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Memory and Cognition, Research Proposal Example

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Research Proposal

The Rationale of The Study

Research geared towards establishing the difference between memory and cognition has attracted the interests of different scholars across various disciplines, particularly psychology and philosophy. As a process, cognition leverages one’s existing knowledge to generate related but novel concepts using skills such as attention, memory evaluation, reasoning, problem-solving decision making, comprehension, language production, and judgment. On the other hand, memory encompasses one’s ability to encode, store, and retrieve information. Previous studies have proved that human brains do not operate in complete blank slates but are predisposed to environments that help them learn and organize information Taylor & Workman (2021). Taken together, cognition and memory are crucial for covering the human memory and learning processes and how each of the processes described above relates to learning. Memory and cognition constitute an important aspect of cognitive psychology which has several benefits for mental health practice.

The topic of memory and cognition is crucial because it helps researchers understand how human beings process information and gain deeper insights into the working framework of the brain. Besides, understanding the relationship between human cognitive capabilities and memory functionality helps psychologists mechanize new approaches for helping individuals with psychological dysfunctions and limitations (Ding, Liu, & Yang, 2017). One such area in which the study on memory and cognition is important is the rising incidence of attention disorders such as autism and dyslexia. Yet, attention to such mental issues as attention and problem solving is still minimal, especially among children (Zivoder et al., 2018). This is because of such anomalies as autism and dyslexia, despite their potential implications. They are interwoven into the fabrics of our day-by-day lives that most people fail to recognize their significance.

However, cognitive psychology professionals who have specialized in memory and cognition have produced solutions to individuals who have previously experienced issues in mental processes (Smith, 2017). For instance, the knowledge that short-term memory only lasts 20 to 30 seconds with a holding capacity of five to nine items has led to the development of rehearsal activities which helps transfer the information to long-term memory in children with dyslexia and autism (Ferreira et al., 2015). With the outcome of this research experiment, the researcher hopes to contribute valuable knowledge on various aspects and processes inherent in human memory with cognition and how dyslexia and autism in children affect these processes.

Overall Aim/Objectives

The current experiment investigates the extent to which learning disabilities such as dyslexia and autism affect memory and cognition among school-going children. How all the three types of memory, sensory, short-term, and long-term memory, interact with one’s cognitive capabilities constitutes the processes of learning, which may be impaired by learning disorders, particularly autistic spectrum disorders (Alkoby et al., 2018). It has already been determined that our ability to recall a word is dependent on the meaningfulness and concreteness’ of such words to the individual in question (Mkrtychian et al., 2018). As young learners solve problems and make plans, they practice cognitive flexibility, which enables them to maneuver and shift from one perspective, goals, or tasks in the face of changing situations (Weber, 2020). While meaningfulness reflects how important the word is to the individual, concreteness refers to the ability of the word to form a mental image of the individual (Pollock, 2018). Particularly, the study aims to determine the extent to which memory relates to cognition by determining how factors such as concreteness and meaningfulness determine memory. The research objective is to determine the relationship between memory and word concreteness and meaningfulness using letters.

Literature Review

Concrete thinking and concrete learning have been investigated from different perspectives, including language learning among children with learning disabilities. The dual coding theory has been proposed to explain the concreteness effect. The theory posits that a verbal-based system exists upon which an imagery-based system that regulates our semantic memory operates (Alkoby et al., 2018).  The outcome of this process is the addictive effect with which individuals regard concrete words (Norriss,2017). Aside from the theory, the concreteness effect has been explained using the context availability hypothesis (Taylor et al., 2019). The hypothesis explains that the concreteness of a word potentially emerges from the availability of contextual content within it, which is retrieved upon the appearance of a stimulus (Joseph et al., 2019). In the converse, the absence of contextual information in abstract words gives them their processing disadvantage.

The mechanisms with which neurodevelopmental problems like autism and dyslexia impair language learning have been investigated over the years, and various suggestions posited. It is known that neurodevelopmental challenges challenge how the brain responds to input from the environment, including detecting pattern changes necessary for a child’s learning process (Boorse et al., 2019). Previous findings suggest that autism or dyslexia development begins in childhood with normally developing brains; they still have the capabilities to separate speech from nonspeech content, relate one word to another, and link words with visible actions or gestures, and differentiate between sentences and other discoursal forms (Chojnicka & Wawer, 2020). However, for children with developed symptoms of neurodevelopmental challenges, particularly ASD, mastering and retaining concrete content to speech and nonspeech content becomes a problem (Weber, Ethoferab, & Ehlis, 2020). The outcome often involves repeated questions instead of responding, complex sentences, unusual intonation, and challenges in comprehending spoken language.

