Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

Please note that all times are shown in the time zone of the conference. The current conference time is: 17th May 2024, 07:48:03am GMT

 
 
Session Overview
Session
09 SES 02 B: Exploring Mathematical Development, Self-Concept, and Achievement in Education
Time:
Tuesday, 22/Aug/2023:
3:15pm - 4:45pm

Session Chair: Trude Nilsen
Location: Gilbert Scott, 253 [Floor 2]

Capacity: 40 persons

Paper Session

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Presentations
09. Assessment, Evaluation, Testing and Measurement
Paper

The Development of Mathematical Thinking Skills and Mathematical Self-concept from the Third Grade to the End of Basic Education

Natalija Gustavson1, Satu Koivuhovi2, Mari-Pauliina Vainikainen3, Mikko Asikainen1

1University of Helsinki, Finland; 2University of Turku, Finland; 3Tampere University, Finland

Presenting Author: Gustavson, Natalija

One of the basic skills for success in the knowledge society is the ability to learn. The Finnish national learning to learn (L2L) assessment program was launched in the mid-1990s as a result of a worldwide interest in the measurement of cross-curricular competences (Hautamäki et al., 2013).

The Learning to learn longitudinal assessment brings significant value and gathers sufficient information about learning outcomes and monitor changes in students’ competence during the basic education (Hoskins & Deakin Crick, 2010).

In Finland, L2L is assessed by administering cognitive tasks measuring general reasoning and thinking skills, and self-evaluation scales measuring beliefs and attitudes towards learning (Hautamäki & al., 2002). The concept of mathematical thinking is a traditional part of Learning to learn assessment.

Children’s learning-related beliefs, self-concept and interest in a particular subject play an important role in their school performance, particularly in mathematics. In educational research, academic self-concept has been defined as students' perception of themselves within the academic environment (Marsh, 1990, Marsh and Scalas, 2010).

In this regard, it is of interest how the development of mathematical thinking occurs in schoolchildren during schooling and what other factors can influence the development and improvement of mathematical thinking.

Of particular interest in presented study was the development of mathematical thinking skills and mathematical self-concept (Marsh et al.,1988), as part of learning-related beliefs from the third grade to the ninth grade during the completion of basic education.

The main purpose of this study is to answer the following questions:

  1. How do pupils` mathematical thinking skills and mathematical self-concept develop during the comprehensive school years from the third to the ninth grade?
  1. Do mathematical self-concept on the third and the sixth grade predict the level of mathematical thinking skills on the sixth and the ninth grade?
  2. How do gender and mother’s education explain the level differences and change of mathematical self-concept?

Methodology, Methods, Research Instruments or Sources Used
Data (=2200) were drawn from a longitudinal Learning-To-Learn study in which a whole age cohort of third graders from the capital area of Finland were followed up until the end of the comprehensive school.  Data collection consisted of three measurement points (i.e. year 2016 when pupils were at third grade, year 2018 when pupils were at sixth grade and year 2021 when pupils were at ninth grade).
Measures that were used based on the framework of Finnish learning to learn test (Hautamäki et al., 2002).
Mathematical thinking skills were measured with two task types. The first task type, the Hidden Arithmetical Operators task (Arithmetical Operations for short) was developed by Demetriou and his colleagues (Demetriou et al., 1991). In each item there were one to four hidden operators (e.g., [(5 a 3) b 4 = 6).
In the second task sections of invented mathematical concepts (Sternberg et al., 2001), two invented mathematical concepts, lag and sev, were conditionally defined (for example, if a > b, lag means subtraction, otherwise multiplication, etc.). After this, the student was given a problem to solve (for example, how much is 4 lag 7 sev 10 lag 3), where the definitions had to be applied.

Mathematical self-concept was measured with a scale based on Marsh’s work on academic self-concept (Marsh et al., 1988).  The scale consisted of three items on a seven-point Likert scale ranging from one (not true at all) to seven (very true).
Data were analysed with SPSS24 for descriptive statistics and Mplus 7.2 for linear growth curve models. First, we analysed the development of mathematical thinking skills and mathematical self-concept at the level of the whole data, after which differences in development depending on the gender and mother’s education level were examined.

