Language ability, executive functioning and behaviour in school-age children.

Karasinski, C. (2015). Language ability, executive functioning and behaviour in school-age children. International Journal of Language & Communication Disorders, 50(2), 144–150.

Executive functions are the complex thinking skills that enable us to use self-control, set goals, track our progress while executing those goals, and adjust our strategies if necessary. We use our executive functions whenever we solve problems or break away from our usual routine. The three most commonly studied components of executive function are inhibition, working memory, and task switching. This paper sought to examine the connections between executive function, language, and behaviour, in school-age children.

A total of 42 children (8–11 years) with a range of abilities completed measures of language, nonverbal intelligence, and executive functioning. In the executive function measure, children were required to sort pictures according to a changing rule. Parents also completed questionnaires about each child’s attention, behaviour, and executive function abilities. Data were analyzed first by looking for correlations between measures, and second by testing possible predictors of language, attention, and behaviour ratings.

Results showed a tenuous connection between language ability and executive functioning. Although both the executive function measures correlated with language, they did not predict language ability as well as nonverbal intelligence did. Behaviour was best predicted by the parent’s responses to questions about their child’s ability to inhibit responses. This finding is consistent with other research showing a relation between poor inhibition and attention difficulties.

Blogger: Laura Pauls, PhD Candidate

Learning and Long-Term Retention of Large-Scale Artificial Languages

Frank, M. C., Tenebaum, J. M., Gibson, E. (2013). Learning and long-term retention of large-scale artificial languages. PLoS ONE 8(1): e52500. doi:10.1371/ journal.pone.0052500

Studying the way that a person learns an artificial language, a made up language never seen before, is a useful tool in helping researchers understand the important cues to natural language learning. A shortcoming with typical artificial language learning studies is that the languages have been quite different from natural languages – usually the number of words in the language is quite small, and each word occurs equally often. In order to “scale up” the artificial language used in the current experiment, the researchers adopted an artificial language with a 1,000-word vocabulary. Word frequency was also manipulated: Words occurred as few as 10 times, to as many as 8,000 times. Unique from the typical lab experiment, the participants had the artificial language downloaded on personal iPods so that their 10 hours of exposure could occur throughout their everyday activities, like during their daily commute or exercising. Importantly, the only cue to segment or learn words from the artificial language was the probability of syllable co-occurrences – syllables that belonged together within a word were more likely to occur together than syllables that spanned a word boundary. This cue exists in natural languages, and may help language learners learn word units over in addition to other cues such as pauses or stress patterns. 

Following 10 hours of listening to the large-scale artificial language, participants were tested on their ability to identify words from the language immediately after the 10 hours had been completed, 1-2 months after, or 3 years after. Participants were able to identify words from the language immediately after listening for 10 hours, and scored just as well 1-2 months after, with higher scores for high than low frequency words. At the end of 3 years, participants still were able to identify high frequency words from the artificial language. Although they did not show retention of low frequency words, this is an incredibly impressive finding as the words from the artificial language were nonsense, meaningless words. This study demonstrated that language learners could successfully segment words from an artificial language with a large vocabulary, and that the retention of newly learned words depended on word frequency. These processes might support the learning of second languages. For example, you might remember words from a second language you’ve studied in the past, especially the ones you heard most often. The results suggest, too, that listening to a new language for several hours might help you learn something about the words in that language.

Blogger: Nicolette Noonan, PhD student with Drs. Lisa Archibald and Marc Joanisse, and coordinator of the Canadian SLP blog.

A Culturally and Linguistically Responsive Vocabulary Approach for Young Latino Dual Language Learners

Mendez, L.I., Crais, E.R., Castro, D.C. & Kainz. (2015). A culturally and linguistically responsive vocabulary approach for young Latino Dual Language Learners. Journal of Speech, Language, and Hearing Research, 58, 93-106. doi: 10.1044/2014_JSLHR-L-12-0221.

Dual Language Learners (DLLs) know different words in each of their languages; as a result, they know fewer words in any one language than their monolingual peers.

The present study examined the impact of the language of vocabulary instruction in supporting the ability to understand English vocabulary in DLL from low income families attending Latino preschools. Instruction using only English as the language of vocabulary instruction was compared to using both Spanish (first language; L1) and English (second Language; L2).  

Spanish-speaking preschoolers were randomly assigned to either vocabulary instruction group. In each group, DLLs were presented with 30 words using similar shared reading instruction. In the dual language instruction group, the target words were presented first in L1 (Spanish) then in L2 (English), while in the single language group the target words were presented in English only.    

The main finding was that DLLs demonstrated higher vocabulary acquisition in English and Spanish when in the dual than single language instruction group. This result suggests that presenting English target words in L1 first might help DLLs to use the lexical and conceptual knowledge from L1 to facilitate learning in L2. Importantly, using both L1 and L2 as languages of vocabulary instruction supports language development in DLLs.

Blogger: Areej Balilah, PhD Candidate  

Domain-specific knowledge and why teaching generic skills does not work.

Tricot, A., & Sweller, J. (2014). Domain-specific knowledge and why teaching generic skills does not work. Educational Psychology Review, 26, 265-283.

Domain-general skills are skills that can be used to solve any problem in any area. Tricot and Sweller argue that these skills are acquired automatically for biological evolutionary reasons and so are unteachable. Examples of such biologically primary knowledge include learning to listen and speak, learning to recognize faces, engage in social relations, or basic number sense.

Domain-specific knowledge, on the other hand, refers to memorized information that can lead to action permitting specified task completion over indefinite periods of time. Tricot and Sweller argue that acquiring domain-specific knowledge requires learning of specific rules for solving a problem (e.g., an equation), and the moves associated with this state (e.g., when the equation must be applied). The authors consider domain-specific information to be teachable aspects of problem solving skills. The acquisition of this domain-specific or biologically secondary knowledge is viewed as heavily dependent on the prior acquisition of primary knowledge. Tricot and Sweller go on to review several lines of evidence showing that expert knowledge in a specific domain does not yield expertise across domains, but can be applied within the domain to advantage.

The authors provide two examples of instructional strategies that follow from their views on the acquisition of domain-general (biologically primary) and domain-specific (biologically secondary) information. (1) The worked example effect. Novice learners benefit from studying worked example formats. Studying a worked exampled reduces the amount of extraneous (unnecessary) work being done by working memory to generate a large set of potential solutions to a problem. By seeing the solution, working memory resources can be devoted to learning to recognize the problem and its associated moves. (2) The expertise reversal effect. Reviewing worked examples is a disadvantage for expert learners probably because working memory resources are devoted to information the expert learner has already acquired. Instead, expert learners need practice at solving the problems so that they can more automatically recognize the relevant problems and their associated moves.

Blogger: Lisa Archibald