Individual differences in semantic short-term memory capacity and reading comprehension
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湖南师范大学硕士学位论文英汉句子基本结构的逻辑关系的比姓名:***申请学位级别:硕士专业:英语语言文学指导教师:***20011001摘要f语言是人类认知现实,进行交流的工具。
我们每天使用语言,我们蛀活在一个语言文字的世界里,时时刻刻都有人在说话、写字或阅读。
语言对人类来说实在是不可缺的,我们的生活越来越有赖于正确而高效地运用语言。
这就是语言的共性(普遍性)。
但我们知道世界上有上千种语言,不同的民族使用的是不同的语言,这就是语言的个性(特殊性)。
语言的差异并没有给人类的交流带来障碍,在人类的成功交流的后面是什么在起作用?这就是撰写本文的目的。
、夕撰并极其语义表现的一致性来探索语言的普遍性及其人类的翻译活动的可译性和忠实性。
f人是有理性的,思维是每一个具有正常大脑的人都有的一种能力,、具有全人类的性质。
思维是理性的、抽象的,语言是思维的物质外壳,是思维的表现形式,是反映人类思维过程和客观实际的。
大量的研究事实证明:说不同语言的人地们对客观世界的认知,如果正确的话,是没有什么差异的。
无论何种肤色或何种民族的人,他们的逻辑思维必须反映事物的客观规律性,砝客卿疼姆的认识才会有统一性,不同民族的语言交流才能成功:j’’~属维的共性使得“普遍语法”存在于人脑中,表现了人类语言的实质,反映了人在掌握语言过莽起够具有的一个普遍共同的基础。
这就是语言共性论的基础。
吵/f,我们首先阐述了当代美国著名语言学家chomsky的观点,他根据普遍语法创立了转换生成语法(TG语法)。
按照转换生成语法理论来分析,句子的基本句型是由NP十VP(即:s—NP+vP)的基本结构构成。
每个句子有两种结构:即表层结构和深层结构。
一个句子从深层结构到表层结构的转换意味着从内容到形式的转换。
句子的形式是由句子的表层结构表达的,句子的意义是由其深层结构表达的。
表层结构反映语言的差异性,深层结构反映语言的相似性。
一个句子的语义表现(即:一个命题)是语义规则在深层结构的运过程)以及这个过程中参与者(施事和受事)、属性、环境之间的关系。
[Individual,differences,in,English,Learning,Strategies]differences怎么读Abstract:Some learners’ personal factors,such asgender, major, motivation and language proficiency,influence the use of languagelearning strategies. This paper reports the results of a survey study which investigates the individual differences and the employment of English learning strategies, examines the association between enjoyment and strategy use, motivationand strategy use, gender and strategy use, major and strategy use, English proficiencyand strategy use. Key words:Individual differences Learning strategies Englishlearning I Background of Research Since the early seventies, researchconcerns in the field of L2 teaching and learning have shifted from methods of teachingto learner characteristics and their influence on the process of acquiring an L2.It has been acknowledged that L2 acquisition is a complex process involving many interrelated variables, the most obvious being learning processes, learners”cognitive styles, affective factors and learning settings. Researchers realize thatfocusing research on teaching methods alone cannot draw on the latest achievementsin the relevant fields, nor can it cover all the various factors concerned (Stern,1983). Instead of seeking the best method as the only way to facilitate L2 acquisition,more and more researchers have initiated studies on the learner. They have been payingmore attention to individual differences in L2 acquisition. II Instruments and Procedures The instruments used in the quantitative part of the study were theadapted SILL preceded by a questionnaire and a national English proficiency test.In December,2009, After filling out the SILL questionnaires, the students all tookpart in College English Test (CET) Brand 4, a nation-wide, standardized English testtaken each year by thousands of university non-English majors across China at theend of their second year. This is a general proficiency test, rather than acurriculum-specific achievement test. Like all English tests in China, it testsstudents” English proficiency level in reading, listening, writing, and vocabulary,but no speaking. It consists of five parts. The first part tests students” listening comprehension questions. The second part is made up of reading passages with comprehension questions. Part 3 is integrated tests including a cloze test. The finalpart in this test is a piece of writing, in which students are given a title andrequired to write a 100~120 word passage. III Data analysis Data analysisis not a simple description of the data collected but a process by which I can bring interpretation to the data( Powney and Watts, 1987).Using SPSS11.0 , I first obtainedthe subjects” background information and descriptive statistics (means, standard deviation, frequency) to see the overall patterns of strategy use by the students.Then, I performed ANOVA to determine the effects of certain background variables onlearners” mean strategy use across the entire SILL and on the six SILL categories.To determine significance throughout the study, I used the standard of p In distinguishing frequency of strategy use for various learning groups,Oxford(1990:291) defines a mean of all subjects in the range of 3.5-5.0 on a SILLitem as high use of that strategy, 2.5-3.4 medium use, and 1.0-2.4 low use. The overall SILL mean in the present study was 3.01, with a standard deviation of 1.18. This means that, in the EFL setting where this study was located, the Chinese subjects used LLS at medium frequency. Table 1 lists the overall SILL means and standard deviations for the background variables. Table 1Overall mean scores of frequency of strategy use and variation in overall strategy use (ANOVA) for subjects by enjoyment, motivation, English proficiency, major field of study, gender. IV Conclusion The results show that the students in this study showed significant individual differences in their strategy use. Although the individual students varied tremendously from each other in their strategy use, they shared some special characteristics in selecting learning strategies for their English learning. As all of them learnt English as a foreign language in the Chinese context, they used LLS at medium frequency. They showed high use of affective strategies, but low use of social strategies. Their general patterns of strategy use indicate that they preferred the learning strategies related to examination preparations, analysis of grammatical rules and linguistic details, repetition, review and respect for teacher”s authority, but ignored the learning strategies leading to the improvement of communicative competence. The findings presented , organized in terms of overall strategy, strategy categories and individual strategies, are descriptive in nature. They provided the basis for a deeper analysis in regard to the influences of various factors on the students’ strategy use . References: [1]Chamot, A. The Learning Strategies of ESL Students [M]. Englewood Cliffs,NJ: Prentice Hall,1987.