Neuropsychologia 63 (2014) 226–234

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Neuropsychologia journal homepage: www.elsevier.com/locate/neuropsychologia

Effects of context on implicit and explicit lexical knowledge: An event-related potential study Sungmook Choi a,n, Jingu Kim b, Kwangmin Ryu b a b

Department of English Education, Kyungpook National University Teachers College, 80 Daehakro Bukgu, Daegu 702-701, South Korea Department of Physical Education, Kyungpook National University Teachers College, South Korea

art ic l e i nf o

a b s t r a c t

Article history: Received 31 March 2014 Received in revised form 28 August 2014 Accepted 1 September 2014 Available online 8 September 2014

Although much is known about how contextualized and decontextualized learning affects explicit lexical knowledge, how these learning conditions contribute to implicit lexical knowledge remains unclear. To address this problem, Korean high school students were instructed to learn 30 English words by reading meaningful passages (i.e., in context) and another 30 English words using a wordlist (i.e., out of context). Five weeks later, implicit lexical knowledge was gauged by reaction time and the N400 event-related brain potential component, and explicit lexical knowledge was assessed with an explicit behavioral measure. Results showed that neither learning type was superior to the other in terms of implicit lexical knowledge acquisition, whereas learning words out of context was more effective than learning words in context for establishing explicit lexical knowledge. These results suggest that the presence or absence of context may lead to dissociation in the development of implicit and explicit lexical knowledge. & 2014 Elsevier Ltd. All rights reserved.

Keywords: Implicit knowledge Explicit knowledge Context Vocabulary Contextualized and decontextualized learning Event-related potentials (ERPs) N400 Reaction time

1. Introduction Much second language (L2) research has focused on whether novel words should be learned in context or out of context (Krashen, 1981, 1989; Oxford & Crookall, 1990; Laufer & Shmueli, 1997; Webb, 2007; Elgort, 2011). Learning words in context (contextualized learning) occurs when learners encounter and learn new words while engaged in meaningful activities such as reading books for pleasure. This also includes situations where learners encounter new words embedded in a sample sentence or several sample sentences, as in previous studies (e.g., Laufer & Shmueli, 1997; Baleghizadeh & Shahry, 2010). Given that novel words are not processed as individual units but as part of the overall meaning of the passage, words encountered in context are more likely to be linked with the meaning of the passage (Masson & MacLeod, 2000). In contrast, learning words out of context (decontextualized learning) occurs when words are learned isolated from context. This type of learning typically entails rote memory of unfamiliar L2 target words and their familiar first language (L1) equivalents (i.e., definitions), through the use of flashcards or wordlists. Unlike first language (L1) learners who acquire most of their lexical knowledge

n

Corresponding author. Tel.: þ 82 53 950 5828; fax: þ82 53 950 6804. E-mail address: [email protected] (S. Choi).

http://dx.doi.org/10.1016/j.neuropsychologia.2014.09.003 0028-3932/& 2014 Elsevier Ltd. All rights reserved.

through engagement with meaningful contexts, L2 learners rely heavily on decontextualized approaches such as wordlists, flashcards, and vocabulary notebooks that are either paper-based (Walters & Bozkurt, 2009; Chun, Choi, & Kim, 2012) or computerassisted (Hirschel & Fritz, 2013). However, decontextualized learning has come under strong criticism since the advent of communicative language teaching methods three decades ago. Many researchers claim that decontextualized learning contributes little to the speaking and writing skills of L2 learners (Krashen, 1989; Oxford & Crookall, 1990; Oxford & Scarcella, 1994; Nation, 2011). In addition, these researchers argue that words learned out of context are more likely to fade from memory, whereas words learned in context are better assimilated and retained, because of the cognitive effort required to infer word meanings. Folse (2004) also posited that learning words isolated from context can be unengaging to many learners. Although contextualized learning has been strongly advocated by a number of vocabulary researchers (e.g., Krashen, 1989; Oxford & Crookall, 1990), research to date has demonstrated “little evidence indicating that context facilitates vocabulary learning” (Webb, 2007, p. 63). Many researchers have reported that learning words in context results in relatively small gains in lexical knowledge (e.g., Seibert, 1930; Dupuy & Krashen, 1993; Prince, 1996; Laufer & Shmueli, 1997). In contrast, learning words devoid of context led to sizable gains in lexical knowledge (e.g., Walters &

S. Choi et al. / Neuropsychologia 63 (2014) 226–234

Bozkurt, 2009; Elgort, 2011). For instance, Elgort (2011) examined how intentional learning of 48 novel words from word cards (i.e., without meaningful context) affected L2 vocabulary acquisition. Participants were 10 male and 38 female L2 learners of English in New Zealand, who ranged in age from 18 to 52 years old. Results based on form priming, masked priming, and semantic priming procedures showed that intentional learning of unfamiliar words promoted learning of representational and functional dimensions of lexical knowledge. Based on these findings, Elgort (2011) concluded that intentional learning through word cards is a very efficient means of acquiring novel L2 words. The empirical studies cited above provide some evidence that decontextualized learning may be a more efficient means of acquiring L2 vocabulary than contextualized learning. However, these studies only used off-line, explicit measures of lexical knowledge and focused on how explicit lexical knowledge is acquired as a function of context. Therefore, little is known about how learning novel words in context or in isolation affects implicit lexical knowledge in L2 learners. Given that the development of implicit knowledge is the ultimate goal of L2 acquisition (DeKeyser, 2003; Ellis, 2005; Hulstijn & Ellis, 2005; Williams, 2009; Bowles, 2011; Sonbul & Schmitt, 2013), it is imperative to determine how contextualized and decontextualized learning conditions affect implicit lexical knowledge.

