During the history of PISA studies, all results have shown a clear gender gap in reading literacy favouring girls in all countries and economies. Still, there are differences in the variations of girls' and boys' reading literacy proficiencies depending on the country's location, economic wealth, and cultural background. In PISA 2018, girls outperformed boys in reading by almost 30 score points. However, the size of the gender gap was not related to the average performance (OECD, 2019a). In 16 out of the 25 countries and economies whose mean score was above the OECD average, the difference in the reading performance between boys and girls was smaller than the average gender gap across OECD countries (OECD, 2019b). Amongst these high performing countries, the difference between girls' and boys' performance ranged from 13 score points in B-S-J-Z (China) to 52 score points in Finland. The gender difference in reading performance was the most minor (12 points) in Colombia. Also, the average score in reading (412) was amongst the lowest of all participants. 

There is substantial variation in gender differences, but no equal starting point given the considerable differences between countries in their provision of preschool education, age of entry into formal schooling, community resources such as libraries, training of teachers or general learning cultures (Topping et al., 2003). So, it is not easy to adduce which factors have the most significant influence on gender differences and why. Large-scale assessment studies can provide indicators of how a national education policy is working compared to others. However, they are less helpful in identifying particular causal factors or actions that should or could be taken to create a gender-equal school system.

Even though gender differences are probably the most commonly examined education outcomes, it remains somewhat unclear the underlying causes of the existing differences. Maccobly and Jacklin (1974) concluded their substantially extensive review regarding gender differences in various abilities. While some patterns persisted, for example, female superiority in verbal skills and male superiority in mathematical skills (Liu, Wilson & Paek, 2008), it was not easy to untangle the influence of stereotyping on individuals' perceptions of and behaviour towards events and objects. According to  Maccobly and Jacklin (1974), it was also challenging to separate out if and to what extent innate or learned behaviours underpinned the development of behavioural or cognitive gender differences. The focus on masculinity in crisis is potentially fruitful, however, in the sense that it shifts the emphasis away from structural factors in post-industrial societies, which position boys as inevitable 'losers'. Instead, it would be needed to explore the characteristics of masculinity that inhibit boys as learners and citizens and how these might be challenged (Epstein et al., 1998).

A study comparing the gender outcomes of the PISA studies for Sweden and Switzerland suggests that while both countries performed at the upper end of the international spectrum, Sweden had an educational climate with a higher degree of gender equity (Fredriksson et al., 2009). In asking what the two countries might learn from each other, the authors suggest that the study shows Switzerland to get more equity without reducing quality. In Sweden, the quality can be further improved, but it does not necessarily mean that gender equity has to be reduced. 

The research question of this paper formulates around the issue of what a well-performing country such as Finland can learn from a low performing country such as Colombia. Despite some recent progress, the education system in Colombia has not been capable of providing higher learning outcomes (OECD, 2016). Thus, the gender gap in these two countries represents the opposite ends of the comparison.

This study is based on the ground of statistical analyses used in the PISA study (OECD 2019). Finland's and Colombia's data were compared with the IDB analyser utilising SPSS program. Linear regression analysis was conducted separately on the predictors for girls' and boys' reading literacy scores calculated with ten plausible values. The predicting factors were examined as computed variables with Weighted Likelihood Estimate (WLE) values. Finally, a set of path analyses using Mplus was conducted to examine the structure of predictors for girls' and boys' reading literacy in both Finland and Columbia. First, students' attitudes towards reading for enjoyment and use of digital devices were added as predictors. Second, only dispositional motivation and fear of failure predictors were specified. Third, both factors were specified to predict financial literacy simultaneously. Finally, a set of socio-demographic control variables (i.e., gender, grade, socioeconomic background, and parents' education) was added to the model.

The focus of this study was to examine how the predicting factors for girls' and boys' reading literacy differ in Finland and Columbia. In Finland, the strongest examined predictors for reading proficiency were reading engagement, time used for reading, socioeconomic background, ICT-use, perseverance, self-efficacy, fear of failure and competitiveness. According to linear regression, gender predicted 7 per cent of the variance of reading proficiency in Finland but had zero predicting effect on the reading proficiency of Colombia. Based on the first analysis, the strongest predictors of reading proficiency were still rather similar both in Finland and Colombia. It remains open what could be the actual causes for the different gender gap structures in Finland and Colombia. The presentation will discuss further the results from the further analysis as well as possible other cultural or education policy-related factors regarding the different manifestation of the gender gap on these two extremes, still OECD member countries.

Epstein, D. Ellwood, J., Hey, V. & Maw, J., 1998. Failing boys? Issues in gender and achievement. Buckingham: Open University Press. Fredriksson, U., Holzer, T., McCluskey-Cavin, H. & Taube, K., 2009. Strengths and weaknesses in the Swedish and Swiss education systems: A comparative analysis based on PISA data. European Educational Research Journal, 8(1), 54–68 Liu, O., L., Wilson, M., Paek, I. 2008. A multidimensional Rasch analysis of gender differences in PISA mathematics. Journal of applied measurement, 9(1), 18–35. Maccoby, E.E. & Jacklin, C.N., 1974. The psychology of sex differences. Stanford: Stanford University Press. OECD 2019a. PISA 2018 Results. Volume I. What Students Know and Can do? Paris: OECD Publishing. OECD 2019b. PISA 2018 Results. Volume II. Where All Students Can Succeed. Paris: OECD Publishing. OECD (2016), Education in Colombia, Reviews of National Policies for Education, OECD Publishing, Paris, https://doi.org/10.1787/9789264250604-en.