[2]Cohen, A. D. Strategies in Learning and Using a Second Language [M].New York:Addison Wesley Longman Inc,1998. [3]Ellis, R. The Study of Second Language Acquisition [M]. Oxford: Oxford University Press,1994.532-546. [4]O’Malley,J.M.etal.Learning strategy application with students of English as a second language[J].TESOL Quarterly ,1985,19 (3):582-584. 本文系山东省教育科学规划课题“高职生英语词汇学习策略培训的综合途径研究”阶段性成果之一。
individual differences造句篇一:《不一样的我们:谈谈个体差异(individual differences)》我呀,在我们班上可算是见识到了啥叫“individual differences”,也就是个体差异啦。
我们班有个叫小明的同学,他就像一只小猴子似的,整天蹦蹦跳跳的,精力超级旺盛。
不管是课间休息还是体育课,他总是跑来跑去,好像有着用不完的劲儿。
有一次,学校组织爬山活动,小明那可真是一马当先啊。
他蹭蹭蹭地就往山上爬,就像脚底装了弹簧一样。
我们在后面气喘吁吁地跟着,他还时不时回头喊:“你们快点呀,这山可好玩啦!”再看看我的同桌小花,她就像一只慢悠悠的小蜗牛。
做什么事情都是不慌不忙的。
上课的时候,老师提问,她总是要想好久才会举手回答。
有一回,老师让我们在课堂上写一篇作文,大家都开始奋笔疾书,我都写了一大半了,小花还在那里咬着笔头,思考着怎么开头呢。
我就忍不住问她:“小花,你咋这么慢呀?”小花却说:“我得想好了再写,不然写出来不好看。
”这和小明那种风风火火的性格可真是差太多了。
还有小刚呢,他简直就是个数学小天才。
那些数学难题在他眼里就像一个个小玩具,他轻轻松松就能把它们搞定。
每次数学考试,他都能拿到很高的分数。
有一次,数学老师在黑板上写了一道超级难的奥数题,我们大家都愁眉苦脸的,感觉脑袋都要想破了。
小刚呢,眼睛一亮,拿着笔在本子上算了几下,然后就举手说:“老师,我算出来了!”我们都像看外星人一样看着他,心想:这脑子是怎么长的呀?我呢,我觉得我就像一只小百灵鸟。
我特别喜欢唱歌,只要一有空闲的时间,我就会哼起小曲儿来。
在学校的文艺表演上,我站在舞台上唱歌,感觉自己就像一颗闪闪发光的小星星。
我可不像小刚对数学那么痴迷,也不像小明那么爱动,更不像小花那么慢悠悠的。
你看,我们这几个人是不是有很大的不同呢?这就是个体差异呀。
这就好比花园里的花,有红的、有蓝的、有高的、有矮的。
每一朵花都有自己的特点,每一个人也都有自己独特的地方。
Advances in Social Sciences 社会科学前沿, 2017, 6(12), 1493-1500Published Online December 2017 in Hans. /journal/asshttps:///10.12677/ass.2017.612209Individual Differences in Adolescents’Creative Scientific Problem Finding:The Predictive Effect of PersonalityHaiyan LiBeijing Academy of Educational Sciences, BeijingReceived: Nov. 20th, 2017; accepted: Nov. 30th, 2017; published: Dec. 7th, 2017AbstractWith the method of questionnaire survey, this paper explores the personality factors behind indi-vidual differences on Adolescents’ Creative Scientific Problem Finding. The results showed that: there were significant differences on CSPF of different groups in Extraversion, Conscientiousness, Openness; Openness has a significant positive effect on Creative Scientific Problem Finding. The results show that the personality of adolescents’ is associated with Creative Scientific Problem Finding; in addition to emphasis on intelligent culture in education, we have to be concerned about personality education, which is the need of the healthy personality development of adoles-cents, but also is the inevitable choice of the modern school for future-oriented community.KeywordsCreative Scientific Problem Finding, Personality, Adolescents青少年创造性问题提出能力的个体差异:谈人格的预测效应李海燕北京教育科学研究院,北京收稿日期:2017年11月20日;录用日期:2017年11月30日;发布日期:2017年12月7日摘要本文通过问卷法测查青少年创造性科学问题提出能力的表现,并探索个体差异背后的人格因素。
理解个体差异的素材英语作文Understanding Individual Differences.Humans are a diverse species, exhibiting a wide range of characteristics, abilities, and experiences. These variations, collectively known as individual differences, are a fundamental aspect of human nature and have significant implications for our interactions, relationships, and development.One of the most prominent dimensions of individual differences is personality. Personality traits are stable characteristics that shape an individual's thoughts, feelings, and behaviors. The Five Factor Model of personality, also known as the "Big Five," identifies five broad personality dimensions: Openness to Experience, Conscientiousness, Extraversion, Agreeableness, and Neuroticism. These traits vary in intensity across individuals, contributing to unique personality profiles.Intelligence is another key aspect of individual differences. Intelligence is typically measured by IQ tests, which assess cognitive abilities such as problem-solving, verbal comprehension, and perceptual reasoning. While IQ scores provide a general indication of intellectual potential, they do not fully capture the complex nature of intelligence. Other forms of intelligence, such asemotional intelligence and creativity, also playsignificant roles in shaping individual capabilities.Cognitive style refers to the ways in which individuals process information and make decisions. Some people preferto approach problems analytically, while others rely on intuition. Some are highly structured in their thinking, while others are more flexible and open-minded. Understanding cognitive style can help individuals optimize their learning and problem-solving strategies.Cultural background is a major source of individual differences. Culture shapes values, beliefs, norms, and behaviors. Individuals from different cultures may exhibit distinct communication styles, social customs, andattitudes towards conflict. Cultural sensitivity is essential for effective communication and collaboration across cultural boundaries.Gender and sex also contribute to individual differences. Biological and cultural factors influence the development of gender identity and roles. While there is considerable overlap in