natgillin/translations-raw huggingface dataset:
Males outperformed females in the Czech Republic, Hungary, the Netherlands, Austria and Island.
V raziskavi TIMSS-R 1999 je bilo ugotovljeno, da so v osmem letu šolanja fantje uspešnejši od deklet v
There was no gender gap in the Flemish Community of Belgium, Bulgaria, Italy, Cyprus, Romania, Finland and Turkey.
(5) Razlik med spoloma ni bilo v flamski skupnosti v Belgiji, Bolgariji, Italiji, na Cipru, v Romuniji, na Finskem in v Turčiji.
Boys scored higher in the Czech Republic, Latvia, Lithuania, Hungary, the Netherlands, Slovenia, Slovakia and the United Kingdom (England) (Martin et al., 2000).
Fantje so dosegli boljši rezultat na Češkem, v Latviji, Litvi, na Madžarskem, Nizozemskem, v Sloveniji, na Slovaškem in v Združe- nem kraljestvu (Angliji) (Martin in sod., 2000).
Gender Differencesin Educational Outcomes lower self-concept than males in science i.e., on average, girls had lower levels of belief in their scientific abilities than boys in all European countries. Boys also had higher selfefficacy, i.e. a higher level of confidence in tackling specific scientific tasks in all countries, except Austria, Poland and Portugal.
2. poglavje: Vzorci dosežkov po spolu v mednarodnih pregledih o preverjanju znanja razlik med spoloma med letoma 1995 in 1999 (vendar zato, ker so bili fantje manj uspešni kot prej in ne zato, ker bi dekleta napredovala); v preostalih državah se razlike med spoloma niso spremenile.
As PISA 2006 focused on science, it reported other interesting issues.
Raziskava TIMSS 2003 je razkrila, da v četrtem letu šolanja v večini držav (amski skupnosti v Belgiji, Italiji, Latviji, na Madžarskem, v Sloveniji, Združenem kraljestvu (Angliji) in na Norveškem) ni bilo razlik med spoloma.
On average females were stronger in identifying scientific issues, while males were stronger at explaining phenomena scientifically.
V osmem letu šolanja pa so v večini držav fantje izkazali dosti boljše dosežke kot dekleta.
In most other aspects of self-reported attitudes towards science there were no consistent gender differences.
Le v Estoniji in na Cipru pri dosežkih iz naravoslovja ni bilo razlik med spoloma.
Both boys and girls had similar levels of interest in science and there was no overall difference in boys' and girls' inclination to use science in future studies or jobs (OECD, 2007b).
V povprečju pa so dekleta bolj napredovala kot fantje, posebno v primerjavi z letom 1999 (Martin in sod., 2004).
Data on low achievers and/or students without basic skills are invaluable indicators of inequality in education.
Fantje so bili uspešnejši na Danskem in v Avstriji, dekleta pa v Latviji (OECD, 2001).
The PISA scores are allocated to scales divided into difficulty levels that represent groups of PISA test questions.
PISA 2003 je razkrila prednost fantov le v nekaj državah (na Danskem, v Grčiji, Luksemburgu, na Poljskem, Portugalskem, Slovaškem in v Lihtenštajnu) in nikakršnih razlik med spoloma v večini držav.
The scales allow concentrating on performance or competencies levels, including examination of poor performance.
Dekleta so bila boljša kot fantje na Finskem in Islandiji (OECD, 2004).
For example, a student demonstrating the most basic skills is allocated to proficiency Level 1, while a student without the skills needed to correctly complete the easiest questions on a PISA test is classified as below Level 1.
Razlike med rezultati iz raziskav TIMSS in PISA je mogoče pojasniti s tem, da so bili v programu PISA med predmeti, ki so se preverjali, bolj poudarjeni predmeti iz ved o živi naravi. To pa je področje, na katerem so se tudi v raziskavah TIMSS dekleta izkazala kot uspešnejša (OECD, 2001).
Table 1 (in annexe) shows the relative risk of scoring at the lowest proficiency levels (Level 1 or below) in reading, mathematics and science by gender.
