Language Learning
ISSN 0023-8333
A Comparison of the Effects of Reading
and Listening on Incidental Vocabulary
Acquisition
Karina Vidal
Universidad Autónoma de Madrid
This article compares the effects of listening and reading on the incidental acquisition
and retention of vocabulary. Two hundred thirty students participated in the study: They
either (a) read three academic texts, (b) watched three lectures, or (c) received no input at
all and just completed the vocabulary measures. This study also assessed and compared
the relationship between acquisition through each of these presentation modes and
the following factors: frequency of occurrence, type of word, type of elaboration, and
predictability from word form and parts. The reading subjects made greater vocabulary
gains than the listening subjects for all four levels of proficiency analyzed. Inspection of
pairwise comparisons seemed to indicate that the difference in gains between the reading
and listening conditions decreased as the students’ proficiency increased. Similar trends
emerged for retention. Reading also resulted in greater retention 1 month after the input,
except for the highest proficiency students. For this group, no significant difference was
found between the listening and reading delayed posttest scores. The relationship among
each of the four factors was analyzed and vocabulary acquisition was also found to vary
across input modes.
Keywords vocabulary; reading; listening; incidental acquisition; retention; proficiency;
frequency; word type; word form; elaboration
Introduction
Apart from their role in the dissemination of scholarly knowledge, academic
listening and reading have been found to be sources of vocabulary acquisition
for second language (L2) learners (Parry, 1991; Vidal, 2003). This is especially
Correspondence concerning this article should be addressed to Karina Vidal, Department of English
Philology, Facultad de Filosofı́a y Letras, Universidad Autónoma de Madrid, Ciudad Universitaria
de Canto Blanco, 28049 Madrid, Spain. Internet: karina.vidal@uam.es
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C 2010 Language Learning Research Club, University of Michigan
DOI: 10.1111/j.1467-9922.2010.00593.x
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Incidental Vocabulary Acquisition
relevant for students entering English-medium institutions who need to enhance
the breadth and depth of their vocabulary knowledge in order to succeed in their
academic and professional pursuits.
Despite the relevance of listening and reading for vocabulary acquisition,
little is known about the differences underlying both processes. The research
study described here was conducted with the aim of determining how both
processes compare. It followed from a previous experimental study (Vidal,
2003) that demonstrated successful learning of vocabulary from listening to
lectures.
Listening and Reading Comprehension: Basic Processes
Research findings with first language (L1) subjects tend to support the notion that listening and reading comprehension involve the same processes
(Daneman & Carpenter, 1980; Kintsch & Kozminsky, 1977; Stitch & James,
1984; Walker, 1976) or, stated otherwise, that “a common core of comprehension processes [. . .] underlie both listening and skilled reading” (Kintsch &
Kozminsky, 1977, p. 491). This view is also supported by the “Structure Building Framework of Comprehension,” which proposes that the same processes
are used in the comprehension of any material, whether written text, spoken
discourse, or a series of pictures (Gernsbacher, Varner, & Faust, 1990).
At the beginning of schooling, L1 pupils can comprehend language better
by auding1 than by reading. As they progress through the school grades, they
acquire more and more skill in reading and eventually close the gap between
listening and reading skills. “[. . .] With extensive practice in reading we might
expect to find reading more efficient than auding” (Stitch & James, 1984,
pp. 296 and 299).
It is worth noting here, though, that most of the studies that confirmed
the hypothesis that the same general processes underlie both listening and
reading comprehension and therefore support the unitary process view used
narrative texts. However, a recent study (Diakidoy, Stylianou, Karefillidou, &
Papageorgiou, 2005) that employed both written and oral expository texts with
native speakers of Greek in Grades 2, 4, 6, and 8 found a weaker relationship between listening and reading. As Diakidoy et al. (2005) argued, their
results were probably due to lack of familiarity with expository structures and,
therefore, call for further research.
Kintsch and Kozminsky (1977), who presented narrative texts through listening and reading to L1 college students, pointed to the possibility of “differences in favour of reading for difficult texts, for which a well-established
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schema is not available or the content is unfamiliar.” However, they concluded
that “modality differences matter remarkably little for college-student subjects”
(pp. 497–498).
Findings with L2 learners also suggest that reading and listening comprehension processes are similar, although the nature of the modality seems to
“cause listeners and readers to approach a comprehension task differently”
(Lund, 1991, p. 201). In effect, in a study designed to compare listening and
reading recall among beginning and intermediate college German students,
Lund (1991) found that readers and listeners differed in several aspects. Readers recalled more total information—higher order ideas and details—than listeners. Listeners, on the other hand, recalled a higher proportion of higher order
ideas and “produced more erroneous but also idiosyncratic, creative constructs
for the text” (Lund, 1991, p. 200). Some of these latter differences could also
be considered to be partly due to the level of L2 proficiency of Lund’s sample.
Low-proficiency L2 listeners tend to experience special difficulty with speech
segmentation, as will be discussed later.
Academic Reading, Academic Listening,
and Vocabulary Acquisition
It is “almost universally accepted in SLA” that input plays a fundamental role in
the development of a linguistic system by L2 learners (VanPatten, 2004, p. 35).
Naturalistic contexts provide plenty of opportunity for making form-meaning
associations.
Most research into vocabulary learning from context has focused on learning from intensive and extensive reading, learning from taking part in conversations, and learning from listening to stories, films, television, or radio (e.g., Brown, Waring, & Donkaewbua, 2008; Elley, 1989; Horst, 2005;
Hwang & Nation, 1989; Paribakht & Wesche, 1993; Pigada & Schmitt, 2006).
Results have shown that theme-related texts, which allow for repetition of unknown vocabulary in varied contexts, provide favorable conditions for learning
(Nation, 2001). Most of these studies, conducted to find out about and maximize the benefits of extensive reading programs, used mainly graded readers,
stories, newspaper, and general interest articles. However, very little research
has addressed the contribution of academic genres—which also allow for repeated encounters with lexical items—to the vocabulary development of the
more advanced learner. Two studies that have looked into vocabulary acquisition through academic reading and listening were those conducted by Parry
(1991) and Vidal (2003), respectively.
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Parry’s (1991) longitudinal study required four adult learners from different
origins to keep lists of any words they encountered that caused them any
difficulty while they read their anthropology textbook assignments. Results
showed reasonable success in guessing from context: Each student recorded a
considerable proportion of correct glosses and got more than half of the total
at least partly correct. Contrary to the researcher’s expectations, most of the
words that the students identified as unknown were not particularly subjectmatter related but were in the register of formal expository prose. Another
important finding of this study, pointing to the difficulty of teaching vocabulary
directly, is that there was very little overlap among the words glossed by the
four students. The four subjects also used significantly different strategies for
learning vocabulary and these strategies were found to affect the way in which
they learned new words. No information is given in the article as to which type
of words showed the greatest gains.
Vidal’s (2003) study of 116 university students’ incidental acquisition of
vocabulary through lecture presentation also showed significant vocabulary
gains. Results of a delayed posttest indicated that the vocabulary knowledge
retained 4 weeks after the treatment was still superior to the knowledge the
students had before listening to the lectures. In this research, students made
greater gains for technical than for academic or low-frequency words, which,
on the one hand, highlights the importance of technical words in lecture comprehension and, on the other hand, points to the difficulty of acquiring academic
words from listening to talks. This issue will be further analyzed in the light of
the results of the present study.
Despite the relatively low vocabulary gains obtained through these input
modes, it is undeniable that academic reading and listening play an essential
role in the development of high-proficiency learners’ vocabulary knowledge.
Students who embark on content courses taught through the medium of English
are bound to come across the specialized terms of their field of study and a vast
number of nonspecialized infrequent words that characterize English academic
genres (Hofland & Johansson, 1982; Parry, 1991). Additionally they face the
unavoidable task of expanding their vocabulary on their own, usually while
reading or listening to lectures. Ellis (1995) considered reading the “ideal
medium” for vocabulary acquisition: Print material allows learners more time
for processing a new word, “whereas in speech it passes ephemerally” (p. 106).
The present study was conducted in an attempt to further explore this issue and
compare empirically the effectiveness of academic listening and reading for L2
incidental vocabulary acquisition and retention.