the traits and abilities of men and women, on average, there are some differences in cognitive abilities, risk-taking behaviors, and social preferences.The concept of individual differences is not limited to these specific dimensions. It encompasses the full range of human characteristics, including physical attributes, motivations, interests, and values. Understanding these differences is crucial for developing effective policies, designing inclusive environments, and fostering harmonious relationships.Recognizing individual differences has several important benefits. First, it promotes empathy and understanding. By appreciating the unique perspectives andexperiences of others, we can develop a broader and more inclusive worldview. Second, it helps us tailor interventions and support systems to meet the specific needs of individuals. Whether in education, healthcare, or social services, customized approaches can lead to better outcomes.Third, understanding individual differences allows us to celebrate diversity and harness the strengths of all individuals. By valuing the differences that make each person unique, we can create a more vibrant and equitable society. Finally, it fosters self-awareness and personal growth. By understanding our own unique strengths and weaknesses, we can develop strategies to maximize our potential and achieve our goals.In summary, individual differences are a fundamental aspect of human nature that shape our lives in countless ways. By understanding these differences, we can promote empathy, tailor interventions, celebrate diversity, and foster self-growth. Embracing the full spectrum of humanvariation is essential for creating a truly inclusive and equitable society.。
Individual differences in semantic short-term memory capacity and reading comprehensionHenk J.Haarmann,a,*Eddy J.Davelaar,b and Marius Usher baDepartment of Hearing and Speech Sciences,University of Maryland,College Park,MD 20742,USAbSchool of Psychology,Birkbeck College,University of London,London WC1E 7HX,UKReceived 26November 2001;revision received 25February 2002AbstractWe report three correlation studies,which investigate the hypothesis that individual differences in the capacity of a semantic short-term memory (STM)component in working memory (WM)predict performance on complex language tasks.To measure the capacity of semantic STM,we devised a storage-only measure,the conceptual span,which makes use of a category-cued recall procedure.In the first two studies,where the conceptual span was administered with randomized words (not blocked by categories),we found that conceptual span predicted single-sentence and text comprehension,semantic anomaly detection and verbal problem solving,explaining unique variance beyond non-word and word span.In some cases,the conceptual span explained unique variance beyond the reading span.Conceptual span correlated better with verbal problem solving than reading span,suggesting that a storage-only measure can outperform a storage-plus-processing measure.In Study 3,the conceptual span was administered with semantically clustered lists.The clustered span correlated with the comprehension measures as well as the non-clustered span,in-dicating that the critical process is memory maintenance and not semantic clustering.Moreover,we found an inter-action between subjects Õperformance on the conceptual span and the effect of the distance between critical words in anomaly detection,supporting the proposal that semantic STM maintains unintegrated word meanings.Ó2002Elsevier Science (USA).All rights reserved.Keywords:Short term memory;Working memory;Reading comprehension;Individual differences;Conceptual span;Reading spanIt is widely recognized that a limited-capacity work-ing memory (WM)system plays an important role in complex cognition,supporting both the temporary storage and processing of information (for a review see Kintsch,Healy,Hegarty,Pennington,&Salthouse,1999).A seminal study by Daneman and Carpenter (1980)demonstrated the importance of WM in the do-main of language processing.Its major finding was that a storage-plus-processing measure of WM,the reading span ,predicted accuracy of text comprehension (see alsoBaddeley,Logie,Nimmo-Smith,&Brereton,1985;Budd,Whitney,&Turley,1995;Daneman &Carpenter,1983;Dixon,Le Fevre,&Twilley,1989;Engle,Cantor,&Carullo,1992;LaPointe &Engle,1990;Masson &Miller,1983),while a storage-only measure,the word span ,did not (see also Turner &Engle,1989).Moreover,when a statistically significant correlation between word span and comprehension is obtained,it tends to be smaller than the correlation between reading span and comprehension (LaPointe &Engle,1990).The reading span test determines the number of sentence-final words a person can recall immediately after reading aloud a set of sentences and thus emphasizes both storage and processing of words.By contrast,the word span is a storage-only measure,which determines the numberofJournal of Memory and Language 48(2003)320–345/locate/jmlJournal of Memory and Language*Corresponding author.Fax:1-301-314-2023.E-mail addresses:hhaarmann@ (H.J.Haar-mann), e.davelaar@ (E.J.Davelaar),her@ (her).0749-596X/02/$-see front matter Ó2002Elsevier Science (USA).All rights reserved.PII:S 0749-596X (02)00506-5words a person can recall in exact serial order immedi-ately after their presentation.Consistent with the WM interpretation of the reading span test,Daneman and