Cho Pyeong Whan, Szkudlarek Emily, Tabor Whitney
Department of Psychology, University of ConnecticutStorrs, CT, USA; Haskins LaboratoriesNew Haven, CT, USA.
Department of Psychology, University of Connecticut Storrs, CT, USA.
Front Psychol. 2016 Jun 8;7:867. doi: 10.3389/fpsyg.2016.00867. eCollection 2016.
Learning is typically understood as a process in which the behavior of an organism is progressively shaped until it closely approximates a target form. It is easy to comprehend how a motor skill or a vocabulary can be progressively learned-in each case, one can conceptualize a series of intermediate steps which lead to the formation of a proficient behavior. With grammar, it is more difficult to think in these terms. For example, center embedding recursive structures seem to involve a complex interplay between multiple symbolic rules which have to be in place simultaneously for the system to work at all, so it is not obvious how the mechanism could gradually come into being. Here, we offer empirical evidence from a new artificial language (or "artificial grammar") learning paradigm, Locus Prediction, that, despite the conceptual conundrum, recursion acquisition occurs gradually, at least for a simple formal language. In particular, we focus on a variant of the simplest recursive language, a (n) b (n) , and find evidence that (i) participants trained on two levels of structure (essentially ab and aabb) generalize to the next higher level (aaabbb) more readily than participants trained on one level of structure (ab) combined with a filler sentence; nevertheless, they do not generalize immediately; (ii) participants trained up to three levels (ab, aabb, aaabbb) generalize more readily to four levels than participants trained on two levels generalize to three; (iii) when we present the levels in succession, starting with the lower levels and including more and more of the higher levels, participants show evidence of transitioning between the levels gradually, exhibiting intermediate patterns of behavior on which they were not trained; (iv) the intermediate patterns of behavior are associated with perturbations of an attractor in the sense of dynamical systems theory. We argue that all of these behaviors indicate a theory of mental representation in which recursive systems lie on a continuum of grammar systems which are organized so that grammars that produce similar behaviors are near one another, and that people learning a recursive system are navigating progressively through the space of these grammars.
学习通常被理解为一个过程,在这个过程中,有机体的行为会逐渐被塑造,直到它与目标形式非常接近。理解运动技能或词汇是如何逐步习得的很容易——在每种情况下,人们都可以设想出一系列中间步骤,这些步骤会导致熟练行为的形成。对于语法来说,用这些术语来思考则更加困难。例如,中心嵌入递归结构似乎涉及多个符号规则之间的复杂相互作用,这些规则必须同时存在,系统才能正常工作,所以这种机制如何逐渐形成并不明显。在这里,我们从一种新的人工语言(或“人工语法”)学习范式——轨迹预测中提供了实证证据,即尽管存在概念难题,但递归习得是逐渐发生的,至少对于一种简单的形式语言来说是这样。具体来说,我们关注最简单递归语言a(n)b(n)的一个变体,发现证据表明:(i) 在两个结构层次(本质上是ab和aabb)上接受训练的参与者,比在一个结构层次(ab)与一个填充句子相结合的情况下接受训练的参与者,更容易推广到下一个更高层次(aaabbb);然而,他们并不会立即推广;(ii) 接受三个层次(ab、aabb、aaabbb)训练的参与者,比接受两个层次训练的参与者更容易推广到四个层次;(iii) 当我们依次呈现这些层次,从较低层次开始并包括越来越多的较高层次时,参与者表现出逐渐在各层次之间过渡的证据,呈现出他们未接受过训练的中间行为模式;(iv) 这些中间行为模式与动力系统理论意义上的吸引子扰动相关。我们认为,所有这些行为都表明了一种心理表征理论,其中递归系统位于一个语法系统的连续统上,这些语法系统的组织方式是,产生相似行为的语法彼此相邻,并且学习递归系统的人正在逐步穿越这些语法的空间。