The Moderating Effect of Gender Equality and Other Factors on PISA and Education Policy
Abstract
:1. Introduction
1.1. Education Policy in the Global Context
1.2. The OECD and PISA
1.3. Critiques of the Power of PISA
1.4. The Moderating Effect of System-Specific Factors
- Which system-specific factors are associated with PISA 2015 results?
- Do these system-specific factors moderate the relationship between education conditions and student outcomes, and if so, how?
2. Theoretical Framework and Selection of System-Specific Factors
2.1. Socio-Economic and Cultural Factors
2.1.1. Human Development
2.1.2. Income Inequality
2.1.3. Gender Equality
2.1.4. Individualism
2.2. Education Policy Variables
3. Methods and Materials
3.1. Methods
3.1.1. Qualitative Comparative Analysis
3.1.2. Correlational Analyses
3.2. Data
3.2.1. Cases
3.2.2. Student Achievement
3.2.3. System-Specific Factors and Education Policy Variables
4. Results
4.1. System-Specific Factors as Outcome-Enabling Conditions
(consistency 0.812, coverage 0.650)
(consistency 1.000, coverage 0.200)
(consistency 0.812, coverage 1.000)
4.2. The Moderating Effect
5. Discussion
5.1. Gender Equality
5.2. Meaningful Peer Countries
5.3. The Future of PISA and Policy Transfer
6. Limitations and Future Research
7. Conclusions
Supplementary Materials
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Factor | Index | Source |
---|---|---|
Wealth | GDP per Capita, 2015 | The World Bank |
Human development | Human Development Index, 2015 | The United Nations Development Programme |
Income inequality | 80/20 Index, 2015 | The World Bank, Income share highest 20% and lowest 20% |
Economic freedom | Economic Freedom Index, 2015 | The Heritage Foundation |
Immigration | Migrant Stock, 10–14 years old, 2015 | The United Nations Department of Economic and Social Affairs |
Gender inequality | Gender Inequality Index, 2015 | The United Nations Development Programme |
Gender gap | Gender Gap Index, 2015 | The World Economic Forum |
Ethnic diversity/tension | Ethnic Fractionalization, 2003 * | Alesina, Devleeschauwer, Easterly, Kurlat, and Wacziarg [55] |
Religious diversity/tension | Religious Fractionalization, 2003 * | |
Language diversity/tension | Language Fractionalization, 2003 * | |
Country population | Country Population Data, 2015 | The United Nations Department of Economic and Social Affairs |
Democracy | Democracy Index, 2015 | The Economist Intelligence Unit |
Code | Country | 2015 PISA Score | Set Membership | |||
---|---|---|---|---|---|---|
Mathematics | Reading | Science | HIGH_PISA (1) | LOW_PISA (2) | ||
ALB | Albania | 413 | 405 | 427 | 0 | 1 |
AUS | Australia | 494 | 503 | 510 | 1 | 0 |
AUT | Austria | 497 | 485 | 495 | 0 | 0 |
BEL | Belgium | 507 | 499 | 502 | 1 | 0 |
BRA | Brazil | 377 | 407 | 401 | 0 | 1 |
BGR | Bulgaria | 441 | 432 | 446 | 0 | 1 |
CAN | Canada | 516 | 527 | 528 | 1 | 0 |
CHL | Chile | 423 | 459 | 447 | 0 | 1 |
COL | Colombia | 390 | 425 | 416 | 0 | 1 |
HRV | Croatia | 464 | 487 | 475 | 0 | 0 |
CZE | Czech Republic | 492 | 487 | 493 | 0 | 0 |
DNK | Denmark | 511 | 500 | 502 | 1 | 0 |
DOM | Dominican Republic | 328 | 358 | 332 | 0 | 1 |
EST | Estonia | 519 | 519 | 534 | 1 | 0 |
FIN | Finland | 511 | 526 | 531 | 1 | 0 |
FRA | France | 493 | 499 | 495 | 1 | 0 |
DEU | Germany | 506 | 509 | 509 | 1 | 0 |
GRC | Greece | 454 | 467 | 455 | 0 | 0 |