Carpenter(1980)found that the ability of low span readers to answer a question about the referent of a pronoun showed a marked deterioration when the number of sentences intervening between the referent and the pronoun was increased,while no such effect was present for high span readers.Furthermore,reading span is a good predictor of word reading times in sen-tence comprehension(for a review see Just&Carpenter, 1992;Miyake,Just,&Carpenter,1994b).While the correlation between comprehension and reading span is well established,its WM interpretation has been subject to debate(Baddeley et al.,1985;Dan-eman&Merikle,1996).Jackson and McClelland(1979) found that listening comprehension is one of the most important predictors of reading comprehension.To-gether with a measure of letter matching it predicted 77%of the variance.Citing this result,Baddeley et al. (1985)asked‘‘How should the correlation between comprehension and working memory span be inter-preted?’’and suggested thatThe original Daneman and Carpenter result was open toa range of interpretations,from the strong suggestion thattheir task was a measure of the capacity of a general working memory system,to the relatively weak interpre-tation that since working memory span itself depended on comprehension,that they were basically replicating the observation of Jackson and McClelland that listening comprehension was the best predictor of reading compre-hension(Baddeley et al.,1985,pp.129–130).Thus,it seemed possible that the correlation between comprehension and reading span was somewhat trivial, that is,due to a great deal of overlap between the two tasks,in particular,their common sentence processing component.This interpretation was further discussed by Daneman and Merikle(1996)who rephrased it as:‘‘sentence comprehension(reading span...)correlates with paragraph comprehension(the criterion comprehen-sion tests)’’(p.424).Indeed,Daneman and Carpenter (1980)suggested that the inclusion of a sentence pro-cessing task in both reading span and comprehension may be crucial to the ability of the reading span to predict comprehension.In particular,they suggested that in both tasks the temporary storage of verbal in-formation could have been worse for poor readers who had to devote some of their limited WM resources to compensate for inefficient reading processes.Subsequent research has ruled out this weak inter-pretation of the correlation between comprehension and reading span and has provided support for the stronger WM interpretation(Conway&Engle,1996;Daneman& Merikle,1996;Engle et al.,1992;Turner&Engle,1989). Turner and Engle(1989)found that the background task of the complex span measure does not have to involve sentence processing in order to predict reading compre-hension.They found that operation span predicts com-prehension as well as reading span.Operation span measures the number of words or digits a person can retain while verifying a sequence of arithmetic problems presented in alternation with the to-be-retained words or digits.More generally,Daneman and Merikle(1996) concluded from a meta-analysis of data from77studies that complex span measures,which include a storage and processing component(e.g.,reading span,operation span),predict comprehension better than storage-only measures(e.g.,word span,digit span),even if the processing component of the complex span task does not involve manipulation of words and sentences.Further-more,both reading span and operation span still predict comprehension,but to a lesser extent,when individual differences in processing efficiency are statistically con-trolled(Conway&Engle,1996;Engle et al.,1992).This finding makes it unlikely that individual differences in complex span are solely due to inter-subject variation in the degree to which a constant capacity is allocated to compensate for differences in processing efficiency. Instead,such differences appear to reflect differences in the capacity of a WM system that supports both storage and processing(Just&Carpenter,1992).A shared assumption of all current models of WM is that it is a multi-component system(for a review see Kintsch et al.,1999).However,it is currently not well understood in what component of the WM system in-dividual capacity differences predicting comprehension reside.One possibility is that there are individual dif-ferences in the capacity of a WM component that is crucial for dual tasking,that is,the ability to coordinate the performance of two tasks.For example,it has been suggested that individual differences in complex span performance could reflect differences in capacity to al-ternate attention between different tasks(Kane&Engle, 2000).This view correctly predicts that complex span measures(reading span,operation span)are better pre-dictors of comprehension than simple span measures (word span,digit span),because the former but not the latter type of task involves a dual-task component.It is nevertheless possible that a storage component plays also a role in predicting comprehension and that the impact of this factor has been underestimated,be-cause most of the studies relied on a phonological measures of span(digit/word span using serial order recall).Recently a number of authors have suggested that the storage of verbal information is supported not only by a phonological short-term memory(STM) (Baddeley,1986)but also by a semantic STM(Haar-mann,Cameron,&Ruchkin,in press;Haarmann& Usher,2001;Hanten&Martin,2000;Martin&Freed-man,2001;Martin&Romani,1994;Martin,Saffran,& Dell,1996;Martin,Shelton,&Yaffee,1994;Potter, 1993;Romani&Martin,1999).In particular,a series ofH.J.Haarmann et al./Journal of Memory and Language48(2003)320–345321neuropsychological studies by R.C.Martin and her colleagues has provided strong evidence for separate phonological and semantic STM components in WM (Hanten&Martin,2000;Martin&Freedman,2001; Martin&Romani,1994;Martin et al.,1994;Romani& Martin,1999).Across a series of immediate recall tasks, two patients, E.A.and A.B.,showed evidence for a double dissociation between phonological and semantic STM impairment(Martin et al.,1994).While the per-formance of E.A.indicated greater phonological than semantic STM deficit,A.B.showed the opposite pattern of deficit.For example,E.A.