The Potential for Learning Specialized Vocabulary of University Lectures and Seminars Through Watching Discipline- Related TV Programs: Insights From Medical Corpora |

The Potential for Learning Specialized Vocabulary of University Lectures and Seminars Through Watching Discipline- Related TV Programs: Insights FromMedical Corpora THI NGOC YEN DANG Uni

The Potential for Learning Specialized Vocabulary of University Lectures and Seminars Through Watching Discipline- Related TV Programs: Insights From

Medical Corpora

THI NGOC YEN DANG

University of Leeds

Leeds, United Kingdom

This study investigated the potential of discipline-related televisionprograms as sources for incidental learning of specialized vocabularyused in university lectures and seminars First, a Medical SpokenWord List (MSWL) of 895 specialized word types was developed from

a 556,074-word corpus of medical lectures and seminars based on amixed method: corpus-driven analysis, specialized dictionary check-ing, and expert ratings Then, an 11,036,771-word corpus of 37 medi-cal television programs was developed and analyzed to examine theextent to which the MSWL words were encountered in these pro-grams Adopting 5 encounters or more, 10 encounters or more, 15encounters or more, and 20 encounters or more as the frequencycutoff points at which incidental learning may happen, this studyfound that the number of MSWL words that met these cutoff pointsincreased as the number of episodes, seasons, and programsincreased This indicates that discipline-related television programsare potential sources for incidental learning of specialized vocabularyused in lectures and seminars if these programs are watched regularlyand in a sequential order

doi: 10.1002/tesq.552

Although specialized vocabulary is essential for academic success inEnglish-medium university programs, it is frequently cited as one

of the greatest challenges for second language (L2) learners studying

in these programs (e.g., Evans & Morrison, 2011) Therefore, it isimportant for researchers and practitioners to help learners of Englishfor academic or special purposes (EAP/ESP) to develop the knowl-edge of specialized vocabulary that they will encounter often in theiracademic studies In response to this call, researchers have created

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specialized word lists from corpora that represent the genres that

EAP/ESP learners engage with in their studies Most of these lists were

based on the analysis of written materials The very few lists

investigat-ing spoken discourse focused on the shared vocabulary of a range of

academic disciplines Creating lists that represent vocabulary in

aca-demic spoken discourse of a specific discipline is important because

EAP/ESP students need to understand not only reading materials but

also lectures and seminars in their academic study (Dang, Coxhead, &

Webb, 2017)

With respect to teaching and learning, to help learners study items

from specialized wordlists, a principled vocabulary program should

combine both deliberate learning and incidental learning (Nation,

2013; Schmitt, 2008; Webb & Nation, 2017) Deliberate learning

means that vocabulary is learned through tasks or exercises whose

pri-mary aim is to retain words in short- and long-term memory

Inciden-tal learning means vocabulary is learned as a by-product of another

task such as reading or listening to texts Although deliberate learning

is essential for acquiring a large amount of specialized vocabulary,

rely-ing solely on deliberate learnrely-ing is inefficient for several reasons First,

there are limits to how much vocabulary can be explicitly taught and

learned in the classroom (Webb & Nation, 2017) Second, not all

EAP/ESP teachers have sufficient background knowledge on learners’

specific disciplines to effectively teach specialized vocabulary

(Cox-head, 2018) Third, vocabulary development is an incremental process

that requires many encounters before new words are learned and

knowledge of known words consolidated (Nation, 2013; Webb &

Nation, 2017) Therefore, apart from deliberate learning, incidental

learning of specialized vocabulary through being exposed to the target

language outside the classroom is an invaluable supplementary

resource for L2 vocabulary learning (Schmitt, 2008)

For incidental learning to happen, learners need to be exposed to a

great deal of input Unfortunately, in many EFL contexts, the amount

of input, especially specialized spoken input, is very limited (Webb &

Nation, 2017) Thus, it is crucial to identify potential resources for

incidental learning of specialized vocabulary used in university lectures

and seminars Both corpus-based studies (Csomay & Petrovıc, 2012;

