Psycholinguistics of Bilingualism

Madison Allardyce, 2nd year

Comparing Working Memory and Long-Term Memory

1. Introduction

In this study I explore the effects and differences between memory systems. Simply, memory consists of the remembrance and recollection of information (Klein, 2015). However, from a more academic approach, the concept of memory involves three major steps:

(1) learning – new information is gathered and encoded into our memory,

(2) storage – the encoded information is then stored to maintain continuity,

(3) retrieval – when we decide to remember the piece of information, we retrieve it from our memory (Klein, 2015). For my research, I specifically investigate the use and comparisons between working memory and long-term memory.

2. Literature Review

Baddeley (2010, 2012) describes working memory as the temporary storage of small amounts of information over brief periods of time. Working memory is located in the pre-frontal cortex of the brain (Conway et al., 2005). This is where complex goal-directed human behaviour is studied (Conway et al., 2005). Within this system there are two main components: domain specific skills, and domain general capability (Conway et al., 2005). Domain specific skills include practices such as grouping and rehearsal (Conway et al., 2005). These practices are also found when using short term memory (Baddeley, 2010). Short term memory describes the temporary storage of information; however, the role of working memory goes beyond this simple storage (Baddeley, 2010, 2012). The role of working memory includes general cognitive control and executive attention, which provides techniques that can be applied practically to activities (Conway et al., 2005; Baddeley, 2010). This means that working memory is domain general (Conway et al., 2005). Baddeley and Hitch’s model (1974) explains that working memory is controlled by the central executive, which is where information is stored (Baddeley, 2010, 2012). This element is important during complex activities as it allows the individual to switch attention and concentrate on different stimuli (Conway et al, 2005). Within the central executive, there are three structural components where information is stored (Baddeley, 2010, 2012). This element is important during complex activities as it allows the individual to switch attention and concentrate on different stimuli (Conway et al, 2005). Within the central executive, there are three structural components where information is processed (Turner & Engle, 1989). First, there is the phonological loop (Baddeley, 2010, 2012). This is where speechlike information is stored and where (sub)verbal rehearsal processing is achieved (Baddeley, 2010). It is suggested that it is more challenging to recall a sequence of words when the words contain similar sounds (Baddeley, 2010). Then there is the visuospatial sketchpad, which processes visual and spatial semantics in real life and reading (Baddeley, 2010, 2012). Finally, there is the episodic buffer, which was added later in Baddeley and Hitch’s (1974) model (Baddeley, 2010). This component temporarily stores visual and auditory information and is linked to long term memory (Baddeley, 2010, 2012).

I chose to use an operation span task (OSPAN) to measure working memory capacity. OSPAN tasks are used to predict the level of complex cognition of individuals and their memory performance (Conway et al., 2005). An OSPAN task consists of two tasks: a word or digit span activity (in this study a word span) in accompaniment with a secondary task (in this study a maths task) (Turner & Engle 1989). These tasks were originally designed from Baddeley and Hitch’s (1974) theory of working memory, whereby they identify the importance of a memory system that can temporarily store information whilst other mental activities are taking place (Conway et al., 2005). Participants are shown sequences of maths equations, which are answered with a true/false answer, followed by a word, usually a concrete noun with 4-6 letters, to remember (Turner & Engle, 1989). Once the sequence is complete the participant records the words they can remember in order that they appeared. The combination of the ‘to-beremembered’ target stimuli (word span) and a demanding processing task (maths equations) stops participants using memory strategies, including rehearsal and grouping, allowing researchers to grasp a full picture of their participants working memory capacity (Conway et al., 2005). The results of these studies highlight that there is no significant difference in performance between the sexes, working memory decreases as age increases, and working memory is lower when a participants’ second language (L2) is used in the experiment (Conway et al., 2005; Baddeley 2012).

