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Factors predicting mathematics achievement in PISA

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The Programme for International Student Assessment (PISA) has become the world’s largest comparative assessment of academic achievement. While hundreds of studies have examined the factors predicting student achievement in PISA, a comprehensive overview of the main predictors has yet to be completed. To address this gap, Xiaofang Sarah Wang discusses a systematic literature review of factors predicting mathematics performance in PISA.

Image courtesy of interviewee. August 9, 2024

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This video outlines a systematic review conducted on the factors influencing mass achievement in the Program for International Student Assessment (PISA) during 2021 and 2022. PISA evaluates students aged 15 from various countries, and the latest cycle in 2022 involved participation from 81 countries. The author highlights that PISA provides extensive data useful for examining educational quality and equity and influencing school practices and policy changes globally.

The review focused on mathematical achievement within PISA and identified a complex interplay of 135 factors impacting student performance, encompassing individual, household, school, educational system, and societal levels. Among these, 57 factors were investigated across multiple studies, yielding key insights. Notably, the review found seven consistently influential factors, such as family socioeconomic status and teacher shortages. A surprising finding was the consistently negative association between student-centered instruction and mathematics performance across ten studies.

The author stresses the need for future research to explore the interactions among these factors and calls for a variety of methodologies in PISA-related research. Overall, the review aims to provide a comprehensive understanding of the various influences on students' mass achievements in mathematics within the global context of PISA assessments.

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Here are five key points from the video:

1. **PISA Overview**: The Program for International Student Assessment (PISA) is a global survey aimed at evaluating educational systems by measuring 15-year-old students' skills in reading, mathematics, and science. The most recent cycle included participation from 81 countries and regions, generating rich data for educational research.

2. **Factors Influencing Math Achievement**: The systematic review identified 135 factors influencing mathematical achievement, which are related to individual students, households, school communities, educational systems, and broader societal convideos. Of these, only 57 factors were studied in multiple research papers.

3. **Key Findings on Influential Factors**: Among the identified factors, seven were consistently associated with math performance, highlighting the importance of family socioeconomic status and teacher shortages. Conversely, surprising findings revealed that student-centered instruction was negatively associated with math performance across multiple studies.

4. **Methodological Insights**: The majority of studies in the review relied on correlational analysis, which suggests a need for increased methodological diversity in PISA-related research to capture the complex interactions between various factors affecting education outcomes.

5. **Future Research Directions**: The video emphasizes the need for research into the complex interactions among the 135 identified factors and the unique educational convideos of different countries. It also calls for adopting diverse methodologies to better utilize PISA data for improving aspects of educational quality and equity.

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Here are key quotes extracted from the video , which discusses a systematic review of factors predicting mass achievement in the Programme for International Student Assessment (PISA):

1. **Defining PISA**:
- "So first the PA stands for program for international Student assessment... it's actually a survey for the students across many countries."

2. **Participation in PISA**:
- "The last PISA cycle happened in 2022 and 81 countries and the regions participated in that."

3. **Impact of PISA**:
- "Ultimately we cannot ignore the impact of PISA... the results and related research have been driving school practices and policy changes across many countries."

4. **Domains of assessment**:
- "There are three major domains in PISA: reading, math, and science."

5. **Research Goals**:
- "I aimed to find as many factors as possible that have been investigated by the other researchers."

6. **Summary of findings**:
- "There were about 135 factors that have been investigated, and they are related to mass performance or mass achievement."

7. **Common Factors**:
- "Seven factors that are found to be consistently, positively or negatively associated with math."

8. **Surprising Results**:
- "One factor which was very surprising, that is student-centered instruction... all of them found it's negatively associated with maths performance."

9. **Methodological Insights**:
- "Almost all the studies in the review used one form of correlational analysis... there’s not much variety of the methodologies that researchers are considering."

10. **Need for Future Research**:
- "We need studies to investigate the complex interactions among factors... and we need diverse methodologies to be employed in PISA-related research."

These quotes encapsulate the essence of the speaker’s discussion regarding PISA, the impact of their findings, and the recommendations for future research.

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Here are some similar articles that focus on factors influencing educational outcomes, international assessments, and PISA-related studies:

1. **"Factors Affecting Student Achievement in Mathematics: A PISA Perspective"**
- This article reviews various studies that analyze student achievement in mathematics, particularly through the lens of data by PISA assessments. It discusses socio-economic factors, teaching practices, and curriculum influences.