Õs performance on an im-mediate probed recognition task was markedly lower with rhyme probes than with semantic category probes, while A.B.showed the reverse pattern.Unlike E.A., A.B.also showed a normal word length effect(i.e.,better recall for short than long words)and a normal modality effect(i.e.,better recall with spoken than written pre-sentation),indicating a relatively preserved phonological STM system.Also,unlike E.A.,A.B.did not show a normal lexicality effect(i.e.,better recall of words than non-words),which suggests a semantic STM deficit (Martin et al.,1994).Additional evidence for a semantic STM comes from functional neuro-imaging studies,which found that the dorso-lateral prefrontal cortex(DL-PFC)is activated by a semantic but not by a phonological working memory task with identical response demands(Crosson et al., 1999;Gabrieli,Poldrack,&Desmond,1998).This finding suggests that the DL-PFC may help to sustain the activation of semantically-sensitive item representa-tions(Haarmann&Usher,2001;Usher&Cohen,1999). While semantic effects in STM have been demonstrated long ago(Raser,1972;Shulman,1972),they have been typically attributed to LTM contributions to recall (Baddeley,1972;Crowder,1979).Recently however, Haarmann and Usher(2001)reported semantic effects in immediate recall that cannot be attributed to LTM contributions.Pairs of weak semantic associates were better recalled at recency positions when they were close together in a list than when they were far apart and this semantic-separation effect was much larger in immediate recall than in delayed recall.In addition,Haarmann and Usher(2001)found that the semantic separation effect in immediate recall is still obtained and of similar magni-tude when encoding in phonological STM is prevented through articulatory suppression(Baddeley,1986).They therefore argued that the effect arose in semantic STM, in line with the neuropsychological evidence for such a WM component(Martin&Freedman,2001).Accordingly,we believe that there is now compelling evidence that,while phonological STM stores phono-logically decaying traces that are refreshed through subvocal rehearsal,semantic STM stores lexical-semantic item representations(i.e.,word meanings)that are actively maintained until they can be integrated into a meaning relation with words that occur later in the sentence(Gunter,Jackson,&Mulder,1995;Haarmann et al.,in press;Miyake et al.,1994b).Moreover,while neuropsychological dissociations indicate that an intact phonological STM is not crucial for on-line sentence comprehension(Butterworth,Campbell,&Howard, 1986;Caplan&Waters,1990,1999;Martin,1990; Martin&Romani,1994),the semantic component seems to play an important role in this process.The larger an individualÕs semantic STM capacity,the better the chances the meaning of a to-be-integrated word is maintained during the processing of words that inter-vene between it and words with which it is to be inte-grated(see Haarmann,Just,&Carpenter,1997,for a computational model).Thus,we expect semantic STM to be a better and more reliable predictor of compre-hension than phonological STM.This expectation is not necessarily at odds with the observation that storage-only measures(i.e.,word span and digit span)are poor predictors of comprehension(Daneman&Merikle, 1996),because the previously used storage-only mea-sures rely primarily on phonological STM(Baddeley, 1986)and may not rely much on semantic STM. Conceptual span testIn the present study,we used a category cued-recall test as a relative index of the capacity of the semantic STM component of WM.Since this system supports the maintenance of concepts associated with words,we will refer to the category-cued recall test as the‘‘conceptual span’’test.On each trial in the test,participants silently read a randomly ordered list of nine words,consisting of nouns in three different semantic categories with three nouns per category.Immediately following the presen-tation of the last word,the name of one of the three categories appears and participants attempt to recall aloud all three words in that category(e.g.,lamp,pear, tiger,apple,grape,elephant,horse,fax,phone,FRUIT? Correct answer:apple,pear,grape).Their score is the average number of words they could recall out of three words across a series of such trials.The conceptual span test was designed so as to minimize the contribution of LTM to task performance and maximally engage STM.First,the words are pre-sented at a relatively fast rate(i.e.,one word per second) in order to minimize participantsÕability to encode the items into a script-type representation in