学习者的认知风格与英语专业教学

对于认知风格的研究再度引起人们的高度关注,且应用型的研究变得越来越重要。在＂教—学—研＂的过程中,学生的认知风格不仅会影响其选择学习策略,也影响教师自身对教学策略的抉择。如果教师能了解学生不同的认知风格结构对学习的影响,就能针对不同的学习任务、有差异的学习环境等因素制定不同的教学方案及策略。社会对高素质外语人才的需求与日俱增,在这种大环境中,对外语学习者的认知风格的研究就显示出前所未有的重要性。     

场独立与场依存型认知风格差异对大学英语教学的启示

学习者具有不同的认知风格,认知风格直接参与并操纵语言学习的基本过程,并对学习者的学习方式和学习效果产生影响。场独立和场依存型认知风格是二语习得中最常见的认知风格,对学生的学习心理及学习习惯都会产生很大影响。本文对场独立与场依存型认知风格的英语学习者加以剖析,并指出就大学英语教学而言,教师如能在教学中了解学习者在认知风格上的差异性,并运用相应的教学策略引导学习者的认知风格,将极大地提高大学英语教学效果。     

认知风格对中学生英语学习的影响

认知风格是影响学生学习成绩的重要因素之一,文章介绍了几种常见的认知风格及其在学习过程中所显现的特征,探讨不同认知风格对学生英语学习成绩的影响,不同的认知风格在特定学习情境中各具优势,学生学业成绩的优劣除了受先天智力因素或是其自身的努力程度影响,还会受到其成长过程中认知风格的影响,通过研究认知风格的差异对学生英语学业成绩的影响,以便教师能够在教学中做到因材施教,最大化地提高学生的二语学习成绩。     

场依存性、场独立性与商务英语阅读教学

不同的学习目标、不同的学习任务和不同的学习环境,需要不同的认知风格和学习策略。在商务英语阅读教学中,关注学生的个别差异,利用认知风格中的场独立性和场依存性的理论指导阅读教学有其重要意义。教师的教学应结合学生的认知方式的特点,以培养提高学生的阅读理解能力。教师对学生认知方式的了解和尊重,能使自己的教学特点与学生的需要有机地联系起来,建立良好的师生关系,根据学生的认知特点因材施教,就能取得好的教学效果。     

认知风格对学习的影响及其应用

认知风格是一个人在感知觉、记忆、思维等方面一贯的加工方式的偏好。学生的认知风格一般会通过对不同学科的偏爱和自身学习风格表现出来,教师的认知风格则会体现在不同的教学方式中,并且它们都对学生的学习成绩有一定的影响。教师只有掌握学生认知风格和自身认知风格影响学生学习成绩的途径,才能更有针对性地进行有效教学。     

基于不同学习风格的英语教学设计

认知心理分析研究表明:在二语习得中,学习者个人的学习风格在一定程度上影响着学习效果。因此,教师在进行课堂教学设计时,要针对不同学习风格的学生采用相应的教学策略。同时,认知因素和非认知因素也极大地影响着学生的语言习得,教师应该充分利用学生认知因素和非认知因素来进行英语教学设计。     

认知风格的差异性与阅读教学策略的多样性

认知风格是影响学习的一个重要因素,既影响个人的学习行为方式和成绩,又决定课堂教学的效率。当前在基础教育教学改革的研究中,对学生认知风格研究的忽视或不足,导致教学效率低下,教学效果不佳;认知风格的多元化的存在,致使语文阅读教学过程中会表现出不同的行为活动方式,思维呈现不同的特点。因此,教师要依据不同的认知风格特点,采用不同的阅读教学策略,才能提高语文教学效率。     

认知风格与外语学习关系探索

在外语学习中,学生的自主性和个性化学习需要学生了解自身的认知风格,同时教师也要了解学生的学习风格。然而,对学习风格在外语学习中的作用与影响的研究起步晚,研究少且范围窄。在对艾尔曼(Ehrman)和利物尔(Leaver)的10种认知风格类型中的学习者特征及与外语学习的关系进行探讨的基础上,应用认知风格,提出了外语教学和学习的建议。     

基于认知风格的教师教学行为

教师的认知风格影响学生认知内容、学习风格和师生关系,因此教师要按照自身认知风格安排适当的教学行为。场独立型教师要找准教学目标、有效传授知识和及时采纳建议;场依存型教师要掌握系统知识、形成个性教学风格和实施多维评价。教师还需在教学、学习、评价、职业引导上和学生认知风格匹配,使不同认知风格学生的认知发展处于一种平衡互补状态。     