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index of automatic processing or a comparatively higher degree of implicit knowledge (Ashcraft & Radvansky, 2010). ERPs are online electrophysiological brain responses to visual or auditory stimuli such as congruent and incongruent word pairs. ERPs have been used by many researchers as a reliable and viable indicator of implicit knowledge (Hahne & Friederici, 2001; Friederici, Steinhauer, & Pfeifer, 2002; McLaughlin, Osterhout, & Kim, 2004; Tocowicz & MacWhinney, 2005; Osterhout, McLaughlin, Pitkanen, Frenck-Mestre, & Molinaro, 2006; Morgan-Short, 2007; Williams, 2009). Unlike functional magnetic resonance imaging (fMRI) and positron-emission tomography (PET), ERPs provide excellent temporal resolution of language processing (Tokowicz & MacWhinney, 2005; Batterink & Neville, 2011; Malins et al., 2013). Williams (2009, p. 325) claimed that “Neurological measures perhaps provide the most promising approach to the identification of automatic processing” because ERP responses are generated “within a few hundred milliseconds of semantic and syntactic violations and so are not likely to be the result of conscious thought processes”. Among the various ERP components, the present study focuses on the N400, which is a negative-going deflection with a posterior and bilateral distribution (Kutas & Hillyard, 1980). The N400 is typically elicited around 300 ms and peaks at around 400 ms (hence the term “N400”) after the onset of an anomalous stimulus such as semantically incongruent word pairs (e.g., planet-coffee) compared with congruent word pairs (e.g., planet-earth). 1.2. The N400 effect

1.1. Definition and measurements of explicit and implicit lexical knowledge Although there is no consensus among L2 researchers on the exact nature of explicit and implicit knowledge, consciousness is at the heart of the explicit–implicit knowledge distinction (Bialystok, 1981; Williams, 2009). Specifically, explicit knowledge is typically defined as intentional and declarative knowledge. In contrast, implicit knowledge refers to unconscious and procedural knowledge. Implicit knowledge is associated with effortless (i.e., fluent) and automatic processing (Segalowitz, 2003; Segalowitz & Hulstijn, 2005). In the present study, explicit lexical knowledge refers to the intentional and conscious retrieval of novel word meanings and the learners' ability to verbalize the meanings of novel words. In contrast, implicit lexical knowledge refers to the unconscious retrieval or processing of lexical information and the degree of processing fluency, that is, how unintentionally and automatically learners process the meaning of target words (Hulstijn & de Graaff, 1994). Explicit lexical knowledge is the conscious knowledge of lexical information. It has been measured through direct, off-line techniques such as translation (Hulstijn, Hollander, & Greidanus, 1996), recall (Laufer & Rozovski-Roitblat, 2011), recognition tasks (Bowles, 2011), untimed lexical decision tasks (Ellis, 2005), and multiple-choice vocabulary tests (Rott, 1999; Tekmen & Dakoğu, 2006). In the present study, explicit lexical knowledge was assessed by a vocabulary translation test in which participants were asked to write down the meaning of target words. Implicit lexical knowledge is unintentional, non-reflective, and automatic knowledge that learners process without awareness. Therefore, it has been assessed using indirect, on-line measures. In the present study, we used reaction times (RTs) and event-related potentials (ERPs) as indicators of implicit lexical processing. RTs are an index of speed of processing in terms of the elapsed time between the presentation of visual or auditory stimuli and the subsequent response (e.g., a button press), and have been used to tap into unintentional and automatic processing of lexical information, that is, the degree of fluent lexical processing (Williams, 2009; Elgort, 2011). Given that conscious and deliberate efforts require more processing time, shortening of RTs can be taken as an