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Vocabulary Retention
Research into the integration of newly learned word forms with existing ones
in the mental lexicon has shown that a period of memory consolidation is involved in the establishment of the new lexical entry (Clay, Bowers, Davis, &
Hanley, 2007; Dumay & Gaskell 2005, 2007; Gaskell & Dumay, 2003). It
seems plausible that “initial memory for novel vocabulary items is based on
an episodic memory trace, and that a further abstraction or consolidation process is required to generate a new lexical entry” (Gaskell & Dumay, 2003,
p. 106). Therefore, as Dumay, Gaskell, & Feng (2004) pointed out, immediate
measures of vocabulary learning “only tell us about the strength of the traces
left by exposure not whether a new lexical entry per se has been created”
(p. 339).
In order to obtain at least a tentative indication of the contribution of
academic listening and reading to the establishment of lexical representations,
the present study analyzes the delayed retention of the vocabulary initially
learned after exposure to either three lectures or three readings.
Word-Related Features and Learning From Context
The present research also aims to gain further insight into the factors and
conditions conducive to increasing the rate of vocabulary growth in naturalistic
reading and listening situations. More precisely, it compares the effects of
elaboration, frequency, predictability from word forms and parts, and type of
word on incidental vocabulary gain through listening and reading. Findings
concerning these factors will be briefly reviewed next.
Elaboration
Both lectures and university textbooks create specialized knowledge through
naming, defining, classifying, and explaining (Flowerdew, 1992; Wignell,
1998).
Most studies into written definitions have taken a taxonomic approach,
providing lists of semantic properties and syntactic features and showing the
variation in form according to subject areas (Bramki & Williams, 1984; Chaudron, 1982; Chung & Nation, 2003; Darian, 1981; Flowerdew, 1992; Selinker,
Trimble, & Trimble, 1976; Wignell, 1998). However, there does not seem to be
any documented evidence as to their contribution to the comprehension of the
text or to the acquisition of the terms elaborated.
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With regard to spoken elaborations, their role has mainly been studied
in short listening tasks (see Ellis & He, 1999; Loschky, 1994). Very little
research has analyzed the relationship between vocabulary elaboration and
vocabulary acquisition thorough academic listening. A study that has looked
into this issue was that conducted by Chaudron (1982). In his analysis of
subject-matter lessons taught to English-as-a-second-language (ESL) learners, Chaudron noted that the structures of definition, questioning, naming, and
description make the elaboration more explicit and, therefore, facilitate comprehension and acquisition. On the other hand, the structures of apposition,
parallelism, and paraphrase, which tend to be used in implicit elaborations, can
be extremely ambiguous and often suggest additional rather than alternative information to L2 learners. The notes that Vidal’s (2003) students took during the
lectures also revealed this trend for certain instances of parallelism, paraphrase,
and synonymy. However, on the whole, her findings confirmed that words that
were elaborated achieved greater gains than those that received no elaboration
and that the more explicit the elaboration that accompanied the target word,
the higher the gain. The present study intends to explore whether this positive
effect is maintained for acquisition through reading because research findings
have revealed that the effect of elaborations depends on the nature of the task
that is being performed (Barcroft, 2002).
Frequency of Occurrence
Frequency is a key determinant of acquisition (Ellis, 2002). Several L1 and L2
studies lend support to this claim by demonstrating that most vocabulary learning requires repeated exposures to the item (Beck, McKeown, & Omanson,
1987; Elley, 1989; Hulstijn, Hollander, & Greidanus, 1996; Rott, 1999; Sternberg & Powell, 1983; Webb, 2007). Research findings have also shown that a
single exposure can provide L1 school children with substantial information
about a new word (Nagy, Anderson, & Herman, 1987), provided that it is not
a conceptually difficult term. In the light of these and other research results,
Nagy et al. (1987) claimed that conceptually difficult words can be learned
from context when conceptually explicit texts are employed. In effect, Rott
(1999) found a positive effect for frequency of exposure during L2 incidental
reading and partly attributed the students’ gains—greater than those reported
by Knight (1994) and Hulstijn et al. (1996)—to the rich contextual clues in
the text. Webb (2007), who controlled for type of written context in which the
target word occurred, also found that learners who encountered an unknown
word more times in informative contexts achieved significantly larger gains
than learners who had fewer encounters with the given word.
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As the studies above evidence, most research into the effect of frequency
on incidental vocabulary acquisition has focused on nonacademic genres. Now,
research into academic listening (Vidal, 2003) has also revealed a positive correlation between frequency of word occurrence and vocabulary acquisition,
although of the four factors analyzed, it was the one that contributed least to
vocabulary learning. In this respect Nation (2001) pointed out that “repetition
is only one of a number of factors affecting vocabulary learning and the correlations between repetitions and learning generally are only moderate” (p. 81).
Different studies have demonstrated that the effect of frequency is negligible
when the learner is not ready, when the form is not salient, when it requires
explicit learning, or when it is processed in a different way (see VanPatten,
Williams, & Rott, 2004, p. 15). Research on learning and memory has also
shown that for repetition to be effective, it should be distributed across a period of time rather than massed together: The space between exposures should
become larger, with initial repetitions being closer in time and later repetitions
much further apart (Baddeley, 1999).
Predictability of Word Meanings on the Basis of Form and Parts
Foreign language (FL) words that remind us of the corresponding L1 words
because of their phonological and orthographic form are usually more easily
retained than words that bear no resemblance to L1 words (de Groot & Keijzer,
2000; Ellis & Beaton, 1993; Holmes & Ramos, 1993). Likewise, words whose
meaning can be deduced by breaking them into word parts also tend to be
acquired with greater ease (Vidal, 2003). On the other hand, false cognates,
polysemous words and words with deceptive morphological structure normally
induce error (Laufer, 1989, 1990) and therefore take longer to acquire. As
VanPatten et al. (2004) claimed, attaching a new meaning to a given form
initially mapped onto a different meaning seems to be a slow process. For
instance, in the case of polysemous words, students tend to stick to the L1
meaning they know and build a representation of that part of the text around
it, even when it makes no sense in the context in which the word is used
(Holmes & Ramos, 1993; Vidal 2003). The analysis of word parts may also be
misleading: FL learners sometimes mistakenly assume that the meaning of a
word such as nevertheless equals the sum of meanings of its components (e.g.,
nevertheless = never less) (Laufer, 1989). Research findings have also shown
that even the mastery of the word forms of a word family is difficult for L2
proficient learners (Schmitt & Zimmerman, 2002).
The present research aims to explore whether this factor, which was found to
be a crucial determinant of vocabulary acquisition through academic listening
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(Vidal, 2003), also influences acquisition through academic reading to the same
extent.
Types of Words
Nation (2001) classified words as high frequency, academic, technical, and
low frequency. Academic words are those that are not in the most frequent
2,000 words of English—referred to as high-frequency words—but that are
common to a wide range of academic texts. With regard to technical words,
they are items closely related to a subject area but not so common elsewhere. Finally, the low-frequency group “include[s] all the words that are
not high-frequency words, not academic words and not technical words for a
particular subject” (Nation, 2001, p. 12). For a detailed account, see Nation
(2001).
Following this classification, a previous study (Vidal, 2003) explored the
relationship between these types of words and their acquisition through academic listening. As already mentioned, results revealed that word type was a
very important predictor of vocabulary gain and that students made greater
gains for technical items than for academic or low-frequency ones. The difficulty posed by academic and low-frequency words is also evidenced by
Parry’s (1991) findings. Her research into acquisition through academic reading revealed that whereas specialized terms accounted for about 12–20% of
all the words identified as difficult by her four subjects, words “in the register of formal expository prose”2 (Parry, p. 637) accounted for over 40–
50% of all the words listed. It is worth highlighting here that in Parry’s
study, the assignments the students were asked to read were from introductory anthropology textbooks, which could have meant a smaller proportion of new concepts. Probably, as well, the key specialized words were defined in the texts, which could also partially account for the lower number of technical words in the students’ lists. With regard to levels of word
learning, no information is given in the article as to which type of words
showed the greatest gains. In view of the inconclusive evidence available, the
present research attempts to compare gains for word types across listening and
reading.
In sum, as the above literature review shows, little is known about the
differences underlying vocabulary acquisition through academic listening and
reading. The present study was therefore conducted with the aim to understand
more fully how both processes compare and to identify possible differences in
the relationship they hold with the above factors.
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The Present Study
Research Questions
Analyses by Subject
1. How do the effects of academic lectures and readings on ESL vocabulary acquisition compare (as measured by pretest and immediate posttest
vocabulary scores)?
