Gender differences in out-of-school experience and interests in the school science curriculum among 13-year-old Bulgarian pupils | Статья в журнале «Школьная педагогика»

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Автор:

Рубрика: Внеучебная работа

Опубликовано в Школьная педагогика №1 (1) апрель 2015 г.

Дата публикации: 09.04.2015

Статья просмотрена: 36 раз

Библиографическое описание:

Герджикова, Нина Димитрова. Gender differences in out-of-school experience and interests in the school science curriculum among 13-year-old Bulgarian pupils / Нина Димитрова Герджикова. — Текст : непосредственный // Школьная педагогика. — 2015. — № 1 (1). — С. 49-54. — URL: https://moluch.ru/th/2/archive/2/79/ (дата обращения: 16.04.2024).

In this paper the author has examined the impact of gender on the out-of-school experience and learning preferences of 13-year-old pupils in Bulgarian comprehensive schools. The sample of 205 pupils in the 6-th grade has helped in demonstrating various patterns of gender differences. Using inferential statistics of a sample — Chi square test — the study has confirmed the cultural origins of the attitudes to the science curriculum.

Key words: interest, science, adolescence, learning, experience.

 

The science and technology have been described closely interlinked throughout the history of mankind. Formalized knowledge has been treated as the potent source of innovations in the praxis. Scientists play an important role in problem-solving procedures which explain complex phenomena in the real world. The interest in the surrounding living and non-living world involve the application of systematic knowledge. The trial-and-error method certainly plays a central part in the development of pupils’ attitudes to scientific ideas and their inventors. Furthermore, the motivation and methods for producing the artifacts and the scientific principles used have been the result of powerful cultural influences.

In view of the above issues, I have carried out research work, which is part of the comparative international survey guided by Prof. S. Sjöberg from the University of Oslo, Norway. This paper is based on a field study exploring the interests of pupils with specific reference to science and scientists. («Science and Scientists» — Questionnairy). It presents some of the findings from a research sub-question of a larger investigation exploring the problem of «How the learning within and out of the educational contexts fosters interest development of the six grade pupils». The question of relevance addressed in this paper is:

Are there gender differences in pupils’ out-of-school experience and interests and in their attitudes toward science and scientists?

Theories of pupils’ interests

The term ‘interest’ was first systematically introduced in pedagogy in the middle of the 19th century by Johann Herbart. Since then there have been various attempts to arrive at a definition. They have ranged from «an individual’s predisposition to attend to certain stimuli, events and objects through the «interest elicited by particular aspects of the environment», the understanding that «the level of interest [is] triggered when a definite topic is presented» (Ainley, Hidi & Berndorff, 2002, p. 545). These definitions are focused on three types of interest: they are individual, situational, and topical.

The term ‘interest’ is used by Krapp (2005, p. 381) from the perspective of the «person-object-theory». The interest describes the quality of this relationship and is qualified by its content or object specificity. Hidi & Renninger extend the definition and note that «an interest always refers to focused attention and/or engagement with the afford of a particular content» (Hidi & Renninger, 2006, p. 112). They found the powerful influence of pupils’ interest in their learning, specifically on attention, goals and levels of learning. However, in school practice, teachers often think they could not help unmotivated students and claim the interest either exists or does not exist, and they could not contribute to its development.

Contrary to this recognition, the findings from some large-scale surveys of occupational interests suggest that their development can be encouraged. The presence of the interest is connected with particular content over time in the individual learning history of the pupil. Therefore, Hidi & Renninger (2006, p. 113) propose a four-phase model of interest development. From this perspective, they put emphasis on the educational circumstances and on the models of teaching. The development of the individual and situational interests underlies the cognitive and affective processes. Each phase of interest has within itself some kind of different levels of «effort, self-efficacy, goal setting and ability to self-regulate behavior»(Hidi & Renninger, 2006, p. 114). Further, the authors describe four phases, as follows:

-          Phase 1: Triggered Situational Interest: It refers to a psychological state of interest that 3results from short-term changes in affective and cognitive processing;

-          Phase 2: Maintained Situational Interest: It refers to a psychological state of interest that is subsequent to a triggered state, involves focused attention and persistence over an extended episode in time, and/or reoccurs and persists again;

-          Phase 3: Emerging Individual Interest: It refers to a psychological state of interest as well as to the beginning phases of a relatively enduring predisposition to seek repeated engagement again with particular classes of content over time;

-          Phase 4: Well-Developed Individual Interest: It refers to the psychological state of interest as well as to a relatively enduring predisposition to reengage with particular classes of content over time.