Extant evidence suggests that the N400 is a sensitive marker of lexical and semantic word knowledge (McLaughlin et al., 2004; Mestres-Missé, Rodriguez-Fornells, & Münte, 2007; Batterink & Neville, 2011). However, the exact nature of the N400 has been debated. To date, two major accounts of the N400 have been proposed: (a) semantic integration of a critical word with the current context and (b) retrieval of lexical information stored in long-term memory (for review, see Lau, Phillips, and Poeppel (2008); also Swaab, Ledoux, Camblin, and Boudewyn (2012)). According to the semantic integration account, the N400 may be associated with “the process of semantic integration of the critical word with the working context” (Lau et al., 2008, p. 921). For example, the N400 amplitude is larger in a semantically incongruent sentence relative to a semantically congruent sentence because integration of a critical word with the incongruent sentence is more difficult than with the congruent sentence. According to Batterink and Neville (2011), this integration process may be dependent upon conscious awareness and explicit lexical knowledge. In other words, the N400 effect may reflect a contextually-dependent explicit memory process. Specifically, these researchers investigated neural correlates of real-time meaning acquisition of novel English words (pseudowords) presented in a discourse-level context (a story). Participants (N ¼21) were adult learners who were monolingual native speakers of English. Data from the explicit recognition task showed that correctly recognized target words evoked an N400 effect, whereas incorrectly recognized ones failed to elicit the N400 effect. During the recognition task, more emphasis was placed on accuracy rather than speed of response. Based on these results, Batterink and Neville (2011) concluded that the N400 reflects a semantic integration process that may rely on explicit representation of word meanings. According to the retrieval account, the N400 effect indexes “facilitated activation of features of the long-term memory representation that is associated with a lexical item” (Lau et al., 2008, p. 921), suggesting that the N400 may reflect an implicit memory process. Likewise, Kutas, Van Petten, and Kluender (2006, p. 669) have concluded that “N400 amplitude is a general index of the ease or difficulty of retrieving stored conceptual knowledge

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associated with a word”. The retrieval account has been supported by many researchers (e.g., Deacon, Hewitt, Yang, & Nagata, 2000; McLaughlin et al., 2004; Grossi, 2006). For instance, McLaughlin et al. (2004) used the N400 as a marker of implicit lexical knowledge. In their study, participants were learners of French who were given approximately 14, 63, and 138 h of classroom instruction. Results showed that although the participants could not separate words from pseudo-words (i.e., orthographically permissible non-words) in a behavioral lexical decision task, the N400 responses significantly differed between words and pseudowords after only 14 h of classroom teaching. Based on these results, McLaughlin et al. (2004, p. 704) concluded that “ERPs (the N400) might more accurately reflect implicit learning and continuous change in knowledge than do explicit, categorical judgments”. In sum, it can be suggested that the N400 effect may not exclusively depend on either implicit or explicit memory processes. However, findings on the effects of orthographic neighborhood and word frequency are “more difficult to reconcile with the semantic integration account of the N400” (Swaab et al., 2012, p. 417). For instance, electrophysiological studies on the effects of word frequency have consistently demonstrated that words with a higher frequency of occurrence elicit greater N400 responses than those with lower frequency of occurrence (e.g., Van Petten & Kutas, 1990; Allen, Badecker, & Osterhout, 2003). Furthermore, masked semantic priming studies demonstrated that lexical access can be achieved in the absence of awareness, indicating that accessing word knowledge may be accomplished in the absence of explicit retrieval of word meanings from long-term storage (e.g., Deacon et al., 2000; Grossi, 2006).

2. Present study The primary purpose of this study is to shed light on how learning words in context or out of context affects implicit and explicit lexical knowledge in L2 learners. Two learning conditions were compared in a within-group design: (a) the contextualized learning condition, in which L2 learners deliberately learned new words while reading two short stories, and (b) the decontextualized learning condition, in which the same learners focused on learning new words from a wordlist. In the present study, “context” refers to meaningful passages at a discourse level. Defining the scope of context is important because its definition varies across studies. For instance, Webb (2007) and Baleghizadeh and Shahry (2010) defined context as one and three sample sentences, respectively, whereas Laufer and Shmueli (1997) included both a sample sentence and a discourselevel text. Electrophysiological studies of vocabulary learning also involved different types of context. Sentence-level context was used by Mestres-Missé et al. (2007). In the experiment, these researchers investigated the online acquisition of novel word meanings by instructing participants to infer the meaning of a novel word in three consecutive sentences. By contrast, a discourse-level context (i.e., a story) was used by Batterink and Neville (2011) who examined incidental learning of novel English words in real-time. As indicated above, explicit lexical knowledge was measured by the delayed vocabulary test in which participants were asked to write the meaning of target words. Implicit lexical knowledge was assessed by both RTs and the N400 ERP responses obtained during a semantic decision task. In order to reduce premeditated intention, the task required participants to judge as rapidly as possible whether a target word matches a prime word. The specific research questions addressed in this study include the following. To what degree do contextualized and decontextualized

learning affects implicit and explicit lexical knowledge? What is the relationship between implicit and explicit lexical knowledge? That is, do the two lexical knowledge representations develop together or differentially as a function of context? In terms of explicit lexical knowledge, we predict that learners remember more decontextualized words than words learned in context. This prediction is in line with previous findings (e.g., Laufer & Shmueli, 1997). In terms of acquisition of implicit lexical knowledge and the relationship between explicit and implicit knowledge, no priori prediction is formulated due to lack of prior research.

