Creating coherence in real‐life decision processes: Reasons,differentiation and consolidation

Svenson, O. & Jakobsson, M. (2009). Creating coherence in real‐life decision processes: Reasons, differentiation and consolidation. Scandinavian Journal of Psychology, 51, 93–102. Differentiation and Consolidation Theory describes human decision making as a process in which attractiveness values are restructured in order to reach a decision and support the decision made. Here, the theory was developed to include reasons pro and con alternatives and tested on students making decisions between two university psychotherapy training programs (cognitive‐behavioral and psychodynamic therapy). Before and also after the decision, the attractiveness of the chosen alternative was upgraded and the non‐chosen alternative downgraded. Different measures of evaluations of an alternative, such as “best” or “worse” converged over time until shortly after the decision. The number of reasons pro and con alternatives give a more complete picture than attractiveness and increased from the first to the last session. The reasons supporting the chosen alternative increased in strength, but reasons against the non‐chosen alternative decreased. In informal comments participants reported that the study also served as a decision aid.     

No frills: Simple regularities in language can go a long way in the development of word knowledge

Recent years have seen a flourishing of Natural Language Processing models that can mimic many aspects of human language fluency. These models harness a simple, decades-old idea: It is possible to learn a lot about word meanings just from exposure to language, because words similar in meaning are used in language in similar ways. The successes of these models raise the intriguing possibility that exposure to word use in language also shapes the word knowledge that children amass during development. However, this possibility is strongly challenged by the fact that models use language input and learning mechanisms that may be unavailable to children. Across three studies, we found that unrealistically complex input and learning mechanisms are unnecessary. Instead, simple regularities of word use in children's language input that they have the capacity to learn can foster knowledge about word meanings. Thus, exposure to language may play a simple but powerful role in children's growing word knowledge. A video abstract of this article can be viewed at https://youtu.be/dT83dmMffnM .

Research Highlights

• Natural Language Processing (NLP) models can learn that words are similar in meaning from higher-order statistical regularities of word use.
• Unlike NLP models, infants and children may primarily learn only simple co-occurrences between words.
• We show that infants' and children's language input is rich in simple co-occurrence that can support learning similarities in meaning between words.
• We find that simple co-occurrences can explain infants' and children's knowledge that words are similar in meaning.