The other task included in my study is a continuous visual memory task (CVMT) which measures long term memory (Paolo, 1998). Within long term memory there are two main systems: declarative memory and procedural memory (VanPatten et al., 2020). The declarative memory system is located in the hippocampus and other medial temporal lobe (MTL) (Ullman, 2016). This area of the brain is where: language is learned, knowledge and experiences and linked together, and where information and events are remembered (Ullman, 2016; VanPatten et al., 2020). More specifically within the MTL, the perirhinal cortex contributes to object recognition, the para-hippocampal cortex contributes to spatial recognition, and the hippocampus contributes to higher-level concept recognition (Ullman, 2016). The procedural memory system is based in the frontal, basal-ganglia circuits (Ullman, 2016). Processes including learning motor and cognitive skills and learning to predict probabilistic outcomes are done in this area of the brain. Declarative memory acquires knowledge quicker, therefore explicit instructions and attention on stimuli increases learning in this system (Ullman, 2016). However, procedural memory processes knowledge quicker, therefore implicit, complex instructions increase learning in this system (Ullman, 2016). Research has proven that both memory systems decline through age as memory plateaus after adolescence and procedural memory decreases in adulthood (VanPatten et al., 2020). Ullman (2016) discovered that women rely more on declarative memory because higher levels of oestrogen result in better declarative memory. Due to this, men tend to use more procedural memory (Ullman, 2016). Research also shows that early language learners (L2) rely more on procedural memory, whereas later language learners rely on declarative memory (Ullman, 2016).

CVMT measures visual learning and declarative memory (Paolo, 1998). It removes the motor component linked with drawing tasks and decreases verbal labelling that may appear on tests involving simple geometric shapes (Paolo, 1998). In a continuous visual memory task, a series of shapes appear on a screen (in this study 112 pictures were shown). Participants are required to state whether the picture is new or old; this promotes the use of their long-term memory (Paolo, 1998). Unlike Ullman’s(2016) discoveries CVMT are not influenced by gender or education, which is supported by Trahan and Larrabee’s (1988) test model (Paolo, 1998). However, Paolo’s study (1998) showed the CVMT results were largely influenced by age. Furthermore, PiliMoss et al. (2019) identified that declarative learning is the main predictor of accuracy in comprehension tasks.

3. Methodology

The first task, to conduct my study, was to develop a research question: How do the effects of working and long-term memory differ, in relation to various demographic factors?

After this, I began to create my experiment. I used gorilla software to clone the OSPAN and CVMT tasks into my experiment (Gorilla Experiment Builder, 2016). Furthermore, I provided an information sheet, consent form, and background questionnaire at the beginning of the experiment to provide the participants with information about the experiment, choice to participate, and give information about themselves - which would later be compared.

Due to the cloning, I made alterations to each section in order for them to correspond with what specifically I was investigating. For example, in the questionnaire I included questions about the participants’ age, sex, education, first language (L1), and potential second language (L2). Moreover, I changed the OSPAN task to consist of 42 sequences, three sets of 2-5 sequences sorted randomly, and ensured that 50% of the maths equations were correct (Turner & Engle, 1989).

Once my experiment was complete, I sent the experiment to multiple friends and family members via various social media platforms and email. Overall, 30 anonymous participants were collected and categorised accordingly:

Figure 3.1

Sex of participants

12

18

Male Female

60% of participants were female and 40% were male.

3.2

Age of participant

The age of the participants ranged between 19-75. I separated the participants’ ages into 4 groups to later compare.

3.3

Participant education

Undergraduate degree Postgraduate degree Other

School until age 16 School until age 18

Most of the participants have an undergraduate degree (30.3%).

The other forms of education by the participants include: RMN and specialist practitioner diploma level, Registered Nurse qualified 1991 pre-degree, and City and Guilds C&G 015 in agricultural engineering.

Majority of the participants’ first language is English (93.3%).

30% of the participants have reported that they can speak another language.

4. Results

4.1 OSPAN Task

Table 4.1.1

OSPAN Task - Correct Words

Table 4.1.1 shows the results from the target stimuli in the OSPAN task. The y-axis represents the words in the task (42) and the x-axis shows the results from the participants. The highest participants scored 41 (97%) and the lowest scored 4 (10%). The average score of the participants was 31 out 42 (74%).

