中國科技大學通識教育中心英語文證照奬勵金實施要點 中華民國 105 年 1 月 8 日通識教育委員會議通過 一、 中國科技大學(以下簡稱本校)為鼓勵本校學生通過具公信力機構之英語文能力測驗或 取得證照,特訂定「中國科技大學通識教育中心英語文證照獎勵金實施要點」(以下簡 稱本要點)。 二、 學生於就讀本校期間,通過歐盟共同架構(CEFR)語言能力參考指標 B1(中級)同等級英 語文能力測驗以上(含)者,得依據本要點酌予獎勵。檢測項目請參閱本中心「歐洲語言 學習、教學、評量共同參考架構與各英語檢測分級對照表」(參見附表);未列於標準 對照表之測驗項目不給予獎助。 三、 凡本校學生,除應英系外,均得申請。大學部學生通過同等級以申請一次為限,在學期 間得重複申請,但該次申請之級別不得低於前次。 本獎勵金每學期核發乙次,每次核發全校前 10 名,各名次核發金額如附表。 四、 申請人應提供在學期間,申請當(學)期參加考試之證明文件及成績證明或證照,以憑辦 理。 五、 獎勵金申請作業:請至通識教育中心網頁下載「英語文證照獎勵金申請表」(附件 1), 填妥後檢附成績單正本及影本(背面簽名並註明與正本無異)各一份、本人金融帳戶存 簿(郵局或土地銀行)封面影本送至通識教育中心。 通識教育中心得每學期遴選受獎代表,擇期公開頒奬,並辦理後續請款作業。 六、 奬勵金申請期限:通過相關證照考試半年內應提出申請,逾期視同放棄。 七、 本要點之獎勵金由學校開設通識教育中心專戶,一切收支專款專用;每年度如有剩餘 款,則移至翌年度繼續使用。 八、 本要點經通識教育中心會議審查通過,陳請校長核定後公告實施,修訂時亦同。

文化と言語の多様性の中のCommon European Framework of Reference for Languages: Learning, teaching, assessment (CEFR)--それは基準か? (第10回明海大学大学院応用言語学研究科セミナー 講演)

Complexity, accuracy, and fluency have proved useful measures of second language performance. The present article will re-examine these measures themselves, arguing that fluency needs to be rethought if it is to be measured effectively, and that the three general measures need to be supplemented by measures of lexical use. Building upon this discussion, generalizations are reviewed which focus on inter-relationships between the measures, especially between accuracy and complexity, since positive correlations between these two areas have been less common in the literature. Some examples of accuracy–complexity correlations are reviewed. The central issue here is how to account for these correlations, and so the discussion explores rival claims from the Cognition and Trade-off Hypotheses. It is argued that such joint raised performance between accuracy and complexity is not a function of task difficulty, as the Cognition Hypothesis would predict, but that instead it reflects the joint operation of separate task and task condition factors. Extending the theoretical discussion, connection is made with the Levelt model of first language speaking, and it is proposed that the results obtained in the task-based performance literature can be linked to this model, modified to take account of differences between first and second language processing, particularly as these stem from differences in the underlying mental lexicons.

Modelling Second Language Performance: Integrating Complexity, Accuracy, Fluency, and Lexis

A cognitive approach to language learning

Cognition and Second Language Instruction

https://dialnet.unirioja.es/descarga/articulo/2927343.pdf

Problems in SLA

In this paper we describe a taxonomy of task demands which distinguishes between Task Complexity, Task Condition and Task Difficulty. We then describe three theoretical claims and predictions of the Cognition Hypothesis (Robinson 2001, 2003b, 2005a) concerning the effects of task complexity on: (a) language production; (b) interaction and uptake of information available in the input to tasks; and (c) individual differences-task interactions. Finally we summarize the findings of the empirical studies in this special issue which all address one or more of these predictions and point to some directions for continuing, future research into the effects of task complexity on learning and performance. 1. The Cognition Hypothesis: Task complexity, task design and task sequencing This special issue consists of a theoretical overview of two models of attention that have prompted extensive research into the effects of task demands on selective attention and co-ordination of attentional resources during dual and multitask performance, followed by four empirical studies examining the effects of manipulating dimensions of task complexity on; (i) the accuracy, fluency and complexity of second language (L2) speech production; (ii) the extent of interaction and uptake of premodified input occurring during task performance, and iii) learner perceptions of task difficulty. A great number of previous studies have examined the effects of one or another aspect of L2 task demands, such as the availability of planning time (see Ellis 2005), or the nature and extent of participation on tasks (see Pica, Kanagy and Falodun 1993), individually. Drawing on this, and other previous research the studies in this special issue all address the issue of task complexity in the Triadic Componential Framework (Robinson 2001, 2005a, 2007a) which specifies component dimensions of task complexity in terms of three superordinate cognitive, interactive and learner factors in order that each dimension can be studied separately, and also that

/pdf/task-complexity-the-cognition-hypothesis-and-second-language-32zoeivmjs.pdf

Task complexity, the Cognition Hypothesis and second language learning and performance