Recent neuroimaging studies have added to the previous clues on the underlying neurofunction related to the behaviors of ASD children. For example, one study suggested that the brain’s temporal lobes, which often coordinate differential speech processing, experience abnormal functional patterns in children with such cognitive disabilities (Norriss, 2017). In another study in which children were made to view and read a letter, typical peers could accurately record the letter’s name (Vigliocco et al., 2018). However, adults with autistic characteristics failed to recode the concrete linguistic aspects of the discographic because they had processed the information using the left-hemisphere and the frontal working memory sections of their brains (Vigliocco et al., 2018). Taken together, these findings suggest that children with neurodevelopmental challenges such as autism and dyslexia encounter the challenge of language learning.

Research Methodology

The experiment will be conducted through four activities conducted in groups. Each activity will respond to different memory and cognition activities and results recorded in a table.

Activity 1 (in groups)- Present to the group members a try with ten objects carefully covered by a towel. Once each group member is ready, the leaders will remove the towel to reveal the objects for approximately 30 seconds, after which the towel should be covered back. The group members should then be asked about the objects that they remember. The procedure should be repeated twice and with two other objects. The items recalled will be recorded.

Activity 2 (With one member of the group)- With one group member, one member will read to the other a list of numbers given at a rate of 1 word after each second. Record all the numbers the partner recalls. Then, the researcher will read out the second list of numbers in the order given at the same rate. Again, record numbers the number they remember.

Activity 3 (Concreteness)- The researcher will read through a list of words provided with the subject with one group member. Record the number of words memorized by the partner.  The procedure should be repeated using abstract words and, lastly, nonsense words.

Activity 4: With five more volunteers from the group, read the list of 20 words provided at a rate of 1 word per second. Each group member should write down all the words they can recall as soon as they read them. The results will then be collected and recorded in a table shown in the results section.

Proposal Summary

Title: Memory and Cognition

Project Summary: The proposed experiment explores how childhood neurodevelopmental challenges such as autism and dyslexia affect language learning among school-going children. Understanding the relationship between neurodevelopmental anomalies and language learning patterns is important in designing interventional approaches for children living with such disabilities.

Aims and Objectives: Language learning is crucial for communication and other areas of development during childhood and in later cognitive abilities. Determine the relationship between memory and word concreteness and meaningfulness using letters. The experiment’s findings will assist in designing interventional therapies to help children with learning disabilities master language better.

Research Design: The research takes the design of a classroom experiment conducted in groups—children with varied learning abilities will be involved in a classroom experiment to assess how learning disabilities such as dyslexia affect cognition and memory.

Method: The experiment takes the form of four activities taken among children with different learning abilities practicing cognition and memory with letters and numbers. The first activity involves group members. The second involves two group members and numbers. The third aims to determine memory and cognition around concrete content. The last activity involves volunteers reading through words to determine the levels of memory and cognition. Collectively, the responses from these activities will be analyzed to produce meaningful results used to reach conclusive findings.

References

Alkoby O., Alkoby, A. Abu-Rmileh, O. Shriki, D. Todder (2018). Can we predict who will respond to neurofeedback? A review of the inefficacy problem and existing predictors for successful EEG neurofeedback learning. Neuroscience 378 (2018), 155-164. https://doi.org/10.1016/j.neuroscience.2016.12.050

Barletta, N. P. (2018). High-functioning autism and second language development: A case study. Revista Interamericana De Psicología/Interamerican Journal of Psychology52(2). https://doi.org/10.30849/rip/ijp.v52i2.345

Boorse, J. Cola, M., Plate, S., Yankowitz, L., Pandey, J., Schultz, R.T., Parish Moses, J. (2019). Linguistic markers of autism in girls: evidence of a “blended phenotype” during storytelling. Molecular Autism, 10(14), 7-19. https://doi.org/10.1186/s13229-019-0268-2

Chojnicka I, Wawer A (2020) Social language in autism spectrum disorder: A computational analysis of sentiment and linguistic abstraction. PLoS ONE 15(3): e0229985. https://doi.org/10.1371/journal.pone.0229985

Ding, J., Chen, S., Wang, L., & Yang, Y. (2017). Thematic and taxonomic relations of novel words learned from action and perceptual features. Journal of Neurolinguistics 41, 70–84. http://doi.org.10.1016/j.jneuroling.2016.10.002

Dittinger, E., Barbaroux, M., D’Imperio, M., Jäncke, L., Elmer, S., and Besson, M. (2016). Professional music training and novel word learning: from faster semantic encoding to longer-lasting word representations. Journal of Cognitive Neuroscience 28, 1584–1602. http://doi.org.10.1162/jocn_a_00997