Task - Maths Equations

Table 4.1.2 highlights the results from the secondary processing task in the OSPAN task. The y-axis shows the number of equations in the task and the x-axis represents the results from the participants. The highest score was 42 (100%) and the lowest score was 22 (52%). The average score of the participants was 37 out of 42 (89%).

4.2 CVMT Task

Table 4.2.1 displays the results from the continuous visual memory task. The y-axis shows the number of pictures that appeared in the task (the total number was 112 therefore the axis was rounded to 120). The x-axis represents the results from the participants. The highest score was 98 (87%) and the lowest score was 49 (43%). The average score of the participants was 74 out of 112 (66%).

4.3. Relationship between memory tasks and demographic factors

Table 4.3.1 demonstrates the relationship between the memory tasks and the sex of the participants. The y-axis represents the accuracy of the tasks, and the x-axis shows the sex’s results of each task. It is clear that the female participants outperformed the males in both tasks. However, the difference between the sexes is not significant – 2.98% (OSPAN) and 4.27% (CVMT).

Table 4.3.2

Table 4.3.2 displays the relationship between the memory tasks and the age of the participants. 35-50 group performed best in the OSPAN task and 19-34 group performed best in the CVMT.

Table 4.3.3 highlights the relationship between the memory tasks and the participants’ L2 ability. On both tests participants who could speak an L2 performed better – significantly in the OSPAN task and slightly in the CVMT (note that the results from the OSPAN task only include the data from the word span).

5. Analysis and Discussion

From the results of the task, it is clear that there are differences between the memory systems in regard to the demographic factors that I compared. Table 4.3.1 shows that female participants outperformed males in both tasks. My results from the OSPAN task contradict Baddeley’s ideology (2010) that the task is not influenced by gender. However, the CVMT results support the claims proposed by Ullman (2016). Females usually rely on their declarative memory during long-term memory tasks due to their level of oestrogen (Ullman, 2016). Due to this, female participants are able to acquire knowledge at a faster rate, even after little exposure to the stimuli, therefore are more likely to perform better on the CVMT (Ullman, 2016). This idea opposes Paolo’s study (1998) whereby sex does not have an influence on the results. To resolve this, another CVMT test can be conducted, with different participants, to identify whether sex has an influence on long-term memory.

Evidence from the scholars, in the literature review, agree that the largest influence on memory is age. Conway et al. (2005) explained that working memory declines with age, and Ullman (2016) found that declarative memory plateaus during adolescence and begins to decline in adulthood. Therefore, it can be predicted that younger participants have a greater memory capacity than older participants. However, from the results of Table 4.3.2, this is not the case. Whilst the 67+ group had the lowest score on the OSPAN task (53.96%), which supports the claim made by Conway et al. (2005), on average the oldest group performed the second best on the CVMT test (67.26%). Paolo’s study (1998) included 177 participants with the age range of 60-94 and found that as the age increased the results of that task, and declarative memory capacity decreased. In order to make my test results more reliable, next time I will target more participants of an older generation. One way this can be achieved is to publish my experiment on different platforms, as older participants may not use social media.

Table 4.3.3 highlights the influence of knowing a second language on the memory tasks. In both tasks, participants who stated they knew a second language performed better than those who did not. It has been discovered that there are links between working memory and declarative memory, due to the same frontal brain structures used when the systems are activated (Ullman, 2016). As Pili-Moss et al. (2019) stated, declarative memory promotes accuracy in comprehension tasks. This could answer why participants with an L2 performed better on the OSPAN and CVMT tasks. This study did not explore how the memory systems were affected when participants were using their L2 to complete the tasks, therefore it would be interesting to see if Baddeley’s

(2012) claims that working memory is lower in participants’ L2 are accurate.