Conclusions, Expected Outcomes or Findings
Preliminary analyses showed that students’ mathematical thinking skills improved over time whereas self-concept in mathematics decreased statistically significantly from the third to the ninth grade.  This result aligns with earlier international findings of the decline of self-beliefs by age.
The linear growth curve model fitted the data well (RMSEA = .035; CFI = .992; TLI = .973).
The initial level of self-concept in the third grade statistically significantly predicted the student's success in the sixth-grade mathematical thinking test. Sixth grade’s mathematical thinking skills test score correlated significantly with the slope of mathematical self-concept indicating that the development of pupils’ mathematical self-concept differed depending on their performance in mathematical thinking skill test. Students who did well in the test of mathematical thinking skills at sixth grade experienced a milder decrease in their mathematical self-concept than other students.

Mathematical thinking skills test score at sixth grade, initial level of mathematical self-concept at third grade as well as the slope of mathematical self-concept predicted statistically significantly the test result in mathematical thinking skill test at ninth grade.  Overall, the model explained about 38% of the variance of ninth grade mathematical thinking skills test result.  
Gender was a statistically significant predictor of children’s mathematical self-concept. Boys' mathematical self-concept was stronger than that of girls. In addition, girls experienced a stronger decline in their self-concept over time than boys did.

References
Bong, M., & Skaalvik, E. M. (2003). Academic self-concept and self-efficacy: How different are they really? Educational Psychology Review, 15(1), 1–40. Hox, J. J.
Demetriou, A., Platsidou, M., Efklides, A., Metallidou, Y., & Shayer, M. (1991). The development of quantitative-relational abilities from childhood to adolescence: Structure, scaling, and individual differences. Learning and Instruction, 1, 19–43.
Guay, F., Marsh, H. W., & Boivin, M. (2003). Academic self-concept and academic achievement: Developmental perspectives on their causal ordering. Journal of Educational Psychology, 95(1), 124–136. https://doi.org/10.1037/0022-0663.95.1.124
Hautamäki, J., Arinen, P., Eronen, S., Hautamäki, A., Kupiainen, S., Lindblom, B., & Scheinin, P. (2002). Assessing learning-to-learn: A framework. National Board of Education, Evaluation 4/2002.
Hautamäki, J., Kupiainen, S., Marjanen, J., Vainikainen, M.-P., & Hotulainen, R. (2013). ). Oppimaan oppiminen peruskoulun päättövaiheessa: Tilanne vuonna 2012 ja muutos vuodesta 2001 [Learning to learn at the end of basic education: Situation in 2012 and change from 2001]. University of Helsinki. Department of Teacher Education Research Report 347. Unigrafia.
Hoskins, B., & Deakin Crick, R. (2010). Competences for learning to learn and active citizenship: Different currencies or two sides of the same coin? European Journal of Education, 45(1), 121–137. Crossref. ISI.
Marsh, H. W., Byrne, B. M., & Shavelson, R. J. (1988). A Multifaceted Academic Self-Concept: Its Hierarchical Structure and Its Relation to Academic Achievement. Journal of Educational Psychology, 82(4), 623–636. https://doi/10.1037/0022-0663.80.3.366
Marsh, H. W. (1990). The structure of academic self-concept: The Marsh/Shavelson model. Journal of Educational Psychology, 82(4), 623–636. https://doi.org/10.1037/0022-0663.82.4.623
Marsh, H. W., Scalas, L. F., & Nagengast, B. (2010). Longitudinal tests of competing factor structures for the Rosenberg Self-Esteem Scale: Traits, ephemeral artifacts, and stable response styles. Psychological Assessment, 22(2), 366–381. https://doi.org/10.1037/a0019225
Sternberg, R., Castejon, J.L., Prieto, M.D., Hautamäki, J., & Grigorenko, E. (2001). Confirmatory factor analysis of the Sternberg Triarchic Abilities Test in three international samples. European Journal of Psychological Assessment, 17, 1-16.
Vainikainen , M-P & Hautamäki , J 2022 , Three Studies on Learning to Learn in Finland :Anti-Flynn Effects 2001-2017 ' , Scandinavian Journal of Educational Research , vol. 66 , no. 1 , pp. 43-58 . https://doi.org/10.1080/00313831.2020.1833240