场独立与场依存的认知风格对外语教学的启示

认知风格是学习者在学习一种语言中,对语言信息的理解、转换、存储并利用过程中的形成的比较稳定的学习方式和态度,认知风格直接影响着一种语言学习的基本过程。对于中国学生学习英语来说,有不同的认知风格,而二语习得中最为常见的是场独立和场依存型认知风格。对于外语教学来说,教师要充分掌握住学生在英语学习的认知风格方面的差异,并针对不同学生的学习特点,制定相应的教学策略,因材施教,才能真正提高英语教学的效果。因此,本文主要对场独立与场依存型认知风格进行深入分析,并探讨场独立与场依存的认知风格对外语学习的影响,从而得到其对外语教学的一些启示。     

The role of cognitive style in educational computer conferencing

This paper reports an investigation of the impact of students’ cognitive style on their effective use of educational text‐based computer‐mediated conferences. The research centres on an empirical study involving students from three courses run by the British Open University. Statistical analysis of the data does not suggest that cognitive style has a strong influence on student participation in the conference, but does suggest that, contrary to expectations, ‘imagers’ may send more messages to conferences than ‘verbalisers’. The data also suggest a possible link between certain cognitive styles and course completion, and that the interaction of different styles within a group, as described by Riding and Rayner's (1998 ) team roles, may have an indirect influence on task completion.     

认知风格对英语阅读及写作的影响——以计算机本科二年级学生为例

场独立／场依存作为认知风格的核心,是影响二语习得的重要因素之一。对非英语专业学习者的认知风格测试发现：在非英语专业学生中,确实存在认知风格差异,并且此差异会对学生的阅读理解成绩产生一定的影响,但对写作成绩的影响不大。因此在英语教学中,教师应充分了解学生的认知风格,并采取相应的匹配教学策略,以达到事半功倍的教学效果。     

Using learning styles theory in engineering education

Studies have shown that, while learning different concepts, people sometimes take different approaches (learning styles). Accordingly, their performance reflected differently in their academic studies. With the effect of globalisation to the educational environments, the influence of individual learning styles on educational performance is getting more significant. In this study, a learning style assessment tool was used to examine the relationship between students’ learning styles and their performance in engineering education programmes. At the beginning of the programme, 285 students’ learning styles were measured using a learning style assessment tool. Four years after the engineering education, their performance in the programme was compared with their individual learning styles. This study shows that most of the students are assimilators. Divergers and convergers follow the assimilators. The number of accommodators is very limited. The relationship between engineering students’ learning styles and their performance is found: assimilators and convergers performed better than the divergers and accommodators. The performance difference between assimilators and divergers is statistically significant. The results of this study show that the learning style theory is a potential tool for guiding the design and improvement of courses and helping students to improve their individual performance.     

Differences in concept mapping,hypertext architecture,and the analyst–intuition dimension of cognitive style

There is now evidence to suggest that the degree to which hypertext or web‐based instructional systems facilitate recall of information appears to be contingent on an individual’s cognitive or information processing style. Concept maps also reflect the way in which individuals process information and therefore it is possible that cognitive style and hypertext architecture might influence concept map drawings produced by hypertext users. In this study, 55 participants were assigned to one of three hypertext conditions and were required to recall information and produce maps of the hypertext. Cognitive style was assessed using the analyst–intuition dimension of cognitive style. The findings confirmed earlier research that individuals possessing different cognitive styles differed in recall performance when using different hypertexts. Furthermore, the concept maps produced by participants with different cognitive styles differed between architecture conditions. The findings are explained partly as being due to differences between individuals’ perceived ease of use of hypertext.     

不同归因风格大学生认知差异研究的现状与前瞻

自20世纪60年代,"归因"概念产生以来,归因以及相关内容一直是心理学领域着力探讨的一个重要课题。综观国内外有关归因风格的研究可见,归因风格与人的教育、生活、学习等密切相关,是人身心健康的重要因素。对不同归因风格者在认知方面的差异进行研究,既可促进大学生人格的完善和个性的发展,也可为教师的因材施教、促进学生全面发展探寻新的路径。     

Exploring the Relationship between Cognitive Style and Teaching Style

To a great extent the nature of the relationship between the cognitive style of a student teacher and their predominant teaching style in the classroom has been ignored by educational research. This study used an opportunist sample of 84 trainee teachers studying for one year full time for a Post Graduate Certificate in Education, in a range of subject specialist areas, based at a single English university. Students' cognitive styles were assessed, and those with more extreme cognitive style scores were selected to participate in semi‐structured interviews. A subject specialist mentor had been assigned to each student; 77% (n=59) completed a questionnaire on their perceptions of the teaching style of their PGCE student. Statistically significant differences in approaches to learning and teaching were identified between the four cognitive styles. Gender differences were also noted with analytic‐verbaliser females adopting the most analytical style in the classroom and wholist‐imager males the most wholist style. Qualitative analysis identified differences in approach to teaching between the students with more extreme cognitive styles. Wholists were more sensitive than analytic students to situational factors such as the culture of the school, support from the mentor, and in their ability to accept criticism. Further research is recommended to verify such findings. In this respect, a longitudinal study focusing on changes in cognitive style and approach in the classroom could be fruitful. Consequently, universities need to adopt varied teaching and assessment tools varied in order to accommodate the continuum of cognitive styles.     

