To Constrain Used in a Funny Sentence Constrain in a Simple Sentence
Introduction
The accumulation of vocabulary is the foundation of linguistic communication learning, particularly for i's second linguistic communication (L2). The majority of vocabulary learning in L2 learners very oftentimes comes from explicit exposure and explicit teaching in the classroom (Ellis et al., 1994; Skehan, 1996; Willis, 1996; Ellis, 2000). However, explicit education cannot cover all the words that L2 learners need to master. A significant proportion of L2 words are acquired contextually. This is to say, L2 learners could larn novel words by extracting their pregnant from linguistic context.
The Behavioral Enquiry on L2 Contextual Discussion Learning
I controversial issue is how many encounters L2 learners need to acquire the meaning of a novel word (Nagy et al., 1987; Krashen, 1989; Pitts et al., 1989; Hulstijn et al., 1996). Some researchers believe that L2 learners need multiple times (Horst et al., 1998; Waring and Takaki, 2003; Tekmen and Daloglu, 2006; Webb, 2008; Pellicer-Sánchez and Schmitt, 2010). In Horst et al. study (1998), English language as second language learners from Oman listen and read a simplified version of the novel, The Mayor of Casterbridge, to learn new words whose occurrence frequencies ranged from 2 to 17. Results showed that gaining the meaning of a new word needed at least eight exposures of that word. In Webb study (2007), English language learners from Japan read sentences to learn new words, with the frequency of new words at one, three, vii, or x. After reading, learners were tested on discussion form cognition, morphological knowledge, and meaning. Results showed that the words were fully mastered when learned 10 times through reading. Waring and Takaki (2003) studied learners from Japan with lower L2 English proficiency. These learners were asked to read novels to learn new words, but these new words were pseudowords for an already known, very common concept, such every bit windle meaning "house." Firsthand testing after learning showed that these learners could master word form knowledge later reading the new words viii–ten times. All the same, fifty-fifty afterwards they read novel words 15–18 times, they could non chief the meaning of words. Based on these findings, researchers believed that to acquire the pregnant of novel discussion needs more 20 exposures. Here word class noesis refers to the spelling of the word, and it is usually tested by request participants to circle whatsoever words they could recognize from the text, every bit was used in Waring and Takaki (2003)'s study. Word meaning refers to the conceptual knowledge, and it is tested by request participants to interpret words into L1 (Waring and Takaki, 2003).
In sum, previous behavioral studies take shown that quantity of exposure, i.due east., frequency of exposure, is of import to L2 contextual give-and-take learning and that several repetitions are needed for learning to occur. However, what was left out in these studies was the judgement constraint effect. It has been found that learners learn fast in high constraint sentences. For example, in the study of Ma et al. (2015), Chinese learners of English were asked to read sentences with either high or low contextual constraint. Novel words (i.e., pseudowords) were embedded in these sentences. Afterwards reading, a pair of novel word and a existent give-and-take with related or unrelated meaning was presented and the participants were asked to do a semantic relatedness judgment task. Results showed that the meaning of the novel words could exist acquired in high constraint sentences but not in depression constraint sentences, suggesting that high sentence constraint facilitates the acquisition of L2 contextual word meaning. This facilitation upshot of high sentence constraint was besides demonstrated in another study (Ma et al., 2016).
L2 contextual word learning was also influenced by proficiency level. Pulido (2003) recruited L2 learners with different proficiency levels and asked them to read narratives of familiar or less familiar topics in club to report L2 vocabulary acquisition and retention. These narratives contained non-sense words. So, participants completed recognition tests ii and 28 days afterwards reading the narratives. The author found that no matter how familiar the topic was, learners with high proficiency acquired more than words through reading and maintained their learning better. In the study by Tekmen and Daloglu (2006), Turkish learners of English at different proficiency levels read text to learn English language words, and the results showed that college proficiency readers acquired more words than lower level readers. In the study by Ma et al. (2015), adults with higher L2 proficiency performed better than lower-proficiency L2 learners in high constraint sentences. These findings demonstrate that higher proficiency levels could facilitate novel word learning.
