Abstract
This paper summarizes recent psychological research and theory on the topic of consciousness and looks at three questions in second language learning related to the role of consciousness in input processing: whether conscious awareness at the level of 'noticing' is necessary for language learning (the subliminal learning issue); whether it is necessary to consciously 'pay attention' in order to learn (the incidental learning issue); and whether learner hypotheses based on input are the result of conscious insight and understanding or an unconscious process of abstraction (the implicit learning issue). I conclude that subliminal language learning is impossible, and that noticing is the necessary and sufficient condition for converting input to intake. Incidental learning, on the other hand, is clearly both possible and effective when the demands of a task focus attention on what is to be learned. Even so, paying attention is probably facilitative, and may be necessary if adult learners are to acquire redundant grammatical features. The implicit learning issue is the most difficult to resolve. There is evidence for it, as well as for a facilitative effect for conscious understanding, but accounting for implicit learning may entail abandonment of the notion of unconscious 'rules'of the type usually assumed in applied linguistics.
Keywords
Affiliated Institutions
Related Publications
ON THE STABILITY OF THE SIMPLEST SOLUTION OF THE EQUATIONS OF HYDROMAGNETICS
Emotions coordinate our behavior and physiological states during survival-salient events and pleasurable interactions. Even though we are often consciously aware of our current ...
Achieving coordination tasks in finite time via nonsmooth gradient flows
This paper introduces the normalized and signed gradient dynamical systems associated with a differentiable function. Extending recent results on nonsmooth stability analysis, w...
Backpropagation training for multilayer conditional random field based phone recognition
Conditional random fields (CRFs) have recently found increased popularity in automatic speech recognition (ASR) applications. CRFs have previously been shown to be effective com...
Using Embeddings to Improve Named Entity Recognition Classification with Graphs
Richer information has potential to improve performance of NLP (Natural Language Processing) tasks such as Named Entity Recognition. A linear sequence of words can be enriched w...
Publication Info
- Year
- 1990
- Type
- article
- Volume
- 11
- Issue
- 2
- Pages
- 129-158
- Citations
- 4587
- Access
- Closed
External Links
Social Impact
Social media, news, blog, policy document mentions
Citation Metrics
Cite This
Identifiers
- DOI
- 10.1093/applin/11.2.129