Tudi v programu PISA 2006 so bile, gledano v celoti, razlike med spoloma najmanjše pri naravoslovju, zlasti če jih primerjamo s tistimi pri matematiki in branju.
Reflecting average gender differences, boys are more likely to be amongst the poorest performers in reading in all countries except Liechtenstein.
Kot kaže preglednica 2.2c, v povprečju v večini držav ni bilo razlik med spoloma.
In mathematics, among low achievers, the proportion of females and males is approximately equal in most countries.
Dekleta so bila uspešnejša v Bolgariji, Grčiji, Latviji, Litvi, Sloveniji in Turčiji, fantje pa na Danskem, v Luksemburgu, na Nizozemskem in v Združenem kraljestvu (Angliji).
Girls are at greater risk of scoring at the lowest proficiency levels in the Czech Republic, Denmark, Germany, Italy, Luxembourg, the Netherlands, Austria, Portugal, Slovakia and the United Kingdom (England, Wales and Northern Ireland).
Čeprav so bila dekleta enako uspešna kot fantje, pa so imela v vseh evropskih državah slabšo samopodobo in v povprečju slabše mnenje o svojih naravoslovnih sposobnostih.
Only in Iceland boys are more likely to be amongst low achievers in mathematics.
Fantje so bolj verjeli v svojo učinkovitost, višja je bila raven samozaupanja, da se zmorejo spoprijeti s posebnimi nalogami, in sicer v vseh državah, razen v Avstriji, na Poljskem in Portugalskem.
In science, there are no gender differences amongst low achievers in most countries.
V programu PISA 2006 je bila posebna pozornost namenjena naravoslovju, zato so bila pripravljena tudi poročila o drugih zanimivih vprašanjih.
Boys are more likely to have low scientific literacy in Bulgaria, Ireland, Latvia, Lithuania, Slovenia, Finland, Iceland and Turkey.
V zvezi z večino drugih vidikov, npr. glede odnosa do naravoslovja, pa ni bilo enotnih razlik med spoloma.
Interestingly, there were no gender differences amongst the poorest performers in those countries where boys on average tend to perform better than girls (Germany, Luxembourg, the Netherlands and the United Kingdom (England)).
Dekleta in fantje so izkazali podobno raven zanimanja za naravoslovje, oboji so izkazali tudi nagnjenost, da si naravoslovje izberejo za prihodnji študij ali službo (OECD, 2007b).
Motivation, or interest, in certain study fields is often considered as a factor for predicting achievement (Renninger et al., 1992). Figure 2.1 shows gender differences in perceived importance of doing well in reading, mathematics and science.
Podatki o učencih s slabimi dosežki in tistih, ki niso osvojili temeljnega znanja in spretnosti, so neprecenljivi pokazatelji neenakosti v izobraževanju.
The data suggests that the perceived importance of doing well in mathematics and science, on average, does not differ by gender.
Rezultati PISA so razporejeni v težavnostne ravni, ki predstavljajo skupine testnih vprašanj.
Reading, however, is considered important by far more girls than boys in all European countries.
Lestvice omogočajo pripravo zbirnih podatkov o ravneh uspešnosti in kompe-
Chapter 2: Gender Patterns in International Assessment Surveys
2. poglavje: Vzorci dosežkov po spolu v mednarodnih pregledih o preverjanju znanja
Figure 2.1: Gender difference (M-F) in perceived importance of doing well in reading, mathematics and science for 15 year-old pupils, 2006
Preglednica 2.1: Razlike med spoloma (M-Ž) o pomenu znanja branja, matematike in naravoslovja pri 15-letnikih, 2006
Countries that did not contribute to data collection
Države, ki niso posredovale podatkov.
The results are based on answers to the question: 'in general, how important do you think it is for you to do well in the subject below?' with four answer categories: very important, important, of little importance and not important at all.
Rezultati so pripravljeni na podlagi odgovorov na vprašanje: 'Na splošno, kako pomembno se ti zdi dobro znanje naštetih predmetov?' s štirimi mogočimi odgovori: zelo pomembno, pomembno, manj pomembno, nepomembno.