Guasch, M., Ferré, P., Emotion and concreteness effects when learning novel concepts in the native language, Psicológica, 42(2):177-191. http://dx.doi.org/10.2478/psicolj-2021-0009

Ferreira, R. A., Göbel, S. M., Hymers, M., and Ellis, A. W. (2015). The neural correlates of semantic richness: evidence from an fMRI study of word learning. Brain Lang. 143, 69–80. http://doi.org.doi: 10.1016/j.bandl.2015.02.005

Fishell, Andrew K.; Burns-Yocum, Tracy M.; Bergonzi, Karla M.; Eggebrecht, Adam T.; and Culver, Joseph P., (2019). “Mapping brain function during naturalistic viewing using high-density diffuse optical tomography.” Scientific Reports https://digitalcommons.wustl.edu/open_access_pubs/7998

Joseph, R.M., Skwerer, D.P., Eggleston, B., Meyer, S, R. & Tager-Flusberg, H. (2019). An experimental study of word learning in minimally verbal children and adolescents with an autism spectrum disorder. Autism & Developmental Language Impairments, 4, 1-8. https://doi.org/10.1177%2F2396941519834717

Li, C, Hu, Z. and Yang, J. (2020) Rapid acquisition through fast mapping: stable memory over time and role of prior knowledge. Learning & Memory, 27 (1), 177-189. http://doi.org.10.1101/lm.050138.119

Kepinska, O. & Schiller, N. O. (2016). Possible neural oscillatory mechanisms underlying learning. Cognitive Neuroscience, 8(2), 128-129 https://doi.org/10.1080/17588928.2016.1205578

Kruk-Slomka, M., Boguszewska-Czubara, A., Slomka, T., Budzynska, B., & Biala, G. (2016). Correlations between the Memory-Related Behavior and the Level of Oxidative Stress Biomarkers in the Mice Brain, Provoked by an Acute Administration of CB Receptor Ligands. Neural plasticity2016, 9815092. https://doi.org/10.1155/2016/9815092

Mestres-Missé, A., Münte, T. F., & Rodriguez-Fornells, A. (2016). Mapping concrete and abstract meanings to new words using verbal contexts. Second Language Research, 30(2), 191-223. Retrieved from https://doi.org/10.1177%2F0267658313512668

Mkrtychian, N., Blagovechtchenski, E., Kurmakaeva, D., Gnedykh, D., Kostromina, S., & Shtyrov, Y. (2019). Concrete vs. Abstract Semantics: From Mental Representations to Functional Brain Mapping. Frontiers in Human Neuroscience. Retrieved from https://doi.org/10.3389/fnhum.2019.00267

Norriss, D. (2017). Short-Term Memory and Long-Term Memory are Still Different. Psychological Bulletin, 143(9), 189-196, http://dx.doi.org/10.1037/bul0000108

Pawlett, J. (2017). Removing Barriers to Learning for Children with Autism Spectrum Disorder. BU Journal of Graduate Studies in Education, 9(2), 21-36.

Pollock, L. (2018). Statistical and methodological problems with concreteness and other semantic variables: A list memory experiment case study. Behavioral Research Methods, 50, 11-1216. https://dx.doi.org/10.3758%2Fs13428-017-0938-y

Smith, D. M. (2017). Effects of Language for Learning on Young Children with Autism Spectrum Disorder. (Doctoral dissertation).  https://scholarcommons.sc.edu/etd/4450

Taylor, S. & Workman, L. (2021). Cognitive Psychology: The Basics. Routledge, New York, N.Y.

Taylor, R.S., Francis, W.S., & Borunda-Vazquez, L., Carbajal, J. (2019). Mechanisms of word concreteness effects in explicit memory: Does context availability play a role? Memory and Cognition, 47(1), 169–181. https://dx.doi.org/10.3758%2Fs13421-018-0857-x

Vigliocco, Gabriella and Ponari, M. and Norbury, Courtenay (2018) Learning and Processing Abstract Words and Concepts: Insights from Typical and Atypical Development. Topics in Cognitive Science. https://doi.org/10.1111/tops.12347

Weber, L. A., Ethoferab, T., & Ehlis, A.-C. (2020 ). Predictors of neurofeedback training outcome: A systematic review. NeuroImage: Clinical, 102301.

Zivoder, I., Martic-Biocina, S., Vodanovic Kosic, S., & Bosak, J. (2016) Neurofeedback application in the treatment of autistic spectrum disorders (ASD). Psychiatria Danubina, 27 (1) 1: S391-4, PMID: 26417802.

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