Wednesday, April 19, 2017

What’s statistical about learning? Insights from modelling statistical learning as a set of memory processes

Statistical learning is a term used to describe the discovery of patterns within incoming information, and has been widely applied to language learning. Language is composed of many different, and learnable, patterns. For example, knowing that the two syllables “ba” and “nan” will be followed by “a”, to make the word “banana”. Or, learning the pattern “is verb-ing”, such as “is running”, “is hopping” or “is skipping”. Infants are sensitive to these patterns when learning language, and considerable research over the last two decades has highlighted statistical learning as one of the primary ways in which humans acquire language.

This paper distinguished between two types of patterns, or statistics, learned via statistical learning. The first are conditional statistics, which refer to the likelihood of two or more elements co-occurring, such as syllables or words. Conditional statistics are useful because they go beyond the simple frequency of co-occurrence. For example, given the phrase “the dog”, you know they are two distinct words because of the low conditional relationship between them; Although “the dog” is a frequent phrase, the conditional relationship between “the” and “dog” is low because the word “the” occurs in combination with many other words. The other type of statistic is known as a distributional statistic, which refers to how the variability of items stored in memory shapes what is subsequently stored within memory. For instance, if a newly encountered item matches something that is already stored in memory, it won’t be stored as a unique item. However, if this item is distinct from what is already stored in memory, it will be stored as a unique item. Learning the distributional regularities within a language plays an important role in learning the phonemes within your native language, and other patterns across language.

The statistical learning of conditional and distributional statistics are natural extensions of processes we know to exist in memory more generally. These memory processes include recognizing familiar items already stored in memory, gradually forgetting items stored in memory if they are not re-encountered, and interference between similar items stored in memory. Looking at statistical learning from the perspective of memory has a couple of important implications. First, it connects statistical learning, and thereby language learning, to other types of learning. Second, it gives and explanation as to why the ability to learn a language tends to decline with age. If statistical learning is linked to memory processes, and memory changes with age, changes in memory over the lifespan may help explain why language learning tends to decline with age. Exploring the connection between statistical learning and memory is important for theories of language acquisition because it connects language acquisition with what we know about human cognition.  

Blogger: Nicolette is a Psychology Ph.D. student, supervised by Dr.s Lisa Archibald and Marc Joanisse

Friday, February 10, 2017

Skills underlying mathematics: The role of executive function in the development of mathematics proficiency

Reading difficulties (poor literacy) are commonly associated with social and academic challenges. Only recently has the importance of math skills for economic well-being been recognized. Recent research suggests that numerical skills and more general cognitive processes like executive functions influence a child’s success in mathematics.  Executive functions (EF) refer to the cognitive processes that enable us to control and coordinate purposeful, goal-oriented thought and action. Three classes of EF have been identified: the ability to suppress distracting information (inhibition), the ability to think flexibly (shifting), and the ability to simultaneously hold and manipulate information (working memory). This paper reviewed the evidence linking executive functions and mathematic ability.
Correlational studies have consistently shown a relationship between working memory in mathematical performance across a range of age groups. What is particularly important is that this variance cannot be explained by other variables such as language skills, reading skills, or intelligence. Other studies have examined this relationship more directly, and shown that math performance declines when participants are engaged in working memory tasks. A small number of studies have attempted to train Executive Function skills to determine whether this will lead to improvements in learning mathematics. While training programs have been effective in enhancing working memory, there is currently no consistent evidence that they in turn improve mathematical achievement.
            Understanding the role of EF skills in mathematical performance is essential for parents and teachers. A greater awareness of the relationship between EF skills and learning mathematics may allow educators to better facilitate children’s learning and performance of mathematics in an academic environment.

Blogger: Natalie Pitch is an undergraduate currently completing her honours thesis in psychology under the supervision of Lisa Archibald

Wednesday, January 25, 2017

Working Memory in Children with Learning Disabilities in Reading Versus Spelling: Searching for Overlapping and Specific Cognitive Factors

The written language (orthography) of English is considered opaque because the letters in a word don’t always correspond to the sounds of that word when spoken. Of course, the word ‘AND’ is transparent: It has three letters, each of which correspond as expected to the common sounds those letters make. But, the word ‘WERE’ is opaque: The letters don’t correspond all that well to the sounds in the spoken word. There are lots of these ‘irregular words’ in English writing, so English orthography is considered opaque. Importantly, opaque orthographies are difficult to read because the words on the page don’t always predict the sounds in the word, AND spell because the sounds you want to write might correspond to different possible letter patterns. As would be expected, then, many studies demonstrate that English children who have difficulty reading, also have difficulty spelling.

German orthography, on the other hand, is considered transparent because the letters in the written words correspond well to the sounds of that word when spoken. That makes reading easier: You can sound out the corresponding sounds in the written word to decode the word. Nevertheless, there can be different ways to spell a sound in German (e.g., /ee/ can be spelled ‘ee’ or ‘eh’). As a result, spelling requires more processing of the individual sounds in a word, or more phonological processing.  Branderburg et al. reasoned that reading and spelling problems may not always co-occur in German children, and that different impairments might be associated with different cognitive processes.

The researchers compared the performance of 3rd grade children with either reading disorder, spelling disorder, reading and spelling disorder, or no reading and spelling disorder (control group) on measures tapping phonological processing (short-term memory; speaking rate) or working memory (the ability to store and process phonological information). The results revealed phonological short-term memory impairments in children with spelling disorder compared to the control group, and working memory impairments in children with reading disorder compared to the control group.

The results provide further support for the important role of phonological processing in supporting literacy, especially when there is some ambiguity in the correspondence between letters and sounds. The findings also highlight the cognitive demands of reading possibly related to supporting reading comprehension processes.

Blogger: Lisa Archibald