Rodgers & Webb, 2011; Webb & Rodgers, 2009) and intervention

stud-ies (Peters & Webb, 2018; Rodgers, 2013) have indicated that

inciden-tal vocabulary learning can happen through viewing television

programs, and therefore, television programs may be potential

resources for incidental vocabulary learning in EFL contexts

The extent to which television programs can help learners learn

specialized vocabulary of academic lectures and seminars, however, is

less transparent The common assumption is that television programs

may be irrelevant resources to learn specialized vocabulary of sity lectures and seminars due to the differences between the two gen-res University lectures and seminars are likely to be more formal andacademic (as opposed to the more informal and entertaining nature

univer-of television programs) However, if we consider this issue more fully, discipline-related television programs may be potential resourcesfor learning specialized vocabulary of university lectures and seminars.Previous research found that watching discipline-related television pro-grams offers more opportunities for incidental vocabulary learningthan watching unrelated programs (Rodgers & Webb, 2011; Webb,2011) Additionally, specialized vocabulary tends to occur more fre-quently in specialized texts than in nonspecialized texts (Chung &Nation, 2003; Nation, Coxhead, Chung, & Quero, 2016) It follows,therefore, that discipline-related programs may contain a considerablenumber of specialized words of university lectures and seminars.Watching these programs may then provide great opportunities for fre-quent encounters with these words and help incidental learning tohappen To date, no studies have investigated the potential of disci-pline-related television programs as sources for incidental learning ofthe specialized vocabulary that EAP/ESP students are likely to encoun-ter in academic lectures and seminars

care-To fill these gaps, the present study aims to (a) develop a list of cialized vocabulary of university lectures and seminars in medicine and(b) examine the potential for incidental learning of items in this listthrough watching medical television programs It is important to inves-tigate specialized vocabulary in academic speech of medicine Dangand Webb (2014) found that academic speech from life and medicalsciences is more challenging in terms of vocabulary than academicspeech from arts or humanities, physical sciences, and social sciences;that is, to achieve reasonable comprehension of academic lectures andseminars, learners would need a larger vocabulary size in the case oflife and medical sciences (5,000 word families) than in the case ofother disciplines (3,000–4,000 word families) However, no medicalspoken wordlists are available, and existing medical written wordlistsmay not be sufficient in helping learners deal with academic speechbecause there might be differences between spoken and written lan-guage Additionally, the growing number of English language medicaltelevision programs (e.g., Grey’s Anatomy, The Good Doctor) that L2learners can easily access through DVD, cable television, and onlinemedia websites suggests that these programs may be potentialresources for EAP/ESP students to learn specialized vocabulary ofmedical lectures and seminars incidentally

spe-Specialized Vocabulary in Medicine

There are two views toward defining specialized vocabulary (Liu &

Lei, 2020; Nation, 2016) The narrow view defines vocabulary as those

words that are common in a specific discipline or a group of

plines but are uncommon in other disciplines or other groups of

disci-plines (e.g., Coxhead, 2000; Wang, Liang, & Ge, 2008) The broad

view (e.g., Ha & Hyland, 2017; Lei & Liu, 2016; Lu, 2018) considers

specialized words as those that are closely related to a particular

disci-pline They can range from items that are typically known only by

spe-cialists in that discipline (e.g., aorta, renal) to items also known by

people who are not specialists in that discipline (e.g., heart, blood) This

view takes into consideration the argument that many words may have

high frequency in general use but also carry specialized meanings

within a particular discipline, and they deserve to be classified as

spe-cialized vocabulary (e.g., Dang et al., 2017; Gardner & Davies, 2014;

Ha & Hyland, 2017; Lei & Liu, 2016; Lu, 2018) The broad view is

taken in the present study

Specialized vocabulary is important because it can make up a large

proportion of words in a specialized text Let us take the field of

medi-cine as an example Specialized vocabulary accounts for 12.24%–

31.75% of the words in medical texts (Chung & Nation, 2003; Hsu,

2013; Lei & Liu, 2016; Wang et al., 2008) This suggests that

special-ized vocabulary may present a great learning burden for L2 learners

In fact, specialized vocabulary was listed as one of the biggest

chal-lenges faced by L2 learners at English-medium universities (e.g., Evans

& Morrison, 2011) Such a situation highlights the need for EAP/ESP

researchers and teachers to support L2 learners in the study of

special-ized vocabulary

Much of the effort around specialized vocabulary in EAP/ESP

research has focused on the development of wordlists from specialized

corpora for L2 learners Several corpus-based wordlists have been

specifically created to serve the need of EAP/ESP students who wish

to study medicine (Hsu, 2013; Lei & Liu, 2016; Wang et al., 2008) All

of them are written wordlists, and available specialized spoken

word-lists—Academic Spoken Word List (Dang et al., 2017), Soft Science

Spoken Word List (Dang, 2018b), and Hard Science Spoken Word List

(Dang, 2018a)—present shared words between medicine and other

dis-ciplines rather than all the words that occurred frequently in academic

speech of medicine Developing a medical spoken wordlist is

impor-tant because vocabulary in spoken discourse may be different from

that in written discourse Moreover, previous research has suggested

that there was a substantial variation in the lexical items of academic

speech from different disciplines (Dang, 2018b), and the lexicaldemands of academic speech from life and medical sciences are likely

to be greater than those from other disciplines (Dang & Webb, 2014).The development of a medical spoken wordlist would generate furtherinsights into the nature of vocabulary in medical spoken English aswell as providing EAP/ESP students with a useful tool for vocabularylearning