2. How do retention scores (as measured by a delayed posttest administered
4 weeks after the immediate posttest) compare?
3. How does the effect of students’ proficiency on vocabulary acquisition and
on retention compare across input modes?
Analyses by Word
4. How does the relationship between vocabulary gains and each the following
factors—frequency of occurrence, type of word, type of elaboration, and
predictability from word form and parts—compare across presentation
modes?
Null hypotheses were formulated for each of the research questions presented
above, given the scarce evidence there is in this area.
Method
Subjects
The subjects were 248 first-year undergraduate students who were studying
in the English medium as part of a regular ESP course at the Universidad
Autónoma de Madrid. One of the aims of the course was to assist tourism
undergraduates in developing their reading and listening skills to enable them
to cope with the demands of academic courses. The subjects participated in
the experiment as part of their course requirement. They were tested in intact
classes, each of which was assigned to one of the experimental conditions. One
hundred twelve students were assigned to the listening condition, 80 to the
reading condition, and 38 subjects were used as controls: They neither listened
to the lectures nor did the readings. Eighteen students who had missed at
least one of the sessions were excluded from the study. The students’ average
TOEFL score was 495.43 and these scores ranged from 328.33 to 661.67.
Table 1 displays the scores for each group.
Materials
Lectures and Readings
Three video-taped lectures and three readings on the economic, sociocultural,
and environmental impacts of tourism were constructed for use in this study. The
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Table 1 Descriptives for TOEFL
Listening group
Reading group
Control group
n
Mean
SD
112
80
38
504.07
485.20
489.91
54.38
53.81
52.60
lectures were of approximately equal length (14–15 min): The first contained
1,738 running words and the second and third contained 1,837 and 1,812 tokens,
respectively (see Appendix A for an excerpt). With regard to the readings, they
were also similar in length: They ranged from 1,516 to 1,723 words (see
Appendix A for an excerpt).
The three lectures and the three corresponding readings were developed
from the same spoken and written authentic sources and therefore had the same
content and the same target words. Because the lectures were of the reading
style (Dudley-Evans, 1994), they were similar in their linguistic form to the corresponding academic texts. As Biber (1989) claimed, prepared speeches tend to
involve elaborated grammatical structure, which is typical of the informational
discourse to which academic prose belongs.
Target Words
Thirty-six target words were used in this study—12 in each lecture/reading (See
Appendix B). The vocabulary tests also included 18 nonwords (Anderson &
Freebody, 1983; Meara & Jones, 1990) with the purpose of controlling for
students’ overestimating their vocabulary knowledge. These nonwords, which
amounted to 33% of the total number of words analyzed in this study, were
formed by changing some letters in real words. Nonwords with English-like
spelling were also used (Anderson & Freebody, 1983).
Type of words. Following Nation (2001), the target words were classified
as technical, academic, and low frequency. In order to compare how academic
listening and reading contribute to the acquisition of these types of words, gains
were calculated for word types.
All of the academic words used in the materials are included in the University Word List (Xue & Nation, 1984) and most of them are listed in the
Academic Word List (Coxhead, 2000). The words pursue and advocate are examples of this class. With regard to the technical target words, they are closely
related to the topic and subject area of the texts and cover the four categories
of technical vocabulary proposed by Nation (2001, pp. 198–201). This class
included words such as offset and commodification. The target words classified
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as low frequency—except for the word overwhelming—have a frequency that
ranges from two to seven occurrences per million words. Their frequency was
checked against different frequency counts: mainly the British National Corpus, West’s (1953) count, Kucera and Francis’s (1967) list, and Johansson and
Hofland’s (1990) count. Examples of this class are the words jeopardise and
loom. See Vidal (2003) for a more detailed account.
Frequency of word occurrence. Repetitions were kept constant across conditions. The number of occurrences were fixed at six, five, four, three, two, and
one times.
Word elaboration. Following Selinker et al. (1976) and Chaudron (1982),
the elaborations that accompanied the target words were classified as explicit
and implicit (see Darian, 1981, for further discussion). Explicit elaborations
combined formal and semiformal definitions, descriptions, and naming and
questioning statements. Implicit elaborations included paraphrase and synonymy (Bramki & Williams, 1984; Chaudron, 1982; Darian, 1981; Flowerdew,
1992; Selinker et al., 1976; Wignell, 1998). The same words were elaborated in
both modes of presentation and there was a group of target words that received
no elaboration at all. Although written texts tend to define mainly technical
terms (Chung & Nation, 2003), in the present research some low-frequency
and academic words were also elaborated to allow for the tight design of the
study.
As already mentioned, the lectures were of the reading style; therefore,
both spoken and written explicit elaborations had very similar form. That
is to say, they had the same semantic content and were realized by the
same syntactic features (characteristic of both written and spoken academic
discourse). Some of the spoken definitions were preceded by a rhetorical/elicitation question “whose function was to signal the impending definition” (Flowerdew, 1992, p. 214). To give an example, in lecture 1 the word
enclave was accompanied by the following explicit elaboration: “Now, do
you see the exact meaning of the word enclave here? It is an area, within a
country or city that is inhabited by people of a different nationality or culture from the rest of the inhabitants of the country or city.” In the reading,
on the other hand, this definition was not preceded by a grounder and therefore read like this: “An enclave is as an area, within a country or city that is
inhabited by people of a different nationality or culture from the rest of the
inhabitants of the surrounding country or city.” This was the only type of difference between written and spoken definitions. As Flowerdew (1992) states,
“although spoken definitions are subject to the false starts, hesitation, repetition, repair, etc. associated with spoken language in general, in terms of their
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semantic content of term, class, and characteristic, they are remarkably precise”
(pp. 209–210).
As for implicit elaborations, they also had the same form in both learning
conditions. In other words, they were signaled—as described earlier—by linguistic devices that are common in both written and spoken academic discourse.
For example, the word offset received the following implicit elaboration in both
input modes: “foreign currency helped them to offset these deficits, that is, to
counterbalance them.”
Predictability from word form and parts. The target items were classified
as similar to Spanish, morphologically predictable, deceptively transparent,3
and unpredictable. This classification, which draws on the results of a previous
pilot test and on the raters’ experience with university students at this learning
stage, was meant to reflect the students’ recourse to phonological, orthographic,
and morphological word features in order to guess the meaning of a word
encountered in context.
The words regarded as similar to Spanish were those that, because of
their phonological, orthographic, and semantic similarity to L1 words, could be
expected to be recognized and understood by the subjects on hearing the lectures
or reading the texts. It is important to highlight that special care was taken not
to select words whose meaning could be directly deduced when encountering
them in isolation. As the pretest scores showed, the subjects could not identify
these words out of context. For instance, the word niche is cognate with the
Spanish term nicho. Now, this is a very low-frequency word in Spanish—with
a low level of activation. Therefore, the similarity in form is not enough to
activate its meaning; the aid of the context is needed.
The target words categorized as morphologically predictable were those
whose meaning could be determined by analyzing their parts or by relating
them to known words. The word hinterland is an example of this class.
Items categorized as deceptively transparent were those that (a) were false
cognates, (b) were polysemous (the students only knew one of the word meanings and were unable to consider any other possibility), and (c) looked transparent from their parts but whose meaning could not be guessed in such a way.
This class included words such as enclave, province, and acculturation. Even
though the word enclave is cognate with the English term enclave, over the
past few years it has been used in the Spanish media to refer to “tourist resorts”
and this has become its most frequently used meaning. With regard to the word
province, it is used in the present texts to refer to “sphere or field of activity
or authority.” This sense is unknown to most Spanish undergraduate students,
who only master its first meaning (i.e., “an administrative division or unit of
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a country”). As for acculturation, because of the students’ knowledge of the
meaning of the prefix “a–”, it is often mistakenly interpreted as meaning “with
no culture, ignorant.”
Finally, words categorized as unpredictable were those whose meaning
could not be deduced on the basis of their form.
The classification of the target words was carried out by a native teacher of
English, an experienced Spanish teacher of English, and the researcher herself.
When there was no complete agreement, the final classification was based on
the categories on which at least two of the raters agreed.
Measurement
Lecture/Reading Comprehension
For each of the learning conditions, three sets of 10-item true-false questions
and three sets of 20-item cloze tests were used to measure comprehension. It is
worth noting that none of the target word forms were used in the comprehension
measures. These tasks did not include questions that encouraged students to
make form-meaning connections related to any of the target words.