3. Methods 3.1. Participants and design The participants were Korean high school students (N ¼ 15) who were learning English as a foreign language (EFL). To increase homogeneity within the sample, all participants were male, 10th graders, and native speakers of Korean with no experience studying in English-speaking countries. The average age of participants was 16.34 years (SD ¼ .34). In addition, only intermediate-level English learners were recruited by using the English test scores on the preparatory College Scholastic Aptitude Test (CSAT). The test administered nationwide has been used by L2 researchers for screening purposes (e.g., Oh, 2001; Park, Choi, & Lee, 2012). Specifically, the preparatory CSAT mandated for all Korean high school students assesses Korean high school students' academic abilities in content areas such as mathematics and physics as well as English reading skills. CSAT has been administered by the Korea Institute for Curriculum and Evaluation (KICE) for the last two decades. The English section of the CSAT focuses primarily on reading skills. According to the test results, participants' test score percentiles ranged from 72 to 79. Although they volunteered for the experiment, time and effort were compensated with 30,000 KR Won (approximately 29 U.S. dollars). All were righthanded with no neurological history or psychiatric disorders and had normal or corrected-to-normal vision. This study was conducted under the guidance of the local Institutional Review Board, and written informed consent was obtained from each participant prior to the experiment. A within-group design was used, which enabled us to control for a number of learner-related variables such as working memory capacity (Baddeley, 1997; Baddeley, Gathercole, & Papagno, 1998), partial word knowledge (Nation, 2005), word guessing skills (Coady, 1997), and language proficiency (Tekmen & Dakoğu, 2006). Holding these variables constant is critical because such variables have been shown to be significant predictors of learners' ability to learn new words. For instance, a number of studies have shown that working memory capacity is an important variable in learning novel words during reading (Baddeley, 1997). Therefore, high-span learners may have more cognitive resources available for processing and encoding novel words than their low-span counterparts, regardless of the role of context in vocabulary learning. Context (two levels: contextualized, CT, and decontextualized, DCT) was the only independent variable in this experiment. There were multiple dependent variables, including behavioral (vocabulary test scores, reaction times) and electrophysiological (i.e., N400) data.

3.2. Procedure The 8-week experiment was administered in two phases: the study phase occurred at a participating high school and the unannounced testing phase occurred in a dedicated EEG lab. There were three sessions in the study phase. The intervals between the three study sessions and the testing phase are summarized in Fig. 1. In study session 1 (week 1), participants read the first story (The Lady or the Tiger?) at their own pace. They spent approximately 12 min reading the story. The CT words (pseudowords) were embedded in the story, and the definitions of these words were provided in the bottom margin to prevent participants from making erroneous guesses of word meanings. After reading the first story, participants marked their reading time and continued to study the first half of the target CT words for 5 min while skimming through the story. Next, participants studied the first half of the 30 DCT words for 5 min. The DCT words (pseudowords) were displayed together on the wordlist with their L1 counterparts (e.g., thol – 왕). In study session 2 (week 2), participants repeated the procedure of study session 1. The only difference was the order of studying CT and DCT words. Participants studied the second half of the DCT words first and then the second half of the CT words after reading the second story (Miss Bracegirdle's Night of Fear). Average reading time was approximately 19 min. Finally, in study session 3 (week 3), participants learned all CT words while skimming through the two stories and studied all 30 DCT words. 10 min was allowed for each type of words. The order of studying CT and DCT words was

S. Choi et al. / Neuropsychologia 63 (2014) 226–234 counterbalanced across the participants. Throughout the sessions, participants were instructed to direct their full attention to the task and remember as many words as possible. An immediate vocabulary test was administered shortly after the final study session. During the test, participants were given a sheet listing all the pseudowords and were asked to fill in a corresponding meaning for each pseudoword in their native language (Korean) at their own speed. Analysis of the results showed that participants remembered a similar number of CT (M ¼24.60) and DCT (M¼ 24.53) words (t14 ¼.061, p ¼.952). The testing phase (week 8) included a delayed vocabulary test and EEG recording. The five-week interval between the final study session and the testing phase is based on Laufer and Shmueli (1997) who examined the effects of discourse-level context on acquisition of explicit lexical knowledge by using a five-week delayed vocabulary test. Comparing our data with that of those researchers would be informative. During the vocabulary test, participants were asked to write down the meaning of CT and DCT words, which were randomly displayed on the vocabulary test sheet. As in the immediate vocabulary test, participants responded to the test at their own speed. After the vocabulary test, participants moved to a shielded testing room for EEG recording.

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3.3. Contextualized and decontextualized words Participants in the present study were instructed to learn two sets of target words: 30 CT words (i.e., words integrated into two reading passages) and 30 DCT words (i.e., words presented in a wordlist), as summarized in Table 1. Thirty CT words were integrated into two stories (The Lady or the Tiger? and Miss Bracegirdle's Night of Fear; 1675 and 2687 words, respectively). These stories were adapted from Simply Suspense from the Penguin Readers series. The frequency of occurrence of the 30 CT words ranged from 4 to 35. At the bottom of the reading material, marginal definitions (i.e., Korean translations of the target words) were provided. Here, the graded reader is part of a series of simplified books containing texts of varying levels of difficulty. The books are designed to promote extensive reading for L2 learners of English. Thirty DCT words were presented in two separate wordlists, each containing 15 DCT words typed on A4 paper. Each target word in the wordlist was displayed with a target word and its short definition in Korean. Therefore, participants could simultaneously study both word form and meaning.

