Make an Update: Describe an application of the quantitative methods of educational psychology. This could be for broad institutional analysis, or it could be a description and analysis of tests and test results in the specialist area of psychometrics. What are the benefits and limitations of such work?

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Quantitative psychologists study and develop methods for measuring human behavior. Their work involves the use of statistical methods, research methodologies, the modeling of psychological processes, and data analysis of psychological data.

Its use frequently involves the application of quantitative methods such as simulation, advanced statistics, and data mining of large-scale, secondary data sets to study classroom learning, educational policies, programs, and interventions developed to promote student learning. This was illustrated well by the presentations in our course materials by Dr. Cimpian on their quantitative analyses of policy changes for the reclassification of English language learners. For this, Dr. Cimpian and colleagues applied regression discontinuity and instrumental variable methods to student outcome data.

This Update #4 will consider the application of quantitative psychology to the issue of language delay or impairment in young children and its impact on education.

To begin, we must first understand what is meant by “language impairment” -- or Specific Language Impairment (SLI) as it is often called. The term is relatively recent, first appearing in the 1990s to refer to a language disorder not connected to neurological damage, deafness, or mental disability. A child with an SLI has difficulties at the cognitive and language level -- for example, children who have trouble speaking or understanding speech. They may have trouble expressing themselves, in forming questions, using the right words in a sentence, or have reading problems. [1]

As quantitative psychological studies have shown, children with SLIs experience notable challenges in their daily lives - and specifically in learning at school. In particular, students with language impairments experience problems in their relationships with peers -- such as difficulties in working together in teams or collaborating in learning in the classroom. This can create obstacles for the child’s learning in school. [2]

SLIs are not an isolated problem - but a common, global issue. For example, the problem of speech delay (kids who are slow to begin speaking their primary language), affects between 2.3% and 24.6% of children globally. [3] The frequency found in studies is a very wide range, but the general point is that learning impairments like speech delay are fairly common.

Even more importantly, “[c]hildren with speech sound disorders are more likely to have reduced social and educational outcomes than typically developing children.” [4] This is due to a variety of specific impacts, as multiple studies have found -- such as increased risk for difficulties with reading, higher likelihood of needing additional support at school, higher frustration levels among students with SLIs, and higher risks of being victims of bullying.

As one quantitative study showed, negative impacts on learning can be connected to language delays among preschool age children. [5] Specifically, language delays among preschoolers (both boys and girls) are associated with excess risk of poor literacy of children at the age of 8 years - and this was true whether their language delays were persistent or more transient. [6]

Note the test scores in the table below for children with “No LD” being much higher than scores for children with either “Transient LD” or “Persistent LD.”

Note: The study’s analyses used a quantitative method known as binary logistic regression to make predictions about risk. [7]

If we take a closer look at one study that looked at early speech–language pathologies (SLPs) among kindergarten students and the implications for their learning and academic performance in 3rd grade, we can see an example of how quantitative analysis is used.

The research method used was to analyze two datasets together. The first was what is called an “Early Development Instrument” (or EDI) for kindergarten data. This EDI was simply a questionnaire completed by kindergarten teachers that measures children’s ability to meet age-appropriate developmental expectations in five domains. This data was matched together with data from Grade Three school-system standardised tests of reading, writing and maths. The goal was to determine the presence or absence of learning impairments and education impacts among 3rd graders who showed an SLP in kindergarten. [8]

Part of the work for the analysis required the researchers to identify and designate kids into the correct groupings (e.g., those who had a SLP, those who did not, those who did not meet the criteria for inclusion in the study, etc.). The flowchart below is an example of one tool used by the research team. It shows the exclusion criteria applied (listed on the left side) and group designations arrived at (rectangles at the bottom) using test scores and speech–language pathology designations.

Shaded rectangles represent children who met the corresponding criteria; unshaded rectangles are children who did not and were excluded from the data analysis. The bottom four rectangles represent the four study groups used throughout the analysis. [9]

The research results found that even though the vast majority (over 70%) of kids with an SLP in kindergarten no longer showed a learning impairment in Grade 3, they were still more likely to have lower achievement levels and special educational needs in 3rd Grade. The conclusion drawn from this research was clear: “These population level results provide strong evidence to indicate that all children who present with an SLP in kindergarten face further academic challenges, even if their SLP resolves over time.” [10]

The benefits of applying quantitative methods of educational psychology are numerous. They enable a level or granularity of analysis that enables testing of the hypotheses, patterns, or insights generated from qualitative research -- which focuses on concepts or experiences and produces data more often in narrative form. Also, it is often easier for other researchers to evaluate, build upon, or try to replicate quantitative research results in later studies. Since it produces numeric data, results can be more easily compared, rigorously tested, and validated by others more readily. This makes quantitative results very compelling in proving or disproving theories about education. Quantitative approaches also offer techniques for analyzing very large datasets, or combinations of large data. This can be very hard and hugely time-consuming using a qualitative research approach.

As with anything that depends upon data, there are limitations in using quantitative methods of educational psychology. For example, the data used in a quantitative analysis may be robust enough to explain very complex issues. This may happen where surveys are not able to capture the complexity and nuance of an issue, especially where hard-to-measure things like values are involved. It also runs the risk of creating a “numbers bias.” With its emphasis on statistical relationships, researchers and others might miss crucial broader issues or relationships. Quantitative research may also be hard to understand for the wider audience of stakeholders working in a given area. Even finding or generating appropriate data can be difficult, or expensive to do.

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Sources:

1. Social Skills of Children with Specific Language Impairment: Occupational and Speech Therapists‟ Perceptions, A.Papalexopoulou and G.Charitaki, Asian Journal of Applied Science and Technology (AJAST), Volume 1, Issue 5 (June 2017). http://ajast.net/data/uploads/50.pdf

2. A.Papalexopoulou and G.Charitaki, AJAST, Volume 1.

3. Law, J., Boyle, J., Harris, F., Harkness, A., & Nye, C. (2000). Prevalence and natural history of primary speech and language delay: Findings from a systematic review of the literature. International Journal of Language and Communication Disorders, 35(2). https://doi.org/10.1080/136828200247133

4. Daniel, G. R., & McLeod, S. (2017). Children with Speech Sound Disorders at School: Challenges for Children, Parents and Teachers. Australian Journal of Teacher Education, 42(2). http://dx.doi.org/10.14221/ajte.2017v42n2.6

5. Daniel, G. R., & McLeod, S., Australian Journal of Teacher Education.

6. Jin, Fufen & Schjolberg, Synnve & Wang, Mari & Eadie, Patricia & Nes, Ragnhild & Røysamb, Espen & Tambs, Kristian. (2020). Predicting Literacy Skills at 8 Years From Preschool Language Trajectories: A Population-Based Cohort Study. Journal of Speech, Language, and Hearing Research. https://www.researchgate.net/publication/342998930_Predicting_Literacy_Skills_at_8_Years_From_Preschool_Language_Trajectories_A_Population-Based_Cohort_Study

7. Jin, Fufen, et al, Journal of Speech, Language, and Hearing Research.

8. Magdalena Janus, Chantal Labonté, Ryan Kirkpatrick, Scott Davies & EricDuku, The impact of speech and language problems in kindergarten on academic learning and special education status in grade three. International Journal of Speech-Language Pathology 21(1), November 2017. https://www.researchgate.net/publication/321277111_The_impact_of_speech_and_language_problems_in_kindergarten_on_academic_learning_and_special_education_status_in_grade_three

9. Janus, Labonté, et al, International Journal of Speech-Language Pathology.

10. Janus, Labonté, et al, International Journal of Speech-Language Pathology.