designing the methodology for a particular corpus investigation, with the tutor or technician still charged with executing it. If the question to be put to the corpus is simply “can one say X in English?”, it will usually suffice to have students search for exact phrases on the internet using a standard search engine.
Experiments: Most lexical semantics courses will not have the time/facilities to teach experimental methods, nor to teach students to use the types of software usually used in psycholinguistic experimentation. Some experiments, however, like some used by Eleanor Rosch (1978) to demonstrate prototype effects, can be carried out with pen and paper and extended to different words/categories.

3.2 Structuring a course around original research

Stand-alone assignments and seminar activities can be based on any (or several) of the above methodologies. It is also possible to devise a course in which student-led research provides the themes to be discussed.
Adopt-a-Word: My own lexical semantic courses are structured around an assignment called ‘Adopt-a-Word’, which allows students to apply a number of key concepts and methodologies to a single word, thus building up a portfolio of short assignments around the theme of a word. (The Adopt-a-Word scheme for a year 1 lexicology course is described in more detail at the LLAS event report, listed in the web links below.) That course is also designed to establish key disciplinary, academic and transferable skills. (See Hudson 2003 for discussion of skills development.) For a more advanced/specific lexical semantics course, suitable assignments can be designed. (Murphy, forthcoming, provides a number of ideas, most of which have been tested in a final-year course in the US.)
In my courses, students receive at the beginning of the term a document with a dozen or so possible Adopt-a-Word assignments. After each student is assigned (or chooses) their own word, it is up to the student to determine (with some guidance) which assignments suit the word. For instance, an assignment on argument structure may not be suitable for many nouns. The student then does a number of assignments on the same word. The same assignments can be used without adopting a word—i.e. the tutor could assign different words for each assignment, thus allowing students to be assessed on every element of the course, rather than just those that suit their word.
One advantage of the Adopt-a-Word method is that the student becomes an ‘expert’ on a word, and thus later assignments are informed by work for previous ones. Another is that using the adopted word as a theme for the term allows for greater continuity and coherence in a survey course that flits from descriptive/theoretical topic to topic. Finally, involving students in original research greatly reduces the potential for (intentional or unintentional) plagiarism in essay-writing.
Dissertations in lexical semantics: While Adopt-a-Word allows for a broad-based approach to semantics/lexicology, some upper-level courses require more in-depth research projects, as can be assessed through a dissertation. Here, again, it is very doable for students to tackle original lexical semantic research, preferably using more than one of the methodologies discussed above. To give some examples, here are short descriptions of some recent final-year dissertations at Sussex:
Is David Beckham black? An investigation of the meaning of the racial term black in the UK, testing hypotheses based on Social Identity Theory posited in Murphy 1997. Data sources included dictionary definitions, questionnaire responses and examples of usage from the press.
Child and adult in Japan and Britain. A study by a Japanese native speaker based on Wierzbicka’s (1997) contention that the meaning/use of particular words can offer insight into cultural differences. The student used dictionary definitions, legal definitions and questionnaire responses to contrast the denotations and connotations of words for ‘child’ and ‘adult’ in the two cultures.
Bizarre: a case study of near-synonymy. This student used corpus data and affect-based questionnaires both to demonstrate that exact synonyms for bizarre do not exist and to determine the ‘semantic prosody’ (Louw 1993) of bizarre and its synonyms.

4. Closing note

This guide has briefly raised some issues concerning the teaching of lexical semantics, but it has necessarily been based mostly on my own experience. In order to improve the guide, please contact me (m.l.murphy@sussex.ac.uk) with information on your successes in teaching lexical semantics and/or feedback on your experience of any of the methods discussed here.

Sumber https://www.llas.ac.uk/resources/gpg/2821
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