The Event Related Potentials (ERP) Inquiry on L2 Contextual Word Learning
Compared with behavioral studies, the ERP technique has loftier temporal resolution and could reveal ongoing brain responses of linguistic communication processing. The amplitude of the N400 component measured at centroparietal electrodes is an index of the difficulty in integrating semantic data into context (Kutas and Hillyard, 1980; Holcomb and Neville, 1990; Nobre et al., 1994; Perfetti et al., 2005; Balass et al., 2010; Kutas and Federmeier, 2011). A larger N400 indicates more hard semantic integration. In a similar sense, a decreasing N400 indicates the ease in processing. More recently, some researchers argue that the N400 is a measure out of prediction in language processing (Federmeier et al., 2007, 2010; Brothers et al., 2015), with its amplitude being attenuated if the preceding context pre-activates the meaning of a discussion. The learning process of novel words could be revealed through changes in N400 amplitude (Mestres-Missé et al., 2007). Specifically, more than frequent exposure to a novel word in a certain context would convalesce the difficulty in semantic integration, which could be reflected by a smaller N400.
Borovsky et al. (2010) adopted the ERP paradigm to explore the agreement and usage of L1 novel words learned through sentence reading. In their study, 26 English native speakers read high-constraint or depression-constraint sentences with known words or unknown words(non-words, e.k., marf)embedded as the objects of transitive verbs in the test sentences, and and so made a plausibility judgment of these words. The structure of the examination sentence was always Pronoun-Transitive Verb—Article/Pronoun—Target word. Learners needed to determine if the word was used appropriately, e.grand., they drove the marf. The plausibility effects could be reflected by a smaller N400 component in the appropriate condition than the inappropriate status. The results showed the N400 component reduced only when the novel word was embedded in a high constraint sentence, suggesting that novel word usage could be rapidly acquired through high constraint sentences in native speakers.
Borovsky et al. (2012) further explored the gene of judgement constraint in the integration of novel discussion meanings into semantic memory using the same materials as in their 2010 report. Adult native speakers of English language were asked to read high-constraint or low-constraint sentences that ended with known or unknown words. After reading, the participants did a lexical determination chore to see whether the ending words (known or unknown) would show a priming effect on related, unrelated, and synonym target words. ERPs were also recorded during the experiment. The results showed that only when unknown words were embedded in high-constraint sentences, N400 amplitudes were different between related and unrelated target words, with unrelated targets eliciting the largest N400 and synonym targets eliciting the smallest N400. The results demonstrated that adult native speakers could quickly integrate discussion meaning information into their mental lexicons by reading loftier constraint sentences.
Mestres-Missé et al. (2007) also observed real-fourth dimension give-and-take meaning conquering during sentence reading through amplitude changes in the N400. In this study, Spanish native speakers were asked to read three sentences with the aforementioned Spanish novel word. The meaning of the novel word was either consequent across the three sentences (congruent meaning, Thou+) or inconsistent (incongruent significant, M−). The results showed that in the G+ status, the N400 amplitude decreased across the three sentences, implying the conquering of novel word pregnant. Batterink and Neville (2011) used the same paradigm as Mestre-Missé, with pseudowords embedded in paragraphs. They also found decreased N400 amplitude as the number of sentences increased, but merely in the congruent meaning status. These studies indicate that for adult native speakers, when the quality of language input is high, give-and-take learning happens chop-chop.
However, there have been few ERP studies investigating L2 contextual word learning. Elgort and Warren (2014) investigated the issue of L2 proficiency on L2 contextual give-and-take learning using the ERP technique. In this study, rare English words (i.e., critical words) were embedded in iii high-constraint sentences. Participants read these sentences at their own footstep. The post-obit day, participants read these sentences again but with the critical words in the sentence-last position, followed by related or unrelated meaning probes. They were required to make semantic relatedness judgments about the critical words and the meaning probes, while ERPs were recorded. Results showed that for the higher proficiency group (students recruited in education and international business concern courses at the University of Pittsburgh), the N400 amplitude was significantly smaller in related trials than unrelated trials. However, this was non constitute in low proficiency learners (students recruited from English proficiency courses at the University of Pittsburgh, whose TOEFL iBT scores were beneath 100). These findings suggest that it is easier for learners with higher L2 proficiency to predict the pregnant of rare words and form initial lexical semantic representations. Although Elgort and Warren (2014) examined the upshot of L2 proficiency on L2 word learning, they did not record the change of brain responses as the novel words were being learned.
The Current Report
It is withal unknown how many exposures a learner needs for successful L2 contextual word learning. Few studies have manipulated the quality of judgement reading materials to study L2 contextual word learning. Variation of sentence constraint and/or comprehension difficulty of reading materials may lead to the unpredictability of L2 word learning times. Thus, nosotros hypothesized that multiple times in L2 word learning are needed for low-constraint contexts. When reading materials were highly constrained (i.e., loftier quality), give-and-take learning can happen very rapidly. To verify this hypothesis, we used high-constraint sentences to explore the effect of number of exposure on L2 contextual word learning. Furthermore, L2 proficiency was also investigated in the electric current study.