LTM and thereby engage their STM system to a larger extent (Cowan,2001;Haarmann&Usher,2001).This pre-sentation rate is thought to be fast enough to enable semantic encoding of individual words in semantic STM (Potter,1993).Second,participants read all words twice immediately prior to the start of the test,and are pre-sented the word materials during the test from afixed322H.J.Haarmann et al./Journal of Memory and Language48(2003)320–345word pool.Such repeated exposure is likely to induce proactive interference(PI),which affects retrieval from LTM more than from STM(Craik&Birtwistle,1971; Halford,Maybery,&Bain,1988)and which may, therefore,help to promote the use of STM rather than LTM in the conceptual span test.Following Cowan (1999,2001),we regard STM as the capacity-limited, activated part of LTM and assume that PI affects re-trieval of inactive representations in LTM.Investigating the role of the semantic STM compo-nent of WM for comprehension by means of the con-ceptual span test has several advantages.First,the test does not include a dual-task requirement.As a result, positive correlations between conceptual span and comprehension cannot be attributed to individual dif-ferences in the ability to perform a dual-task or,alter-natively,to an individualÕs willingness to shift attention away from the secondary processing task to the primary storage task(Waters&Caplan,1996).In addition,since the conceptual span test does not involve any sentence processing,correlations between conceptual span and comprehension accuracy cannot be attributed to indi-vidual differences in sentence processing efficiency, which might arise for example at a non-semantic,syn-tactic level and which may not be correlated with indi-vidual differences in semantic STM capacity.The latter possibility is consistent with thefinding of a double dissociation between syntactic judgment ability and se-mantic STM deficit in brain-damaged patients(Martin &Romani,1994).Furthermore,the use of a category cued recall procedure is likely to engage semantic STM and minimize the contribution of phonological STM and its sub-vocal rehearsal component.The latter is suggested by the lack of a word length effect in category-cued recall(Haarmann&Usher,2001)and the relative preservation of category-cued recognition performance in patients with a severe phonological but mild semantic STM deficit(Martin et al.,1994).Moreover,the preex-posure to,and repeated use of the words in the con-ceptual test makes it unlikely that obtained performance differences reflect inter-individual variation in the effi-ciency of word encoding processes.We present here three correlation studies with col-lege-age adults,whose major aim was to measure the contribution of a semantic STM component of WM to language comprehension.Thefirst two studies included the conceptual span test,the reading span test,a series of span tests and a series of comprehension tests.The third study was designed to test the alternative view that the conceptual span test measures clustering ability1instead of semantic STM capacity.Moreover,the third study was designed to test the hypothesis that semantic STM maintains unintegrated word meanings to support their on-line integration during sentence processing(Martin &Romani,1994).Given the capacity-limited nature of semantic STM,this hypothesis predicts an interaction between subjectsÕconceptual span performance and the effect of the distance between critical words in on-line anomaly detection,such that participants with a low conceptual span show larger distance effects than par-ticipants with high conceptual span.Study1Study1included the conceptual span test,the read-ing span test,the word span test,a sentence compre-hension test,and a text comprehension test.In accordance with previous results(Daneman&Carpen-ter,1980;LaPointe&Engle,1990;Turner&Engle, 1989),we expected reading span to be a better predictor of sentence and text comprehension than word span. Furthermore,we reasoned that the conceptual span test provides a better measure of the semantic STM com-ponent in WM than word span and that this component may be an important determinant of the performance on the reading span test.We therefore expected conceptual span to predict sentence and text comprehension better than word span and possibly as well as reading span.We also investigated whether conceptual span accounts for unique variance in text comprehension above and beyond the variance contributed by reading span.Such a finding could indicate that conceptual span provides a more sensitive measure of semantic STM than reading span.Alternatively,such afinding could indicate that conceptual span measures semantic STM,whereas reading span measures some other ability,such as, domain-specific sentence processing skills or ability to control attention(Kane&Engle,2000;Kane,Bleckley, Conway,&Engle,2001).MethodParticipants.Sixty-six undergraduate students from the University of Maryland at College Park,all native speakers of English,participated.They received either a seven-dollar payment or extra-credit for their partici-pation.TestsEach participant was tested individually and per-formedfive tests,given in the same order,namely, conceptual span,reading span,word span,text com-prehension,and sentence comprehension.A test session lasted about1h and15min.Three participants did not perform thefinal sentence comprehension test because of time constraints.Presentation