09. Assessment, Evaluation, Testing and Measurement
Paper

Tracking in English and Mathematics: Consequences for Compulsory School Students’ Self-Concept

Thea Klapp, Jan-Eric Gustafsson, Stefan Johansson

University of Gothenburg

Presenting Author: Klapp, Thea

The study's overall purpose is to explore the formation of student academic self-concept (ASC) in the subjects of English and mathematics. ASC is commonly defined as self-perceived academic ability and is related to cognitive and non-cognitive outcomes such as academic engagement, goal-setting, task choice, persistence and effort, intrinsic motivation, strategy use, academic achievement, and future career selection (Bong & Skaalvik, 2003; Marsh et al., 2019). When students perceive their previous experiences of academic activities to be positive and when they perceive that they are capable of managing future academic activities, it is thus an advantage that goes beyond immediate academic success. Rather, ASC has been shown to have prolonged effects (Marsh et al., 2001).

Because ASC frequently has been shown to be important for student success, much research has been dedicated to explaining how it is formed. The main explanation is the big-fish-little-pond effect (BFLPE), which posits that equally abled students perceive their abilities differently depending on their context (Marsh et al., 2008). A student in a high-achieving context would rate their ability to be lower than a student in a lower-achieving context, even if both students have the same abilities.

In 1962, tracking was introduced in the subjects of English and mathematics in all secondary schools in Sweden (Grades 7-9). With recommendations from teachers, students were to choose between advanced and general courses in the two subjects (Marklund, 1985). The general courses were easier and given at a slower pace than the advanced courses and tended to have lower class-average achievement. Tracking is no longer a formal practice in Swedish compulsory education, but it commonly occurs when teachers organise education in Sweden and internationally (Trautwein et al., 2006).

ASC is a well-researched area, but so far, only a few studies have conducted longitudinal analyses to investigate effects over time. There is also a need for studies that look at how ASC is affected by school systems with some form of tracking (i.e., ability stratification, ability grouping etc.). The specific purpose of the study is to explore the effects of non-tracking and tracking in secondary school on ASC in upper secondary schools. With longitudinal data from the 1980s and 90s, ASC will be measured in Grade 6 (pre-tracking) and Grade 10 (post-tracking).

Previous Research

In a longitudinal study, Marsh et al. (2001) compared students from former East and West Germany (N = 2 778). They found that when East and West Germany reunited and the schools merged, the students who had attended the selective and ability-stratified schools in West Germany were more strongly affected by the negative BFLPE when compared to the East German students. Before the reunification, East German students had not experienced an ability-stratified school system. The difference between the merged students decreased with time when the former East German students became integrated with the more selective school system. Overall, the findings of Marsh et al. (2001) indicate that school policies and systems may have an impact on the formation of student ASC.

Similarly, Liem et al. (2013) found that compulsory school students in low-ability streams in English and mathematics had higher self-concepts than students in high-ability streams when student achievement was controlled for. However, Herrmann et al. (2016) investigated the German within-school track system (N = 1 330) and found that the negative BFLPE for students in the advanced mathematics track disappeared when they controlled for positive assimilation effects. The positive assimilation effect is similar to the basking-in-reflected-glory (BIRG) effect, which both refer to the notion that attending a high-achieving class or school positively affects ASC.


