Name: experimental paradigm for measuring the effect of induced emotion on grammar learning
Uploaded: 2020-01-29T15:30:00
Description: Watch this Scientific Journal Video about Experimental Paradigm for Measuring the Effect of Induced Emotion on Grammar Learning at JoVE.com

This study was supported by the key project [18AYY003] of the National Social Science Foundation of China, the National Research Centre for Foreign Language Education (MOE Key Research Institute of Humanities and Social Sciences at Universities), Beijing Foreign Studies University, and the post-funded project of Beijing Foreign Studies University [2019SYLHQ012].

The experiment was approved by the Ethics Committee of Beijing Foreign Studies University and it complied with the guideline for experiments with human subjects. All subjects in this research provided written informed consent.
1. Stimuli construction
<ol>
	<li>Design experimental stimuli based on the specific research questions. As this study is intended to examine foreign language learning using a semi-artificial language, create the experimental sentences by rearranging sentences in the pa...

<ol>
	<li>Arnold, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Affect in Language Learning. , (1999).</li><li>Egidi, G., Caramazza, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mood-dependent+integration+in+discourse+comprehension:+Happy+and+sad+moods+affect+consistency+processing+via+different+brain+networks.">Mood-dependent integration in discourse comprehension: Happy and sad moods affect consistency processing via different brain networks.</a> NeuroImage. 103, 20-32 (2014).</li><li>Hinojosa, J. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Negative+induced+mood+influences+word+production:+An+event-related+potentials+study+with+a+covert+picture+naming+task.">Negative induced mood influences word production: An event-related potentials study with a covert picture naming task.</a> Neuropsychologia. 95, 227-239 (2017).</li><li>Hinojosa, J. A., Moreno, E. M., Ferr&#233;, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Affective+neurolinguistics:+towards+a+framework+for+reconciling+language+and+emotion.">Affective neurolinguistics: towards a framework for reconciling language and emotion.</a> Language, Cognition and Neuroscience. , 1-27 (2019).</li><li>Kuperman, V., Estes, Z., Brysbaert, M., Warriner, A. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Emotion+and+language:+valence+and+arousal+affect+word+recognition.">Emotion and language: valence and arousal affect word recognition.</a> Journal of Experimental Psychology: General. 143 (3), 1065-1081 (2014).</li><li>Rodr&#237;guez-Ferreiro, J., Davies, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+graded+effect+of+valence+on+word+recognition+in+Spanish.">The graded effect of valence on word recognition in Spanish.</a> Journal of Experimental Psychology: Learning, Memory, and Cognition. , (2018).</li><li>Vinson, D., Ponari, M., Vigliocco, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=How+does+emotional+content+affect+lexical+processing.">How does emotional content affect lexical processing.</a> Cognition and Emotion. 28 (4), 737-746 (2014).</li><li>Kotz, S. 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A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Processing+words+with+emotional+connotation:+an+FMRI+study+of+time+course+and+laterality+in+rostral+frontal+and+retrosplenial+cortices.">Processing words with emotional connotation: an FMRI study of time course and laterality in rostral frontal and retrosplenial cortices.</a> Journal of Cognitive Neuroscience. 16 (2), 167-177 (2004).</li><li>Hinojosa, J. A., M&#233;ndez-B&#233;rtolo, C., Carreti&#233;, L., Pozo, M. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Emotion+modulates+language+production+during+covert+picture+naming.">Emotion modulates language production during covert picture naming.</a> Neuropsychologia. 48 (6), 1725-1734 (2010).</li><li>Larsen, K. 