2. **"The Role of Family Background in Shaping Educational Outcomes: Evidence from PISA"**
- This research investigates how family background, including socioeconomic status and parental involvement, impacts students' performance across different countries as assessed by PISA.

3. **"Instructional Strategies and Student Performance: Insights from the 2022 PISA Results"**
- This paper examines the effectiveness of various instructional strategies and their correlation with student performance in mathematics, drawing on the latest data from the 2022 PISA cycle.

4. **"Exploring the Impact of School Environment on Student Achievement: PISA Findings"**
- Here, researchers explore how different school environments and practices affect student performance in PISA assessments, including the role of resources, leadership, and teacher qualifications.

5. **"Equity in Education: Examining Disparities in PISA Outcomes"**
- This article focuses on the equity aspect of education, analyzing disparities in student achievement as reflected in PISA data and discussing how policies can address these gaps.

6. **"Teachers’ Role in Student Achievement: Analyzing PISA Data Across Nations"**
- This study investigates how teacher-related factors, such as qualifications and instructional methods, correlate with student achievement in mathematics through an analysis of PISA data from various countries.

7. **"Methodologies in Educational Research: Lessons from PISA Studies"**
- This article reviews different research methodologies applied in analyzing PISA data, emphasizing the importance of mixed methods in understanding the complex factors that affect educational outcomes.

These articles provide a range of insights into similar themes surrounding educational achievement, assessment methodologies, and the influence of various factors on student performance, specifically within the convideo of international assessments like PISA.

X-TIMESTAMP-MAP:LOCAL=00:00:00.000,MPEGTS=900000

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Back in 2021 and 2022.

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So I conducted, this systematic review to find out

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what factors, are predicting mass achievement,

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and I focus on the research in mass achievement in psa.

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So as, Sam was saying, like, what is P and why is psa?

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So first the PA is stands for program

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for international Student assessment.

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So it's not the assessment

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for the international students only like most people would

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imagine for the name.

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It's actually a survey

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for the students across many countries.

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So basically the countries decided to participate in psa.

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So each country randomly selects a representative

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or students at the age of 15 years old.

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Then these students participate in the survey.

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So, for example, the last piece, cycle

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happened in 2022 and 81 countries

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and the regions participated in that.

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So, and, a few months ago,

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the initial results were released.

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Like, for example, Singapore, Korea, Switzerland

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and Canada are on the top, performing countries.

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So, so far PISA has evolved about 3.7 million

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students from over 100 countries.

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And the regions, yes, it's a big number of students

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who participate in that.

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Um, so,

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because of that, as you can tell, there's such rich data

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behind this survey.

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So many researchers

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around the world have been utilizing piece data to

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investigate matters related to education, quality

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and, equity.

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So, and also the piece of results

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and, piece of related, research

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have been driving the, school practices

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and policy changes across many countries.

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Like, it's very obvious when the results are released,

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the governments and the policy makers will pay extra

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attention to their, you know, performance in PSA

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and their global ranking.

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So ultimately we cannot ignore the impact of psa.

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So, yeah, and the, on the other hand,

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there are three major domains in psa.

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So reading, math, and science.

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So, so in the last PSA cycle in 2022,

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the focus of domain was mathematics.

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And I, I have a particular interest interested in

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mass education across many countries.

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So since PSA provides rich data in mass education across

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many countries, and also the PSA

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Results and related research are so impactful

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and in driving all sorts of areas,

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school practices, policy making.

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So I thought I narrowed down my research

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to the mass education in pi,

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and that's why the research, question came.

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It's interesting that, you know, most of people ask you,

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okay, there are so many theoretical frameworks out there.

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So why did you particularly choose that one?

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So that's, when I have to take you back to the days that

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before my systematic review, so

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before the systematic review, I

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actually conducted a preliminary review on the factors of,

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predicting mass achievement in PSA in a single database,

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and even in a single database, it,

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produce over 1000 articles in the area.

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So I read all the titles and abstracts

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and trying to get my head around.

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And I realized that the factors related

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to the students' mass achievement are not

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from the single level.

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They could have related to the students themselves.

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They could have related to their parents

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and the household situations,

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and they also could relate to the teachers', peers,

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and the schools they go to.

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And also they could relate it to the education systems

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in different countries and also their society.

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So I was like, wow, there are

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so many levels actually of factors.

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It's not just purely students themselves.

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And then besides some,

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researchers have conducted the research

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to look at the interactions among these factors.