The graph shows coefficients of three different simple linear regression models.
Graf prikazuje količnik treh različnih enostavnih linearnih regresijskih modelov.
For further information on the PISA survey, see the Glossary. Values that are statistically significant (p < .05) are indicated in bold.
Za več informacij o raziskavi PISA glej Pojmovnik.Statistično pomembne vrednosti (p < ,05) so označene krepko.
Factors influencing achievement and gender gaps
Dejavniki, ki vplivajo na dosežke in razlike med spoloma
2.2.1.Impact of streams(tracks) andfalling behind at school
2.2.1 Vpliv usmeritev (programov) in zaostajanje v šoli
It is also relevant to consider to what extent the gender gap is related to gender differences in the distribution of students across different streams or tracks (school programmes) and year groups.
Upoštevati je treba tudi, koliko so razlike med spoloma povezane z razporeditvijo učencev po različnih usmeritvah in poteh (po izobraževalnih programih) in šolskih letih.
Almost all educational systems at upper secondary level divide pupils into separate study streams that have distinct curricula and award different school leaving certificates for the different qualifications acquired by pupils.
V skoraj vseh šolskih sistemih se na višji sekundarni ravni dijaki razdelijo po različnih izobraževalnih usmeritvah, z različnimi kurikulumi, različnimi spričevali in kvalikacijami, ki si jih lahko pridobijo.
Several European education systems introduce different streams immediately after primary school.
V več evropskih državah se različne usmeritve vpeljejo takoj po končani primarni šoli.
General or academically-oriented study streams usually provide easier access to university programmes, while vocational streams traditionally prepare pupils for particular occupations and entry into the labour market (although they often also provide possibilities for further education).
Splošne, akademsko naravnane usmeritve omogočajo lažji dostop v univerzitetne programe, poklicne usmeritve pa dijake tradicionalno pripravljajo za posamezne poklice in vstop na trg dela (čeprav pogosto omogočajo tudi nadaljevanje izobraževanja).
Boys and girls tend to participate in different study programmes, with more girls in more demanding, academically-oriented and humanities-based tracks, while more boys are in vocational streams (see also Chapter 5).
Fantje in dekleta se odločajo za različne programe, več deklet za zahtevnejše, akademsko naravnane in humanistične smeri, več fantov pa je v poklicnih usmeritvah (glej tudi 5. poglavje).
Boys tend to both fall behind in school (due to starting school later) and be required to repeat school years more frequently than girls (see Chapter 5).
Fantje v šoli večkrat zaostajajo (ker šolanje začnejo pozneje), večkrat kot od deklet se od njih zahteva, da razred ponavljajo (glej 5. poglavje).
PISA 2006 revealed that, in most countries, there were statistically significant differences in the number of school years completed by 15 year-old boys and girls, with more boys than girls having completed only the lower school years.
Program PISA 2006 je razkril, da so v večini držav statistično pomembne razlike v številu let šolanja, ki so jih končali 15 let stari fantje in dekleta; več fantov kot deklet je končalo nižji razred.
Pupils in different study programmes or school years have different curricula, which should be taken into account in considering achievement levels.
Dijaki v različnih izobraževalnih programih in šolskih letih imajo različne kurikulume, kar je treba pri proučevanju dosežkov upoštevati.
Figure 2.2 allows comparison between the previously-discussed average gender gaps computed by a simple linear regression models, and average gender gaps computed by multilevel models that control for school year and streaming in schools.
Preglednica 2.2 omogoča primerjavo med prej omenjenimi povprečnimi razlikami med spoloma, zračunanimi z enostavnim linearnim regresijskim modelom, in povprečnimi razlikami, zračunanimi z večnivojskim modelom, pri katerem se upoštevata leto šolanja in usmeritev.
The gender differences relating to streaming and falling behind in school tend to favour females when measuring the average gender gap.
Razlike med spoloma, povezane z usmeritvijo in zaostajanjem v šoli, so v prid dekletom, če se merijo povprečne razlike.