3.4. EEG stimuli The EEG recording included 120 trials: 60 matching trials (30 trials each for CT and DCT words) and 60 mismatching trials (30 trials each for CT and DCT words). Specifically, each trial included a prime-target pair that either matched (e.g., chiss— 버스) or mismatched (e.g., gazz—열차). All trials were presented visually at the center of the computer screen in a randomized order. All prime (in lowercase letters) and target words were displayed in white against a black background. The trial sequence and timing were as follows: first, a central fixation cross (“ þ” symbol) was displayed for 500 ms. Then, a prime word was presented on the screen for 1000 ms. The prime word was replaced by a target word (i.e., the Korean equivalent of the prime word). When the target stimulus was presented, participants made a semantic decision (i.e., whether the prime and target matched or not) as quickly as possible by pressing “1” for a matching pair or “2” for a mismatching pair. The target word remained on the screen for 2000 ms or until a response was made. The experimental paradigm was implemented using the TeleScan software package (Laxtha Inc., Daejeon, Korea).

3.5. EEG recording and N400 analyses Fig. 1. Schematic description of the spacing between the study sessions and the testing; VT¼ vocabulary test.

EEG recording was performed in a sound-attenuating and electrically shielded EEG room. Participants were seated comfortably and responded to the visual

Table 1 Target CT and DCT words, meaning, Korean counterparts, and concreteness ratings. CT words

Meaning

Korean counterparts

Concreteness ratings

DCT words

Meaning

Korean counterparts

Concreteness ratings

Larb Tdal Feech Naul Ghed Shume Thol Ouds Ceve Fudd Kern Yoan Dwarse Haut Cern Aifs Dawed Wadd Phafe Feuce Wrirt Knuck Nutch Crea Wrol Kien Ploe Trulse Scir Codge

Door Man People Room Bed Stadium King Daughter Home Time Hotel Day Tiger Night Girl Eyes Woman Wrongdoer Place Train Letter Brother Hand Hair Workers Police Knife Friends City Tea

문 남자 사람들 방 침대 경기장 왕 딸 집 시간 호텔 하루, 날 호랑이 밤 소녀 눈 여자 범죄자 장소 기차 편지 남자형제 손 머리카락 노동자 경찰 칼 친구들 도시 차

4.6 3.7 3.2 3.9 4.7 4.1 4.0 3.7 3.3 1.6 4.1 2.0 4.6 2.5 3.5 4.4 3.5 3.3 1.9 4.5 3.6 3.5 4.5 4.5 3.3 4.1 4.8 2.8 3.0 4.1

Dirp Shung Rutch Jurr Pauge Cheme Rauk Gazz Shas Lube Rhoile Orged Vairs Yorch Ghit Dyth Wheef Yuys Zobe Pauve Chiss Chout Guff Veap Crer Woap Pler Kague Vease Varl

Desk Boy Adult Window Chair Stage Queen Granddaughter Apartment Watch Hut Morning Lion Noon Bathroom Children Shoulder Grandmother Judge Airport Bus Postoffice Sister Foot Head Factory Robber Fork Friendship Travel

책상 소년 성인 창문 의자 공연무대 여왕 손녀 아파트 손목시계 오두막 아침 사자 정오 욕실 아이들 어깨 할머니 판사 공항 버스 우체국 여자형제 발 머리 공장 강도 포크 우정 여행

4.7 3.3 2.5 4.5 4.7 3.8 3.4 3.6 3.9 4.4 4.0 2.0 4.5 2.0 4.4 3.4 4.5 3.8 4.1 4.3 4.6 4.5 3.3 4.7 4.1 3.8 3.8 4.8 1.2 2.2

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stimuli presented at a distance of approximately 60–70 cm. Prior to ERP data collection, 10 practice trials were performed to familiarize participants with the task. During EEG recording, participants were asked to avoid blinking, swallowing, and other muscle movements to minimize artifacts. Continuous EEG recording was obtained using silver–silver chloride electrodes embedded in the ElectroCap. By using the Grass ohmmeter, the electrode impedance was kept below 5 kΩ. Electrooculographic activity was measured using electrodes placed at the outer canthi of the right eye (horizontal EOG) and above and below the right eye (vertical EOG). EEG signals were recorded with mastoids as the reference and were referenced again offline using the average of mastoid signals. EEG signals were amplified by WEEG32 (Laxtha Inc., Daejeon, Korea). Brain potentials were digitized at a sampling rate of 256 Hz using TeleScan, and EEG signals were sampled 200 ms before the onset of each target stimulus and continued for 800 ms. Before averaging, individual EEG recordings were visually inspected to scan for artifacts such as eye and muscle movements, blinking, and electrode drifting. In addition, all signals 75 ㎶ above or below baseline were removed. After the removal of all contaminated trials, remaining trials were averaged and corrected using a 200 ms pre-stimulus baseline. Following baseline correction, epochs containing noise were rejected, and a low-pass filter was set at a 10 Hz cutoff for data from all participants. Then, the average of artifact-free ERPs was computed for each participant and condition (contextualized vs. decontextualized) and collapsed to form a grand average. Following previous research (e.g., Mueller, Girgsdies, & Friederici, 2008; Chun et al., 2012; Barber, Otten, Kousta, & Vigliocco, 2013), only trials with correct responses were averaged.