The quotation above defines the development of the interest as its deepening enabled by the learning environment, positive personal feelings and the anticipation of the steps in working with tasks. The interests of pupils are considered as mediators of both their psychological states and their teachers’ instructional efforts. There have been enough representative empirical data sets, which raises the question whether it is possible for the existing developmental differences to appear to be linked with the particular gender.

There has been a consistent belief in everyday life that women and man are different. Recently, Chen, Chen, Ghang, Lee & Chen (2010) have published results about «gender reality» and its influence on the multi-domains of school-age children. The authors explain gender reality as balanced, recognizing both gender differences and gender similarities (Chen et al., 2010, p. 475). The data sets were collected via 11 psychological tests within a sample of Taiwanese children aged 6–17. The developmental trends are specified via dividing children into four rough age levels, which correspond to the school stages: elementary, middle, and high. The target group of my investigation is 12–14-year-old pupils.

The above-mentioned authors have proposed that gender reality at this age stage establishes clear differences between females and males in cognitive patterns. Girls are better in cognitive reasoning, comprehension of social events, grammar and word error recognition. Boys exceed girls in working memory and non-verbal abilities such as pictures, concepts and non-verbal, mechanical, and numerical reasoning (Chen et al., 2010, p. 476). The individual differences in learning style, interest and personality remain unchanged.

Although some gender differences become obvious at this age stage and girls have a «verbal advantage», while boys have a «non-verbal advantage», the results of the cited authors do not elicit changes in styles of personality, learning styles, emotions, and interests after finishing elementary school. This conclusion is true when the processed information and the field of learning are considered as independent from the learner, as something outside him or her. Some studies after 1980 «showed women to be slightly more field dependent» — claim Severiens &Ten Dam (1994, p. 489).

There are a number of evidence lines from Kolb’s theory, which have been used to support the distinction between men and women. According to Kolb women tend to prefer concrete learning styles, while men are more likely to opt for abstract conceptualization modes of learning. Still, this assumption does not explain how teaching and learning styles could be synchronized in the classroom and at which age stages gender differences would remain stable.

The theories, which underline that the learning outcomes result from the environment, find gender differences in extrinsic and intrinsic motivation. Men are more extrinsic oriented whereas women are intrinsic oriented. In addition, women appear to be surface approached in comparison with men, which are deep approached (Severiens &Ten Dam, 1994, p. 491).

Considering these research prerequisites, I shall try further to test, whether girls and boys in grade 6 have different life experience and distinctive scientific interests. In this paper, I have estimated the differences between the means of both girls and boys. The statistical significance will be determined by calculating the probability of error (p value) when p = 0.05 or less. My dependent variables are the science test scores of the pupils. The independent variable is gender: male or female.

Methods: subject selection, instrument and research procedure

The 225 participants were recruited from five compulsory junior high schools (grades 5–8) in the town of Smolyan, Bulgaria. All participated in the study voluntarily. There were 120 females with an average age of 13.3 and 105 males with an average age of 13.4 who successfully completed all items in the questionnaire.

The questionnaire was developed by Prof. Svein Sjöberg from the Department of Teacher Education and School Development at University of Oslo. The Science and Scientists questionnaire contains the following groups of items:

-          Scientist as a person: it elicits what children think «real scientists» are like;

-          Out of school experiences: What I have done: the items cover a large variety of activities, which may produce a positive effect of learning sciences at school;

-          Things to learn about: it lists the possible topics to be included in the science curriculum.