Vocabulary Gain
Both the reading and listening students were tested on their knowledge of the
target words before the treatment, after each treatment, and 1 month later. The
control subjects were also given the tests but did not receive any treatment.
For each target word, the subjects were asked to respond to the following
prompts:
1. Have you heard/seen this word before? If so, where/when?
2. Provide a full explanation (in Spanish or in English) of all the meanings of
the word you know.
3. Provide a Spanish translation of the word.
4. Make a sentence in English using the word.
Their level of knowledge for each target item was measured with a modified
version of the Vocabulary Knowledge Scale (VKS; Paribakht & Wesche, 1997;
Wesche & Paribakht, 1996). This adapted scale had been pilot tested and used
in a previous study and had proved reliable (Vidal, 2003). As can be seen below,
our scoring scale added three more categories to Paribakht and Wesche’s (1997)
original five and had slightly different scale ratings. These modifications, which
were meant to reflect the different levels of word knowledge the students’ pilottest responses had revealed, were included in the scale in an attempt to capture
more fully the early development of vocabulary knowledge. This adapted scale
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accepted only self-reported word knowledge of question 1; the rest of the
answers were assessed by the researcher and another rater. In order to control for
learners’ overestimating their vocabulary knowledge in question 1—especially
for those cases in which they responded that they had heard/seen the word but
did not answer any of the other questions—18 nonwords4 were included in
the vocabulary tests (Anderson & Feebody, 1983; Meara & Jones, 1990). With
regard to the sentence illustrating the meaning of each word (Prompt 4), we
judged whether the illustrated meaning was grammatically and semantically
appropriate. Interrater agreement was 98%. All disagreements were resolved
through discussion. The scoring scale was as follows:
–1 point: recognizes a nonword
0 points: does not recognize the word
1 point: recognizes having seen/heard the word
2 points: has a vague/partial idea of the meaning of the word
2.5 points: has a vague/partial idea of the meaning of the word but produces
a clear example, similar to the one in the lecture/reading
3 points: shows a full understanding of the meaning of the word
4 points: shows a full understanding of the meaning of the word and is able to
provide a Spanish translation or use the word in a sentence
5 points: shows a full understanding of the meaning of the word and is able to
provide a translation and use the word in a sentence.
Procedure
The students were pretested on their knowledge of the target words some
days before the experiments took place. Then, within a 4-week period and
on different days, the subjects were presented with a series of either three
lectures or three readings. Before reading the texts or listening to the lectures,
all participants were oriented to the task of reading or listening for the purpose
of subsequently answering comprehension questions about the texts. There
was no mention of the vocabulary learning focus of the study. It took the
lecturer approximately 15 min to read each lecture. Readers were also allowed
15 min for each reading.5 After reading the texts or hearing the lectures, the
participants completed a cloze test and answered 10 true-false comprehension
questions. These comprehension tasks were administered first to ensure that
the learners concentrated on understanding the texts. Immediately afterward,
the subjects were tested on their knowledge of the target words introduced
in the given text. A month later they were posttested on the total number of
target words. The control group also completed the different vocabulary tests
but neither heard nor read the texts.
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Table 2 Reliability coefficients and descriptive statistics
Vocabulary measures
Mean
SD
n
k
r
Listening group
Pretest
Immediate posttest
Delayed posttest
1.08
28.94
15.13
2.30
22.35
15.25
112
112
112
54
54
54
.63
.89
.85
Reading group
Pretest
Immediate posttest
Delayed posttest
1.82
42.67
20.96
2.66
20.67
12.64
80
80
80
54
54
54
.62
.86
.84
Control group
Pretest
Immediate posttest
Delayed posttest
2.29
2.24
2.60
2.79
2.23
2.42
38
38
38
54
54
54
.81
.74
.83
Results
Analyses by Subject
Table 2 shows the number of subjects, means, and standard deviations for the
vocabulary tests (pretests, immediate posttests, and delayed posttests) for both
treatment groups and for the control group. The reliability measures of each
test are also displayed. The relatively lower reliability of the pretest vocabulary
exams was possibly due to the fact that many of the words tested were lowfrequency words and technical words that not even high-proficiency students
knew. Thus, there were too many low scores grouped together, showing little
variance among item types. All of the other vocabulary tests did discriminate
among item types and individuals and they have, therefore, higher reliability.
An ANOVA with repeated measures revealed no significant difference (F =
1.06, df = 2, p = .348) between the scores of the immediate vocabulary posttests
administered after each lecture. No significant difference (F = 0.639, df = 2,
p = .529) was found either between the scores of the immediate vocabulary
posttests administered after each reading. This indicated that the three lectures,
on the one hand, and the three readings, on the other hand, were equivalent in
terms of response—none of them was unusually difficult or easy. Aggregate
scores were then used for the listening and reading immediate vocabulary
posttests (the sum of the three lecture vocabulary scores and the sum of the
three reading vocabulary scores, respectively), as is shown in Table 2.
Academic Reading Versus Academic Listening
The vocabulary scores were analyzed in a 3 × 3 analysis of covariance
(ANCOVA) with test (pretest vs. immediate posttest vs. delayed posttest) as a
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within-subjects factor, source of acquisition (listening vs. reading vs. no input)
as a between-subjects factor, and proficiency as a covariate. Previous findings
had shown that lecture comprehension, as measured by both true-false questions and cloze tests, correlated highly with proficiency (Vidal, 2003). The
reading comprehension measures administered in this study were also found to
correlate highly with proficiency; therefore, none of these data was included in
the present analyses.
The ANCOVA yielded a significant test main effect, F(1.76, 393.58) =
40.76, p < 0.001, partial eta squared = 0.15, two significant two-way interaction effects, test × source of acquisition, F(3.51, 393.58) = 12.28, p < 0.001,
partial eta squared = 0.10, and test × proficiency, F(1.76, 393.58) = 73.47, p <
0.001, partial eta squared = 0.25, and a significant three-way interaction effect, test × source of acquisition × proficiency, F(3.51, 393.58) = 17.340, p <
0.001, partial eta squared = 0.13. These results indicate that the acquisition and
retention scores for the reading, listening, and control groups were significantly
different. The three-way interaction effect reveals, at the same time, that these
differences varied depending on the proficiency levels within each group. To
explore the nature of this interaction, pairwise comparisons between treatment
groups and for different levels of proficiency (as measured by TOEFL scores)
were calculated. With this purpose, SPSS was run repeatedly to apply the
ANCOVA model to different values of TOEFL and to calculate the corresponding pairwise comparisons and profile plots. The selected proficiency
values were as follows: 25th percentile, TOEFL = 457; mean, TOEFL = 496;
75th percentile, TOEFL = 528; 95th percentile, TOEFL = 586.
Before analyzing the interaction effects in the light of the pairwise comparisons, it is worth highlighting three points. First, for the control group, no
significant differences were found between any of the levels of the withinsubjects factor (pretest vs. immediate posttest; immediate posttest vs. delayed
posttest; delayed posttest vs. pretest, all ps = 1.00 for each of the TOEFL values
selected). This indicates that the students did not learn vocabulary by doing
the exams. Second, for both the listening and reading groups, significant differences were found between the pretest and the immediate posttest; between the
immediate posttest and the delayed posttest, and between the delayed posttest
and the pretest (all ps < .001). This indicates that both treatments resulted
in vocabulary learning and that the vocabulary knowledge retained in memory after 4 weeks was still superior to the knowledge the students had before
receiving the treatments. Third, the pairwise comparisons for all four levels
of proficiency showed no significant difference between the pretest scores of
the control and treatment groups (control vs. listening; listening vs. reading;
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Listening
80
70
70
60
60
50
50
Estimated means
Estimated means
Reading
80
40
30
20
10
0
Pretest
Immediate
posttest
Delayed
posttest
40
30
20
10
0
Pretest
Immediate
posttest
Delayed
posttest
Control
80
70
60
Proficiency
mean
Estimated means
50
40
25th pctl
30
75th pctl
20
95th pctl
10
0
Pretest
Immediate
posttest
Delayed
posttest
Figure 1 Profile plots for different levels of proficiency.
control vs. reading, all ps > .68), indicating that the three groups had similar
prior knowledge of the target words.