Whilst the main purpose of the study was to compare working memory task and the long-term memory task, it is also worth comparing the two activities in the OSPAN task. Table 4.1.3 displays that the participants performed better on the secondary task compared to the word span task. One limitation of the OSPAN task is that participants could guess the true/false questions in order to remember the target stimuli (Conway et al., 2005). However, this is not the case from this experiment. Therefore, the results from the word span task accurately represent the use of the participants working memory over their short-term memory. As well as this, the results from table 4.1.1 and 4.1.2 show that participants who recall the most target words perform better on the processing task (Conway et al., 2005). One way to test the reliability of the OSPAN results is to compare them to other span tasks (digit span tasks and reading tasks) (Conway et al., 2005). Even though I have chosen to use a mathematical secondary task, reliability can still be achieved between word and maths scores (Conway et al., 2005).

6. Conclusion

Overall, in this study it has been identified how various demographic factors affect our memory systems. The factor that has the most impact on memory is age (Conway et al., 2005; Paolo, 1998). However, it is interesting to discover how aspects of predetermined human anatomy (i.e. hormones) can cause significant differences between participants’ results. For future research, it would be compelling to explore how additional learning needs (dyslexia) affect the performance of the memory systems (Ullman, 2016).

If I were to perform this study again, I would collect the reaction times of the participants whilst they were performing the tasks. This would further prove if the results were reliable.

References

Baddeley, A. (2010). Working memory. Current Biology, 20(4), R136–R140. https://doi.org/10.1016/j.cub.2009.12.014 https://doi.org/10.1146/annurev-psych-120710- 100422

Baddeley, A. (2012). Working Memory: Theories, Models, and Controversies. Annual Review of Psychology, 63(1), 1–29.

Baddeley, A. D., & Hitch, G. (1974). Working Memory. Psychology of Learning and Motivation, 8(1), 47–89. https://doi.org/10.1016/s0079-7421(08)60452-1 https://doi.org/10.3758/bf03196772 https://app.gorilla.sc/admin/home https://doi.org/10.1002/wcs.1333 https://doi.org/10.1016/s0887-6177(97)00018-8 https://doi.org/10.1017/s1366728919000543 https://www.scirp.org/(S(351jmbntvnsjt1aadkposzje))/ref erence/ReferencesPapers.aspx?ReferenceID=1281327

Conway, A. R. A., Kane, M. J., Bunting, M. F., Hambrick, D. Z., Wilhelm, O., & Engle, R. W. (2005). Working memory span tasks: A methodological review and user’s guide. Psychonomic Bulletin & Review, 12(5), 769–786.

Gorilla Experiment Builder. (2016). Gorilla.

Klein, S. B. (2015). What memory is. Wiley Interdisciplinary Reviews: Cognitive Science, 6(1), 1–38.

Paolo, A. (1998). Continuous Visual Memory Test Performance in Healthy Persons 60 to 94 Years of Age. Archives of Clinical Neuropsychology, 13(4), 333–337.

Pili-Moss, D., Brill-Schuetz, K. A., Faretta-Stutenberg, M., & Morgan-Short, K. (2019). Contributions of declarative and procedural memory to accuracy and automatization during second language practice (*). Bilingualism: Language and Cognition, 1-13.

Trahan, D.E. and Larrabee, G.J. (1988) Continuous Visual Memory Test. Psychological Assessment Resources, Odessa, FL.

Turner, M. L., & Engle, R. W. (1989). Is working memory capacity task dependent? Journal of Memory and Language, 28(2), 127–154. https://doi.org/10.1016/0749596x(89)90040-5 https://doi.org/10.1016/b978-0-12-407794-2.00076-6 https://ebookcentral.proquest.com/lib/swanseaebooks/detail.action?pqorigsite=primo&docID=6120993#

Ullman, M. T. (2016). The Declarative/Procedural Model. Neurobiology of Language, 953–968.

VanPatten, B., Keating, G. D., & Wulff, S. (Eds.). (2020). Theories in second language acquisition: An introduction. Taylor & Francis Group.