Incidental Language Learning: Listening (and Learning) Out of the Corner of Your Ear

Saffran, Jenny R.; Newport, Elissa L.; Aslin, Richard Ν.; Tunick, Rachel A.; Barrueco, Sandra

doi:10.1111/j.1467-9280.1997.tb00690.x

Cited by 501 publications

(534 citation statements)

References 25 publications

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“…It is in line with previous results showing that statistically driven segmentation can occur even in conditions in which attention is not fully allocated to the AL stream (e.g., Toro et al, 2005; see also Saffran, Newport, Aslin, Tunick, & Barrueco, 1997, who observed ALL with a concurrent drawing task), and with listeners who cannot be formally instructed to attend to the speech stream (human infants-see, e.g., Saffran, Aslin, & Newport, 1996-or nonhuman primates-see, e.g., Hauser, Newport, & Aslin, 2001). More generally, these results converge with evidence showing that the speech signal (or other dynamic and complex auditory stimuli; see, e.g., Jones, Macken, & Murray, 1993) is processed even when participants are asked to ignore it, as demonstrated, for example, by the irrelevant sound effect (or irrelevant speech effect, cf.…”

Section: Methodssupporting

confidence: 80%

“…In sum, ALL was penalized in a graded way by a depletion of attention resources, independently of the fact that Likewise, attention load and intention to learn may have different and perhaps additional effects on ALL. Their joint action may, for example, explain why in Saffran and colleagues' studies, ALL performance was much lower (only 59%) when participants performed a resource-consuming task in incidental learning (Saffran et al, 1997) than when there was no diverting task and learning was intentional (in which case performance reached 76%; .…”

Section: All Performancementioning

confidence: 99%

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The impact of attention load on the use of statistical information and coarticulation as speech segmentation cues

Fernandes

Kolinsky

Ventura

2010

Attention, Perception, & Psychophysics

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MaterialAL material. To achieve realistic coarticulation, we used naturally produced utterances rather than synthesized speech, and created concatenated and coarticulated versions of the AL stimuli (for the detailed method, see Fernandes et al., 2007). On the basis of Fernandes et al.'s pretests, we already know that the use of naturally produced rather than synthesized utterances does have an impact on ALL performance.All the natural speech stimuli were recorded in a soundproof room (using WaveLab Lite Program, version 2.52) by a European Portuguese female native speaker using a Shure M58 microphone and sampled at a rate of 22.05 kHz with 16-bit conversion. Adobe Audition 1.5 and Praat 4.2.24 (available at http://fon.hum.uva.nl/ praat/) were used for editing of the digitized versions of the stimuli (i.e., syllables, words, and part-words). These stimuli were closely matched to a synthesized stream in all relevant acoustic parameters, such as speaking rate (approximately 270 syllables per minute), AL stimuli duration, lack of lexical stress cues to word boundaries, and pitch contour (through flattening to monotone 220 Hz).The AL used by Fernandes et al. (2007) was adopted here. It was constituted by six trisyllabic AL words (i.e., / /, / /, / /, / /, / /, / /). TPs between adjacent syllables were always higher within than between AL words. Half of the AL words had higher TPs (high-TP words, ranging from .75 to 1) than the other half (low-TP words, ranging from .50 to .58), but all occurred with the same frequency in the AL stream.

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Section: Methodssupporting

confidence: 80%

Section: All Performancementioning

confidence: 99%

The impact of attention load on the use of statistical information and coarticulation as speech segmentation cues

Fernandes

Kolinsky

Ventura

2010

Attention, Perception, & Psychophysics

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“…Following exposure, infants showed sensitivity to the difference between the three-syllable sequences and foil sequences made up of the same syllables recombined in a different order, demonstrating that they were able to use the statistics of the input stream to discover word boundaries in connected speech (Saffran et al 1996a). Subsequent studies indicated that older children and adults also have this ability, becoming capable of discriminating between nonsense words and foil sequences after relatively short periods of exposure to input (Saffran et al 1996b(Saffran et al , 1997. Although statistical learning was initially implicated in language acquisition, it is a domain-general mechanism, also operating across nonlinguistic stimuli.…”

mentioning

confidence: 99%

“…Statistical learning has been demonstrated both when stimuli are presented passively without any explicit task (e.g., Saffran et al 1999;Aslin 2001, 2002;Toro et al 2005), and when participants are engaged in a cover task unrelated to the underlying pattern (Saffran et al 1997, Turk-Browne et al 2005). In addition, statistical learning seems to be unaffected by the precise instructions given to participants (Arcuili et al 2014;Batterink et al 2015).…”