‘Learning Style’: frameworks and instruments

In both education and training an important aspect of the design, development and delivery of learning is the role of individual differences between learners in terms of their ‘learning styles’. One may identify four broad categories of what have been termed ‘learning style’: (i) ‘cognitive personality elements’ (e.g. Witkin et al. 1977; Riding, 1991); (ii) ‘information‐processing style’ (e.g. Kolb, 1984; Honey & Mumford, 1992); (iii) ‘approaches to studying’ (e.g. Entwistle & Tait, 1994); (iv) ‘instructional preferences’ (e.g. Riechmann & Grasha, 1974). A study of 245 university undergraduates in business studies aimed to: (i) describe the range of individual differences present within the sample; (ii) investigate the relationship between learners’ cognitive styles, learning styles, approaches to studying and learning preferences; (iii) consider the implications of ‘learning style’ for teaching and learning in higher education. The present study suggested some overlap between the dimensions measured by the Learning Styles Questionnaire (Honey & Mumford, 1986; 1992) and the Revised Approaches to Studying Inventory (Entwistle & Tait, 1994). No statistically significant correlations were found between cognitive style, as measured by the Cognitive Styles Analysis (Riding, 1991) and any of the other ‘style’ constructs used. Further research is required to investigate these relationships, as is a large‐scale factor analytical study of the Honey and Mumford and Kolb instruments. The notions of whole brain functioning, integra‐tive approaches to studying and degree of learning activity are discussed.     

Towards Inclusive Teacher Education: Sensitising individuals to how they learn

Higher education has struggled to acknowledge and translate into better teaching and learning practices that sizeable literature base suggesting a link between cognitive style, learning preferences, and performance. Research is reported in which 80 undergraduate students on a primary education degree were studied to examine the relationship between their cognitive style, their learning preferences, and perceived impact on their teaching practices. All students completed the CSA measure of cognitive style, the ASSIST, two further questionnaires exploring learning preferences and perception of good teaching during the course, and an evaluation at the end of the teaching unit. Significant differences were found between the three cognitive styles investigated: wholist, intermediate, and analytic. In terms of learning preferences, using ANOVA statistically significant differences were found between the three styles with wholists being most concerned about speed of delivery and least liking computer‐assisted learning. In addition, wholists preferred less structure than analytics in their teaching and claimed to use more images while analytics claimed to use more speech in their teaching. Intermediates demonstrated a greater preference for tangential approaches to teaching and were least happy with the nature of the teaching they had received while at university. Many of the differences reported in the literature between the different cognitive styles were not evident in this study. However, the interpersonal and intrapersonal characteristics of wholists and analytics, respectively, were evident and perceived to impact on planning and delivery in the classroom. While further school‐based research involving greater numbers is required, interest in learning styles remains especially relevant if one intends to offer a truly inclusive education for all learners.     

Performance on Middle School Geometry Problems With Geometry Clues Matched to Three Different Cognitive Styles

ABSTRACT— This study investigated the relationship between 3 ability‐based cognitive styles (verbal deductive, spatial imagery, and object imagery) and performance on geometry problems that provided different types of clues. The purpose was to determine whether students with a specific cognitive style outperformed other students, when the geometry problems provided clues compatible with their cognitive style. Students were identified as having a particular cognitive style when they scored equal to or above the median on the measure assessing this ability. A geometry test was developed in which each problem could be solved on the basis of verbal reasoning clues (matching verbal deductive cognitive style), mental rotation clues (matching spatial imagery cognitive style), or shape memory clues (matching object imagery cognitive style). Straightforward cognitive style–clue‐compatibility relationships were not supported. Instead, for the geometry problems with either mental rotation or shape memory clues, students with a combination of both verbal and spatial cognitive styles tended to do the best. For the problems with verbal reasoning clues, students with either a verbal or a spatial cognitive style did well, with each cognitive style contributing separately to success. Thus, both spatial imagery and verbal deductive cognitive styles were important for solving geometry problems, whereas object imagery was not. For girls, a spatial imagery cognitive style was advantageous for geometry problem solving, regardless of type of clues provided.