of all tests was visual and computer controlled.1We would like to thank Nelson Cowan for pointing outthis alternative view to us.H.J.Haarmann et al./Journal of Memory and Language48(2003)320–3453231.Conceptual span.On each trial,participants si-lently read a sequence of nine nouns(in small letters) followed by a category name(in capital letters),pre-sented at a computer-controlled rate of1word/s.The nine words consisted of three groups of three nouns, with each group belonging to a different semantic cat-egory,and were presented in a random order.Partici-pants were instructed to try to recall aloud the three nouns in the named category in any order(e.g.,lamp, pear,tiger,apple,grape,elephant,horse,fax,phone FRUIT?Answer:pear grape apple).The materials for the test came from a pool of48nouns with eight nouns in each of six semantic categories.The assignment of categories and nouns within categories to a trial se-quence and the selection of the cued category within a trial sequence was random and with replacement.Prior to the test participants were shown each of the eight categories and its nouns and asked to read aloud the nouns while thinking of how itfit within the category. They did this twice in succession.The actual test con-sisted of two practice trials and16test trials.A par-ticipantÕs conceptual span was defined as the number of words recalled across the16test trials(the maximum possible score was48).2.Reading span.This test was an adapted version of the Daneman and Carpenter(1980)reading span test. On each trial,participants read aloud a set of sentences, presented one sentence at a time on a display monitor. As soon as the participantsfinished reading the last word in a sentence,the experimenter pushed a key that led to the display of the next sentence in the set.At the end of each set a question mark appeared and partici-pants attempted to recall aloud all the sentence-final words in the set in their order of presentation.The set size varied from two tofive sentences and there were two trials at each set size.A particular sentence occurred only once in the test,always ended in a concrete noun, and could be from13to16words long.(An example of a trial at set size2is Josh wanted tofinish his homework, but he forgot to go to the store.Chris liked being a sheriff, but he didn’t like to wear the hat.Answer:store,hat.)The reading span test started with two practice trials at set size2and the actual test began at this set size.Each time a participant answered one or two trials at a particular set size correct,the set size was increased with one sen-tence and participants were warned that such an increase would take place.Testing was discontinued if a partici-pant got zero trials correct at a particular set size.A correct trial was one in which all the sentence-final words in a sequence of sentences were recalled in their order of presentation.A participantÕs reading span was defined as the total number of correct trials(the maxi-mum possible score was10).3.Word span.On each trial,participants read alouda set of words,presented at a computer-controlled rate of one word/s.Immediately after the offset of the last word,a question mark appeared and participants at-tempted to recall aloud all words in the set in their order of presentation.The length of the sequences varied from three to nine words and there were two trials at each set size.The different nouns were se-mantically and phonetically as unrelated as possible. The word span test started with two practice trials at set size two and the actual test began at this set size. Each time a participant answered one or two trials at a particular length correct,the length was increased by one word and participants were warned that such an increase would take place.Testing was discontinued if a participant got zero trials correct at a particular set size.A correct trial was one in which all the words in a set were recalled in their order of presentation.A participantÕs word span was defined as the total num-ber of correct trials.A particular word occurred only once in the test and was always one-syllable long and a concrete noun.4.Text comprehension.The materials were taken from a practice version of the Verbal Scholastic Apti-tude Test(VSAT)and consisted of two written stories that were related in theme(i.e.,the role of a mentor in the early education experiences of an artist).All partic-ipants indicated that they were not familiar with the two stories prior to the test.To avoid re-reading of the sto-ries,the presentation mode was self-paced,line-by-line. With each press of a button,participants would replace the current line of text with the next line of text in the middle of the screen.The two stories consisted of a total of120lines of text,or1180words.The last line of the last story was followed by13written,multiple-choice questions,each of which required a combination of fact retrieval and inference making,either involving thefirst story,the second story,or a comparison of a similar theme in both stories.There werefive answer alterna-tives per question.The display monitor showed only one question at a time together with its answer alternatives. Participants indicated their answer choice out loud and the experimenter recorded whether or not it was correct. The answer to a question could not be changed once the next question appeared on the display.The score on the story comprehension test was defined