We used the ERP technique, which has high temporal resolution, to explore the above questions. Following the design of Mestres-Missé et al. (2007), we embedded pseudowords at the terminate of the sentences, creating iii conditions: pseudowords embedded in four consequent meaning sentences (M+ condition); pseudowords embedded in four inconsistent meaning sentences (K− condition); and a control condition with real words embedded in four consistent meaning sentences (R condition). Whereas, Mestres-Missé et al. (2007) focused on native speakers, the current written report focused on L2 learners and the result of their L2 proficiency.
Learners read four high-constraint sentences containing the same target discussion, and then judged the semantic relatedness betwixt the target discussion and a meaning probe. The accuracy rates and response times were recorded to reveal their comprehension and acquisition of the meaning of novel words. Encephalon potential activities were recorded during judgement reading to find the change of brain responses as the novel words were beingness learned.
In accordance with previous studies, we chose 300–500 ms post-stimulus every bit the time window to observe the N400 effect, which indicates the process of meaning acquisition (Perfetti et al., 2005; Mestres-Missé et al., 2007; Balass et al., 2010; Borovsky et al., 2010, 2012; Batterink and Neville, 2011) and meaning prediction in language processing (Federmeier et al., 2007, 2010; Brothers et al., 2015). For the behavioral data in the semantic relatedness judgment job, we predicted that at that place would be significant differences between the R and Thousand- weather, too as between the Yard+ and K− conditions, but no difference between the R and M+ conditions. The proficiency of L2 may facilitate this learning procedure. For the ERP data, we predicted that the number of exposures would play a limited role in high-constraint sentences. More specifically, N400 amplitudes evoked past the last words of sentences in the R and M+ conditions would decrease as the number of sentences increased. As the same existent discussion was used for the four sentences in the R condition, the N400 amplitude would keep unchanged across the 2d, third, and fourth readings since no endeavour is needed for meaning prediction. However, in the M+ condition, the meaning of the pseudoword is continually being predicted across the four sentences, so the N400 aamplitude might keep decreasing following a downward slope. In the 1000− condition, no consistent meaning could be fatigued from the four sentences, so the N400 amplitude would not change. Additionally, participants with higher English L2 proficiency might be fast learners in predicting the meaning of pseudowords, and thus would bear witness a larger decrease of the N400 amplitude in the M+ condition.
Methods
Participants
40-iv right-handed higher students, who were all native Chinese speakers learning English as a second linguistic communication, were recruited from Beijing Normal University. All participants had normal or corrected-to-normal vision. This written report was approved past the ethics committee of the School of Psychology, Beijing Normal University. All participants gave their written informed consent before the experiment.
Materials
Real Words
Existent words were 108 high frequency concrete nouns. Word frequency (mean logFreq = 10.04, SD = 0.95; logFreq refers to log-transformed HAL frequency norms) was rated co-ordinate to HAL norms (Hyperspace Analog to Language Frequency Norms, Lund and Burgess, 1996; Balota et al., 2007). Concreteness (M = 578.37, SD = 42.54) was rated based on the MRC database (Medical Enquiry Council Psycholinguistic Database, Wilson, 1988). Familiarity was rated using a 5-point scale (1 = very unfamiliar, v = very familiar) by a homogenous split group of 26 college students from the same university (mean familiarity = 4.83, SD = 0.xviii).
Pseudowords
One hundred and 8 pronounceable pseudowords were constructed using Wuggy (Keuleers and Brysbaert, 2010). Wuggy is a multilingual pseudoword generator using a specific algorithm to generate pseudowords which are matched with real English words in subsyllabic structure and transition frequency. We used real English words as base words to generate pseudowords (non the existent words used equally materials in Real Words). These real words have 2 or iii syllables, and ranged from 5 to 7 messages in length. All pseudowords were randomly paired with existent words every bit experiment materials.
Word length of pseudowords ranged from 5 to seven (M = 5.69, SD = 0.57), and real words ranged from 3 to 10 (K = 5.thirteen, SD = one.54). There was a significant departure between the word length of pesudowords and their respective real words, t = 3.73, p < 0.01. Considering that word length difference may cause variances, we added word length (both pseudowords and real words) as a dummy predictor in the behavioral data analysis.