With regard to acquisition, significant differences were found between the
listening and reading immediate posttest scores for all four levels of proficiency
analyzed (all ps < .001). As the estimated means (Table 3) show, the gains of
the reading group were greater than those of the listening group, which answers
research question 1—that is, academic reading led to greater vocabulary gains
than academic listening for all four levels of proficiency analyzed. The profile
plots displayed in Figure 1 describe this finding. The plots also show that
the higher the proficiency, the greater the gains for both learning conditions.
Inspection of the estimated means displayed in Table 3 seems to indicate that
the difference in gains between the reading and listening conditions decreased
as the students’ proficiency increased. These results partially answer research
question 3.
If we consider the maximum score on the vocabulary measure6 (a total
of 180 points; i.e., 5 points for each target word), we could say that average
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Table 3 Estimated means
95% Confidence
interval
for the difference
Test
Mean
Std. error
Upper
bound
Lower
bound
1
2
3
2.45
2.33
2.70
0.40
2.19
1.64
1.67
–1.97
–0.53
3.23
6.64
5.93
Listening
1
2
3
2.00
26.08
13.38
0.23
1.28
0.96
1.54
23.55
11.49
2.45
28.61
15.28
Reading
1
2
3
2.05
46.70
22.21
0.28
1.52
1.14
1.50
43.69
19.96
2.59
49.70
24.46
1.28
1.63
2.01
0,47
2.58
1.93
0.36
–3.44
–1.79
2.20
6.71
5.82
Source of acquisition
TOEFL = 496 (mean)
No input
TOEFL = 457 (25th percentile)
No input
1
2
3
Listening
1
2
3
1.07
13.82
5.95
0.30
1.68
1.26
0.47
10.51
3.47
1.66
17.13
8.43
Reading
1
2
3
1.22
36.11
17.42
0.31
1.70
1.27
0.60
32.77
14.92
1.80
39.45
19.93
3.46
2.94
3.29
0.49
2.70
2.02
2.50
−2.38
−0.69
4.42
8.25
7.27
TOEFL = 528 (75th percentile)
No input
1
2
3
Listening
1
2
3
2.80
36.62
19.78
0.25
1.39
1.04
2.30
33.89
17.73
3.29
39.35
21.83
Reading
1
2
3
2.77
55.81
26.32
0.35
1.92
1.44
2.09
52.03
23.49
3.46
59.59
29.16
(Continued)
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Table 3 Continued
95% Confidence
interval
for the difference
Test
Mean
Std. error
Upper
bound
Lower
bound
TOEFL = 586 (95th percentile)
No input
1
2
3
5.24
4.01
4.33
0.83
4.58
3.43
3.61
−5.01
−2.42
6.87
13.03
11.09
Source of acquisition
Listening
1
2
3
4.21
55.25
31.08
0.42
2.30
1.72
3.39
50.72
27.69
5.03
59.77
34.48
Reading
1
2
3
4.06
71.90
33.59
0.58
3.20
2.40
2.92
65.60
28.87
5.20
78.21
38.31
Note. 1 = pretest; 2 = immediate posttest; 3 = delayed posttest.
acquisition rates ranged from 19.38% (25th percentile) to 37.69% (95th percentile) for the reading group and from 7.08% (25th percentile) to 28.35%
(95th percentile) for the listening group.
In order to explore the levels to which the target words were learned after
each treatment, the scale scores were combined into four categories (No recognition, Recognition, Partial knowledge, and Full knowledge) and the percentage
of responses for each category were calculated (see Figure 2). Inspection of
Figure 2 shows that the main difference between reading and listening lies in
the number of responses that indicate recognition of the target words; in other
words, readers remembered having encountered a greater number of words
than listeners. Readers also provided a higher number of responses indicating
partial and full knowledge of the target words, but group differences in these
categories were not so marked.
The retention of the lexical knowledge acquired also varied across input
modes and proficiency level, as the three-way interaction indicates. For the
TOEFL mean, the 25th percentile, and the 75th percentile, significant differences were found between the reading and the listening delayed posttest scores
(all ps < .001). For these levels of proficiency, reading, which also led to greater
immediate vocabulary gains, resulted in greater vocabulary retention 1 month
after the treatment was completed (Table 3). As for students with a higher level
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80 %
70 %
60 %
50 %
40 %
Reading
Listening
30 %
20 %
10 %
0%
No recognition
Seen/heard
Partial knowledge
Full knowledge
Figure 2 Immediate vocabulary test responses compared. Note. The scale scores were
combined into four categories: 0 pts.: no recognition; 1 pt.: seen/heard; 2–2.5 pts.: partial
knowledge; 3–5 pts.: full knowledge.
of proficiency (95th percentile), no significant difference was found between
the listening and the reading delayed posttest scores (p = 1.00). In other words,
as the estimated means show (Table 3), although higher proficiency readers
showed significantly higher gains than listeners after the immediate posttest,
the amount of lexical knowledge both higher proficiency readers and listeners
retained 1 month after either reading or listening was about the same (reading immediate posttest = 71.90 vs. listening immediate posttest = 55.25, p <
0.001; reading delayed posttest = 33.59 vs. listening delayed posttest = 31.08;
p = 1.00). This would seem to suggest that for higher proficiency students,
vocabulary acquired through listening is more resistant to forgetting.
In effect, the profile plots displayed in Figure 1 show that the slopes decline
more steeply for reading than for listening. A comparison of losses also seems to
indicate that readers (except the lowest proficiency ones) experienced greater
loss of the knowledge shown at the immediate posttest than listeners. More
specifically, those readers and listeners represented by the 95th percentile lost
respectively 56.5% and 47% of their gain; the readers and listeners with a
TOEFL score of 528 (75th percentile) lost respectively 55.6% and 49.8% of
their gain; the readers and listeners represented by the mean lost 54.8% and
52.7%, respectively, and the readers and listeners with the lowest proficiency
(25th percentile) lost respectively 53.6 and 61.7% of their gain. Taken together
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Table 4 Reading: Standardized coefficients, zero-order, part, and partial correlations
for transformed variables
Standardized
coefficients
Frequency of occurrence
Predictability from word form
Type of word elaboration
Type of word
Correlations
Beta
Std. error
F
Partial
Part
0.44
0.36
0.37
0.23
0.09
0.08
0.09
0.09
23.19
17.69
15.05
6.55
.687
.636
.605
.448
.398
.348
.321
.212
with the results presented earlier, these analyses provide a complete picture of
the whole process and help to fully answer research questions 3 and 2.
Analyses by Word7
The relationship between vocabulary gain and these four variables—type of
word, frequency of word occurrence, type of word elaboration, and predictability from word form and parts—was analyzed by categorical regression with
optimal scaling (CATREG). These four factors were found to influence vocabulary acquisition differently across learning conditions, as will be explained
below.
With regard to reading, CATREG yielded an R2 of .82, indicating that
82% of the variance in the transformed vocabulary gain is explained by the
four transformed predictors (F = 13.367 p < .001). The model fits well. By
inspecting the partial correlation coefficients, the part correlation coefficients,
and the F-test for each variable (Table 4), it can be concluded that frequency
of occurrence is the best predictor of the dependent variable, accounting for
47% of the variation8 in the transformed vocabulary gain if the effects of the
other variables are removed. Predictability from word form and parts and type
of word elaboration also make an important contribution to the reading model:
They explain, respectively, 40% and 37% of the variation in the gains made.
The partial correlation coefficient for type of word is lower (.448), indicating
that this variable makes less of a contribution to lexical acquisition through
reading.
In the case of listening, the model also fits well. It explains 79% of the
variance in the transformed vocabulary gain (F = 8.009; p < .001). Of the
four variables, predictability from word form and parts is the best predictor of
the dependent variable, accounting for 58% of the variation in the gains if the
effects of the other variables are removed (see Table 5). Type of word is also an
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Table 5 Listening: standardized coefficients, zero-order, part and partial correlations
for transformed variables
Standardized
coefficients
Predictability from form
Type of word
Type of word elaboration
Frequency of occurrence
Beta
Std. error
F
Partial
Part
0.56
0.36
0.28
0.27
0.10
0.10
0.10
0.10
32.49
12.74
8.17
7.50
.758
.589
.504
.488
.538
.337
.270
.259
Decept.
Predict.
Sim.
Reading
Listening
4
4
3
3
Quantification of predictability
Quantification of predictability
Correlations
2
1
0
-1
2
1
0
-1
Unpred.