4. Results 4.1. Validation of target words Memorability, partial word knowledge, and number of letters were held constant across CT and DCT word sets. To balance memorability, the two word sets were matched on word concreteness (i.e., imageability). Specifically, 22 undergraduate students who did not participate in the main study provided concreteness ratings of target words on a five-point Likert-type scale ranging from “very abstract” (1) to “very concrete” (5). The results indicated little difference in mean concreteness ratings between CT and DCT words (t21 ¼.242, p¼.809, d¼.065). A meta-analysis by Sadoski (2005) showed that concrete words are remembered better than abstract words because concrete information can be represented both verbally and pictorially, whereas abstract information can only be represented verbally. In other words, multiple sources of information for concrete words may lead to deeper semantic processing relative to abstract words. To control for partial word knowledge, the two sets of words were converted into pronounceable pseudo-words. Using the ARC non-word database (Rastle, Harrington, & Coltheart, 2002), real words were changed to pseudo-words based on orthographically existing onsets, bodies, and legal bigrams. Substituting pseudowords for actual target words enabled us to control for participants' partial knowledge of target words, thus eliminating the possibility that participants were drawing on any lexical knowledge accrued from previous experience (Hulstijn, 2003; Webb, 2007). Finally, the two word sets were matched based on the number of letters (M ¼4.4 letters per word for both CT and DCT word sets). 4.2. Analysis of N400 and RTs We gauged how learning words in and out of context affected implicit lexical knowledge using ERPs and RTs obtained during EEG recording. First, ERP data was analyzed with a focus on the N400 component. Mean amplitudes in the 350 ms and 550 ms time windows were used. Based on previous research (e.g., Kutas & Federmeier, 2000; Chun et al., 2012), the principal scalp sites of interest were centro-parietal electrode sites (C3, Cz, C4, P3, Pz, and P4). The results of a paired-samples t-test indicated no significant N400 effects (t14 ¼.061, p ¼.952). The effect size was quite small

(d ¼.059) based on Cohen's rule-of-thumb criteria (Cohen, 1988). Fig. 2 shows the grand average ERP waveforms for CT and DCT words from six centro-parietal electrodes. Second, mean RTs for CT and DCT vocabulary items were compared. RT data were obtained from the semantic decision task during EEG recording. As shown in Fig. 3, mean RTs for CT (M¼ .781, SD ¼ .091) and DCT (M ¼.785, SD ¼.108) words were quite similar, and the difference in mean RTs (M ¼.004) failed to reach statistical significance (t14 ¼.579, p ¼.572). The effect size was computed to determine the magnitude of the difference between the two word sets, and was quite small (d ¼.040). Average decision accuracy for CT and DCT words was moderately high: 70.23% (SD ¼ 10.42) and 71.66% (SD ¼ 13.18), respectively. The difference in mean accuracy was not statistically significant (p ¼.255) and showed a small effect size (d ¼.12). 4.3. Analysis of vocabulary test scores Explicit lexical knowledge was determined based on the vocabulary test scores, which were computed by summation of the number of correct responses. As illustrated in Fig. 3, the test score was 16.64% higher for DCT (M¼ 19.26, SD¼5.39) when compared with CT words (M¼15.40, SD¼5.74). A paired sample t-test indicated that the mean difference (M¼3.86) between the two word sets was statistically significant (t14 ¼ 7.132, po.001). The magnitude of the effect of context approached the large range (d¼.694).

5. Discussion and conclusion The primary purpose of the present study was to determine how learning words in context or out of context influences explicit and implicit lexical knowledge in L2 learners. Explicit lexical knowledge was assessed by a vocabulary test, which is more likely to demand conscious effort and various retrieval strategies. Implicit lexical knowledge was determined by ERPs and RTs obtained during the EEG experiment. Results showed that mean N400 amplitudes and RTs barely differed between CT and DCT words, indicating that neither learning type was superior over the other in terms of facilitating processing fluency or implicit lexical knowledge. The results suggest that words learned in and out of context may entail a similar processing cost or may lead to a similar strength of association between the novel L2 word forms and their corresponding L1 meanings. In contrast, the vocabulary test results showed that DCT words were significantly more memorable than CT words. The vocabulary test results neatly parallel to Laufer and Shmueli (1997), who reported that using wordlists was more conducive to long-term explicit vocabulary knowledge acquisition than encountering novel words in discourse-level context. Collectively, these findings suggest that learning words out of context may be more effective than learning words in meaningful contexts in terms of explicit, but not implicit, lexical knowledge. In other words, learning words devoid of context may be more effective in helping learners create explicit links between L2 form and L1 meaning, whereas neither type of learning seems superior for facilitating processing fluency of target words. In the immediate vocabulary test, participants remembered similar number of CT and DCT words (M ¼24.60 and 24.53 for CT and DCT words, respectively). In the delayed vocabulary test, however, participants retained significantly more DCT words (M¼ 19.26; 35.8% loss) than CT words (M¼15.40; 48.7% attrition). The non-significant difference in the immediate vocabulary test result can be attributed to the fact that the immediate vocabulary test was administered shortly after the final study session. Therefore, participants' short-term memory may have