HUN | Hungary | 477 | 470 | 477 | 0 | 0 |
ISL | Iceland | 488 | 482 | 473 | 0 | 0 |
IDN | Indonesia | 386 | 397 | 403 | 0 | 1 |
IRL | Ireland | 504 | 521 | 503 | 1 | 0 |
ITA | Italy | 490 | 485 | 481 | 0 | 0 |
JPN | Japan | 532 | 516 | 538 | 1 | 0 |
LVA | Latvia | 482 | 488 | 490 | 0 | 0 |
LTU | Lithuania | 478 | 472 | 475 | 0 | 0 |
LUX | Luxembourg | 486 | 481 | 483 | 0 | 0 |
MEX | Mexico | 408 | 423 | 416 | 0 | 1 |
NLD | Netherlands | 512 | 503 | 509 | 1 | 0 |
NZL | New Zealand | 495 | 509 | 513 | 1 | 0 |
NOR | Norway | 502 | 513 | 498 | 1 | 0 |
PER | Peru | 387 | 398 | 397 | 0 | 1 |
POL | Poland | 504 | 506 | 501 | 1 | 0 |
PRT | Portugal | 492 | 498 | 501 | 1 | 0 |
ROU | Romania | 444 | 434 | 435 | 0 | 1 |
RUS | Russia | 494 | 495 | 487 | 0 | 0 |
SGP | Singapore | 564 | 535 | 556 | 1 | 0 |
SVK | Slovak Republic | 475 | 453 | 461 | 0 | 0 |
SVN | Slovenia | 510 | 505 | 513 | 1 | 0 |
KOR | South Korea | 524 | 517 | 516 | 1 | 0 |
ESP | Spain | 486 | 496 | 493 | 0 | 0 |
SWE | Sweden | 494 | 500 | 493 | 1 | 0 |
CHE | Switzerland | 521 | 492 | 506 | 0 | 0 |
THA | Thailand | 415 | 409 | 421 | 0 | 1 |
TUR | Turkey | 420 | 428 | 425 | 0 | 1 |
GBR | United Kingdom | 492 | 498 | 509 | 1 | 0 |
USA | United States | 470 | 497 | 496 | 0 | 0 |
URY | Uruguay | 418 | 437 | 435 | 0 | 1 |
VNM | Viet Nam | 495 | 487 | 525 | 0 | 0 |
Average (all PISA countries) | 461 | 460 | 465 | n = 20 | n = 13 | |
Average (included countries) | 473 | 476 | 478 | |||
Average (OECD) | 490 | 493 | 493 |
HIGH_ GENDER_ EQUALITY | HIGH_ INCOME_ EQUALITY | HIGH_ HUMAN_ DEVELOP | HIGH_ INDIVID | Out | n | Cons. | Cases |
---|---|---|---|---|---|---|---|
1 | 1 | 1 | 1 | 1 | 15 | 0.800 | AUT, BEL, CAN, DNK, FIN, FRA, DEU, IRL, ISL, NLD, NZL, NOR, SWE, CHE, GBR |
1 | 1 | 1 | 0 | 1 | 3 | 1.000 | JPN, SVN, KOR |
1 | 0 | 1 | 0 | 1 | 1 | 1.000 | SGP |
1 | 1 | 0 | 1 | 1 | 1 | 1.000 | EST |
0 | 0 | 0 | 0 | 0 | 13 | 0.000 | BRA, BGR, CHL, COL, DOM, IDN, MEX, PER, RUS, THA, TUR, URY, VNM |
0 | 1 | 0 | 1 | 0 | 4 | 0.250 | CZE, HUN, POL, SVK |
1 | 0 | 0 | 1 | 0 | 4 | 0.000 | ITA, LVA, LTU, ESP |
0 | 1 | 0 | 0 | 0 | 3 | 0.000 | ALB, HRV, ROU |
1 | 0 | 0 | 0 | 0 | 2 | 0.500 | GRC, PRT |
1 | 0 | 1 | 1 | 0 | 2 | 0.500 | AUS, LUX |
0 | 0 | 1 | 1 | 0 | 1 | 0.000 | USD |
0 | 0 | 0 | 1 | ? | 0 | - | |
0 | 0 | 1 | 0 | ? | 0 | - | |
0 | 1 | 1 | 0 | ? | 0 | - | |
0 | 1 | 1 | 1 | ? | 0 | - | |
1 | 1 | 0 | 0 | ? | 0 | - |
HIGH_ GENDER_ EQUALITY | HIGH_ HUMAN_ DEVELOP | HIGH_ INDIVID | Out | n | Cons. | Cases |
---|---|---|---|---|---|---|
0 | 0 | 0 | 1 | 16 | 0.812 | ALB, BRA, BGR, CHL, COL, HRV, DOM, IDN, MEX, PER, ROU, RUS, THA, TUR, URY, VNM |
1 | 1 | 1 | 0 | 17 | 0.000 | AUS, AUT, BEL, CAN, DNK, FIN, FRA, DEU, ISL, IRL, LUX, NLD, NZL, NOR, SWE, CHE, GBR |
1 | 0 | 1 | 0 | 5 | 0.000 | EST, ITA, LVA, LTU, ESP |
0 | 0 | 1 | 0 | 4 | 0.000 | CZE, HUN, POL, SVK |
1 | 1 | 0 | 0 | 4 | 0.000 | JPN, SGP, SVN, KOR |
1 | 0 | 0 | 0 | 2 | 0.000 | GRC, PRT |
0 | 1 | 1 | 0 | 1 | 0.000 | USA |
0 | 1 | 1 | ? | 0 | - |
All Countries | High Gender Equality Countries | NOT High Gender Equality Countries | Comparison between Groups | ||||||
---|---|---|---|---|---|---|---|---|---|
Number of Tests | Mean (sd) | Correlation with PISA Scores | Mean (sd) | Correlation with PISA Scores | Mean (sd) | Correlation with PISA Scores | Difference Means Cohens D (a) | Difference Correlations Z-Score (b) | |