Methodology, Methods, Research Instruments or Sources Used
Participants and procedure

   Data will be retrieved from the Swedish longitudinal project Evaluation through Follow-up (UGU), compiled by Statistics Sweden (Härnqvist, 2000). The sampling was a two-step stratified procedure, where municipalities were selected in the first step and classes in the second step. The UGU samples are nationally representative of their respective populations. Four birth cohorts will be used in the study, 1967 (N = 9 104), 1972 (N = 9 498), 1977 (N = 4293), and 1982 (N = 8 805). Cohorts 1967, 1972, and 1977 experienced tracking and will be merged to get a bigger sample. Cohort 1982 did not experience ability-streamed courses and will function as a control group.

   UGU consists of register, survey, and test data. Survey data was first collected in Grade 6 and then for a second time in upper secondary school. For cohorts 1967, 1972, and 1977 the second data collection occurred in Grade 10 and for cohort 1982 it occurred in Grade 12. Survey data from Grades 6 and 10/12 will be used to measure ASC pre- and post-tracking.
To deal with missing data, calibration weights and full information maximum likelihood (FIML) estimation will be used to correct for bias due to non-participation.

Measures and variables
  
   Cohorts 1967, 1972, and 1977 answered identical questions in Grade 10, while cohort 1982 answered similar but not identical questions as the other three cohorts. Measures of ASC will be constructed to be as similar as possible between the three earlier cohorts and cohort 1982. Factors will be created with indicators of students’ ASC, for example, “What kind of arithmetic skills do you think you have?” and “Did you experience any problems with arithmetic in secondary school”.
Achievement will be operationalized by grade point average (GPA) from Grade 9 and by cognitive ability from Grade 6. Cognitive ability will be measured with three tests measuring students’ verbal, spatial, and inductive abilities. Gender and parental education will also be included.

Method of Analysis

   First, descriptive analyses will be calculated. Measurement models will then be constructed in Mplus with confirmatory factor analysis (CFA), to create latent variables for ASC in Grades 6 and 10/12. Lastly, longitudinal structural equation modelling (LSEM) will be used. The tracking system enables a quasi-experimental research design, that in turn makes it possible to investigate the effect of tracking on subsequent ASC with LSEM and the control group that did not experience tracking.

Conclusions, Expected Outcomes or Findings
    Regarding the possible outcomes of the study, two contradictory effects are relevant to consider. It concerns the previously mentioned BFLPE as well as the basking-in-reflected-glory (BIRG) effect. The BIRG effect predicts that when students perceive their school or class (i.e., their reference group) to have high status, it affects their self-concepts positively (Marsh et al., 2000). The glory of attending a high-status group thus reflects on the individuals in the group, regardless of individual achievement level. In contrast, the BFLPE predicts that attending a high-achieving group affects students’ self-concept negatively, because of negative social comparison processes. Even if both effects concern the formation of self-concept, research has indicated that the BFLPE is the most dominant effect of the two (Marsh et al., 2000). I.e., the negative social comparison effect tends to have a greater impact on students’ self-concept than the positive effect of attending a high-status group.
  
   In the present study, the BFLPE hypothesis would be that students who attended the advanced courses in English and mathematics reported lower ASC in Grade 10 because their ASCs were negatively affected by the comparisons with high-ability peers in secondary school. However, it may also be that the BIRG effect is present rather than the BFLPE, which would mean that students in the advanced courses express higher ASC due to reflected glory.

References
Bong, M., & Skaalvik, E. M. (2003). Academic Self-Concept and Self-Efficacy: How
   Different Are They Really? Educational Psychology Review, 15(1), 1–40.

Herrmann, J., Schmidt, I., Kessels, U., & Preckel, F. (2016). Big fish in big ponds:
   Contrast and assimilation effects on math and verbal self‐concepts of students in
   within‐school gifted tracks. British Journal of Educational Psychology, 86(2), 222–
   240.

Härnqvist, K. (2000). Evaluation through follow-up. A longitudinal program for
   studying education and career development. In C.-G. Janson (Ed.), Seven
   Swedish longitudinal studies in behavioral science (pp. 76–114). Stockholm:
   Forskningsrådsnämnden.

