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

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

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.

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 de- sign, 42 lower-intermediate students were asked to perform three different tasks 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 ma- nipulated along +/− elements, and the decision-making task which is manipu- lated 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 low- proficiency and high-proficiency participants. Results show an overall effect of Task Complexity on self-repairs behavior across task types, with different be- haviors 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 (Robin- son 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)

In this article we explore how oral and written modes may differentially influence processes involved in second language acquisition (SLA) in the context of task-based language teaching (TBLT). We first start by reflecting on the differences between spoken and written language. In what follows, we provide a general description of tasks in relation to the SLA processes. We then establish the links between the learning processes and task phases/features in the two modes. Concluding that the role of mode has been underresearched, we call for a more integrative and mode-sensitive TBLT research agenda, in which hybridness of discourse (i.e., mingling of the two modes within one communicative event/task) is taken into account.

The study measures the impact of increasing cognitive task demands on the use of L2 learners’ pragmatic moves. L2 Spanish/Catalan learners of English (n = 36) were grouped into pairs and performed two types of problem-solving tasks. Task complexity was independently measured by means of a learners’ perceptions questionnaire, time on task, and time estimation. Interactions were analyzed for the use of requests and suggestions. Results showed an impact of task complexity on the number of moves for one of the tasks, indicating a clear task effect. No differences in terms of the variety of moves were found between the simple and complex versions of tasks. Results showed a clear task effect with some moves being exclusively associated with some tasks but not others.