Decept.
Predict.
Sim.
Unpred.
Predictability from word form & parts
Predictability from word form & parts
Figure 3 Transformation plots for predictability.
important predictor, explaining 35% of the variation in the response. Type of
word elaboration and frequency of occurrence make a smaller contribution to
the model: They explain, respectively, 25% and 24% of the variation in lexical
gain.
With regard to the trends in each variable, the transformation plots also
reveal differences between the reading and the listening models. To begin with,
as Figure 3 shows, in both models the gain rises as the degree of predictability
of the word rises, but the difference in gains between words similar to Spanish
and morphologically predictable words is smaller in the reading model. In other
words, when reading, encountering a morphologically predictable word seems
to be as facilitative for vocabulary learning as encountering a cognate. When
listening, on the other hand, the effect of a known phonological form appears
to be more effective.
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Listening
Reading
4
Quantification of frq. of occurrence
Quantification of frq. of occurrence
4
3
2
1
0
-1
-2
3
2
1
0
-1
-2
1
2
3
4
Frequency of occurrence
5
6
1
2
3
4
Frequency of occurrence
5
6
Figure 4 Transformation plots for frequency of occurrence.
In both conditions, gain also increases as the word is repeated more times
(Figure 4); however, the effect of repetitions varies across modes. In the reading
model, the greatest increase in gain occurred between two and three repetitions.
From three to five repetitions, gains kept increasing more gradually. The graph
also seems to indicate that there was no important difference in gains between
the words that the students encountered five times and those they encountered
six times. In the listening model, on the other hand, gains started to increase
moderately from three to five repetitions, and the greatest increase occurred
between five and six times. The transformation plot suggests that in connected
speech, students need more than three repetitions to notice and attend to the
target word and, consequently, to begin showing signs of learning. This difference in trends between both groups makes evident why frequency of word
occurrence is the most important predictor in the reading model and the least
important in the listening model.
The transformation plot for type of word displayed in Figure 5 also shows
differences between both models. In the reading model, there is only a very
slight difference in gains between technical and low-frequency words and a
very pronounced difference between these two types of words and academic
words. In the listening model, on the other hand, technical words show the
greatest gains and low-frequency words seem to be acquired only slightly more
easily than academic words. To summarize, listeners seemed to attend mainly
to technical words. Readers, on the other hand, focused almost as much on
technical words as on low-frequency words. Academic words received the least
attention in both reading and listening.
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Listening
1.5
1
1
Quantification of type of word
Quantification of type of word
Reading
1.5
0.5
0
-0.5
-1
-1.5
Low freq.
Type of word
Academic
0.5
0
-0.5
-1
-1.5
Low freq.
Type of word
Technical
Academic
Technical
-1.5
Implicit
No elab.
Type of word elaboration
Explicit
Figure 5 Transformation plots for type of word.
Listening
Quantification of type of w. elaboration
Quantification of type of w. elaboration
Reading
1.5
1
0.5
0
-0.5
1
0.5
0
-0.5
-1
-1.5
No elab.
Implicit
Type of word elaboration
1.5
Explicit
-1
Figure 6 Transformation plots for type of word elaboration.
As for type of word elaboration, the plot in Figure 6 shows that both readers
and listeners made greater gains for explicitly elaborated words. However, the
difference between no elaboration and implicit elaboration is greater in the
listening model; in the reading condition, words that were not elaborated and
those with implicit elaborations showed similar small gains. To put it another
way, whereas listeners made greater gains for words implicitly elaborated than
for those that received no elaboration, readers did not.
Discussion and Conclusions
Vocabulary Acquisition
The present findings seem to indicate that although both academic reading
and listening result in vocabulary gains, reading is a more efficient source of
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acquisition.9 This is especially so for low-proficiency students, who appear
to have more difficulty coping with academic lectures that need real-time
processing and therefore can profit more from written texts over which they
have more control: They can dwell upon words they cannot understand and
backtrack if necessary.
The recognition of unfamiliar words in the context of continuous speech
poses a serious difficulty for nonnative listeners. Nonnative listening is characterized by a reduced knowledge of the probabilities of phoneme sequences
and word structure and therefore by a reduced capacity for extracting words
from running speech contexts (Cutler, 2002). Very frequently, nonnatives’ phonetic sensitivity, which has developed according to the contrasts relevant for
native phonemic discrimination, appears to be inappropriately applied to L2
speech. Research findings have shown that spoken input automatically activates not only native words but also words that are spuriously present in
the utterance via embedding within or across the actually spoken words (see
Cutler, 2002). Cutler, Tyler, and Perruchet (2006) pointed out that this insensitivity to L2 characteristics not present in the L1 can be overcome with L2
experience.
In effect, the findings of the present study seem to suggest that as the
students’ proficiency increases, the difference in gains between reading and
listening decreases. Most probably the students with higher proficiency had
greater vocabulary knowledge and managed to split up the message more
effectively; therefore, more vocabulary learning took place.
The frequencies of the responses to the immediate vocabulary measure
showed that the main difference between readers and listeners was that readers
remembered having encountered a greater number of words than listeners.
Readers also provided a higher number of responses indicating partial and full
knowledge of the target words, but group differences in these categories were
not so marked.
It is finally worth noting that, as the results presented above show, the gains
both groups made were small. It should be noted, though, that many of the
target words were technical concepts that most of the students did not know
prior to the study. Therefore, for these words, they had to create a new meaning
and attach it to the form they encountered in the text rather than just attach the
new form to a preexisting concept.
Vocabulary Retention
Research findings have revealed that “different types of materials are forgotten
at different rates” (Baddeley, 1999, p. 112). The results of the present study
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could be taken to suggest that different presentation modes—all other factors
being equal—might also have different effects on rate of forgetting.
For the TOEFL mean, the 25th percentile, and the 75th percentile, significant
differences were found between the reading and the listening delayed posttest
scores: For these levels of proficiency, academic reading resulted in greater
vocabulary knowledge 1 month after the input. Higher proficiency students,
however, did not follow this trend. Although the highest proficiency learners
(represented by the 95th percentile) made greater immediate vocabulary gains
through reading, the lexical knowledge acquired this way appeared to decay
more easily than that acquired through listening. Therefore, no significant
difference was found in the delayed retention scores between the reading and
listening highest proficiency learners.
With regard to forgetting, a comparison of losses seems to reveal that, except
for the lowest proficiency subjects, less of what was learned at the time of the
immediate posttest was lost by the listening group than by the reading group. In
other words, listening appears to leave more durable traces than reading. This is
especially so for higher proficiency students who have developed a higher level
of listening skills. However, very low-proficiency listeners, as represented by
the 25th percentile, had serious difficulties with the processing of speech and
had to struggle for meaning in real time. Therefore, they made very small gains
and showed greater losses of initial gains than readers of the same proficiency
level.
Needless to say, the findings presented here are not meant to be generalized but rather are used to reveal possible trends worth examining in further
research. A plausible explanation for the listening subjects’ higher retention of
original gains could be found in the role of phonological memory in vocabulary
acquisition. Research findings suggest that adequate temporary phonological
storage contributes to the construction of stable long-term memory representations (Gathercole & Baddeley, 1993). Whereas items presented auditorily are
directly registered in the phonological store, visually presented material needs
to be verbally recoded by means of subvocal articulation for it to gain access
to the phonological store (Baddeley, 2007). During reading, phonological recoding via subvocal articulation is used to identify unfamiliar letter strings.
However, this process may be partial and therefore unsuccessful. Research has
indeed revealed acoustic confusions when subjects recall visually presented
consonants (Baddeley, 2007). It therefore seems reasonable to suppose that
direct—and in some cases repeated—access to the phonological storage might
result in more stable, distinct, and durable memory traces.
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These results highlight the importance of auditory presentation for longterm vocabulary acquisition and also indirectly point to the probable contribution of aural input to the construction of stable long-term memory representations for words previously encountered only in written contexts. Kelly’s (1992)
and Brown et al.’s (2008) findings with subjects who both read and listened to
written texts also point in this direction.
It is worth noting that the immediate vocabulary posttests—administered
after the two comprehension exercises—provided the listening and reading
subjects with an opportunity to recall the items from memory. This probably enhanced long-term retention. Indeed, research has demonstrated that
retrieval from memory has beneficial effects for long-term retention of vocabulary (Bahrick, Bahrick, Bahrick, & Bahrick 1993; Carrier & Pashler, 1992).