Television as a Source for Incidental Learning of Specialized Vocabulary

Most research on incidental vocabulary learning has looked at ing from reading (e.g., Pellicer-Sanchez & Schmitt, 2010; Webb &Chang, 2015) and listening (e.g., van Zeeland & Schmitt, 2013; Vidal,2003) In recent years, however, there has been increasing interest invocabulary learning through audiovisual input such as television pro-grams The motivation behind this trend may be the wide availability

learn-of English language television programs through DVDs, cable sion, and online media websites These programs are valuable sources

televi-of L2 spoken input in many EFL contexts, where there may be limitedopportunities for L2 listening Surveys with EFL learners revealed thatwatching L2 television programs is a more important source of out-of-class exposure to L2 than reading books (Peters, 2018) Experimentalstudies with EFL learners also indicate that L2 vocabulary may belearned incidentally through watching television programs (Nguyen &Boers, 2018; Peters, Heynen, & Puimege, 2016; Peters & Webb, 2018;Rodgers, 2013)

Corpus-driven studies have examined incidental learning throughwatching television from two perspectives: (a) the number of wordsneeded to comprehend television programs and (b) the frequency ofreoccurrences of words in these programs The first line of researchdraws on studies investigating the effect of lexical coverage on compre-hension Lexical coverage is the percentage of known words in a text(Nation & Waring, 1997) Because of its close relationship with com-prehension (e.g., Schmitt, Jiang, & Grabe, 2011; van Zeeland & Sch-mitt, 2013), lexical coverage is an important factor that allows us todetermine the extent to which learners might be able to understand atext and incidentally learn vocabulary from that text Although theamount of lexical coverage needed for incidental learning may varyaccording to discourse types, it is commonly accepted that a coverage

of 95% is necessary in the case of listening (van Zeeland & Schmitt,2013) Previous research (Rodgers & Webb, 2011; Webb, 2011; Webb

& Rodgers, 2009) has consistently indicated that if programs were

ana-lyzed as a whole, 3,000 word families plus proper nouns and marginal

words would provide 95% coverage of television programs; however,

there was a variation in the amount of vocabulary needed to reach

95% of each genre/program This indicates that although 3,000 word

families is generally necessary for incidental vocabulary learning from

television programs to happen, the vocabulary size required may vary

from genre to genre and program to program

The second line of research determines the extent to which

inci-dental learning may occur through watching television programs by

examining how often words reoccurred in these programs Because

this line of research is directly related to the purpose of the current

study, it is discussed in more detail This line of research builds on

empirical evidence that the more often particular words are

encoun-tered in television programs, the more likely they are to be learned

(Peters & Webb, 2018; Peters et al., 2016; Rodgers, 2013) Most

previ-ous studies have focused on incidental learning of low-frequency

words Webb and Rodgers (2009) analyzed vocabulary in a

264,384-word corpus drawn from 88 television programs of various genres

They found that 69.15% of the low-frequency words in their corpus

occurred only once or twice, and 15.6% were encountered five or

more times This indicates that incidental learning was unlikely to

occur for most low-frequency words with limited viewing over a variety

of genres However, Webb and Rodgers argued that the number of

programs in their study was relatively small compared to the amount

of time people watch television in their first language; therefore, if

stu-dents watched television regularly over a long period of time, the

potential for learning would increase They also suggested that

watch-ing television programs from subgenres with similar topics and story

lines may be an effective way to increase vocabulary learning through

viewing

Webb and Rodgers’s (2009) suggestion was confirmed by

subse-quent studies Rodgers and Webb (2011) compared the vocabulary in

142 episodes from six related television programs with those in 146

episodes from random television programs They found that episodes

from related programs had lower vocabulary loads than episodes from

unrelated programs and that low-frequency words reoccurred more

often in related programs than in unrelated programs Webb (2011)