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I., Anwander, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+brain+differentiates+human+and+nonhuman+grammars:+Functional+localization+and+structural+connectivity.">The brain differentiates human and nonhuman grammars: Functional localization and structural connectivity.</a> Proceedings of the National Academy of Sciences of the United States of America. 103, 2458-2463 (2006).</li><li>Williams, J. N., Kuribara, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparing+a+nativist+and+emergentist+approach+to+the+initial+stage+of+SLA:+An+investigation+of+Japanese+scrambling.">Comparing a nativist and emergentist approach to the initial stage of SLA: An investigation of Japanese scrambling.</a> Lingua. 118, 522-553 (2008).</li><li>Grey, S., Williams, J. N., Rebuschat, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Individual+differences+in+incidental+language+learning:+Phonological+working+memory,+learning+styles,+and+personality.">Individual differences in incidental language learning: Phonological working memory, learning styles, and personality.</a> Learning and Individual Differences. 38, 44-53 (2015).</li><li>Williams, J. N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Learning+without+awareness.">Learning without awareness.</a> Studies in Second Language Acquisition. 27, 269-304 (2005).</li><li>Leung, J. H. C., Williams, J. N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+implicit+learning+of+mappings+between+forms+and+contextually+derived+meanings.">The implicit learning of mappings between forms and contextually derived meanings.</a> Studies in Second Language Acquisition. 33, 33-55 (2011).</li><li>Leung, J. H. C., Williams, J. N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Constraints+on+implicit+learning+of+grammatical+form-meaning+connections.">Constraints on implicit learning of grammatical form-meaning connections.</a> Language Learning. 62, 634-662 (2012).</li><li>Pratt, N. L., Kelly, S. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Emotional+states+influence+the+neural+processing+of+affective+language.">Emotional states influence the neural processing of affective language.</a> Social Neuroscience. 3 (3-4), 434-442 (2008).</li><li>Chwilla, D. J., Virgillito, D., Vissers, C. T. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+relationship+of+language+and+emotion:+N400+support+for+an+embodied+view+of+language+comprehension.">The relationship of language and emotion: N400 support for an embodied view of language comprehension.</a> Journal of Cognitive Neuroscience. 23 (9), 2400-2414 (2011).</li><li>Williams, J. N., Paciorek, A., Mackey, A., Marsden, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Indirect+tests+of+implicit+linguistic+knowledge.">Indirect tests of implicit linguistic knowledge.</a> Advancing Methodology and Practice: The IRIS Repository of Instruments for Research into Second Languages. , 25-42 (2016).</li><li>Rebuschat, P., Williams, J. N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Implicit+and+explicit+knowledge+in+second+language+acquisition.">Implicit and explicit knowledge in second language acquisition.</a> Applied Psycholinguistics. 33, 829-856 (2012).</li><li>Liu, X., Xu, X., Wang, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+effect+of+emotion+on+morphosyntactic+learning+in+foreign+language+learners.">The effect of emotion on morphosyntactic learning in foreign language learners.</a> PloS One. 13 (11), 0207592 (2018).</li><li>Bradley, M. M., Lang, P. 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The results indicate that participants rated their emotions to be significantly more positive after being exposed to the positively-valenced music. These subjects were significantly happier than the control group. This suggests that our emotion manipulation was successful. Participants in the positive-emotion group were found to be significantly less accurate and efficient than those in the control group. One possible reason is that participants employed an inductive strategy in grammar learning, resulting in a strong re...