It should also be noted, though, that the subjects did not learn vocabulary by
completing the exams per se, as the results of the control group show.
In general terms, it can be concluded that both the reading and the listening
subjects lost a considerable proportion of their initial gains (average losses of
55% and 52.9% for the reading and listening groups, respectively). This is what
normally happens with relatively poorly learned material: Forgetting is rapid at
first although it then slows down (Baddeley, 1999). However, the gains would
probably have been greater if the exposure had extended over time—that is,
if the students had had frequent opportunities for encountering and rehearsing
the new words, as is normally the case with learners who do academic study in
English and are exposed to large amounts of input.
Factors Affecting Acquisition Through Listening and Reading
With regard to the different factors that have been studied in connection with
incidental L2 vocabulary acquisition, Hulstijn (2003) claimed that findings
show that “it is elaboration of or involvement in the lexical information being processed rather than any of the factors per se that determines retention”
(p. 364). In effect, empirical evidence seems to support the proposition that
“more meaningful processing is usually associated with higher levels of recollection” (Craik, 2002, p. 316).
As for the four factors analyzed in this study, the results seem to suggest
that these variables made an important contribution to the encoding of new
lexical items—probably because they fostered focusing on the given words.
Results also indicate that these four factors influenced vocabulary acquisition
differently across learning conditions.
In general terms, L2 listeners appear to attend mainly to those words that
are similar to words in their L1 and to those that they perceive as relevant to
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the main purpose of the lecture, as evidenced by the greater gains achieved by
technical words and by those similar to L1 items. Readers also attend to words
that are similar to L1 words and to technical words, but to a greater extent what
seems to draw their attention to the new item is its repetition in the text. For
listeners, however, repetition does not always seem to be so effective, as will be
discussed later. Another difference between readers and listeners is that readers
do not focus mainly on technical words: Having more control over the text,
they attend to low-frequency items almost as much. As for elaboration, both
in reading and in listening, explicit elaborations were found to facilitate the
acquisition process, whereas implicit elaborations proved to be less effective,
especially in reading. Each of these factors will be explored in more detail
later.
Predictability From Word Form and Parts
Of the four factors studied, predictability from word form and parts was the best
predictor of vocabulary acquisition through listening, making a much greater
contribution to the gains achieved than any of the other three variables. It
accounted for 57% of the variation in vocabulary gain if the effects of the other
variables are removed. The contribution of this factor to acquisition through
reading is also of paramount importance (it explains 40% of the variance),
although clearly this factor is more important in the listening model. Most
probably the greater contribution of predictability from word form and parts
to listening is due to the above-mentioned difficulty of segmenting L2 speech
into words. Cognates and words similar to L1 ones appear to be especially
salient in speech and, therefore, have a clearer facilitative effect for listeners.
Readers, however, have more control over the text and can make better use of all
the cues available to them. Because of this same reason, readers made similar
gains for both words similar to Spanish and morphologically predictable words,
whereas listeners achieved greater gains for cognates than for morphologically
predictable words.
Previous research has shown that L2 learners, especially those who have
been warned about the existence of false friends, tend not to use cognates that
they have not encountered in context either because they do not trust the words
with similar spelling in the two languages to have the same meaning or because
they are simply unaware that the word exists in English (Lightbown & Libben,
1984). The results of this study therefore seem to confirm that listening and
reading facilitate the acquisition of cognates and words similar to L1 ones,
which L2 learners may not be aware of or which they may not feel confident
about using.
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With regard to deceptively transparent words (i.e., false cognates, polysemous words, and items that deceptively look deducible from their parts), both
readers and listeners found it hard to suppress the activation of the wrong L1
entry with which they had mistakenly equated the L2 target. For instance, in
the case of false cognates, many of the subjects failed to notice the difference
in meaning between the L2 concept and the L1 one they related it to, and in the
case of polysemous words, they tended to stay with the meaning they already
knew. These results highlight the difficulty of acquiring deceptively transparent
words incidentally from aural and written input. Attaching a new meaning to
a given form initially mapped onto a different meaning seems to be a slow
process. As VanPatten et al. (2004) claimed, “the additional meaning may be
delayed or suppressed altogether” (p. 13). Most probably, a greater number of
encounters are necessary for the restructuring of this type of form-meaning
connections.
Frequency of Word Occurrence
Frequency of word occurrence was the variable in the reading model that best
predicted vocabulary acquisition, whereas in the listening model it was the factor that contributed least to vocabulary gain. This factor explained respectively
47% and 24% of the variation in gains. Repetition seems to draw readers’ attention to the target word. Repeated encounters with an item seem to make readers
perceive it as an important concept that they should attempt to understand and
learn. As the transformation plot for the reading model shows (Figure 4), the
greatest increase in gain occurred between two and three repetitions. From
three to five repetitions, gains kept increasing more gradually. Figure 4 also
seems to indicate that there was no important difference in gains between the
words that the students encountered five times and those they encountered six
times.
Listeners, however, do not seem to be able to take as much advantage of
repetition: Unless they can segment speech properly and consequently identify
the target item, the effect of repetition on vocabulary acquisition is negligible. Obviously, successful speech segmentation is just the first step. As the
transformation plot in Figure 4 illustrates, the listening subjects required more
exposure to the target items. Gains started to increase moderately from three to
five repetitions and the greatest increase occurred between five and six times.
These findings could be taken to suggest that in listening, more encounters are
necessary for repetition to have an impact on vocabulary learning.
As already mentioned, because of design constraints, the subjects were
exposed to the target words over a short period of time. Most probably,
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Incidental Vocabulary Acquisition
repetition would have been more effective if the encounters had been spread
over a greater period of time, as is normally the case in naturalistic learning
environments.
Type of Word
Type of word was the second best predictor of the vocabulary gains obtained
through listening: It accounted for 35% of the variation in vocabulary gain.
Listeners performed much better on the technical items than on academic or
low-frequency ones; scores for low-frequency words were slightly higher than
scores for academic words. These results indicate that listeners focused heavily
on understanding the topic and main points of the lectures, and, consequently,
they acquired the words used to express these main concepts. In the reading
condition, however, type of word was the variable that made the smallest contribution to the gains obtained (it explained 20% of the variance). The reading
subjects made only slightly larger gains for technical than for low-frequency
words. The low-frequency items in the present study share some of the characteristics of technical words and are closely related to the topics of the texts,
which may be the reason why they achieved high gains in the reading condition. In any case, these results suggest that reading allows learners to focus
on a wider range of words. As Hildyard and Olson (1978) claimed, whereas
listening requires a closer attention to the gist or coherence of the text, reading
allows more attention to be focused on language form.
Both the listening and reading subjects achieved small gains for academic
words, although the difference in gains between academic and the other two
types of words was greater in the case of readers. The reading subjects achieved
much greater gains for low-frequency words than for academic words, whereas
listeners achieved only slightly higher gains for low-frequency words than
for academic items. Unlike low-frequency words, which tend to share some
characteristics with technical words and may be perceived as more relevant
to the understanding of texts, academic words do not appear to be salient to
foreign language learners—most probably due to their function in the given
text. Consequently, given the online nature of listening and the need for maintaining comprehension and preventing interference, most academic words did
not appear to have received enough of the listeners’ attention to have been
acquired by them. As for readers, although they had the opportunity to reread
parts of the text and attend to language form, they did not achieve high gains
for this type of words either. Considered together, the present findings would
seem to suggest that academic words are more resistant to learning from
context.
Language Learning 61:1, March 2011, pp. 219–258
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Incidental Vocabulary Acquisition
Type of Word Elaboration
This variable accounted for 37% and 24% of the variation in the gains made
in reading and listening, respectively. Both the listening and reading subjects
made higher gains for the words that were explicitly elaborated than for those
that received implicit elaboration. This is probably due to the formal characteristics of explicit elaborations, which clearly signal that the given item is being
elaborated upon, and therefore enable both the listener and reader to focus on it.
These results suggest that explicit elaborations help to make robust connections
between form and meaning.
With regard to implicit elaborations, readers did not make greater gains for
words accompanied by this type of elaboration than for words that received
no elaboration. Surprisingly, listeners did. This could be attributable to the
facilitative effect of the phonological and prosodic features of teacher talk
that signal to the learners that a particular word is being elaborated upon (for
a detailed explanation, see Chaudron, 1982). In any case, the present results
show that, as Chaudron (1982) claimed, implicit elaborations are syntactically
complex structures whose contribution to clarifying the meaning of vocabulary
items is not easily recognizable.