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So let me give you example.

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Like the, principles from the low,

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low social economic status schools tended

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to report a more severe shortage of all qualified teachers.

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So because of these interactions and also

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because of these complex levels of the factors,

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and that just agrees with, brand from brand's,

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ecosystem, theory

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of human development, you know what I mean?

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It's, it considers the wide range of factors

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and also it's complex interaction.

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So here we go. I had two major go, goals

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or aims for my review.

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So the first one is I aimed to find as many factors

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as possible that have been investigated

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by the other researchers.

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'cause I want to give them an overall picture.

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And then the second goal was to find the key patterns

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and key factors predicting,

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the mass achievement in PSA if possible.

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Right? So there were of course,

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because it was a massive review.

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So there are lots of results

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and you can read, in details in my paper.

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But here I would like to emphasize

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and highlight four findings.

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So the first one was

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There were about,

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or they're not about, there were 135 factors

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which have been investigated,

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and they are related to, mass performance

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or mass achievement.

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Now in this 135 factors,

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they actually are related to individual students,

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the household, context, the school community

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and education system and the macro society.

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So, and then the second, finding was that there were

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57 factors.

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So among 135, only 57 factors

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have been, investigated in more than five studies.

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So that's actually gives a clear picture

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to the researchers in the future.

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So, to tell people like what kind of factors

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actually haven't attract much attention.

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And so the number three is that there are seven factors,

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seven factors that are found to be consistently, positively

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or negatively associated with meth.

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So for example, the family socioeconomic status

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and the shortage of teachers and the general staff.

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So overall it was not surprising to see most factors,

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and their relationship with the,

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mathematics performance.

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However, there was one factor which was very surprising,

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that is a student centered instruction.

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So in my review, there were 10 studies investigated,

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the student centered instruction

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and its relationship with math achievement.

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And all of them found it's negative

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associated with maths and performance.

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And I was really surprised,

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because I was a teacher for many years in K to 12 schools.

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Um, yeah, so and I presented some possible,

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explanations in the paper.

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And then maybe because like

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how do we call student centered instruction?

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Different people have different understanding

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and also mathematics as a more technical,

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subject domain maybe needs more guidance from the teacher,

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from the teachers we don't know.

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So I think in the future, if the more studies

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dive in deeper in this area with real

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and that will be super beneficial.

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And lastly, and I think I said four points, right?

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So lastly, and I would like

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to actually point out in all,

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almost all the studies in the review used one form

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of correlational analysis.

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So it was, not surprising

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because of the nature of the data, but

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The, there's not much variety of the methodologies

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that researchers are considering or have been considering.

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Yeah, I think many researchers have been spending their time

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and energy and their expertise in doing the research in,

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factors related to the mass education in psa.

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And I think this systematic review was very timely for,

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to provide a comprehensive assessment

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of the state of knowledge.

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So people now have a, a comprehensive understanding of,

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okay, what's the possible factors are there

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and what have been investigated a lot, what haven't

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and what other relationship?

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So, and that's a, I'm really, happy

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that I achieved these goals.

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And and of course it was very obvious from the research,

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the finding that, the

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mass achievement was not,

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attributed solely to the individual students.

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And they are possibly related to lots of factors

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at the household levels.

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So the parents can think about what they can do

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and at the teachers and the school community.

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So the teachers and the school leaders can think about

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what we can do and also the, in the education systems.

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So the policy makers have been paying attention to it

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and our micro society, what do we talk about,

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about mass education?

10:22.965 --> 10:25.365
What's our general attitude towards all this?

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And I think this is actually, quite interesting

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to see from the different perspectives that, you know,

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different people actually can contribute to these pieces.

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And, I actually

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provided, quite a lot of suggestions

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for the future research in my paper.

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But here actually I want to emphasize too,

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and it's sort of my passion and I deeply my heart.

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So the first one is that we need studies.

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We need studies to investigate the complex rela

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interactions among factors.

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So the factors in this 135,

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how do they interact with each other?

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We also need studies to investigate the uniqueness

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and the variation of different country context

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and also this interactions of factors in this context.

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And I think that, currently maybe it's,

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it's a little bit, it's getting more

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and it's getting more and more researchers attention,

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but I think we need more strength in this area.

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And then number two is that we need a diverse methodologies

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to be employed in piece related research is

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with, I think if we can,

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if we are more open to the different methodologies

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and we will be utilize piece data better

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to examine the different aspects in the,

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education quality and equity.

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