Liem, G. A. D., Marsh, H. W., Martin, A. J., McInerney, D. M., & Yeung, A. S.
   (2013). The Big-Fish-Little-Pond Effect and a National Policy of Within-School
   Ability Streaming: Alternative Frames of Reference. American Educational
   Research Journal, 50(2), 326–370.

Marklund, S. (1985). Skolsverige 1950-1975 D. 4 Differentieringsfrågan.
   Stockholm: Liber Utbildningsförlaget.

Marsh, H. W., Köller, O., & Baumert, J. (2001). Reunification of East and West
   German School Systems: Longitudinal Multilevel Modeling Study of the Big-Fish-
   Little-Pond Effect on Academic Self-Concept. American Educational Research
   Journal, 38(2), 321–350.

Marsh, H. W., Kong, C., & Hau, K. (2000). Longitudinal multilevel models of the
   big-fish-little-pond effect on academic self-concept: Counterbalancing contrast
   and reflected-glory effects in Hong Kong schools. Journal of Personality and
   Social Psychology, 78(2), 337–349.

Marsh, H. W., Pekrun, R., Parker, P. D., Murayama, K., Guo, J., Dicke, T., & Arens,
   A. K. (2019). The murky distinction between self-concept and self-efficacy:
   Beware of lurking jingle-jangle fallacies. Journal of Educational Psychology,
   111(2), 331–353.

Marsh, H. W., Seaton, M., Trautwein, U., Lüdtke, O., Hau, K. T., O’Mara, A. J., &
   Craven, R. G. (2008). The Big-fish–little-pond-effect Stands Up to Critical
   Scrutiny: Implications for Theory, Methodology, and Future Research.
   Educational Psychology Review, 20(3), 319–350.

Trautwein, U., Lüdtke, O., Marsh, H. W., Köller, O., & Baumert, J. (2006). Tracking,
   Grading, and Student Motivation: Using Group Composition and Status to Predict
   Self-Concept and Interest in Ninth-Grade Mathematics. Journal of Educational
   Psychology, 98(4), 788 – 806.


09. Assessment, Evaluation, Testing and Measurement
Paper

The Influence of Mathematics Self-concept and Self-efficacy on Mathematics Achievement: Comparison between the Public and Independent Schools in Sweden

Yi Ding, Alli Klapp, Kajsa Hansen

University of Gothenburg, Sweden

Presenting Author: Ding, Yi

Achievement gaps in mathematics can be found among education systems all over the world in international large-scale assessment studies (ILSAs). In almost all education systems, students’ socioeconomic status (SES) has been documented as one of the most important factors associated with achievement, known as the “socioeconomic achievement gap” (Chmielewski, 2019), while in other education systems, achievement gaps can be accounted for by gender, immigration background, ethnicity and/or urban-rural locations of schools and students (e.g., Bondy et al., 2017; Brozo et al., 2014; Song et al., 2014). In Sweden, remarkable differences can be observed between public and independent schools and the differences might be explained by a larger share of students with well-educated parents in independent schools than in public schools (Klapp Lekholm, 2008). Taking mathematics as an example, students in independent schools perform better than students from public schools in Programme for International Student Assessment (PISA), even after controlling the background variables, and the crucial difference in achievement holds consistent from PISA 2003 to PISA 2012 regardless of the sharp decline, and the advantage of independent schools has emerged over time (OECD, 2019).

The types of schools (private or public as categorised in PISA) are generally differentiated by the ownership of schools. Private schools refer to schools managed directly or indirectly by a non-government organisation (such as a church, trade union, business or other private institution), while public schools are managed by a public education authority, government agency, or governing board appointed by the government or elected by a public franchise (OECD, 2020). In the Swedish context, instead of private schools, it would be more accurate to use the term independent schools, which can be run by private organisations to operate educational activities through a publicly funded voucher system (Yang Hansen & Gustafsson, 2016) and could be running for profit (Wiborg, 2015).