The next five tasks — Things to learn about: it lists the possible topics to be included in the science curriculum; Important for a future job: the items describe the aspects that might be significant for the choice of a future job; Science in action: the items evoke some associations and elicit some attitudes to science, which may be different for each pupil. Draw-a-scientist and the writing task, Me as a scientist will not be discussed in this paper.

Participants completed this questionnaire in a classroom setting. Responses are given for each group of items, as follows:

-          On a five-point scale ranging from strongly disagree to strongly agree (first group);

-          On a three-point scale ranging from often via sometimes to never (second group);

-          On a two-point scale — «yes»/»no» (third group).

Data analysis

Further, I present the results and interpretation from Pearson’s Chi-Square procedure. I begin with the Pearson’s Chi-Square where I compare how girls and boys value the scientists as persons. The group frequency distribution of the person’s traits of both the physicist and the biologist shows that the extreme scores are distributed in different ways. 30.2 % of the pupils strongly agree and 25.8 % agree that the physicist is tidy, neat and orderly. As far as the biologist is concerned — 62.2 % of the pupils strongly agree and 18.2 % — agree with this statement. The pupils have a positive view of both the physicist and the biologist when they estimate their intelligence — 47.7 % strongly agree, 16.9 % — agree that the physicist is clever and 52 % estimate the biologist as very intelligent and 17.8 % — as clever.

The same trend is observed when the pupils evaluate scientists as hard working. The pupils think that the physicist, and the biologist are neither democratic nor authoritarian (36 %: 36.9 %). More girls estimate both the physicist and the biologist higher as imaginative and full of ideas — 20.4 % strongly agree, 14.7 % agree (speaking about P) and 16 % strongly agree, 15.1 % agree (speaking about B). 7.1 % more of the girls think that the biologist is very caring for others but 29.3 % of all pupils express neither a positive nor a negative opinion about the physicist. 39.7 % of the boys agree with the statement that the physicist is social, outgoing and 44.9 % think the same about the biologist. However, they are fewer than the girls (60.3 %: 55.1 %) who share this opinion. The frequency distributions of the traits «interesting, exciting» and «kind, human» people are very similar referring to the two kinds of scientists. The scores for «interesting» are as follows: 29.8 % strongly agree, 26.2 % agree and 22.7 % neither/nor for the physicist and 34.7 %: 24.9 %: 21.3 % for the biologist. The Chi-Square Tests indicate significance of all items, which is higher than 0.05, and it confirms the null hypothesis. Although not statistically significant, there are a number of gender differences. Generally, the females have higher scores than the males at each evaluative level.

Gender differences across all means of out-of-school experience have been examined using at the beginning one-way ANOVA. Gender differences are found in some items at first glance. The differences between the means for boys and girls at a given age period could be classified into three categories:

-          A class of items which are characterized by a small difference: here could be assigned «make clothes for her/himself — means girls to boys 2.6:2.8; Use rope and pulleys for lifting heavy things (2.7:2.5); play with building kits (like Lego)(2.2:2); Use a microscope (2.2:2.1); develop or process films (2.2:2.3); use a measuring tape or stick (23:24); make fertilizer of grass and other debris (2.8:2.8); make yoghourt, butter, cheese or ghee (2.7:2.7); have your own pet animal (cat, dog) — (1.4:1.5); observe or study a rainbow or different types of clouds (2.3:2.3); blow soap bubbles (2:2.2) and so on.

-          A class of items which are characterized by a medium difference: For example: use hand pump for water or other liquids (2.9:2.5); read a map or use a compass (2.5:1.1); make bread or pastry (1.7:2.3); make a windmill or a waterwheel (2.7: 2.3)

-          A class of items which are characterized by a large difference: these include items like Use a saw — girls: boys means 2.4:1.5; use a screwdriver (2.1:1.4); use a hammer (2.1:1.4).

The standard deviation indicates a great deal of variations for some items only: for example, the item «Use rope and pulleys for lifting heavy things» for boys — mean 2.5/ standard deviation 3.09 or the item «Read a map or used a compass» for girls — mean 2.5/standard deviation 2.9. Most of the standard deviation scores are close to the means.