When controlling for school year and streaming, female advantage diminishes as the male lead increases.
Ob upoštevanju leta šolanja in usmeritve se prednost deklet izniči, saj jih fantje dohitijo.
Thus, the poorer overall male performance in reading is less visible in classrooms and schools.
Zato je v razredu in na šoli slabša uspešnost fantov pri branju manj opazna.
However, girls' advantage in reading remains present in schools and the gender gap, even when controlling for school year and streaming, is statistically significant in favour of females in all countries except the Germanspeaking Community of Belgium.
Vendar je prednost deklet pri branju še razvidna, razlike med spoloma pa so tudi ob upoštevanju leta šolanja in usmeritve še naprej statistično pomembne in so v vseh državah, razen v nemško govoreči skupnosti v Belgiji, v prid deklet.
Similarly, in mathematics and science, the small average gender gap might be partly explained by the tendency of females to participate in higher-level school programmes or streams than their male counterparts.
Podobno je tudi pri matematiki in naravoslovju majhne povprečne razlike med spoloma mogoče delno razložiti s tem, da je v zahtevnejših programih ali usmeritvah več deklet kot njihovih vrstnikov moškega spola.
Within individual schools, however, much larger differences are observed.
Na posameznih šolah pa so razlike dosti večje.
In fact, in the same schools, streams and programmes females tend to perform at a lower level in mathematics and science than males.
Pravzaprav je mogoče na istih šolah, usmeritvah in programih opaziti, da dekleta pri matematiki in naravoslovju izkažejo nižjo raven znanja kot fantje.
Controlling for the school year and stream attended, there was a significant gender gap found in mathematics in all European countries except Iceland and Liechtenstein.
Ob upoštevanju leta šolanja in usmeritve, so bile pri matematiki opazne razlike med spoloma ugotovljene v vseh evropskih državah, razen na Islandiji in v Lihtenštajnu.
The difference amounted to about one third of the international standard deviation in Hungary, the Germanspeaking Community of Belgium, Germany, Austria and Portugal.
Razlika je segla do tretjine mednarodnega standardnega odklona na Madžarskem, v nemško govoreči skupnosti v Belgiji, Nemčiji, Avstriji in na Portugalskem.
In science, the gender gap within the schools is the least pronounced, although significant in all countries, except Latvia, Lithuania, Finland, Sweden, the United Kingdom (Scotland), Iceland, Liechtenstein, Norway and Turkey.
Pri naravoslovju so bile razlike med spoloma na šolah najmanj izrazite, vendar opazne v vseh državah, razen v Latviji, Litvi, na Finskem, Švedskem, v Združenem kraljestvu (na Škotskem), na Islandiji, v Lihtenštajnu, na Norveškem in v Turčiji.
Figure 2.2: 'Gross' average gender difference (M-F) and 'net' average gender difference, controlling for school year and stream, in scores for reading, mathematics and science for 15 year-old pupils, 2006
Preglednica 2.2: 'Bruto' in 'neto' povprečne razlike med spoloma (M-Ž) pri rezultatih 15-letnikov iz branja, matematike in naravoslovja, upoštevaje leto šolanja in usmeritve, 2006
Total average gender differences are computed by simple linear regression; average gender differences, controlled for school year and stream are computed by multilevel regression models.
Skupne povprečne razlike med spoloma so zračunane z enostavno linearno regresijo; povprečne razlike med spoloma, upoštevaje leto šolanja in usmeritev, so zračunane z večnivojskim regresijskim modelom.
For further information on the PISA survey, see the Glossary.
Za več informacij o raziskavi PISA, glej Pojmovnik.
Values that are statistically significant (p < .05) are indicated in bold.