Research also indicates that students’ motivational beliefs seem to be important for academic achievement in the Swedish education system (Klapp, 2018). Previous research has established that student self-beliefs could predict and impact academic achievement, among which self-concept and self-efficacy are the most identified ones (Bong & Skaalvik, 2003; Multon et al., 1991). Mathematics self-concept is an individual’s perceived competence in mathematics (OECD, 2013), and was found strongly related to students’ general mathematics achievement (Bong & Skaalvik, 2003; Ma & Kishor, 1997). Mathematics self-efficacy measures students’ expectations and conviction of what can be accomplished when they need to solve pure and/or applied mathematics tasks. Students’ mathematics self-efficacy had a strong direct effect on mathematics problem-solving despite their general mental ability (Pajares & Kranzler, 1995).

It is well established that mathematics self-concept and self-efficacy to a varying degree are associated with students’ mathematics achievement. It has also been observed for many decades that student gender, socioeconomic status and immigration background influence academic achievement, directly and indirectly (e.g., Bondy et al., 2017; Schleicher, 2006). There is still uncertainty, however, regarding how the relations among mathematics self-concept, self-efficacy, student characteristics (SES, gender, immigrationbackground) and mathematics achievement may vary for students in different types of schools (public or independent) in the Swedish education system and over the years.

The main aim of the study was to investigate the relative importance of student mathematics self-concept and self-efficacy for mathematics achievement across Swedish public and independent schools over time, concerning student characteristics such as SES, gender and immigration background.


Methodology, Methods, Research Instruments or Sources Used
This study consists of students from Sweden who participated in PISA 2003 (N=4624, n=186 from independent schools) and PISA 2012 (N=4736, n=787 from independent schools). Mathematics self-concept (MSC) was measured by five items, where the students were asked how they feel when studying mathematics. They were supposed to report whether they strongly agree, agree, disagree or strongly disagree with the statements, such as “I get good marks in mathematics” and “I learn mathematics quickly”. Mathematics self-efficacy (MSE) was measured by eight items, indicating the perceived mathematical abilities. The students were asked to report whether they feel very confident, confident, not very confident or not at all confident in facing pure and applied mathematical tasks, such as “calculating TV discount” and “understanding a train timetable”. Mathematics achievement, as defined as mathematical literacy in PISA, captures student capability in formulating, employing and interpreting mathematics in diverse contexts (OECD, 2013). Five plausible values were generated to represent student mathematics achievement. Students were categorised into males and females in PISA. In this study, students were grouped into natives (students born in Sweden and whose at least one parent was also born in Sweden) and non-natives (students born in Sweden with non-Sweden-born parents, and students born outside Sweden as well as their parents). Student economic, social and cultural status (ESCS) is an index in PISA reflecting student family educational, occupational and cultural status.
Descriptive statistics were first investigated, giving an overview of all the variables. Secondly, multi-group confirmatory factor analyses (MGCFA) were performed to examine the factor structure and measurement invariance across the two PISA cycles and across the school types (the independent and public schools) in Sweden. Then, concerning the cluster sampling strategy in PISA and the intention of making comparisons in this study, multi-group multi-level structural equation modelling (MGSEM) was applied to study the relations between mathematics self-concept, self-efficacy and mathematics achievement, concerning students’ gender and immigration background.
SPSS 28 were used for data management and Mplus 8 for analyses.