S. Choi et al. / Neuropsychologia 63 (2014) 226–234

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Fig. 2. Comparison of ERP waveforms for CT and DCT words in the centro-parietal recording sites.

0.9

0.8

0.7

0.6

0.5 CT words 21 20 19 18 17 16 15 14 13 12 11 10

CT words

DCT words

DCT words

Fig. 3. Mean reaction times (top) and vocabulary test scores (bottom) for CT and DCT words. The vertical bars represent the standard error of means.

played a significant role in diminishing any differences between the two learning conditions. The superiority of decontextualized learning in the delayed vocabulary test may echo different mapping or encoding processes that may take place in contextualized and decontextualized

learning conditions. More specifically, when learners study novel words in a decontextualized manner, they are more likely to focus their attention on linking forms (i.e., target word spelling and sound) and their corresponding meanings, which are already established in their L1 mental lexicon, thus possibly resulting in ample associative training. In contrast, when the same learners study new words in context, that is, in association with meaningful text, they are more likely to divide their cognitive resources between processing form–meaning associations and creating a coherent mental representation of the text by encoding the target words in relation to the surrounding text. Therefore, due to the limited processing resources of most learners (Baddeley et al., 1998), divided attention may leave learners with fewer available cognitive resources for form–meaning mappings. In other words, instead of facilitating form–meaning connections, the context may demand extra cognitive effort, which in turn may interfere with the processing of form–meaning mapping of the target words at a deeper level. These different mapping processes may have a significant effect on long-term explicit lexical knowledge, but not on short-term explicit lexical knowledge. The hypothesized form– meaning mapping processes may also generate dissimilar brain activation patterns, although future research is warranted to confirm our speculations. For instance, the hippocampus has been shown to play a critical role in the initial acquisition of new declarative knowledge (i.e., lexical information), whereas neocortical regions interfacing with the hippocampal memory system have been shown to be implicated in offline consolidation of previously learned lexical information (Squire, 2004; Breitenstein et al., 2005; Ellenbogen, Payne, & Stickgold, 2006; Davis & Gaskell, 2009). Therefore, compared to contextualized learning, decontextualized learning may induce stronger activity of hippocampus when learners map novel word forms and their meanings. Decontextualized learning may also induce higher activity in the neocortical regions elicited by offline consolidation during sleep. By contrast, due to the higher processing load, contextualized learning may show higher activation than decontextualized

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learning in the prefrontal cortex implicated with cognitive control, selective attention, and working memory (Baddeley, 1997). It is noteworthy that participants demonstrated a moderately high degree of decision accuracy (70.23% and 71.66% for CT and DCT words, respectively) with rapid RTs (M ¼.781 and .785 for CT and DCT words, respectively). These results indicate that at least some degree of implicit knowledge was accrued after the initial acquisition of explicit lexical knowledge, although our data is limited by the fact that there were no baseline measures of implicit knowledge. This finding appears to support Ellis (2005) who proposed that explicit knowledge feeds into implicit knowledge. This position has been termed as the weak-interface position. Therefore, our findings do not seem to support the no-interface position (Krashen, 1981; Hulstijn, 2002), which posits that the two types of knowledge are at different representational levels and do not interact due to different processing mechanisms. Finally, the number of participants in the present study was relatively small (N¼15), compared with that of previous electrophysiological studies of vocabulary learning: for example, 21 participants in Batterink and Neville (2011) and 18 participants in McLaughlin et al. (2004). In order to address the possibility that the null effect of RTs and ERP results could be attributed to the relatively small number of participants, we performed a retrospective power analysis by using the power table of Cohen (1988, p. 55) and also by running the GnPower 3.1, a power analysis program (e.g., Faul, Erdfelder, Buchner, & Lang, 2009). According to the power table, the number of participants required to attain significant results was at least 1571 on the basis of obtained effect sizes of .059, .040 for RTs and ERP data, the two-tailed alpha (¼ .05), and the recommended .80 power level (Cohen, 1988). According to the GnPower results, more than 350 and 900 participants are required to obtain significant results for RTs and ERP responses, respectively. These results and considerably small effect sizes of RTs and ERP data clearly show that it is unlikely that the null effect of RTs and the N400 results can be attributed to the current sample size. 5.1. Implications Given that implicit–explicit knowledge distinction is a central construct in L2 acquisition, our findings have important implications for L2 learners and language teachers. Specifically, with the advent of communicative language paradigms, language teachers have discouraged L2 learners from acquiring new words in a decontextualized manner and instead encouraged learning new words in meaningful contexts (e.g., Krashen, 1989; Waring & Takaki, 2003). However, our results and those of previous behavioral studies (e.g., Qian, 1996; Laufer & Girsai, 2008; Lindstromberg & Boers, 2008; Laufer, 2009) provide converging evidence that learning words out of context is an efficient means of acquiring a large repertoire of L2 words. In addition, contrary to the claim that decontextualized learning lacks meaningful interaction and can only lead to explicit lexical knowledge development (e.g., Krashen, 1981), our results indicate that decontextualized learning was equally as effective as contextualized learning for acquiring implicit lexical knowledge. Despite these findings, L2 learners should keep in mind that contextualized learning can support additional aspects of vocabulary knowledge, such as grammatical functions, actual use in a sentence or discourse, polysemous meanings, and collocational knowledge (Nation, 2005, 2011; Webb, 2007). The present study also has implications for L2 acquisition researchers. A large body of evidence has supported the use of ERPs as a valid index of implicit knowledge (e.g., Deacon et al., 2000; McLaughlin et al., 2004; Grossi, 2006). The results of this study demonstrate the value of electrophysiological methods in exploring implicit processing. Unfortunately, very few L2 studies have used such measures. This lack of research can be attributed in part to the