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confidence: 99%

Functional differences between statistical learning with and without explicit training

2015

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Humans are capable of rapidly extracting regularities from environmental input, a process known as statistical learning. This type of learning typically occurs automatically, through passive exposure to environmental input. The presumed function of statistical learning is to optimize processing, allowing the brain to more accurately predict and prepare for incoming input. In this study, we ask whether the function of statistical learning may be enhanced through supplementary explicit training, in which underlying regularities are explicitly taught rather than simply abstracted through exposure. Learners were randomly assigned either to an explicit group or an implicit group. All learners were exposed to a continuous stream of repeating nonsense words. Prior to this implicit training, learners in the explicit group received supplementary explicit training on the nonsense words. Statistical learning was assessed through a speeded reaction-time (RT) task, which measured the extent to which learners used acquired statistical knowledge to optimize online processing. Both RTs and brain potentials revealed significant differences in online processing as a function of training condition. RTs showed a crossover interaction; responses in the explicit group were faster to predictable targets and marginally slower to less predictable targets relative to responses in the implicit group. P300 potentials to predictable targets were larger in the explicit group than in the implicit group, suggesting greater recruitment of controlled, effortful processes. Taken together, these results suggest that information abstracted through passive exposure during statistical learning may be processed more automatically and with less effort than information that is acquired explicitly.

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“…Marsick and Watkins 2001;Newton 2013;Saffran et al 1997;Webb 2008), as we feel that it makes a clearer distinction between a teacher's intended learning objectives and outcomes (both are terms widely used in the classroom), and those outcomes and objectives that were, from the teacher's perspective, wholly unintended. The use of 'unintended', unlike 'incidental', places a greater emphasis on the fact that whilst learning might have taken place in a particular lesson it was, from the teacher's perspective, unintended.…”

Section: Introductionmentioning

confidence: 99%

Unintended Learning in Primary School Practical Science Lessons from Polanyi’s Perspective of Intellectual Passion

2015

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This study explored, from the perspective of intellectual passion developed by Michael Polanyi, the unintended learning that occurred in primary practical science lessons. We use the term 'unintended' learning to distinguish it from 'intended' learning that appears in teachers' learning objectives. Data were collected using video and audio recordings of a sample of twenty-four whole class practical science lessons, taught by five teachers, in Korean primary schools with 10-to 12-year-old students. In addition, video and audio recordings were made for each small group of students working together in order to capture their activities and intra-group discourse. Pre-lesson interviews with the teachers were undertaken and audio-recorded to ascertain their intended learning objectives. Selected key vignettes, including unintended learning, were analysed from the perspective of intellectual passion developed by Polanyi. What we found in this study is that unintended learning could occur when students got interested in something in the first place and could maintain their interest. In addition, students could get conceptual knowledge when they tried to connect their experience to their related prior knowledge. It was also found that the processes of intended learning and of unintended learning were different. Intended learning was characterized by having been planned by the teacher who then sought to generate students' interest in it. In contrast, unintended learning originated from students' spontaneous interest and curiosity as a result of unplanned opportunities. Whilst teachers' persuasive passion comes first in the process of intended learning, students' heuristic passion comes first in the process of unintended learning. Based on these findings, we 123 Sci & Educ (2016) 25:3-20 DOI 10.1007 argue that teachers need to be more aware that unintended learning, on the part of individual students, can occur during their lesson and to be able to better use this opportunity so that this unintended learning can be shared by the whole class. Furthermore, we argue that teachers' deliberate action and a more interactive classroom culture are necessary in order to allow students to develop, in addition to heuristic passion, persuasive passion towards their unintended learning.

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Incidental Language Learning: Listening (and Learning) Out of the Corner of Your Ear

Cited by 501 publications

References 25 publications

The impact of attention load on the use of statistical information and coarticulation as speech segmentation cues

The impact of attention load on the use of statistical information and coarticulation as speech segmentation cues

Functional differences between statistical learning with and without explicit training

Unintended Learning in Primary School Practical Science Lessons from Polanyi’s Perspective of Intellectual Passion

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