PISA scores | 147 | 475.9 (44.6) | - | 502.8 (19.1) | - | 440.2 (43.7) | - | −1.951 *** | - |
Cumulative expenditure on education ($) | 108 | 90,484 (34,108) | 0.418 *** | 101,136 (30,401) | 0.027 | 58,529 (23,022) | 0.549 ** | 1.481 *** | −2.527 * |
Student hours in classroom | 135 | 26.8 (1.9) | 0.025 | 26.8 (1.5) | 0.117 | 26.7 (2.5) | −0.028 | 0.041 | 0.799 |
Class size in language of instruction class | 147 | 27.3 (6.0) | −0.451 *** | 24.8 (3.9) | 0.498 *** | 30.6 (6.7) | −0.426 *** | 1.087 *** | 5.881 *** |
Public school enrolment rate (%) | 141 | 83.4 (17.0) | 0.075 | 82.4 (18.2) | −0.142 | 84.9 (15.3) | 0.430 *** | 0.147 | −3.459 *** |
Private expenditure on primary and secondary education (% of total) | 105 | 8.8 (6.1) | −0.444 *** | 7.4 (5.6) | 0.163 | 12.2 (6.0) | −0.820 *** | 0.836 *** | 5.855 *** |
Teacher salaries ($) | 102 | 36,621 (25,776) | 0.567 *** | 49,094 (23,211) | 0.334 ** | 16,472 (14,570) | 0.243 | −1.602 *** | 0.471 |
Qualified teachers (%) | 138 | 89.5 (9.2) | 0.483 *** | 91.6 (6.0) | 0.396 *** | 86.3 (12.0) | 0.430 ** | −0.592 ** | −0.229 |
Teacher professional development in previous 3 months (%) | 147 | 50.6 (16.5) | 0.237 ** | 53.1 (16.5) | 0.300 ** | 47.4 (16.0) | 0.108 | −0.305 * | 1.181 |
Average years of teacher experience | 93 | 16.6 (2.7) | −0.106 | 16.4 (2.9) | −0.415 *** | 16.8 (2.4) | 0.279 | 0.136 | −3.229 ** |
Teachers that participated in an induction program (%) | 93 | 47.2 (19.5) | 0.037 | 44.6 (22.2) | 0.324 * | 52.1 (12.2) | 0.164 | 0.389 * | 0.756 |
Teachers that have a mentor (%) | 93 | 11.4 (9.7) | 0.095 | 11.8 (10.4) | 0.628*** | 10.7 (8.4) | −0.556 *** | −0.118 | 6.052 *** |
Teacher non-contact hours (% of total) | 87 | 48 (11) | 0.508 *** | 51 (8) | 0.255 | 42 (14) | 0.422 * | −0.871 ** | −0.803 |
GENDER EQUALITY | HUMAN DEVELOPMENT | INCOME EQUALITY | INDIVIDUALISM | ||
---|---|---|---|---|---|
1 | Cumulative expenditure on education | ||||
2 | Student hours in classroom | ||||
3 | Class size | ||||
4 | Public-school enrolment | ||||
5 | Private expenditure on education | ||||
6 | Teacher salaries | ||||
7 | Percentage of qualified teachers | ||||
8 | Rate of teacher professional dev. | ||||
9 | Average years of teacher experience | ||||
10 | Percentage teachers received induction | ||||
11 | Percentage teachers with mentor | ||||
12 | Proportion of non-contact hours | ||||
Statistically significant difference between group means | |||||
Statistically significant difference between group correlations | |||||
Positive correlation in one group; Negative correlation in the other group |
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Campbell, J.A. The Moderating Effect of Gender Equality and Other Factors on PISA and Education Policy. Educ. Sci. 2021, 11, 10. https://doi.org/10.3390/educsci11010010
Campbell JA. The Moderating Effect of Gender Equality and Other Factors on PISA and Education Policy. Education Sciences. 2021; 11(1):10. https://doi.org/10.3390/educsci11010010
Chicago/Turabian StyleCampbell, Janine Anne. 2021. "The Moderating Effect of Gender Equality and Other Factors on PISA and Education Policy" Education Sciences 11, no. 1: 10. https://doi.org/10.3390/educsci11010010
APA StyleCampbell, J. A. (2021). The Moderating Effect of Gender Equality and Other Factors on PISA and Education Policy. Education Sciences, 11(1), 10. https://doi.org/10.3390/educsci11010010