Statistično pomembne vrednosti (p < ,05) so označene krepko.
a) READING boys 60 infavourof
a) BRANJE fantov tih
Controlled for school year and stream
Upoštevaje leto šolanja in usmeritev
-48.45 -44.69 -45.94-43.69-48.42 -27.23 -46.21-30.05 b) MATHEMATICS boys 6050 infavourof
-48,42 -27,23 -46,21 -30,05 b) MATEMATIKA fantov tih
Gender Differencesin Educational Outcomes c) SCIENCE boys 6050 infavourof
Razlike medspoloma priizobraževalnih dosežkih c) NARAVOSLOVJE fantov tih
2.2.2.Relativeimpact of gender, socioeconomic status andimmigrantbackground
2.2.2 Relativen vpliv spola, socialno-ekonomskega položaja in priseljenskega izvora
It is important to consider gender differences in achievement in the context of other sociodemographic characteristics.
Pomembno je, da se razlike med spoloma pri šolskih dosežkih obravnavajo skupaj z drugimi okoliščinami oziroma socialnimi in demografskimi značilnostmi.
Figure 2.3 shows the relative importance of gender, socioeconomic status and immigrant background in explaining variation in the reading, mathematics and science achievement of 15-year-olds using PISA 2006 data.
Preglednica 2.3 kaže relativen pomen spola, social-no-ekonomskega položaja in priseljenskega izvora in pojasnjuje različne dosežke 15-letnikov pri branju, matematiki in naravoslovju, kot so razvidni iz podatkov PISA 2006.
Simple linear regression by country was conducted.
Opravljena je bila enostavna linearna regresija po državah.
As the variables are not on the same scale, we are reporting the percentage of explained variance.
Ker spremenljivke niso na isti merski lestvici, so predstavljene z odstotnimi vrednostmi.
Analysis of PIRLS data yielded very similar results and is therefore not presented in detail.
Analize podatkov iz raziskave PIRLS niso pokazale dosti drugačnih rezultatov, zato niso natančno predstavljene.
Socioeconomic status has greater influence than gender and immigrant background in predicting achievement in all three study fields.
Na vseh treh predmetnih področjih ima socialnoekonomski položaj večjo napovedno vrednost kot spol ali priseljenski izvor.
Controlled for gender and immigrant background, index of economic, social and cultural status explains about 5 - 25 % of variance.
Ob upoštevanju spola in priseljenskega izvora indeks ekonomskega, socialnega in kulturnega položaja pojasni 5- do 25-odstotni delež variance.
It is statistically significant in all countries for the three subjects under discussion.
Pri vseh treh predmetih je v vseh državah nedvomno statistično pomembna.
Gender is less important than socioeconomic status in predicting achievement.
Pri napovedovanju dosežkov je spol manj pomemben kot socialnoekonomski položaj.
Only in reading is gender statistically significant in all countries (controlled for socioeconomic status and immigrant background) and accounts for about 2 - 9 % of total variance.
Le pri branju je spol v vseh državah statistično pomemben (upoštevaje socialnoekonomski položaj in priseljenski izvor) in znaša okrog 2 % do 9 % skupne variance.
In contrast, in Figures 2.3 b and c showing explained variation in mathematics and science gender is scarcely noticeable since it accounts for a maximum of 1 % of variance and is only present in some countries.
Nasprotno pa je vpliv spola, kot kažeta varianci za matematiko in naravoslovje v preglednici 2.3 b in c, komaj opazen, saj je varianca največ 1-odstotna in se pojavi le v nekaterih državah.
Gender is not significant in explaining differences in science achievement in the majority of the European education systems analysed (19 out of 32). Moreover, this is also true in about one third of the analysed education systems (13 out of 32) in explaining differences in mathematics achievement.
Za pojasnjevanje razlik pri naravoslovnih dosežkih v večini analiziranih evropskih šolskih sistemov (19 od 32) spol ni očitno zaznaven.V približno tretjini (13 od 32) analiziranih šolskih sistemov enako velja tudi za matematične dosežke.
Immigrant background, accordingly, has less importance than socioeconomic status or gender in predicting reading achievement (0 - 3 %), but has more importance than gender for predicting
Skladno z navedenim ima tudi priseljenski izvor za napoved dosežkov pri branju manjši pomen kot socialnoekonomski položaj ali spol (0 % - 3 %), pomembnejši kot spol pa je pri napovedovanju dosežkov iz matematike (0 % do 7 %) in naravoslovja (0 % do 6 %). Priseljenski izvor pri pojasnjevanju dosežkov iz
Immigrant background does not have a significant effect in nine education systems in explaining achievement in reading and mathematics. It is also not significant in eight systems for explaining achievement in science.