Limitations and Implications for Future Research
With regard to the retention of incidentally acquired vocabulary, the results
of the present study seem to suggest that for higher levels of proficiency,
listening might lead to somewhat higher retention rates than reading. This
finding deserves further exploration. Future research should aim at obtaining
higher vocabulary gains by exposing learners to larger amounts of input over a
longer period of time. This would enable a more in-depth study of the role of
input mode in the retention and loss of vocabulary knowledge. Research along
these lines would also provide greater insights into the differences in the effect
of frequency on vocabulary acquisition through listening and reading that have
emerged in the present study.
Revised version accepted 22 September 2009
Notes
1 Stitch and James (1984) used the term auding to refer “to the process of listening
to language and processing it for comprehension” (p. 293).
2 This category could be said to comprise the categories of low-frequency and
academic words as described by Nation (2001).
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Incidental Vocabulary Acquisition
3 This term was borrowed from Laufer’s (1990) description of derivational
complexity, but it is used here in a somewhat different and broader sense.
4 Although there is little research into the type and proportion of nonwords as well as
the formula to be used for scoring this type of vocabulary checks, the positive
answers to the nonwords in our study had a very small incidence in the results,
which seems to indicate that, in our case, the students did not tend to mark words
they did not know. The sufficiently high reliability measures of these vocabulary
tests indicate that the formula adopted can be considered a valid measure of
vocabulary knowledge.
5 Research findings revealed that optimal listening rates and reading rates are similar
among English-as-foreign-language learners (Hirai, 1999). These findings are in
line with L1 research that confirmed that the maximal rate of silent reading with
accurate retention corresponds closely to maximal rates of auding (see Hirai, 1999).
The speech rate for each lecture was approximately 125 words per minute. This rate
is very similar to the listening and reading optimal rate proposed by Hirai (1999).
6 It should be noted that it would be impossible to achieve the maximum score. Many
subjects had no prior knowledge of most of the target words and many of them
were repeated only once. As Nagy et al. (1987) claimed, one encounter with a word
usually results in only a small word gain. This total score is used as an estimate of
the magnitude of the gains in order to allow for comparison between groups.
7 The last part of the analyses below present a comparison of the trends for both
input modes as revealed by transformation plots. Statistical tests of significance
were not performed for the comparison of these secondary variables.
8 This percentage was obtained by squaring the partial correlation of this predictor
(reported in Table 4). The squared partial correlation corresponds to the proportion
of the variance in the response explained after removing the effects of the other
variables.
9 It is worth noting that the lectures were of the reading style; therefore, they were
not delivered with the amount of redundancy and interaction that is typical of
conversational-style lectures. Probably conversational-style lectures would have led
to higher comprehension and, consequently, to higher vocabulary gains.
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Appendix A
Reading I Excerpt
In order to understand the overwhelming importance of the tourism sector for
the economy of so many countries, let us begin by tracing its development over
the last five decades.
The story started in the early 60’s when the idea was mooted that international tourism could be a benefit to underdeveloped countries. In 1963 the
United Nations Conference on Tourism and International Travel declared that
tourism was crucial to boost the economic development of underdeveloped
countries. This idea was suggested at a time when the richer nations were
at a high point of economic growth so they had decided to help the more
deprived nations, that is to say the poorer ones. In the following years international organisations carried out an intensive campaign aimed at persuading
less developed countries to adopt this proposal. Many deprived nations did this
enthusiastically, hoping to find in this project a solution to their poverty.
Between 1969 and 1979, twenty-four projects supported by the World Bank
were launched in 18 underdeveloped countries. Huge tourist resorts and enclaves were created in diverse regions around the world including the Caribbean
islands, Spain, Indonesia, Mexico and Thailand, for example. Less developed
countries like these ones, started profiting from tourism, among other things,
because the flow of tourist currency helped them to offset their countries’
balance of payments, that is, to counterbalance them.
Lecture II Excerpt
Today we are going to continue looking at the impacts of tourism, in particular,
I’m going to concentrate on its social and cultural impact on tourist destinations.
As I mentioned in the previous lecture, at the end of the 1960s numerous
poor regions in the world were transformed into holiday resorts for thousands
of holiday-makers from industrial countries. This process was promoted by
international organisations in conjunction with multinational enterprises for
transport and amenities. The official doctrine advocated by these organisations
was that tourism was a key factor for the economic development of a region.
So poor regions felt practically compelled to adopt tourism as their last chance
to be rediscovered and improve their depressed economies.
During the 1980s and 1990s, the world economic crisis started and large
industrial countries also turned to tourism to solve their economic difficulties.
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So, as you can see, the promotion of tourism is becoming a universal model
for development. And nowadays almost every government is trying to derive
advantages from this activity.
Now, what is it that enters a country with tourism? With tourism, what
enters a country is not only visiting tourists and foreign currency but also all
the apparatus of tourist production. Here, the aims of the tourism industry come
first and so the place starts being reconstructed from a tourist point of view.
When a society decides to become a tourist destination it is compelled
to open its frontiers and its homes to foreign visitors and it is usually also
compelled to exhibit, to sell its culture, heritage and traditions. Let me rephrase
this a little bit. Certain groups in the population become merchandised, making
their own lives a “tourist product.” This phenomenon is called commodification.
Language Learning 61:1, March 2011, pp. 219–258
256
257
Type of word
Technical
Academic
Academic
Technical
Technical
Academic
Technical
Academic
Academic
Academic
Technical
Academic
Technical
Technical
Low frequency
Technical
Technical
Target word
Acculturation
Advocate
Asset
Boost
Carrying capacity
Cogent
Commodification
Compel
Comply
Contingent
Conveyances
Deprived
Enclave
Encroachment
Endeavour
Ethos
Fringe group
Appendix B: List of Target Words
1
4
5
5
3
1
6
6
5
1
3
2
6
2
5
3
5
Frequency
Implicit elaboration
No elaboration
Explicit elaboration
No elaboration
Explicit elaboration
No elaboration
Explicit elaboration
No elaboration
Implicit elaboration
Implicit elaboration
Explicit elaboration
Implicit elaboration
Explicit elaboration
Implicit elaboration
No elaboration
Explicit elaboration
No elaboration
Type of elaboration
(Continued)
Deceptively transparent
Deceptively transparent
Unpredictable
Unpredictable
Deceptively transparent
Unpredictable
Unpredictable
Unpredictable
Unpredictable
Deceptively transparent
Unpredictable
Unpredictable
Deceptively transparent
Unpredictable
Unpredictable
Unpredictable
Unpredictable
Predictability
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Incidental Vocabulary Acquisition
Language Learning 61:1, March 2011, pp. 219–258
Type of word
Low frequency
Low frequency
Technical
Low frequency
Low frequency
Technical
Technical
Technical
Low frequency
Low frequency
Academic
Academic
Technical
Technical
Academic
Low frequency
Low frequency
Academic
Low frequency
Target word
Haphazard
Hinterland
Income leakage
Jeopardise
Loom
Manpower
Niche
Offset
Overwhelming
Poignant
Province
Pursue
Sewage
Sustainable development
Trace
Trample
Upheaval
Upsurge
Weave
Continued
Appendix B
5
3
2
3
2
4
3
4
1
2
3
3
5
5
1
1
5
2
5
Frequency
Explicit elaboration
Explicit elaboration
Explicit elaboration
Implicit elaboration
No elaboration
No elaboration
No elaboration
Implicit elaboration
No elaboration
Implicit elaboration
No elaboration
Implicit elaboration
No elaboration
Explicit elaboration
No elaboration
Implicit elaboration
Explicit elaboration
Implicit elaboration
Explicit elaboration
Type of elaboration
Unpredictable
Morphologically predictable
Unpredictable
Unpredictable
Unpredictable
Morphologically predictable
Similar to Spanish
Unpredictable
Unpredictable
Unpredictable
Deceptively transparent
Unpredictable
Unpredictable
Similar to Spanish
Unpredictable
Unpredictable
Unpredictable
Deceptively transparent
Unpredictable
Predictability
Vidal
Incidental Vocabulary Acquisition
Language Learning 61:1, March 2011, pp. 219–258
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