4.4 Article

Is It Better to Select or to Receive? Learning via Active and Passive Hypothesis Testing

期刊

JOURNAL OF EXPERIMENTAL PSYCHOLOGY-GENERAL
卷 143, 期 1, 页码 94-122

出版社

AMER PSYCHOLOGICAL ASSOC
DOI: 10.1037/a0032108

关键词

hypothesis testing; self-directed learning; category learning; Bayesian modeling; hypothesis-dependent sampling bias

资金

  1. Division Of Behavioral and Cognitive Sci
  2. Direct For Social, Behav & Economic Scie [1255538] Funding Source: National Science Foundation

向作者/读者索取更多资源

People can test hypotheses through either selection or reception. In a selection task, the learner actively chooses observations to test his or her beliefs, whereas in reception tasks data are passively encountered. People routinely use both forms of testing in everyday life, but the critical psychological differences between selection and reception learning remain poorly understood. One hypothesis is that selection learning improves learning performance by enhancing generic cognitive processes related to motivation, attention, and engagement. Alternatively, we suggest that differences between these 2 learning modes derives from a hypothesis-dependent sampling bias that is introduced when a person collects data to test his or her own individual hypothesis. Drawing on influential models of sequential hypothesis-testing behavior, we show that such a bias (a) can lead to the collection of data that facilitates learning compared with reception learning and (b) can be more effective than observing the selections of another person. We then report a novel experiment based on a popular category learning paradigm that compares reception and selection learning. We additionally compare selection learners to a set of yoked participants who viewed the exact same sequence of observations under reception conditions. The results revealed systematic differences in performance that depended on the learner's role in collecting information and the abstract structure of the problem.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.4
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据