Emotions play a crucial role in various cognitive activities such as perception, learning, reasoning, memorization, and problem solving. Because language learning requires attention, reasoning, and memorization, emotions may have significant influence on language learning outcomes1. Several prior studies have explored the effect of induced emotions on word production or text comprehension2,3, and have consistently found that emotion had a crucial influence on the two language processes. For example, Egidi and Caramazza found that positive emotion increased the sensitivity to inconsistency in text comprehension in the brain areas specific for inconsistency detection, whereas negative emotion increased the sensitivity to inconsistency in less specific areas2. Hinojosa et al. examined the effect of induced mood on word production and discovered that negative mood impaired the retrieval of phonological information during word production3. In spite of the evidence showing that emotions have a marked impact on text comprehension and word production, it is still not clear whether emotions affect grammar learning, one of the essential aspects of language learning. The present study aimed to explore the effect of learners&#39; emotional states on grammar learning.
Language and emotion are two primary components of human experience4. Their relationships have mostly been explored by studies in affective neurolinguistics. At the single word level, previous studies have consistently found that emotional features, such as arousal or valence, significantly affect the processing of individual words5,6,7. Specifically, some studies have identified a significant advantage for positive words5, and other studies have found an advantage for both positive and negative words7. Although some studies have reported an interaction between valence and arousal, a lack of significant interaction was reported in other research4. The picture is more complex at the level of sentence processing. Previous studies have explored issues concerning the interaction between emotional content and syntactic or semantic unification processes during sentence comprehension. Emotional information has been found to exert different influences on the processing of gender or number features4. Further, positive and negative emotion was connected with different agreement effects4. For instance, positive emotional features facilitated number agreement processing, whereas negative emotional features inhibited these processes4. At the semantic level, emotional features influenced semantic unification processes in both sentence and discourse contexts through the activation of the brain regions involved in single word processing and combinatorial semantic processes4. A review of the previous literature indicates that most prior research has focused on the effects of emotional information on the comprehension of words, sentences, and texts8,9, or the neural basis of emotional effects on language production10,11. However, how individuals&#39; affective states might influence language processing or learning has been largely overlooked.
The most frequently used approach to the studies of emotions in grammar learning is the artificial grammar learning paradigm. Several studies have used artificial grammar tasks to examine the effect of emotion on the learning of a new language12. First introduced by Reber in 196713, the artificial grammar learning paradigm is characterized by the use of non-meaningful materials, such as number strings or non-word letter strings, which are in fact generated by an underlying grammar. Researchers usually exposed participants in different emotional states (positive, neutral, or negative) to the number strings or letter strings presented either visually or audibly and measured their learning outcomes. Studies with the artificial grammar approach typically consist of a training session and a testing session. In the training session, participants are instructed to observe or memorize a list of symbol sequences that are generated from a finite state grammar. Participants are informed that the sequences follow a particular set of rules, but they are not given any details regarding these rules. In the testing session, participants are presented with new symbol sequences, some of which are grammatical and others are not. They are then required to judge whether the strings are grammatical or not. Artificial grammar tasks allow the instantiation of various theories of learning, such as rules, similarity, and associative learning theories14. This approach can effectively minimize the influence of lexical factors on the learning of grammatical rules, as artificial languages are made up of numbers, letters, or other meaningless symbols, rather than words in natural languages. However, many researchers have argued that the knowledge acquired in artificial grammar learning may represent statistical properties that are different from the features of natural grammar used by human beings15. Evidence from neurological studies shows that the grammars in natural languages are processed differently from the finite-state grammars used in artificial grammar learning tasks16,17. Therefore, artificial grammar learning tasks may not reflect the learning of human languages. Studies of the emotion effect on grammar learning using artificial grammars are more likely to reveal how emotion influences statistical learning, rather than the learning of natural grammars in human languages. It is not entirely clear whether findings from the meaningless stimuli can be generalized to foreign language learning.