further compared vocabulary in episodes from the same genres with

those from different genres Using the same corpus as Rodgers and

Webb (2011), he categorized the six related television programs into

three groups based on their genres: medical dramas, criminal forensic

investigation dramas, and spy/action dramas Webb also randomly

grouped the 146 episodes from random television programs into three

sets He found that episodes of programs from the same genres hadlower vocabulary load and higher percentage of low-frequency wordreoccurrences than episodes from random programs Together, Rod-gers and Webb’s (2011) and Webb’s (2011) findings indicate that epi-sodes of programs within the same genres may have greater potentialfor incidental vocabulary learning than episodes of unrelated pro-grams However, it should be noted that in Rodgers and Webb’s(2011) and Webb’s (2011) studies, each program consisted of onlyone season and each genre was represented by only two programs.Further research that focuses on a particular genre such as medicaldramas and examines all seasons in the programs would provide fur-ther insight into the potential for vocabulary learning through televi-sion programs from the same genre.

The only study that has examined the potential for incidental ing of specialized vocabulary through watching discipline-related televi-sion programs was Csomay and Petrovıc’s (2012) study Definingspecialized words as words that appeared in discipline-related moviesand television programs and had specialized meanings in a specializeddictionary, Csomay and Petrovıc created a specialized wordlist from a128,897-word corpus of seven law-related movies and a five-episodelaw-related television program Then, they examined the occurrences

learn-of these words in corpus and found that words with 10 or moreencounters accounted for 73.8%1 of the specialized vocabulary in thecorpus Csomay and Petrovıc provided useful findings and highlight

an area of incidental vocabulary learning that merits investigation.However, they did not intentionally focus on specialized vocabulary inacademic lectures and seminars Their specialized wordlist was devel-oped from law-related movies and television programs rather thanfrom academic lectures and seminars As a result, their study did nottell us the potential for learning the specialized words that EAP/ESPstudents would encounter in academic lectures and seminars in theirfuture study

Taken as a whole, the review of previous corpus-driven research onincidental learning through viewing has indicated that it is essential toinvestigate the occurrences of specialized vocabulary used in academiclectures and seminars in discipline-related television programs, but noresearch has been conducted to address this need If such research isconducted, it should be based on the analysis of vocabulary in a largecorpus of academic lectures and seminars and a large corpus of multi-ple discipline-related television programs

1 There are two possible reasons for this high percentage First, Csomay and Petrov ıc (2012) included high-frequency words in their specialized word list if these words also had specialized meanings Second, their list was validated in the corpus from which it was developed.

Number of Encounters Necessary for Incidental Learning

Through Viewing to Happen

Incidental learning is an incremental process that needs a great

amount of input (Webb & Nation, 2017) Experimental studies (Peters

& Webb, 2018; Peters et al., 2016; Rodgers, 2013) found a relationship

between the number of encounters and incidental vocabulary learning

through viewing; that is, the more often words are encountered, the

more likely they are to be learned However, these studies did not

indi-cate the frequency threshold at which incidental vocabulary learning

through viewing happens However, previous corpus-driven research

on viewing (Csomay & Petrovıc, 2012; Rodgers & Webb, 2011; Webb,

2011) set 10 or more times as the point at which incidental learning

of new words happens, and 5–9 times as the points at which learners

gain partial knowledge of known words However, these cutoff points

were based on studies with reading Imagery presented in television

can make learning words through viewing easier than through

read-ing, but the online nature of viewing may make it more difficult to

learn words through viewing than through reading (Rodgers, 2018)

Therefore, it is unclear whether viewing requires more encounters for

incidental learning than reading In fact, Webb and Nation (2017)

point out that there is no specific frequency threshold for incidental

vocabulary learning to happen; instead, there is a relationship between

the number of encounters and incidental learning Thus, to provide

better insights into the potential for incidental learning specialized

vocabulary through viewing, rather than relying on a specific

fre-quency cutoff point the present study uses a range of cutoff points:

(a) 5 or more encounters, (b) 10 or more encounters, (c) 15 or more

encounters, and (d) 20 or more encounters Words with encounters of

1–4 times are likely to offer a very small amount of learning, whereas

words with higher numbers of encounters may provide a greater

likeli-hood of learning Five encounters and 10 encounters were chosen

because these cutoff points have been used by previous corpus-driven

research on incidental vocabulary learning through viewing The

15-encounter cutoff point was chosen because van Zeeland and Schmitt

(2013) found that at least 15 encounters are needed for incidental

learning from listening As students receive audiovisual support in the

viewing condition, they may need fewer encounters in the viewing

con-dition than in the listening concon-dition Fifteen or more encounters,

thus, is a useful cutoff point to examine the potential for incidental

learning through viewing The 20-encounter cutoff point was chosen

because Uchihara, Webb, and Yanagisawa’s (2019) meta-analysis of

research on incidental learning revealed that the effect of frequency

on incidental vocabulary learning is likely to remain prominent up toaround 20 encounters.