Semantically Related/Unrelated Words
For the semantic relatedness judgment chore, semantically related or unrelated words were selected to pair with the 108 real words. Word length of semantically related words ranged from 3 to eleven messages (M = 5.30, SD = 2.02), and semantically unrelated words ranged from iii to 8 (M = 4.78, SD = ane.30). Word frequency was rated according to HAL norms (Hyperspace Analog to Language Frequency Norms, Lund and Burgess, 1996; Balota et al., 2007; semantic related words: mean logFreq = 9.74, SD = 1.42; semantic unrelated words: mean logFreq = 10.42, SD = 0.96). Semantic relatedness was rated by the 26 higher students who rated the familiarity of real words (and who did non participate in the formal experiment), using a five-point scale (1 = absolutely unrelated, 5 = closely related). For semantically related words, the average score was four.43 (SD = 0.43), for example, "agronomics" was rated to be highly related to "subcontract" in meaning. For semantically unrelated words, the average score was one.18 (SD = 0.21), for instance, "canteen" was rated to exist barely related to "mountain" in meaning.
Sentences
Four sentences were synthetic for each real give-and-take, and and then the real word was replaced by a pseudoword to create the One thousand+ condition, in which the meanings of novel words were consequent and could be abstracted. The M− condition, in which the meanings of novel words were inconsistent and could not be abstracted, was created by reorganizing iv sentences of four words into one grouping and replaced the 4 words with ane pseudoword. The length of sentences ranged from 7 to 17 words, with the primal word (real word or pseudoword) always actualization at the end of the sentence. The constraint of sentences was rated by a carve up group of 43 college students from the same schoolhouse of the participants. They completed the sentences in a cloze test with the first substantive that came to their mind. The cloze probability was calculated by counting the percentage of times the same give-and-take was provided for each judgement. The mean cloze probability of these sentences was 89% (SD = 0.09). Rating through a 5-point calibration (ane = very easy, 5 = very difficult), all sentences were easily understood (M = 1.45, SD = 0.19). And no statistical differences were found among the four sentences synthetic for the same word [constraint: F (3, 428) = 0.217, p = 0.89, Eta2 = 0.002; reading difficulty: F (three, 428) = 1.01, p = 0.39, Eta2 = 0.007]. The sentences were carve up pseudo-randomly into 3 lists to brand sure that no items repeated in one list, and the real words and their corresponding pseudowords never appeared in the same list. For each listing, there were 576 sentences, 36 groups of experimental sentences per condition, and another 36 groups of filler sentences ending with existent words. Each participant received only one of the three lists. Examples of a group of iv sentences and examination pairs of words from each condition are given in Tabular array one.
Table 1. Examples of 4 sentences and test pairs of words from each condition.
English Level Evaluation Tool
The Higher English Test (CET) (come across the Procedure section) and Quick Placement Exam (2001) was used in this experiment to evaluate the participants' English level. The QPT is a flexible test developed by Oxford University Press and Cambridge ESOL to chop-chop evaluate a student's level of English. It includes reading and structure, grammar, and vocabulary. Role one has 40 items and Part two has twenty items, for a maximum score of 60. The scores of QPT are presented in Table 2.
Table 2. Background data of participants by proficiency level: Mean (SD).
Experimental Design
This study used a mixed experimental design: 4 (sentence presentation order: 1st, 2nd, 3rd, quaternary) × 3 (word type: R, M+, Yard−) × ii (proficiency level: higher, lower). Here, sentence presentation order and discussion type were within-subjects factors, and proficiency was a between-subjects factor. All the sentences were counter-balanced across participants co-ordinate to word type (R, Thou+, K−), to make sure no words/pseudowords or sentences were repeatedly presented for each participant. The iv sentences within each group were presented randomly.
Procedure
Participants were divided into two groups based on their College English language Test (CET) levels. The CET is a examination designed past the Ministry of Pedagogy of China to judge the English proficiency level of Chinese college students. It includes listening comprehension, reading comprehension, writing, translation, and cloze chore (Zheng and Cheng, 2008). Twenty-four participants who passed CET Band 6 were categorized every bit college proficiency English learners; 20 participantsane who failed CET Ring 4 were categorized as lower proficiency English language learners. Before the experiment, all participants completed self-ratings of their English listening, speaking, reading, and writing abilities on a 5-point scale (i = very non-proficient, v = very proficient) as well as the QPT. For details nigh participants' scores, see Table 2.
E-prime software version 2.0 was used to present stimuli on a computer screen. Participants were seated in front end of the computer and skilful several trials prior to the formal experiment.