as the number of questions answered correctly(maximum possible score was13).5.Sentence comprehension.On each sentence com-prehension trial participants read a stimulus sentence, followed by a verification statement,and indicated whether the statement made a true or false assertion about the meaning of the stimulus sentence.The details of the test were as follows.Materials.We created64stimulus sentences with a main clause and a relative clause(e.g.,The nurse that thanked the doctor helped the patient).Stimulus sentences varied in their syntactic complexity.They included sub-ject-relative and(more complex)object-relative sentences324H.J.Haarmann et al./Journal of Memory and Language48(2003)320–345(for a review see Miyake,Carpenter,&Just,1994a)with right-branching and(more complex)center-embedded relative clauses(for a review see Stromswold,Caplan, Alpert,&Rauch,1996).The nouns,which referred to human actors,were semantically interchangeable and the degree of their semantic association with one another could be either strong or strong weak.Each stimulus sentence was paired with a verification statement,which probed participantsÕcomprehension of the semantic re-lationship between one of the nouns and one of the verbs (e.g.,The nurse did the thanking.True/False?The nurse was thanked?True or False).The order of presentation of the stimulus sentence verification statement pairs was randomized.We also created sentence materials for two practice trials.Procedure.Each trial consisted of the following events.First,afixation-cross appeared at the center of the display monitor for1000ms.Second,the stimulus sentence was presented one word at a time at the center of the display monitor,each new word replacing the previous one.The word presentation rate was300ms per word plus20ms for every letter in a word.Thus,a wordÕs presentation duration increased linearly with the number of letters(Miyake et al.,1994a),approxi-mating the effect of word length on eyefixations during reading(Just&Carpenter,1992).Third,immediately following the last word of the stimulus sentence,the entire verification statement appeared one line lower with a prompt to press one button for‘‘true’’and an-other button for‘‘false’’.Response-to-key assignment was counterbalanced across participants.The two re-sponse keys wereÔ1ÕandÔ2Õ.There was a response deadline of4s.Both response accuracy and answer time (i.e.,time from onset to verification statement to onset of response)were recorded.Participants did two practice trials followed by64experimental trials.After every16 trials,there was a short one-minute break,during which participants were asked to rest their eyes and focus them at various distances.Participants initiated each next trial with a button press.The score was the percentage cor-rect(out of64trials).ResultsTable1shows the descriptive statistics for conceptual span,reading span,word span,text comprehension,and sentence comprehension.Table2shows the product moment correlations among the span measures and be-tween each of the span measures and each of the com-prehension tests.Conceptual span,2reading span,and word span each showed moderate and significant corre-lations with sentence and text comprehension.Concep-tual span is still significantly correlated with sentence and text comprehension when individual variation in word span was statistically controlled for(r¼:27,p<:05and .32,p<:05,respectively).When individual variation in conceptual span was statistically controlled for,word span no longer correlated significantly with text com-prehension(r¼:19,p¼:14),albeit that it still predicted sentence comprehension(r¼:28,p<:05).The magni-tude of the correlation with text comprehension was somewhat greater for conceptual and reading span than for word span,while the magnitude of the correlation forTable1Descriptive statistics:Study1Measure N Mean a SD Min Max Maximumpossible score Conceptual span b6628.92 5.77134048 Reading span66 4.63 1.482810Word span66 4.48 1.371714Text comprehension66 5.27 2.0811013 Sentence comprehension6374.0013.0052100100a The medians were identical to the means rounded to the nearest integer.b The split-half reliability of the conceptual span test(i.e.,correlation between scores on even and odd items)was.85(p<:001) after Spearman–Brown correction for test length.2Afinal analysis examined the correlations between each ofthe three span measures and sentence comprehension,sepa-rately for the semantically related(M¼75%correct)andunrelated condition(M¼75%correct)in the comprehensiontask.The correlation between conceptual span and compre-hension accuracy was.33(p<:01)in the related and.33(p<:01)in the unrelated condition.The correlation betweenword span and comprehension accuracy was.33(p<:01)in therelated and.31ðp<:05Þin the unrelated condition.Thecorrelation between reading span and comprehension accuracywas.36(p<:01)in the related and.20(p>:10)in theunrelated condition.We did not necessarily expect a largercorrelation between conceptual span and sentence comprehen-sion in the unrelated than related condition.Weakly associatedwords may be more difficult to retain in semantic STM thanstrongly associated words(Haarmann&Usher,2001).How-ever,in on-line sentence processing,weakly associated wordsmay also engage semantic STM to a lesser extent,due a need touse phonological STM to re-process difficult-to-integratewords.H.J.Haarmann et al./Journal of Memory and Language48(2003)320–345325。