The Present Study and Research Questions

The purpose of the present study is to examine the potential forlearning specialized vocabulary through watching medical televisionprograms In particular, it aims to (a) develop a list of specializedvocabulary used in university lectures and seminars in medicine and(b) examine the potential for incidental learning of items in this listthrough watching medical television programs Unlike previous corpus-driven research on incidental vocabulary learning, this study does notmake a list of specialized vocabulary from medical television programsbut rather from medical lectures and seminars Also, instead of relying

on one cutoff point, it uses a range of frequency cutoff points to ine the potential for incidental vocabulary learning The study shedslight on the potential of discipline-related television programs for inci-dental learning of specialized vocabulary used in academic lectures andseminars It seeks to address the following research questions:

exam-1 What are the specialized words in medical lectures and seminars?

2 To what extent can these words be encountered in medical vision programs?

tele-METHODOLOGY

Corpora

Two corpora were developed for this study The Medical AcademicSpoken Corpus (556,074 words) was created from transcripts of 32 uni-versity lectures and 17 university seminars in health and medicalsciences courses from five sources: the British Academic Spoken Eng-lish Corpus, the Michigan Corpus of Spoken English, the PearsonInternational Corpus of Academic English, Yale open courseware, andthe English as a Lingua Franca in Academic Setting corpus

The medical television program corpus (11,036,771 words) wasderived from transcripts of 2,073 episodes from 37 medical televisionprograms Following previous studies (e.g., Rodgers & Webb, 2011;Webb & Rodgers, 2009), these programs were selected based on theavailability of scripts, genres, and popularity (see Appendix A in theonline Supporting Information for detailed information of these pro-grams) A season refers to a short succession of episodes, lasting

usually less than a year A program consists of one or more seasons,

which means that a program includes episodes from all seasons across

time Following previous research on the lexical demands of spoken

discourse (e.g., Dang & Webb, 2014; Webb & Rodgers, 2009),

inaudi-ble words such as stage commands, storyline (e.g., country music

play-ing, chuckles), and speakers’ name (e.g., Chris, nf0157) were removed

from the transcripts Only words that could be heard during the

con-versations were kept for the analysis The two corpora developed in

the present study are the largest medical spoken corpus and medical

television program corpora that have ever been created

Identifying Specialized Vocabulary in Medical Lectures and

Seminars

To identify specialized vocabulary in medical lectures and seminars,

a mixed method was adopted: (a) corpus-driven analysis, (b)

special-ized dictionary checking, and (c) expert ratings This follows the

cur-rent trend in developing specialized wordlists (Dang, 2020; Liu & Lei,

2020; Nation, 2016) The corpus-driven analysis ensured that the initial

list captures the most frequent, wide-ranging, and distinct lexical items

in medical lectures and seminars The specialized dictionary checking

and expert ratings were essential They took into account the fact that

some general high-frequency words (e.g., tissue, delivery) also have

spe-cialized meaning and should be considered spespe-cialized vocabulary and

made sure that the list reflects the words that students are likely to

meet in their discipline (Coxhead & Demecheleer, 2018)

In the corpus-driven analysis, word type was chosen as the unit of

counting of the Medical Spoken Word List (MSWL) because it is a

common unit of counting of specialized wordlists (Liu & Lei, 2020;

Lu, 2018; Nation, 2016) Tokens refer to the word forms occurring in

a text (Nation, 2013) Repeated word forms are counted as separate

tokens In contrast, types are unrepeated word forms occurring in a

text (Nation, 2013) For example, counting words is difficult but it is fun

contains eight tokens but seven word types because the word form is

occurs twice The selected items for the initial list should (a) be

con-tent words, (b) occur with relative frequency of at least 9.4 times per

million in the medical spoken corpus, (c) appear in at least five

tran-scripts, and (d) have the keyness of 28.7 when comparing their

fre-quency in medical speech (represented by the medical spoken corpus)