The first part of each sentence was presented as a whole, with the last word of each sentence presented separately. The experiment began with the presentation of a fixation cross in the center of the screen for 500 ms. After the fixation, the first part of the sentence was presented and would non disappear until learners pressed the spacebar to continue, and then a bare screen lasted 1,000 ms, followed by the last discussion/pseudoword of the sentence which was presented for 500 ms, then a blank screen lasted for 1,200 ms followed by the next trial started.
Each grouping included four sentences of one give-and-take/pseudoword and each block included six groups of sentences. When learners finished a block, a question mark appeared on the screen for 1,000 ms as a prompt for participants to practice the semantic relatedness judgment. In this chore, learners read half-dozen word pairs respective to the half-dozen groups of sentences just presented and judged whether the words were semantically related. Within each block, the 6 groups of sentences and the respective give-and-take pairs were presented in pseudo-random order. "Related" or "Unrelated" responses were made by pressing "F" or "J" on the keyboard. Half of the participants were asked to press "F" for "Related," "J" for "Unrelated." The other half press "J" for "Related," "F" for "Unrelated." The two words appeared on the screen simultaneously, and if no response was detected within 5,000 ms, the stimuli would disappear followed past a blank screen for 200 ms. The whole experiment lasted for 1.5–2 h.
Finally, all participants were given a checklist of all the sentences they had but read to confirm that they had no difficulty in reading these sentences. In this checklist, all the pseudowords were replaced with the respective real words. The participants were asked to mark the sentences or words which were difficult to them. Because no marks were made on any items, we presume the materials could be hands candy by the participants.
Behavioral Analysis
The behavioral data for all 44 participant learners were reviewed. Cases of no response or responding likewise early (less than 200 ms) were excluded (1.66%). A mixed-effects logistic model of accuracy and a mixed-effects model of response time were built to analyze their performance in the semantic relatedness judgment chore (Baayen et al., 2008; Jaeger, 2008). These two models were congenital with subjects and items every bit random intercepts and slopes. All statistical analyses were carried out using R three.1.2 (R Core Team, 2014), implemented with package lme4 (Bates et al., 2013), lmerTest (Kuznetsova et al., 2013), and multcomp (Hothorn et al., 2008).
EEG Recording and Analysis
Participants were seated comfortably in a chair, relaxing, and minimizing eye movements and blinks. They read the sentences quietly. The electroencephalogram (EEG) was recorded from 64 Ag/AgCl electrodes placed co-ordinate to the extended 10–20 positioning NeuroScan iv.five system (http://world wide web.neuroscan.com/). The bespeak was recorded with 500 Hz sampling rate and referenced online to the right mastoid (M2). Electrode impedances were kept below 5 kΩ. The EEG activity was filtered online within a bandpass of 0.05–100 Hz and after low-laissez passer (30 Hz) refiltered offline. Heart blinks were mathematically corrected co-ordinate to the recorded VEOG and HEOG. This mathematical algorithm is a regression analysis in combination with antiquity averaging to produce a reliable and valid method for artifact removal (Semlitsch et al., 1986). The remaining artifacts were manually rejected. The EEG signal was recorded during the entire experiment, including the sentence reading and semantic relatedness judgment tasks.
Segments with electrical activity ±100 μV at any electrode sites were rejected. EEG segments of 800 ms with a pre-stimulus (the concluding discussion of the sentence) baseline fourth dimension of 100 ms were selected and averaged offline to obtain the ERPs. Baseline correction was performed in relation to the pre-stimulus fourth dimension. The signals were re-referenced using an boilerplate value of both correct and left mastoid offline.
One lower proficiency learner was excluded due to too many artifacts (merely 33.33% of trials were bachelor), so the concluding dataset was 43 participants, including 24 higher proficiency learners and 19 lower proficiency learners. After artifact rejection, 5.3% of trials were rejected.
In accord with previous studies, we analyzed the mean aamplitude within the time window of 300–500 ms upon the presentation of the concluding word of the sentence. To increase the bespeak-to-noise ratio over the 64 channels, every bit washed in the study by Batterink and Neville (2013), we focused on 36 electrodes beyond vi scalp areas: left-anterior (AF3, F3, F5, F7, FC3, FC5), left-posterior (CP3, CP5, P3, P5, P7, PO3), right-anterior (AF4, F4, F6, F8, FC4, FC6), right-posterior (CP4, CP6, P4, P6, P8, PO4), key-anterior (F1, Fz, F2, FC1, FCz, FC2), central-posterior (CP1, CPz, CP2, P1, Pz, P2). A five-manner repeated-measures ANOVA with the factors sentence presentation guild (beginning, 2nd, tertiary, fourth), word type (R, M+, M−), proficiency (college, lower), hemisphere (left, central, right), and brain region (anterior, posterior) was applied on the hateful amplitudes. The Greenhouse-Geisser correction was applied on all p-values of master effects and interactions.