This paper analyses the effects of manipulating the cognitive complexity of L2 oral tasks on language production. It specifically focuses on self-repairs, which are taken as a measure of accuracy since they denote both attention to form and an attempt at being accurate. By means of a repeated measures design, 42 lower-intermediatestudentswereaskedto performthree differenttasks types (a narrative, and instruction-giving task, and a decision-making task) for which two degrees of cognitive complexity were established. The narrative task was manipulated along +/" Here-and-Now, an instruction-giving task manipulated along +/" elements, and the decision-making task which is manipulated along +/" reasoning demands. Repeated measures ANOVAs are used for the calculation of differences between degrees of complexity and among task types. One-way ANOVA are used to detect potential differences between lowproficiency and high-proficiency participants. Results show an overall effect of Task Complexity on self-repairs behavior across task types, with different behaviors existing among the three task types. No differences are found between the self-repair behavior between low and high proficiency groups. Results are discussed in the light of theories of cognition and L2 performance (Robinson 2001a, 2001b, 2003, 2005, 2007), L1 and L2 language production models (Levelt 1989, 1993; Kormos 2000, 2006), and attention during L2 performance (Skehan 1998; Robinson, 2002).

/pdf/effects-of-manipulating-task-complexity-on-self-repairs-3wf7je3d8g.pdf

Effects of manipulating Task Complexity on self-repairs during L2 oral production

The goal of this study is to investigate the impact of manipulating the cognitive complexity of three different types of oral tasks on interaction. The study first considers the concepts of task complexity and interaction and then examines the specific studies that have looked at the effects of increasing task complex- ity on conversational interaction. In the experiment, learners of English as a foreign language organized into 27 dyads carry out three different types of tasks: a narrative reconstruction task, an instruction-giving map task, and a decision-making task. Two different versions of each task, one simple and one complex, are presented to learners in different sequences. Task complexity is manipulated along the degree of displaced, past time reference, the number of elements, and the reasoning demands. Audio recordings are transcribed and coded for interactional feedback, which is measured in terms of negotiation of meaning (i.e., confirmation checks, clarification requests, and comprehension checks), recasts, language-related episodes (LREs), and repairs, all of which have been described in the literature as being conducive to acquisition. Both parametric and non-parametric statistical tests are used. Results are discussed in the light of previous studies that have looked at the specific relationship between task complexity and interaction, attention models (Robinson 2001a, 2003, 2005, 2007b; Skehan and Foster 2001), and how different task types may variously affect the way interaction proceeds during task performance.

/pdf/manipulating-cognitive-complexity-across-task-types-and-its-42zzfq6o3n.pdf

Manipulating cognitive complexity across task types and its impact on learners' interaction during oral performance

This study explored the usefulness of dual-task methodology, self-ratings, and expert judgments in assessing task-generated cognitive demands as a way to provide validity evidence for manipulations of task complexity. The participants were 96 students and 61 English as a second language (ESL) teachers. The students, 48 English native speakers and 48 ESL speakers, carried out simple and complex versions of three oral tasks—a picture narrative, a map task, and a decision-making task. Half of the students completed the tasks under a dual-task condition. The remaining half performed the tasks under a single-task condition without a secondary task. Participants in the single condition were asked to rate their perceived mental effort and task difficulty. The ESL teachers provided expert judgments of anticipated mental effort and task difficulty along with explanations for their ratings via an online questionnaire. As predicted, the more complex task versions were found and judged to pose greater cognitive effort on most measures.

/pdf/measuring-cognitive-task-demands-using-dual-task-methodology-4iq8y0lyax.pdf

Measuring cognitive task demands using dual task methodology, subjective self-ratings, and expert judgments: A Validation Study

The objective of this paper is to describe a task-based project in tandem via e-mail, and to discuss the effects of motivation on task performance. In this project, a group of Irish students and a group of Spanish students are asked to carry out a series of tasks in collaboration with their tandem partners via e-mail by means of a web page especially designed for the project. Half the message is meant to be written in the student’s native language and half in the target language, and students are also encouraged to correct one another. The goal behind our research is to discuss the effects of motivation on task performance. We argue that resource directing (such as reasoning demands) and resource depleting factors (such as prior knowledge) which belong to task complexity in Robinson’s model (Robinson, 2001) are closely connected to affective variables which, as is the case with motivation, belong to task difficulty. Motivational factors like interest in the meanings to be exchanged, involvement in the decision-making process, students’ expertise in the topic, media and materials used, and the diffusion of outcomes among others have strong effects on task performance, and should therefore be considered together with complexity variables.

https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0958344002000319

Roger Gilabert

Papers

Task complexity, the Cognition Hypothesis and second language learning and performance

Effects of manipulating Task Complexity on self-repairs during L2 oral production

Manipulating cognitive complexity across task types and its impact on learners' interaction during oral performance

Measuring cognitive task demands using dual task methodology, subjective self-ratings, and expert judgments: A Validation Study

Motivation and task performance in a task-based web-based tandem project