with their frequency in general conversation (represented by Love

et al.’s 2017 Spoken BNC2014) Only content words were selected so

that the MSWL would include meaningful items The frequency and

range criteria ensured that the list captured the most frequent and

wide-ranging words in medical lectures and seminars, whereas the ness criterion ensured the specialized nature of the words; that is, theselected words had significantly higher frequency in medical speechthan in general conversation The frequency, range, and keyness cutoffpoints were set as the result of extensive experimentation that com-pared items included in or excluded from the MSWL at different cut-off points These cutoff points were selected because, unlike morelenient cutoff points, these cutoff points ensured that the MSWL con-sisted of a relatively small number of items (fewer than 900 words);unlike stricter cutoff points, these cutoff points still allow learners torecognize a reasonable proportion of words in medical lectures andseminars (more than 13%) Heatley, Nation, and Coxhead’s (2002)RANGE was used to analyze the frequency and range of items in themedical spoken corpus This program lists the words that occurred in

key-a text bkey-ased on their frequency key-and rkey-ange Anthony’s (n.d.) Antconcwas used to determine the keywords This program compares the fre-quency of words in a specialized corpus and a reference corpus andgenerates a list of key words whose frequency in the specialized corpus

is significantly higher than that in the reference corpus

Items selected in the corpus-driven analysis were then checked intwo well-known medical English dictionaries: Merriam-Webster’s medi-cal English dictionary and Taber’s Cyclopedic medical dictionary.These dictionaries were used by Lei and Liu (2016) to identify itemsfor their medical written vocabulary list Words that appeared in nei-ther dictionary were removed

The degree of technicality of items remaining after the specializeddictionary checking was then rated by two experts The first expert had

a BA in medicine and an MA and PhD in applied linguistics The ond expert had a BA in English language and 18 years’ experienceworking as a doctor A semantic scale was used in the rating (Table 1).This scale was adapted from the scales used in previous research ondeveloping specialized wordlists (Chung & Nation, 2003; Ha & Hyland,2017; Lu, 2018) When the experts were not sure which points to give

sec-to a certain word, concordance lines of that word in the medical spokencorpus were provided to help them make the decision Words rated as 1

by both experts (e.g, cent, fashion, chart) were removed from the list

Analyzing Vocabulary in Medicine-Related Television

Programs

To determine the extent to which the MSWL words are tered in medicine-related television programs, transcripts in the

encoun-medical television program corpus were run through the RANGE

pro-gram with the MSWL as the base word list The occurrences of the

MSWL words were examined from five aspects: (a) in episode 1 of

sea-son 1 of each program, (b) in seasea-son 1 of each program, (c) in each

program, (d) in each group of programs that have the same lexical

demand, and (e) in all 37 programs together This method of analysis

allowed us to systematically determine the potential for learning the

MSWL words through watching a single episode, a single season, a

complete program, a group of programs with the same lexical

demand, and all programs The MSWL words were classified into five

bands based on the number of encounters in the corpus: (a) 1–4

encounters, (b) 5 or more encounters, (c) 10 or more encounters, (d)

15 or more encounters, and (e) 20 or more encounters

To determine the lexical demands of each program, Nation’s

(2012) British National Corpus (BNC)/Corpus of Contemporary

American English (COCA) twenty-five 1,000–word family lists were

used with RANGE to show the 1,000-word levels (1,000–25,000) at

which the word families in the medicine-related drama program

occurred The BNC/COCA lists are the largest and most recent and

popular frequency-based wordlists of general English Words that do

not belong to the most frequent 25,000 word families were classified

by RANGE as proper nouns (list 31), marginal words (list 32),

com-pounds (list 33), abbreviations (list 34), and not in the lists Proper

nouns and marginal words that were listed by RANGE as not in the

lists were added to the relevant lists Following previous research on

lexical demands of movies and television programs (e.g., Webb &

Rod-gers, 2009), proper nouns (e.g., Catherine, Justin) and marginal words

(e.g., uhuh, hmhm) were included in the cumulative coverage at the

1,000-word levels with the assumption that they have a low learning

burden and are likely to be understood in context In the present

study, the lexical demands were represented by the number of word

families together with proper nouns and marginal words needed to

TABLE 1

Semantic Scale Used in the Present Study

Scale Description

1 Word that has no relationship with medicine

2 Word that has a meaning related to medicine and is (almost) the same as the

meaning in everyday language use

3 Word that has a meaning related to medicine and is different from the meaning in

everyday language use

4 Word that has only one (or more) meaning(s) and it is (they are) only related to

medicine