Results
Behavioral Information Results
For each of the two proficiency groups, accuracy and response times for different conditions are shown in Tabular array 3.
Table 3. Accuracy (%) and response fourth dimension (ms) of semantic relatedness judgment task: Mean (SD).
A mixed-effects logistic model of accuracy was congenital in which word type and proficiency were stock-still factors, discipline and item (i.e., combination of sentences and key words) were random factors, and give-and-take length was a covariant (Table iv). A Tukey postal service-hoc test was applied to reveal the unproblematic furnishings of word type. Results were summarized in Table 5. As nosotros tin see from Tables 4, five, there was a significant main consequence of give-and-take type, such that accuracy was higher in the R condition than in the One thousand− condition (z = 9.68, p < 0.001), higher in the Yard+ than in the M− condition (z = eight.02, p < 0.001), merely no significant divergence betwixt the R condition and the M+ status was observed (z = 1.07, p = 0.655).Discussion length did not affect the chief effects of fixed and random factors.
Table iv. Mixed-effects logistic model of accuracy in the semantic relatedness judgment chore.
Tabular array 5. Tukey mail service-hoc test of accuracy in semantic relatedness judgment task.
We also examined whether the accuracy of different conditions was significantly college than chance level. For the R condition, accuracy was above chance level (college proficiency learners: z = 3.92, p < 0.01; lower proficiency learners: z = 3.thirteen, p < 0.01); for the M+ condition, accuracy was also above take a chance level (higher proficiency learners: z = 3.63, p < 0.01; lower proficiency learners: z = 3.22, p < 0.01); for the M- status, withal, there was no significant difference between accuracy and risk level (higher proficiency learners: z = i.86, p > 0.05; lower proficiency learners: z = 1.16, p > 0.05).
For the response time data, a mixed-effects model was constructed in which word type and proficiency were fixed factors, subject and item (combination of sentences and fundamental words) were random factors, and word length was a covariant. Results are summarized in Table 6. A Tukey post-hoc examination was conducted to reveal the simple furnishings of give-and-take type and proficiency. Results are summarized in Table 7. In that location was a significant master effect of word type, such that response fourth dimension was shorter in the R condition than in the M− condition (z = −x.43, p < 0.001), shorter in the 1000+ condition than in the M− status (z = −12.77, p < 0.001), but no significant difference between the R condition and the M+ condition was observed (z = −0.026, p = i.000). And there was as well a pregnant main effect of proficiency, such that higher proficiency learners responded faster than lower proficiency learners (z = vii.75, p < 0.001). Word length did not affect the master effects of fixed and random factors.
Table 6. Mixed-effects model of response time in semantic relatedness judgment task.
Table 7. Tukey post-hoc examination of response time in semantic relatedness judgment task.
EEG Data Results
The group-level boilerplate waveforms and scalp distribution elicited by different give-and-take types are shown in Effigy 1 (the first presented sentences), Figure 2 (the four sentences in the R condition), Effigy iii (the 4 sentences in the M+ status), and Figure 4 (the 4 sentences in the M− condition). We chose the 300–500 ms post-stimulus time window (upon the presentation of the final discussion of the sentence) to analyze the mean amplitudes. From the waveforms and scalp distribution, the M+ and M− conditions evoked obvious negative components in the get-go presented sentences, indicating difficulty in semantic integration. (Figure 1A for higher proficiency learners, Figure 1B for lower proficiency learners).
Effigy 1. The group-level average waveforms and scalp distribution elicited by different word types of the beginning presented sentences for higher proficiency (A) and lower proficiency participants (B).
Figure two. The group-level boilerplate waveforms and scalp distribution elicited by real words of iv sentences (R status) for higher proficiency (A) and lower proficiency participants (B).
Effigy three. The group-level average waveforms and scalp distribution elicited past pseudowords of iv sentences (G+ condition) for higher proficiency (A) and lower proficiency participants (B).
Figure four. The group-level boilerplate waveforms and scalp distribution elicited past pseudowords of different sentences (G- condition) for higher proficiency (A) and lower proficiency participants (B).