The test of homogeneity of variance (Levene’s test) is not highly significant for the items like «Use needle and thread for sewing», «Climb a tree», «Make toys of wire, wood or other material», «Use a kitchen scale or other scales», «Make charcoal from wood», «Play with electric batteries and bulbs or motors»,, «Mend a bicycle tube», «Use a car jack or change wheels on a car», «Charge a car battery or other batteries» and 14 other items. A good half of the items have a significance value over 0.05, which means that the variances are significant.

In order for the condition for homogeneity of the variance in the groups of girls and boys to be completed, I have applied the non-parametric Chi-Square Test for measuring the difference between them. My research hypothesis has two parts:

-          Null hypothesis: There is no relationship between gender and life experience preferences.

-          Alternative hypothesis: There is a relationship between gender and life experience preferences.

The chic-square statistic was computed by the SPSS.10 program for Windows.

There is an example for item «Use needle and thread for sewing» below:

-          The cross-table includes the following information: 26.3 % of the girls and 5.8 % of the boys answer with «often»; 25 % of the girls and 28.6 % of the boys answer with «sometimes»; 2.2 % of the girls and 12.1 % of the boys answer with «never». Pearson Chi-square value is 44.130; the degree of freedom is two and the two-parted significance -.000. It means that this value is less than.05, and this Chi-square is significant; furthermore, there is no difference between girls and boys in the frequency of using a needle.

Logically, I conclude that the differences between girls and boys are not statistically significant for most of the following items: Make your own clothes, Use a screwdriver, Play with building kits (like Lego). For some other items, there is a difference between girls and boys: Use a radio, Use a microscope, Preserve food by salting, smoking, drying, etc., Watch a bird makes its nest, Watch an egg hatching or an animal being born, etc. (See more in Table N: 1)

In particular, I will focus my attention on the items about the Milky Way, the Moon and the rainbow. The difference between boys and girls is clearly identifiable — 53.8 % of the girls to 46.2 % of the boys have been interested sometimes in the Milky Way. A possible explanation of the increased interest of the girls could be that they hold a positive view of the role which esotericism plays in their everyday life. The opposite example is the data concerning the Moon: 42.9 % of the girls and 57.1 % of the boys have seen the phases of the moon. Another clarification should be given for the difference in preparing beer or wine — 53.6 % of the girls and 44.7 % of the boys have never prepared them.

The subtest Things to learn about includes content, which is cross-disciplinary: for example «What is a colour and how do we see different colours?» (From Physics) and «How do animals and plants use colours to hide, attract or scare» (from Zoology). The pupils’ results reported that the objects of study reinforce the impression that boys are competent in areas such as: the car and how it works (62.1 %), AIDIS (50.5 %), lightning and thunder (55.2 %), latest developments in technology (64.8 %), chemicals and their properties (55.9 %).

All in all, the test scores of the females are higher than these of the boys. They have more positive attitudes to issues such as: pollution and dangers of traffic (55.3 %), plants and animals in my neighborhood (62.9 %), plants and animals in other parts of the world (63.1 %), what we should eat to be healthy(57.2 %), the evolution of life on earth (54.2 %), how different plants and animals depend on each other (63.1 %), how the eye can see (51.8 %), how the ear can hear (56.7 %), the Moon, the Sun and the planets (53.8 %), the Universe, the star constellations and the galaxies (52.3 %), how science and technology may help us get a better life (53.5 %), how we can protect air, water, woods and the environment (52.6 %), why people in different parts of the world look different and have distinct colour of the skin (59.8 %), important inventions and discoveries (51.5 %).

The boys seem to be more negative than the girls do to issues such as food processing, conservation and storage (56 %) and how different plants and animals depend on each other (54.9 %). The same trend is found in respect to the plants and animals in other parts of the world — 65.8 % answer negatively. Surprisingly, «The rainbow, what is it and why can you see it» is equally uninteresting to girls and boys as an object of study. 50.5 % of the males wouldn’t like to learn about how the ear can hear. Acoustics and sound are not among preferred objects, too many girls — 52.9 % and 47.1 % of the boys answer this question with «No».