The present study intended to adopt a semi-artificial language paradigm to investigate the effect of emotion on grammar learning. Semi-artificial language tasks were first introduced by Williams and Kuribara to examine language learning. A semi-artificial language is generated with the combination of lexicon in the learners&#39; native language and the grammar of a different language. An example of such language can be found in Williams and Kuribara&#39;s study18. Williams and Kuribara designed a novel semi-artificial language, Japlish, which followed the word order and case-marking rules of Japanese but used English vocabulary18. Sample Japlish sentences in their study are provided in Table 1.
<table border="1" fo:keep-together.within-page="1">
	<tbody>
		<tr>
			<td>Structure</td>
			<td>Examples</td>
		</tr>
		<tr>
			<td>SV</td>
			<td>Horse-ga when fell?</td>
		</tr>
		<tr>
			<td>SOV</td>
			<td>Pilot-ga that runway-o saw</td>
		</tr>
		<tr>
			<td>SIOV</td>
			<td>Student-ga dog-ni what-o offered?</td>
		</tr>
		<tr>
			<td>S when what-o V?</td>
			<td>Bill-ga when what-o sang?</td>
		</tr>
		<tr>
			<td>S who-ni what-o V?</td>
			<td>That doctor-ga who-ni what-o showed?</td>
		</tr>
		<tr>
			<td>S [SOV]V</td>
			<td>John-ga angrily Mary-ga that ring-o lost that said.</td>
		</tr>
		<tr>
			<td>OS[SV]V</td>
			<td>That disease-o vet-ga cow-ga have that declared.</td>
		</tr>
	</tbody>
</table>
Table 1: Sample sentences in a semi-artificial language. The sentences were generated with English lexis and Japanese syntax. The sentences in the table are from Williams and Kuribara&#39;s study18.
As shown in the table, although English words are used, they are combined into sentences in accordance with the Japanese word order and case-marking rules. The Japlish sentences are all verb-final and nouns are case-marked for subject (-ga), indirect object (-ni), or object (-o). A detailed description of Japlish can be found in Grey et al.&#39;s study19. Semi-artificial language tasks involve a training phase and a testing phase. During the training phase, participants are instructed to learn a new language, and in the testing phase, they are required to perform acceptability judgment tasks or sentence-picture matching tasks. The accuracy and reaction times (RTs) of their responses are recorded to assess their learning performance.
Semi-artificial language tasks have mainly three advantages: First, as semi-artificial languages are created using grammatical rules in a new language, the tasks can minimize the influence of prior knowledge of the structures as well as language transfer19. Second, the tasks enable us to control and manipulate the type and amount of exposure participants receive19. In this way, they allow for more accurate assessment of the learning effects. Finally, as the grammars used in semi-artificial language tasks are from human languages, the tasks allow us to measure how participants acquire natural grammars, rather than artificial ones. In this aspect, they are more advantageous than artificial grammar tasks in which sequences of numbers or letters are used instead of real words. The use of natural grammar makes us more confident to conclude that the findings obtained are applicable to natural language learning. Given that prior studies have demonstrated learning effects using the semi-artificial language paradigm20,21,22, it is a useful approach to investigating issues in language learning that are difficult to isolate in the complex context of natural language research. However, semi-artificial language tasks are only applicable to foreign languages that are structurally different from learners&#39; native languages. If the tested language is structurally similar to the learners&#39; native language, it might make the former indistinguishable from the latter.
Compared with the tasks using natural languages, semi-artificial language tasks allow for a more objective assessment of the effects of emotion on grammar learning. This is because words in natural languages are closely associated with specific grammatical functions. For example, inanimate nouns (e.g., desk, nail) are more likely to function as the patients of verbs. Thus, it is difficult to differentiate the performance of vocabulary learning from that of grammar learning because the two are interrelated and inseparable in natural languages. As emotions have been found to have vital influence on word processing23,24, they may have indirect influence on grammar learning. Therefore, it is not easy to clearly differentiate the effect of emotion on vocabulary learning from that on grammar learning. This problem can be easily solved in semi-artificial language tasks because these tasks allow for the separation of vocabulary from grammar, and thus enable us to identify the effect of emotion on grammar learning, without having to worry about the interference from lexical learning.
Although the semi-artificial language paradigm has been used in some studies to investigate linguistic knowledge in second language acquisition25,26, this approach has rarely been used to explore learners&#39; individual differences in emotional conditions in foreign language learning. In this study, we intended to explore how positive induced emotion influences grammar learning using a semi-artificial language. Findings from this study have important implications for foreign language teaching and learning.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>E-prime</td>
			<td>PST</td>
			<td>2.0.8.22</td>
			<td>Stimulus presentation software</td>
		</tr>
		<tr>
			<td>Computer</td>
			<td>N/A</td>
			<td>N/A</td>
			<td>Used to present stimuli and record subjects&#39; responses</td>
		</tr>
		<tr>
			<td>Self-Assessment Manikin (SAM)</td>
			<td>N/A</td>
			<td>N/A</td>
			<td>Used to assess subjects&#39; affective states. From Lang (1980)29</td>
		</tr>
	</tbody>
</table>