A repeated-measures ANOVA was conducted on the mean amplitude in the 300–500 ms time window, and the results showed a significant main effect of word blazon, F (two, 82) = 4.90, p < 0.05, Eta2 = 0.xi. There was also a significant main effect of sentence presentation order, F (3, 123) = 28.73, p < 0.001, Eta2 = 0.41. More importantly, in that location was a pregnant interaction between word blazon and judgement presentation order, F (6, 246) = 12.57, p < 0.001, Eta2 = 0.24. Further analysis found that in the R condition, N400 amplitudes evoked in the commencement presented sentences were significantly larger than in the second (Doc = 3.032, SE = 0.309, p < 0.001), the third (MD = 3.086, SE = 0.306, p < 0.001), and the fourth (MD = 3.210, SE = 0.327, p < 0.001). No deviation was found among the second, third, and fourth sentences. In the Yard+ condition, N400 amplitudes evoked in the kickoff presented sentences were significantly larger than in the 3rd (MD = 1.149, SE = 0.342, p < 0.05) and the 4th presented sentences (MD = ane.291, SE = 0.328, p < 0.01). There were no differences between the first and second sentences or among the 2nd, 3rd, and fourth sentences. In the K− condition, no sentence presentation club result was plant.
In that location was a significant main issue of brain region, F (1, 41) = 12.76, p < 0.01, Eta2 = 0.24, such that N400 amplitudes evoked in the anterior were significantly smaller than in the posterior (MD = −0.937, SE = 0.267, p < 0.01). There was a significant main consequence of hemisphere, F (two, 82) = 22.34, p < 0.001, Eta2 = 0.35, such that N400 amplitudes evoked in the left hemisphere were significantly smaller than in the cardinal midline (MD = −0.715, SE = 0.122, p < 0.001) and right hemisphere sites (Doc = −0.947, SE = 0.148, p < 0.001), while no difference was establish between the central midline and right hemisphere sites (Doc = −0.232, SE = 0.145, p = 0.351).
In that location was a pregnant interaction between sentence presentation gild and brain region, F (3, 123) = xv.91, p < 0.001, Etatwo = 0.28. Further analysis found no brain region result on the first presented sentence (MD = −0.029, SE = 0.248, p = 0.919), while significant brain region furnishings in the second (Medico = −0.978, SE = 0.290, p < 0.01), third (Doctor = −one.334, SE = 0.327, p < 0.001), and fourth presented sentences (Dr. = −1.404, SE = 0.316, p < 0.001) were observed, exhibiting more negative EEG signals at anterior sites than at posterior sites.
In that location was a significant three-way interaction among word type, brain region, and proficiency, F (2, 82) = 5.27, p < 0.01, Eta2 = 0.17. Farther analysis establish significant encephalon region effects for higher proficiency learners in all three conditions: R (Physician = −1.072, SE = 0.347, p < 0.01), Thou+ condition (Doctor = −1.282, SE = 0.389, p < 0.01), and M− (Doctor = −0.769, SE = 0.378, p = 0.048), exhibiting smaller N400 aamplitude at anterior sites than at posterior sites. In lower proficiency learners, significant encephalon region furnishings were only constitute in the M- condition (MD = −ane.114, SE = 0.425, p < 0.05), but not in the R (MD = −0.638, SE = 0.390, p = 0.eleven) and M+ weather (MD = −0.744, SE = 0.437, p = 0.10).
The master findings was that in the R condition, N400 amplitudes evoked in get-go presented sentences were significantly larger than in the second, third, and fourth presented sentences. In the One thousand+ condition, N400 amplitudes evoked in the commencement presented sentences were significantly larger than in the third and the fourth presented sentences, suggesting that participants gradually acquired the meaning of the pseudoword throughout sentence reading. In the 1000− condition, no judgement presentation social club effect was plant.
Give-and-take
The nowadays study explored the furnishings of loftier quality sentence encounters and proficiency level on L2 contextual give-and-take learning. Behavioral results of accuracy showed no statistical divergence between the M+ condition and the R condition for both groups of learners, just lower accuracy in the M− condition. These results suggests that the Yard+ condition—but non the G− condition—effectively facilitates novel word meaning acquisition. As well, accurateness results showed that both groups of learners were every bit familiar with the existent words, and they both caused the novel word meaning in the One thousand+ condition. Even so, response fourth dimension results showed that college proficiency learners spent less time in the semantic relatedness judgment task, suggesting that college proficiency learners were ameliorate at processing novel words as well as already known words.
