Learning new words is difficult. In any naming situation, there are multiple possible interpretations of a novel word. Recent approaches suggest that learners may solve this problem by tracking co-occurrence statistics between words and referents across multiple naming situations (e.g. Yu & Smith, 2007), overcoming the ambiguity in any one situation. Yet, there remains debate around the underlying mechanisms. We conducted two experiments in which learners acquired eight word-object mappings using cross-situational statistics while eye-movements were tracked. These addressed four unresolved questions regarding the learning mechanism. First, eye-movements during learning showed evidence that listeners maintain multiple hypotheses for a given word and bring them all to bear in the moment of naming. Second, trial-by-trial analyses of accuracy suggested that listeners accumulate continuous statistics about word/object mappings, over and above prior hypotheses they have about a word. Third, consistent, probabilistic context can impede learning, as false associations between words and highly co-occurring referents are formed. Finally, a number of factors not previously considered in prior analysis impact observational word learning: knowledge of the foils, spatial consistency of the target object, and the number of trials between presentations of the same word. This evidence suggests that observational word learning may derive from a combination of gradual statistical or associative learning mechanisms and more rapid real-time processes such as competition, mutual exclusivity and even inference or hypothesis testing.

Automaticity in word recognition has been hypothesized to be important in reading development (LaBerge & Samuels, 1974; Perfetti, 1985). However, when predicting educational outcomes, it is difficult to isolate the influence of automatic word recognition from factors such as processing speed or knowledge of grapheme-phoneme correspondences. Cognitive models suggest automaticity could be achieved in different components of word recognition (e.g., by memorizing familiar words or by tuning the mappings between orthography, phonology or semantics). However, the contributions of each path have not been assessed. This study developed a new measure of automaticity to overcome these limitations and relates automaticity to standard outcomes. Subjects were 58 middle-school students (mean age = 13.2 years ± 8 months) with average to below-average reading comprehension. To assess automaticity with an accuracy-based measure, backward masking was used: On half the trials, items were presented for 90 ms and replaced by a nonlinguistic mask; on the other half it was presented unmasked to assess children’s knowledge of the word. This was instantiated in 3 experimental tasks developed to maximize reliance on different reading mappings. Automaticity, particularly in a task stressing meaning, predicted reading fluency over and above knowledge of the relevant grapheme-phoneme mappings. Automaticity in tasks involving nonwords also predicted fluency, suggesting the possibility of automaticity in orthography to phonology mappings. Variation in automatic word recognition did not predict reading comprehension or decoding. This link between automatic written word recognition and fluency has important implications for how automaticity may be targeted to improve reading outcomes.

Considerable debate in language acquisition concerns whether word learning is driven by domain-general (symbolically flexible) or domain-specific learning mechanisms. Prior work has shown that very young children can map objects to either words or nonlinguistic sounds, but by 20 months of age this ability narrows to only words. This suggests that although symbolically flexible mechanisms are operative early, they become more specified over development. However, such research has been conducted only with young children in ostensive teaching contexts. Thus, we investigated symbolic flexibility at later ages in more referentially ambiguous learning situations. In Experiment 1, 47 6- to 8-year-olds acquired eight symbol-object mappings in a cross-situational word learning paradigm where multiple mappings are learned based only on co-occurrence. In the word condition participants learned with novel pseudowords, whereas in the sound condition participants learned with nonlinguistic sounds (e.g., beeps). Children acquired the mappings, but performance did not differ across conditions, suggesting broad symbolic flexibility. In Experiment 2, 41 adults learned 16 mappings in a comparable design. They learned with ease in both conditions but showed a significant advantage for words. Thus, symbolic flexibility decreases with age, potentially due to repeated experiences with linguistic materials. Moreover, trial-by-trial analyses of the microstructure of both children's and adults' performance did not reveal any substantial differences due to condition, consistent with the hypothesis that learning mechanisms are generally employed similarly with both words and nonlinguistic sounds.

Adaptive behaviors are believed to be shaped by both positive (the strengthening of correct associations) and negative (the pruning of incorrect associations or the building of inhibitory associations) forms of associative learning. However, there has been little direct documentation of how these basic processes participate in the learning of rich associative networks that support cognitive behaviors like categorization. Although negative associative learning is an important component of theories of development, it is not clear whether it involves acquiring specific (experience-dependent) content or represents a more general aspect of (experience-expectant) development. The authors thus trained pigeons on a complex many-to-many learning paradigm previously established as an analog to human word learning. Pigeons learned to map 16 objects onto 16 distinct report tokens; the authors manipulated the amount of negative associative learning that could occur by restricting which tokens were available as incorrect options. In testing, accuracy was lower on trials with foils that had not been presented with a target than on trials with previously experienced foils. Moreover, when the correct token was withheld, pigeons preferred foils novel to the target object over previously experienced foils. A second experiment replicated these results and further found that these effects only emerged after some positive associations had been acquired. Findings indicate that the learning of rich associative networks does not depend solely on positive associative learning, but also on negative associative learning; this conclusion has important implications for basic learning theories in both animals and humans, as well as for theories of development. (PsycINFO Database Record

Word learning requires learners to bind together arbitrarily-related phonological, visual, and conceptual information. Prior work suggests that this binding can be robustly achieved via incidental cross-situational statistical exposure to words and referents. When cross-situational statistical learning (CSSL) is tested in the laboratory, there is no information on any given trial to identify the referent of a novel word. However, by tracking which objects co-occur with each word across trials, learners may acquire mappings through statistical association. While CSSL behavior is well-characterized, its brain correlates are not. The arbitrary nature of CSSL mappings suggests hippocampal involvement, but the incremental, statistical nature of the learning raises the possibility of neocortical or procedural learning systems. Prior studies have shown that neurological patients with hippocampal pathology have word-learning impairments, but this has not been tested in a statistical learning paradigm. Here, we used a neuropsychological approach to test whether patients with bilateral hippocampal pathology (N = 3) could learn new words in a CSSL paradigm. In the task, patients and healthy comparison participants completed a CSSL word-learning task in which they acquired eight word/object mappings. During each trial of the CSSL task, participants saw two objects on a computer display, heard one novel word, and selected the most likely referent. Across trials, words were 100% likely to co-occur with their referent, but only 14.3% likely with non-referents. Two of three amnesic patients learned the associations between objects and word forms, although performance was impaired relative to healthy comparison participants. Our findings show that the hippocampus is not strictly necessary for CSSL for words, although it may facilitate such learning. This is consistent with a hybrid account of CSSL supported by implicit and explicit memory systems, and may have translational applications for remediation of (word-) learning deficits in neurological populations with hippocampal pathology.