Inter-individual Differences in Multitasking: Prioritisation and Conceptualisation as Determinants of Efficient Multitasking

多任务处理是指同时执行两个任务。在我们的研究方案中，我们分析了双重任务下绩效的灵活性。为此，我们将把感觉运动和认知任务结合起来。在第一个资助期，我们发现，如果任务是可预测的，无论是通过感知还是通过知识，双重任务的成本都会降低。然而，只有在可预测的任务中，绩效有所提高；其他任务保持不受影响，除非任务的特征相互依赖。对于这些发现，我们假设有两个原因。如果只有一项任务是可预测的，则可以对该任务进行优先排序。在相互依赖的情况下，可以将任务概念化为单个(超级)任务。在我们关于第二个资助期的提案中，我们调查了这两个战略。在项目A中，我们分析了双重任务中优先顺序的个体决定因素的影响；在项目B中，我们分析了任务概念化对双重任务绩效的影响。在我们的研究系列中，我们使用边打字边跟踪的实验范式，参与者必须用左手输入一行数字，同时用右手将移动的光标保持在目标的中间。在项目A的第一阶段，我们通过改变回报函数来操纵行为后果，并分析个体在风险倾向、接近-回避动机、开始偏好或持续注意力方面的差异是否会影响个体对任务的优先顺序。在第二阶段，遵循决策场理论，我们开发并验证了一个模型，该模型根据这些个体差异预测优先顺序。在项目B的第一阶段，我们通过操纵指令(一项或两项任务)和反馈(整合或分离)来分析任务概念化对双重任务绩效的影响。在第二阶段，我们测试概念化是否是应对多任务需求的有用策略，并寻找概念化能力的个体差异。在共同的阶段3中，我们检查特定任务的优先顺序和概念化是否可以通过实践来改进，以及多任务处理的需求是否可以根据个人偏好进行定制。总而言之，我们提出的项目将有助于更好地理解多任务处理绩效的个体差异。从理论角度来看，我们的研究有助于回答这样一个问题：人类多任务行为受损是由于结构限制而不可避免，还是人类可以灵活地适应多任务需求。

Multitasking is the simultaneous execution of two tasks. In our research proposal we analyse the flexibility of performance in dual tasking. For this purpose we will combine a sensorimotor and a cognitive task. In the first funding period we found out that dual-task costs are reduced if tasks are predictable, both by perception and by knowledge. However, performance improved in the predictable tasks only; the other task remained uninfluenced, except when features of the tasks were mutually dependent. We assume two reasons for these findings. If only one task is predictable, this task could be prioritised. In the case of mutual dependence, the tasks could be conceptualised as a single (super)task. In our proposal for the second funding period, we investigate these two strategies. In Project A, we analyse the influence of individual determinants of prioritisation in dual tasking and in Project B we analyse the influence of task conceptualisation on dual task performance. In our research series we use the typing-while-tracking paradigm for our experiments, where participants have to type a line of digits with their left hand while keeping a moving cursor in the middle of a target with their right hand. In Project A, Phase 1, we manipulate behavioural consequences by varying a payoff function and analyse if individual differences in risk tendency, approach–avoidance motivation, starting preferences, or sustained attention influence individual prioritisation of a task. In Phase 2, following decision field theory, we develop and validate a model that predicts prioritisation from these individual differences. In Project B, Phase 1, we analyse the influence of task conceptualisation on dual-task performance by manipulating instructions (one or two tasks) and feedback (integrated or separate). In Phase 2 we test if conceptualisation is a useful strategy for coping with multitasking demands and look for individual differences in conceptualisation abilities. In the common Phase 3 we examine if task-specific prioritisation and conceptualisation can be improved by practice and if multitasking demands can be tailored to personal preferences. To sum up, our proposed project will lead to improved understanding of individual differences in multitasking performance. From a theoretic point of view, our research helps answer the question if impaired human multitasking behaviour is inevitable due to structural constraints or if humans can adapt flexibly to multitasking demands.