For the ERP results, in 300–500 ms time window, meaning negative components were found in the Chiliad+ and M− weather condition compared to the R condition when learners read the first sentence. This negative component ordinarily found between 300 and 500 ms in the frontal and parietal regions was evoked by semantic violation, and it is a typical N400 upshot in sentence reading. Every bit the sentence number increased, the N400 patterns for the three types of words started to differ. In the R condition, the N400 amplitude decreased rapidly; in the 1000+ status, the N400 aamplitude decreased slowly and this decrease became significant upon the third sentence; in the Thou− condition, the N400 amplitude showed no obvious changes beyond the 4 sentences. Consequent with our predictions, this divergence in N400 aamplitude change amidst the three conditions direct reflected the course of discussion learning. Existent words are words learners already know and don't need to be learned once again. Novel words in the M+ status are words for which learners could grade consistent meanings, so they can be learned gradually equally sentence number increases, and this learning process could be reflected directly by the decreasing of the N400 amplitude. Novel words in the M− status are words for which learners could not form consistent meanings, so they cannot exist learned and no changes would be observed in the EEG signal.
Co-ordinate to previous findings, L2 word learning through sentences needs multiple exposures. However, previous studies did not control judgement quality, and take not explored how sentence quality modulates the influence of exposure times. In this study, the EEG signals showed novel words were learned successfully in the One thousand+ condition as sentence number increased, suggesting that the commencement two loftier quality sentences might play an important role in providing multiple exposures. Nosotros believe the central point between few encounters or multiple encounters needed to acquire L2 word meaning is the quality of language input. When the quality of language input is low, more exposures are needed. When the quality of language input is high, L2 learners could rapidly assign pregnant to the novel word. This is to say, when the sentence contexts are highly constrained, the number of exposures of L2 novel words does not thing that much. It is the high quality that actually matters.
The current findings are consistent with previous studies on L1 contextual word learning. Borovsky et al. (2010, 2012) plant that native speakers could rapidly acquire the meaning of unknown words in strongly constrained sentences. Mestres-Missé et al. (2007) recorded ERP signals upon novel words during judgement reading, and plant that with highly constrained sentences, participants were able to predict the significant of novel words at the second presented sentence and fully sympathise the novel word at the 3rd sentence. The current report also found that L2 learners could larn the meaning of novel words chop-chop in highly constrained sentences. These consistent findings from native speakers and L2 learners suggest that high constraint facilitates contextual word learning. What the current report contributes to the L2 literature is that the alter of brain responses upon novel discussion exposures was recorded, revealing the online process of L2 contextual word learning.
Contrary to one prediction, nosotros did not observe the consequence of L2 proficiency in the semantic relatedness judgment accuracy and the N400 amplitude. Yet, higher proficiency learners did respond faster than lower proficiency learners in the semantic judgment task. The possible reasons for this weak L2 proficiency event might be, firstly, that the materials used in this study might be too easy for all the participants; 2nd, the deviation between the higher proficiency level and lower proficiency level might non be large plenty. Nonetheless, because previous findings about the effect of language proficiency in native speakers (Perfetti et al., 2005; Balass et al., 2010) and L2 learners (Pulido, 2003; Tekmen and Daloglu, 2006; Ma et al., 2015), we believe that language proficiency is an important factor in L2 contextual give-and-take learning. Learners with higher proficiency could be better able to learn novel words because they take already accumulated sufficient word cognition.
Here it should exist noted that in the present study, nosotros but focused on the very initial phase of word meaning acquisition, namely, the process of building grade-meaning mapping, but not on the succeeding consolidation phase. To achieve the final goal of give-and-take acquisition, more exposures are needed for the consolidation of grade-meaning mappings.
Decision
In sum, by creating four loftier quality sentences for each novel discussion, and recording the brain electric activity during word learning through reading, we directly observed existent-time L2 contextual word learning. The results provide direct testify that L2 learners can rapidly acquire word meaning in high constraint sentences without multiple times of exposure, and L2 proficiency level affects learners' efficiency of using loftier quality language data.
Author Contributions
TM and BC designed the experiment and wrote the manuscript; TM collected and performed data analysis; LL and HL edited and revised the manuscript.
Conflict of Interest Statement
The authors declare that the research was conducted in the absence of any commercial or fiscal relationships that could be construed every bit a potential conflict of interest.
The reviewer, LM, and handling Editor declared their shared amalgamation.
Acknowledgments
This piece of work was supported past funding from Beijing Education Science Planning of 13th V-Year(CADA17077, The machinery of second language word learning for Chinese-English bilinguals) for BC. We would like to thank Dr. Susan Dunlap for editing the manuscript.
Footnotes
i. ^Due to the longer elapsing (1.5–2 h) of the experiment, nosotros were not able to recruit an equal number of high- and low-proficiency English learners. Hopefully, the mixed-effect model assay would guarantee the validity of the behavioral results despite uneven sample sizes (Lan et al., 2015).
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