fact that many L2 researchers do not have access to high-cost research tools such as EEG. This suggests the need for interdisciplinary, collaborative efforts among L2 behavioral researchers and brain scientists. 5.2. Limitations The first limitation is that the significant difference between the two learning conditions in the delayed vocabulary test could be attributed to the fact that the vocabulary test (retrieval stage) was more similar to the decontextualized learning situation (encoding stage). Therefore, different results in the delayed vocabulary test may be observed when participants are asked to fill in words to complete a sentence, a more contextualized task. The second limitation is that the null of RTs and the N400 effects could be attributed to the fact that participants performed the vocabulary test right before running the EEG experiment. In other words, since the tested words were presented to the participants for the vocabulary test, it is possible that participants would have already activated memories for the words before the EEG experiment. Finally, participants in the present study were homogeneous in terms of gender (male), nonnative English speakers, English language proficiency, and grade (10th grade). Therefore, the findings of this study may not be generalized to female learners, native English speakers, higher- or lowerproficiency learners, and adult or primary-school learners. 5.3. Suggestions for future research The present study used a within-group design to control for a myriad of learner-related confounding factors, including working memory capacity (Baddeley et al., 1998; Chun et al., 2012). Given the important role of working memory capacity in vocabulary acquisition, a useful follow-up study would be to examine the effects of context and working memory capacity in a single study and to determine whether these two variables (i.e., context and working memory capacity) interact in the acquisition of implicit and explicit lexical knowledge. In addition, the present study showed that neither learning type (i.e., contextualized or decontextualized learning) was superior in terms of processing fluency. Given that rapid and fluent processing and retrieval of lexical information are critical for proficient language skills (Ellis, 2006), future research should investigate how other factors facilitate implicit lexical knowledge representations. For instance, Batterink and Neville (2011, p. 14) speculated that the development of implicit lexical knowledge might require massive exposure or “a longer incubation period”. However, this claim has not been tested empirically. 5.4. Conclusion To reiterate, our finding that decontextualized learning was superior in attaining only explicit lexical knowledge suggests that there may be dissociation in the acquisition of implicit and explicit lexical knowledge as a function of context. In addition, the overall findings illustrate the value of learning novel words in a decontextualized manner and challenge the claim that new words should be learned in context (e.g., Qian, 1996; Laufer & Girsai, 2008; Lindstromberg & Boers, 2008; Laufer, 2009). These findings suggest that L2 learners should not be discouraged from acquiring new words in a decontextualized manner, particularly because few L2 learners are allowed sufficient resources and time required for incidental vocabulary acquisition (Horst, Cobb, & Meara, 1998). We recommend using decontextualized learning to supplement contextualized learning because decontextualized learning may facilitate acquisition of certain kinds of lexical knowledge (i.e., acquisition of form–meaning associations), whereas contextualized learning can promote additional aspects of vocabulary

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knowledge, such as grammatical functions and collocational knowledge (Nation, 2005, 2011; Webb, 2007). In terms of the processing nature of the N400, converging results from RTs and the N400 and diverging results from the vocabulary test appear to support researchers who proposed that the N400 indexes the ease or difficulty of retrieval processes associated with a word (e.g., Kutas et al., 2006; Swaab et al., 2012). Finally, the results of this study merit further investigation in order to substantiate the findings of this study.

Acknowledgments This work was supported by the National Research Foundation of Korea Grant funded by the Korean Government (2012S1A5A2A01020715). This research was also supported by Kyungpook National University Research Fund, 2012. The authors thank the anonymous reviewers for their insightful comments, which have allowed us to improve the quality and clarity of our article.

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