In two experiments (N = 179), we studied the effects of contextual similarity and training mode on the comprehension of new vocabulary. Participants were trained on new vocabulary in blocks of semantically similar, phonologically similar, or unrelated items. Each participant was trained through passive exposure, active comprehension, or active production. Same number of items were trained in clusters of 9 in Experiment 1 and clusters of 3 in Experiment 2, manipulating difficulty during training. Results showed a detrimental and persistent effect of semantic similarity, and a less robust effect of phonological similarity, both of which grew larger over time. We also found a negative and largely independent influence of production mode on learning, which, contrary to the similarity effect, shrank with time. Neither effect was modulated by difficulty at training time. These findings shed further light on the factors influencing new vocabulary learning and open new avenues for larger-scale and classroom-level studies.
more »
« less
Effect of similarity and training experiences on new vocabulary learning
In two experiments (N = 179), we studied the effect of contextual similarity and training mode on new vocabulary learning. Adult participants were trained on blocks of items that were semantically similar, phonologically similar, or unrelated to one another. Each participant was trained through passive exposure, active comprehension, or active production of the new vocabulary. Exp 1 trained items in clusters of 9, whereas Exp 2 trained the same number of items in clusters of 3. Exp 2 also assessed delayed retention 48-72 hours after training. Results showed a robust and negative impact of semantic similarity and production mode on vocabulary learning. A detrimental effect of phonological similarity was only observed in the delayed test. These results suggest that adding the challenge of resolving similarity-induced competition and articulating the word-form negatively impacts the quick acquisition of new vocabulary.
more »
« less
- Award ID(s):
- 2346989
- PAR ID:
- 10523494
- Editor(s):
- Samuelson, L K; Frank, S; Toneva, M; Mackey, A; Hazeltine, E
- Publisher / Repository:
- Proceedings of the 45th Annual Conference of the Cognitive Science Society.
- Date Published:
- ISSN:
- 1069-7977
- Format(s):
- Medium: X
- Location:
- UC Merced
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Purpose:Numerous tasks have been developed to measure receptive vocabulary, many of which were designed to be administered in person with a trained researcher or clinician. The purpose of the current study is to compare a common, in-person test of vocabulary with other vocabulary assessments that can be self-administered. Method:Fifty-three participants completed the Peabody Picture Vocabulary Test (PPVT) via online video call to mimic in-person administration, as well as four additional fully automated, self-administered measures of receptive vocabulary. Participants also completed three control tasks that do not measure receptive vocabulary. Results:Pearson correlations indicated moderate correlations among most of the receptive vocabulary measures (approximatelyr= .50–.70). As expected, the control tasks revealed only weak correlations to the vocabulary measures. However, subsets of items of the four self-administered measures of receptive vocabulary achieved high correlations with the PPVT (r> .80). These subsets were found through a repeated resampling approach. Conclusions:Measures of receptive vocabulary differ in which items are included and in the assessment task (e.g., lexical decision, picture matching, synonym matching). The results of the current study suggest that several self-administered tasks are able to achieve high correlations with the PPVT when a subset of items are scored, rather than the full set of items. These data provide evidence that subsets of items on one behavioral assessment can more highly correlate to another measure. In practical terms, these data demonstrate that self-administered, automated measures of receptive vocabulary can be used as reasonable substitutes of at least one test (PPVT) that requires human interaction. That several of the fully automated measures resulted in high correlations with the PPVT suggests that different tasks could be selected depending on the needs of the researcher. It is important to note the aim was not to establish clinical relevance of these measures, but establish whether researchers could use an experimental task of receptive vocabulary that probes a similar construct to what is captured by the PPVT, and use these measures of individual differences.more » « less
-
null (Ed.)Abstract Compared to blocked practice, interleaved practice of different tasks leads to superior long-term retention despite poorer initial acquisition performance. This phenomenon, the contextual interference effect, is well documented in various domains but it is not yet clear if it persists in the absence of explicit knowledge in terms of fine motor sequence learning. Additionally, while there is some evidence that interleaved practice leads to improved transfer of learning to similar actions, transfer of implicit motor sequence learning has not been explored. The present studies used a serial reaction time task where participants practiced three different eight-item sequences that were either interleaved or blocked on Day 1 (training) and Day 2 (testing). In Experiment 1, the retention of the three training sequences was tested on Day 2 and in Experiment 2, three novel sequences were performed on Day 2 to measure transfer. We assessed whether subjects were aware of the sequences to determine whether the benefit of interleaved practice extends to implicitly learned sequences. Even for participants who reported no awareness of the sequences, interleaving led to a benefit for both retention and transfer compared to participants who practiced blocked sequences. Those who trained with blocked sequences were left unprepared for interleaved sequences at test, while those who trained with interleaved sequences were unaffected by testing condition, revealing that learning resulting from blocked practice may be less flexible and more vulnerable to testing conditions. These results indicate that the benefit of interleaved practice extends to implicit motor sequence learning and transfer.more » « less
-
This study describes the development and initial validation of a mathematics-specific spatial vocabulary measure for upper elementary school students. Reviews of spatial vocabulary items, mathematics textbooks, and Mathematics Common Core State Standards identified 720 mathematical terms, 148 of which had spatial content (e.g., edge). In total, 29 of these items were appropriate for elementary students, and a pilot study (59 fourth graders) indicated that nine of them were too difficult (< 50% correct) or too easy (> 95% correct). The remaining 20 items were retained as a spatial vocabulary measure and administered to 181 (75 girls, mean age = 119.73 months, SD =4.01) fourth graders, along with measures of geometry, arithmetic, spatial abilities, verbal memory span, and mathematics attitudes and anxiety. A Rasch model indicated that all 20 items assessed an underlying spatial vocabulary latent construct. The convergent and discriminant validity of the vocabulary measure was supported by stronger correlations with theoretically related (i.e., geometry) than with more distantly related (i.e., arithmetic) mathematics content and stronger relations with spatial abilities than with verbal memory span or mathematics attitudes and anxiety. Simultaneous regression analyses and structural equation models, including all measures, confirmed this pattern, whereby spatial vocabulary was predicted by geometry knowledge and spatial abilities but not by verbal memory span, mathematics attitudes and anxiety. Thus, the measure developed in this study helps in assessing upper elementary students' mathematics-specific spatial vocabulary.more » « less
-
null (Ed.)Abstract Background Hidden Markov models (HMM) are a powerful tool for analyzing biological sequences in a wide variety of applications, from profiling functional protein families to identifying functional domains. The standard method used for HMM training is either by maximum likelihood using counting when sequences are labelled or by expectation maximization, such as the Baum–Welch algorithm, when sequences are unlabelled. However, increasingly there are situations where sequences are just partially labelled. In this paper, we designed a new training method based on the Baum–Welch algorithm to train HMMs for situations in which only partial labeling is available for certain biological problems. Results Compared with a similar method previously reported that is designed for the purpose of active learning in text mining, our method achieves significant improvements in model training, as demonstrated by higher accuracy when the trained models are tested for decoding with both synthetic data and real data. Conclusions A novel training method is developed to improve the training of hidden Markov models by utilizing partial labelled data. The method will impact on detecting de novo motifs and signals in biological sequence data. In particular, the method will be deployed in active learning mode to the ongoing research in detecting plasmodesmata targeting signals and assess the performance with validations from wet-lab experiments.more » « less
An official website of the United States government