2. poglavje: Vzorci dosežkov po spolu v mednarodnih pregledih o preverjanju znanja branja in matematike nima močnega vpliva v devetih šolskih sistemih, kar zadeva naravoslovno znanje, pa v osmih.
Figure 2.3 indicates that the interplay between gender, socioeconomic background and immigrant status (i.e. combined indexes) explains up to 5 - 7 % of variance.
Preglednica 2.3 nakazuje, da je s prepletom spola, socialno-ekonomskega položaja in priseljenskega položaja (t.i. kombiniranim indeksom) mogoče pojasniti kar 5 % do 7 % variance.
However, it is difficult to single out clear pair-wise interactions.
Zelo težko pa je odbrati jasne in smiselne pare, ki se med seboj prepletajo.
OECD (2009a) showed that, the effect of socioeconomic or immigrant background on science performance was the same for both males and females in nearly all countries.
Raziskava OECD (2009a) je pokazala, da imata socialnoekonomski in priseljenski izvor na uspeh pri naravoslovju enak vpliv na fante in dekleta, in sicer skoraj v vseh državah.
Special disadvantaged groups with low attainment amongst males and females are discussed in greater detail in Chapter 5.
Posebno prikrajšane skupine fantov in deklet s slabimi dosežki so podrobneje opisane v 5. poglavju.
Figure 2.3: Percentage of explained variance of reading, mathematics and science achievement by gender, index of economic, social and cultural status, index of immigrant background and combined indexes for 15 year-old pupils, 2006 a) READING
Preglednica 2.3: Odstotni delež pojasnjene variance pri bralnih, matematičnih in naravoslovnih dosežkih po spolu, indeks ekonomskega, socialnega in kulturnega položaja ter indeks priseljenskega izvora pri 15-letnikih, 2006 a) BRANJE
Index of economic, social and cultural status
Indeks ekonomskega, socialnega in kulturnega položaja
Index of immigrant background
Indeks priseljenskega izvora
Country that did not participate in data collection
Države, ki niso posredovale podatkov.
The PISA index of economic, social and cultural status was created to capture wider aspects of a student's family and home background in addition to occupational status.
Indeks PISA o ekonomskem, socialnem in kulturnem položaju je bil sestavljen zato, da bi zajel širše vidike učenčevega družinskega in domačega okolja, skupaj z njihovo poklicno dejavnostjo.
It was derived from the following variables: the highest international socioeconomic index of occupational status of the father or mother; the index of highest educational level of parents converted into years of schooling and the index of home possessions.
Izpeljan je bil iz naslednjih spremenljivk: najvišjega mednarodnega socialno-ekonomskega indeksa položaja v poklicni dejavnosti matere in očeta, indeksa najvišje izobrazbene ravni staršev, štete v letih šolanja, in indeksa o premoženju.
The index of immigrant background was derived from students' responses to questions about whether or not they, their mother and their father were born in the country of assessment or in another country.
Indeks priseljenskega izvora je bil izpeljan iz odgovorov dijakov na vprašanje, ali sta bila mati in oče rojena v državi, v kateri je potekalo preverjanje znanja, ali v kakšni drugi državi.
The exact data values see in Table 2 in Annexes. For more details see OECD (2007a).
Za natančne podatkovne vrednosti glej 2. razpredelnico v Dodatku.Za podrobnosti glej OECD (2007a).
For further information on the PISA survey, see the Glossary.
Za več informacij o raziskavi PISA glej Pojmovnik.
International assessments of student achievement in reading, mathematics and science report some consistent gender patterns.
Pri mednarodnem preverjanju znanja učencev iz branja, matematike in naravoslovja se je pokazalo nekaj stalnih vzorcev razlik med spoloma.