experimental paradigm for measuring the effect of induced emotion on grammar learning

Previous studies have found that emotion has significant influence on the learning of foreign language vocabulary and textual comprehension. However, little attention has been given to the effect of induced emotion on grammar learning. This research examined the influence of positive induced emotion on the learning of Japanese grammatical rules among a group of learners with Chinese as their native language, using a semi-artificial language (i.e. Chipanese), which combines the grammatical rules of Japanese and the vocabulary of Chinese. Music was used to invoke positive emotional conditions in participants. Participants were required to learn Chipanese sentences in a training session through practice and then a grammaticality judgment task was administered to measure learning outcomes. We found that participants in positive emotional states performed less accurately and efficiently than those in the control group. The findings suggest that the protocol is effective in identifying the effect of positive induced emotion on grammar learning. The implications of this experimental paradigm for investigating foreign language learning are discussed.

The aim of this study is to explore the effect of positive induced emotion on foreign language grammar learning. For this purpose, two groups of participants were recruited to participate in the experiment, including a positive-emotion group (15 female, Mage = 20.20, age range: 18&#8211;27) and a control group (16 female, Mage = 20.33, age range: 18&#8211;26). Each group consisted of 30 participants. The two groups did not differ significantly in age, t (58) = -0.215, ...

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Experimental Paradigm for Measuring the Effect of Induced Emotion on Grammar Learning

Here, we present a protocol to measure the effect of positive induced emotion on grammar learning in foreign language learners using a semi-artificial language that integrates the grammatical rules of a foreign language with the lexicon of the learners&#39; native language.

Previous studies have found that emotion has significant influence on the learning of foreign language vocabulary and textual comprehension. However, ...

This method could provide important insight into how learners acquire foreign language grammar, as well as about the rule of individual differences in affective states in grammar learning. This technique separates vocabulary from grammar. So it allows us to assess the effects of induced emotion of grammar learning without having to worry about interference from lexical learning.Have the participant sit in front of a computer and ask the participant to read and sign the written consent forms. Next, give the participant the pencil and paper version of the self-assessment Manikin pictorial rating scale and ask the participant to use a pencil to rate their emotion by marking the corresponding manikin. Have the participants in the experimental group listen to positively valenced music through headphones for 10 minutes.At the end of the emotion induction period, ask the participant to rate their emotional state on a new self-assessment Manikin scale. Before beginning the training task, present written instructions for the task on the screen of the computer in the native language of the participant. The instructions should read, Welcome to our experiment.In this experiment, you will be required to learn a novel language that contains native language words and new grammar. When you are ready, press any key to proceed to the experiment. After the participant has pressed a key, a new set of instructions should appear.Next, you will see some sentences. Please read them carefully and decide whether they are grammatically correct or not. Press one if the sentences are grammatical and zero if they are ungrammatical.After each response you will receive feedback, correct or incorrect, and the correct sentence will be presented. Press any key to proceed to the learning task. The participant should then judge the grammatical acceptability of the sentences on the computer screen as directed and the feedback should be presented on the screen after the participant's response followed by the correct sentence.When all of the trials have been completed, the text, The learning task is finished, should appear on the screen. At the end of the training, give the participant the pencil and paper version of the self-assessment Manikin scale and ask them to rate their emotional condition. When the training task is complete, present the testing session instructions on the computer screen.The instructions should read, Please continue to answer questions similar to those observed during the training. Decide whether the grammatical structures of the following sentences are correct. Press one if you think they are correct and press zero if you think they are incorrect.Press any key to start the experiment. Have the participant read the sentences shown on the screen and judge whether the sentence's structures are grammatical correct as instructed. When all of the trials have been completed, text should appear on the screen that reads, The end.Thank you for participating. Then ask the participant to fill out a questionnaire about their demographic details. In this representative analysis, participants in the positive emotion group reported being significantly happier than those in the control group, indicating a successful emotion induction.Further, the emotional states of the participants in each group were sustained during the training phase. Assessment of the mean accuracy of the grammar learning by the two groups revealed a significant affective emotion and sentence type with the participants in the control group performing significantly more accurately than those in the positive emotion condition group. In addition, subject indirect object direct object verb and subject object verb subject verb structures were comprehended less accurately than subject object verb and object subject verb subject verb structures.Reaction time analysis indicating that there was a significant affective emotion and sentence type with the participants in the control group reacting faster than those in the positive emotional state group. Subject object verb structures were recognized faster than the other three structures and subject indirect object direct object verb structures were recognized more slowly than other structures. It is essential to design a semi-artificial language that contains the lexicon of the participant's native language and the grammar of the tested foreign language.This protocol can also be used to explore the effects of other affective variables on grammar learning, such as anxiety or motivation.

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