Obviously, there are gender differences in the pupils’ attitudes to the science curricula. However, it is noticeable that the differences seem not to be determined by gender. The general pattern is culturally rather than gender based. The best example is maybe the item about the car. Another example is the responses to the question about the evolution of life on the earth: the difference is not statistically significant (p=.789> 0.05) but this is because the pupils which answer negatively are more than all the pupils which answer positively — 54.2 %; in other cases, the positive responses of the females and the males are more than the negative ones — for example, the attitudes to the clean and safe drinking water — 67.1 % of all responses. The same is applied to colours and how we see different colours.

In general, the subjects demonstrate a favourable view of the ecology and the environmental issues, of technology and humankind. They show positive attitudes to Astronomy, Human Anatomy, Zoology. In the process of comparing the two groups — females and males — it becomes clearer how we can benefit from the situational and developmental characteristics of the interest. The cognitive components of the interests have biological roots but the culture, and the education have transformed them and the similarities between girls and boys at the age of 13 are typical of their stage of development. The instructional conditions can cause deepening of the development, individually based interests by building new knowledge by better communication, and through understanding how the current cultural and social forces shape pupils.

Table 1

Chi-Square significance coefficients for «Scientists as person»

 

Personal traits

Pearson Chi-Square (Physicist)

Pearson Chi-Square (Biologist)

1.

Tidy, neat, orderly

.59

.618

2.

Intelligent, bright, clever

.788

.397

3.

Imaginative, full of ideas

.812

.204

4.

Caring for others

.156

.576

5.

Hard working

.138

.319

6.

Social, outgoing

.049

.735

7.

Interesting and exciting person

.079

.12

8.

Kind, humane

.708

.681

9.

Democratic

.219

.024

 

Table 2

Chi-Square significance coefficients for «Have you done this outside school»

 

Have you done this outside school?

Pearson Chi-Square

Asymp.Sig. (2-sided)

1.

Used needle and thread for sewing

44,13

.000

4.

Made your own clothes

10,118

.006

6.

Used a screw driver

64,739

.000

10.

Climbed a tree

10,947

.004

12.

Played with building kits (like Lego)

10,947

.004

14.

Used a radio

1,838

.399

16.

Played video or computer games

13,445

.001

18.

Used a PC (Personal Computer)

11,13

.004

21.

Used a microscope

3,308

.191

25.

Used a wrist watch

7,456

.024

33.

Preserved food by salting, smoking, drying etc.

1,239

.744

34.

Made bread or pastry

42,688

.000

35.

Collected edible berries, mushrooms or plants

7,845

.020

43.

Put on bandages on wounds or used first‑aid equipment

2,474

.290

44.

Watched a bird make its nest

2,553

.279

45.

Watched an egg hatching or an animal being born

.151

,927

51.

Had your own pet animal (cat, dog, hamster, rabbit..)

3,457

.178

60.

Used electric toys (cars, torches etc.)

23,846

.000

63.

Ridden a bicycle

12,508

,002

68.

Observed or studied the Milky Way or the constellations of the stars

.069

.966

69.

Observed or studied the phases of the moon

4,202

,122

70.

Observed or studied the rainbow or different types of clouds

,247

.884

79.

Participated in brewing beer or making wine

1,010

.603

 

Table 3

Chi-Square significance coefficients for «Things to learn about!»

 

Things to learn about!

Pearson Chi-Square

Asymp.Sig. (2-sided)

1.

 The car and how it works

26,425

.000

2.

 The pollution and dangers of traffic

.307

.594

6.

 Plants and animals in my neighbourhood

8,862

.003

7.

 Plants and animals in other parts of the world

16,862

.000

11.

 AIDS: What it is and how it spreads

1,86

.220

14.

What we should eat to be healthy

4,91

,027

17.

The evolution of life on earth

.072

.789

20.

How different plants and animals depend on each other

7,29

.007

22.

How the eye can see

1,697

.193

23.

