Center for Economic Psychology, University of Basel, Petersplatz 1, 4051, Basel, Switzerland.
Max Planck Institute for Human Development, Lentzeallee 94, 14195, Berlin, Germany.
Psychon Bull Rev. 2020 Dec;27(6):1218-1229. doi: 10.3758/s13423-020-01747-2.
The term process model is widely used, but rarely agreed upon. This paper proposes a framework for characterizing and building cognitive process models. Process models model not only inputs and outputs but also model the ongoing information transformations at a given level of abstraction. We argue that the following dimensions characterize process models: They have a scope that includes different levels of abstraction. They specify a hypothesized mental information transformation. They make predictions not only for the behavior of interest but also for processes. The models' predictions for the processes can be derived from the input, without reverse inference from the output data. Moreover, the presumed information transformation steps are not contradicting current knowledge of human cognitive capacities. Lastly, process models require a conceptual scope specifying levels of abstraction for the information entering the mind, the proposed mental events, and the behavior of interest. This framework can be used for refining models before testing them or after testing them empirically, and it does not rely on specific modeling paradigms. It can be a guideline for developing cognitive process models. Moreover, the framework can advance currently unresolved debates about which models belong to the category of process models.
过程模型这个术语被广泛使用，但很少被大家所认同。本文提出了一个用于描述和构建认知过程模型的框架。过程模型不仅可以对输入和输出进行建模，还可以在给定的抽象级别上对正在进行的信息转换进行建模。我们认为，以下维度可以描述过程模型：它们具有包括不同抽象级别的范围。它们指定了一个假设的心理信息转换。它们不仅对感兴趣的行为进行预测，还对过程进行预测。模型对过程的预测可以从输入中推导出来，而无需从输出数据中进行反向推理。此外，假定的信息转换步骤与人类认知能力的现有知识并不矛盾。最后，过程模型需要一个概念范围，为进入大脑的信息、提出的心理事件以及感兴趣的行为指定抽象级别。该框架可用于在测试模型之前或之后对其进行细化，而不依赖于特定的建模范例。它可以作为开发认知过程模型的指南。此外，该框架可以推动目前关于哪些模型属于过程模型类别的未解决的争论。