Conclusions, Expected Outcomes or Findings
As mentioned earlier, Swedish students in independent schools achieve higher than those in public schools despite the extraordinary decline from PISA 2003 to PISA 2012. The overall results suggest that students with high levels of mathematics self-concept and self-efficacy tend to have better performance in mathematics. Students with better economic, social and cultural status are possibly to have stronger mathematics self-concept and self-efficacy and perform better in mathematics. Immigrant students perform considerably worse than non-immigrant students in mathematics and yet they perceive themselves as having higher mathematics self-concept and self-efficacy. Girls who, although performed equally well or even better than boys, hold nevertheless weaker mathematics self-concept and self-efficacy. At the school level, mathematics achievement is positively associated with economic, social and cultural status. Schools with larger portions of immigrant students seem to have lower economic, social and cultural status and mathematics achievement.
Compared to independent schools, the influence of mathematics self-efficacy is stronger than mathematics self-concept in both PISA 2003 and 2012 in public schools. Economic, social and cultural status plays a relatively less important role in mathematics self-concept, self-efficacy and achievement in public schools. Conversely, the effect of immigration background seems to be stronger in independent schools. Girls are found to have even lower levels of mathematics self-concept and self-efficacy in independent schools.
The study has significant implications for researchers and practitioners in the educational and psychological fields. Positive self-beliefs are significant representative constructs in educational psychology (Marsh et al., 2019). The results and findings from this study highlighted the important role of mathematics self-concept and self-efficacy in mathematics achievement across Swedish public and independent schools. It is important to raise teachers’ awareness of promoting students’ self-concept and self-efficacy in mathematics learning, for girls, immigrant students and students with lower SES in particular.

References
Bondy, J. M., Peguero, A. A., & Johnson, B. E. (2017). The children of immigrants’ academic self-efficacy: The significance of gender, race, ethnicity, and segmented assimilation. Education and Urban Society, 49(5), 486–517.
Bong, M., & Skaalvik, E. M. (2003). Academic self-concept and self-efficacy: How different are they really? Educational Psychology Review, 15(1), 1–40.
Brozo, W. G., Sulkunen, S., Shiel, G., Garbe, C., Pandian, A., & Valtin, R. (2014). Reading, Gender, and Engagement. Journal of Adolescent & Adult Literacy, 57(7), 584–593.
Chmielewski, A. K. (2019). The Global Increase in the Socioeconomic Achievement Gap, 1964 to 2015. American Sociological Review, 84(3), 517–544.
Klapp, A. (2018). Does academic and social self-concept and motivation explain the effect of grading on students’ achievement? European Journal of Psychology of Education, 33(2), 355–376.
Klapp Lekholm, A. (2008). Grades and grade assignment: Effects of student and school characteristics. rapport nr.: Acta Universitatis Gothoburgensis 269.
Ma, X., & Kishor, N. (1997). Attitude toward self, social factors, and achievement in mathematics: A meta-analytic review. Educational Psychology Review, 9(2), 89–120.
Marsh, H. W., Pekrun, R., Parker, P. D., Murayama, K., Guo, J., Dicke, T., & Arens, A. K. (2019). The murky distinction between self-concept and self-efficacy: Beware of lurking jingle-jangle fallacies. Journal of Educational Psychology, 111(2), 331.
Multon, K. D., Brown, S. D., & Lent, R. W. (1991). Relation of self-efficacy beliefs to academic outcomes. Journal of Counseling Psychology, 38(1), 30.
OECD. (2013). PISA 2012 assessment and analytical framework: Mathematics, reading, science, problem solving and financial literacy.
OECD. (2019). Sweden - country note - PISA 2018 results.
OECD. (2020). PISA 2018 results (volume v): effective policies, successful schools.
Pajares, F., & Kranzler, J. (1995). Self-efficacy beliefs and general mental ability in mathematical problem-solving. Contemporary Educational Psychology, 20, 426–426.
Schleicher, A. (2006). Where immigrant students succeed: A comparative review of performance and engagement in PISA 2003. Intercultural Education, 17(5), 507–516.
Song, S., Perry, L. B., & McConney, A. (2014). Explaining the achievement gap between Indigenous and non-Indigenous students: an analysis of PISA 2009 results for Australia and New Zealand. Educational Research and Evaluation, 20(3), 178–198.
Wiborg, S. (2015). Privatizing Education: Free School Policy in Sweden and England. Comparative Education Review, 59(3), 473–497.
Yang Hansen, K., & Gustafsson, J.-E. (2016). Causes of educational segregation in Sweden – school choice or residential segregation. Educational Research and Evaluation, 22(1–2), 23–44.


 
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