What are colours and how do we see different colours?

.215

.643

24.

 Acoustics and sound

.034

.891

26.

 How the ear can hear

1,148

.284

30.

 Lightning and thunder

8,229

.004

32.

 The rainbow, what it is and why you can see it

1,479

.224

38.

 The moon, the sun and the planets

.041

.890

39.

 The universe, the star constellations and the galaxies

.13

.718

46.

 Latest developments in technology

20,742

.000

48.

 How science and technology may help us to get a better life

.891

.641

51.

 Food processing, conservation and storage

11,522

.001

54.

 How to get clean and safe drinking water

1,01

,315

55.

 How we can protect air, water, woods and the environment

.093

.777

60.

 Why people in different parts of the world look different and have different colour of the skin

4,964

,026

64.

 Important inventions and discoveries

.479

.489

69.

Chemicals and their properties

10

,002

 

References:

 

1.         Chen,H., Chen,M.-F., Ghang,T.-S., Lee, Y.-S.,&Chen, H.-P.(2010). Gender reality on multi-domains of school-age children in Taiwan: A developmental approach. Personality and Individual Differences, 48, 475–480.

2.         Hidi, S.& Renninger, Ann (2006).The Four-Phase Model of Interest development. Educational Psychologist, 41(2).11–127.

3.         Severiens, S.& Ten Dam, G. (1994). Gender differences in learning styles: a narrative review and quantitative meta-analysis. Higher Education, 27: 487–501.

4.         Söberg, Svein (2000). Science and Scientist: The SAS Study.Cross-cultural evidence and perspective on pupils' interests, experiences and perceptions. Background, Development and Selected Results. http://www.uio.no/~sveinsj/

Основные термины (генерируются автоматически): AIDIS, AIDS, ANOVA, SAS.

Ключевые слова

наука, обучение, интерес, подростковый возраст, опыт., science, interest, adolescence, learning, experience., experience

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Тестирование сервиса показало, что «Скоринг бюро III поколения» совместно со скорингом банка дает дополнительный коэффициент точности более 10 %. Самыми популярными иностранными продуктами являются: FICO, SAS Credit Scoring, EGAR Scoring, Transact SM...

Применение неинвазивной пульсовой диагностики у пациентов...

сахарный диабет, ANOVA, STATISTICA, USA, количественный признак, помощь проведения, ребенок, тип, удлинение интервала. Метаболический профиль при психологическом стрессе у лиц...

Сравнительный анализ сенсомоторного развития детей четырех...

Для оценки влияния возраста на успешность выполнения сенсомоторных проб использовался однофакторный дисперсионный анализ (ANOVA), где в качестве фактора выступал возраст детей четырех и пяти лет.

Использование прогнозной аналитики...

В современных условиях лавинообразного роста информации использование интеллектуальных методов анализа данных в системах поддержки принятия решений является очевидным и закономерным шагом.

Выбор платформы интеллектуального анализа данных для...

Все задачи, связанные с хранением данных, моделей и результатов анализа, в RapidMiner решаются при помощи единого репозитория.

 импорт (Import)  чтение данных из различных форматов хранения (CSV, Excel, XML, SAS, Access, AML, ARFF, XRFF, Database, SPSS, Stata...

A Consideration of the Relationship between Self-esteem and General...

Furthermore I conducted a one-way analysis of variance (ANOVA) to examine whether enjoyment scale’s scores were related to the grade of the students. Распространённость изжоги и качество жизни у пациентов...

Исследование нового системного биохимического показателя...

Концентрации аминокислот рассчитывали, используя норвалин в качестве внутреннего стандарта. Статистическую обработку результатов выполняли с использованием пакета программ SAS 9.3.

Клиентский опыт (Customer Experience) как инструмент обратной...

С помощью таких систем, при персонифицированном взаимодействии с клиентом, вполне возможно менять его поведение, то есть формировать

Лето Банк. SAS Credit Scoring for Banking, SAS Real-Time Decision Manager, интеграция с CRM-системой SAS Marketing Automation.

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