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TEKNOLOJİ KULLANIMI VE TEKNOLOJİYE KARŞI TUTUM: PISA 2003 VERİSİNİN ULUSLARARASI ANALİZİ

Yıl 2014, Cilt: 1 Sayı: 1, 45 - 64, 01.12.2014

Öz

Bu çalışmanın amacı; cinsiyet, coğrafik bölge, ve sosyoekonomik durum açısından bilgisayar kullanımı ve bilgisayara karşı tutumları analiz etmektir. Örneklem PISA 2003 çalışmasına katılan 15 yaş grubundaki öğrencilerini kapsamaktadır. Kullanıma hazır bilgisayar bulunması, bilgisayar kullanım tecrübesi, farklı amaçlar için bilgisayar kullanım sıklığı ve bilgisayara karşı tutum değişkenleri arasında anlamlı farklılıklar bulunmuştur. Matematik kaygısı ile ilgili bağlantı tartışılmıştır. Sonuçlar öyle gösteriyor ki; erkekler bilgisayara karşı daha pozitif bir tutum sergilemekte ve daha sık bilgisayar kullanım eğiliminde olmaktadırlar. Sosyoekonomik seviye yükselirken, bilgisayar kullanım deneyimleri ve bilgisayara karşı (pozitif) tutum artmaktadır

Kaynakça

  • schoolwork. Hence affective factors such as anxiety and motivation are likely to have a role in
  • frequency of use as well as socioeconomic factors. In fact, in a previous study on the same
  • sample (Kahveci & Imamoglu, 2014), researchers found that mathematics anxiety follows a
  • similar trend: medium socioeconomic level students have the highest anxiety, whereas very
  • high and very low socioeconomic level students have lowest mathematics anxiety. Another
  • possible explanation may be that students who do not use computer programs frequently for
  • academic purposes tend to have higher anxiety (in other subjects as well as mathematics).
  • Results for attitudes towards computers also reveal significant mean differences with respect to
  • gender, geographical regions and socioeconomic status. Males have more positive attitudes
  • compared to females. This may be a reason to the result that males use Internet and software
  • programs more frequently. Southeast Mediterranean countries have the most positive attitude
  • towards computers, while Oceania has the lowest. This is opposite to the other findings where
  • Oceania has the highest computer availability of computers, experience and internet use. It also
  • has high scores in self-efficacy, self-concept and motivation, and low mathematics anxiety
  • scores ( Kahveci & Imamoglu, 2014). Southeast Mediterranean countries, on the other hand,
  • have the least computer availability but they are most frequent program users. In addition, they
  • have high mathematics anxiety scores. These results should further be investigated. There is a
  • significant linear relationship between attitudes towards computer use and socioeconomic
  • status, however, the line is close to horizontal, meaning that attitudes towards computer do not
  • show big changes with respect to socioeconomic status. Mathematics anxiety with respect to
  • socioeconomic status does not show a similar trend. Further research can be conducted to
  • investigate direct relationship between math anxiety and attitudes towards computers.
  • Adiguzel, T., & Akpinar, Y. (2004). Improving school children's mathematical word problem solving skills through computer-based multiple representations (ERIC Number: ED485024) (p. 10). Presented at the Association for Educational Communications and Technology, Chicago.
  • Ashcraft, M. H. (2002). Math anxiety: Personal, educational, and cognitive consequences. Current Directions In Psychological Science, 11(5), 181-185.
  • Bovée, C., Voogt, J., & Meelissen, M. (2007). Computer attitudes of primary and secondary students in South Africa. Computers in Human Behavior, 23(4), 1762–1776. doi:10.1016/j.chb.2005.10.004
  • Baloglu, M., & Kocak, R. (2006). A multivariate investigation of the differences in mathematics anxiety. Personality and Individual Differences, 40(7), 1325-1335.
  • Baylor, A. L., Shen, E., & Warren, D. (2004). Supporting learners with math anxiety: the impact of pedagogical agent emotional and motivational support, International Conference on Intelligent Tutoring Systems (Vol. 2006). Maceió, Brazil.
  • Chang, K. E., Sung, Y. T., & Lin, S. F. (2006). Computer-assisted learning for mathematical problem solving. Computers & Education, 46(2), 140-151.
  • Ho, H. Z., Senturk, D., Lam, A. G., Zimmer, J. M., Hong, S., Okamoto, Y., et al. (2000). The affective and cognitive dimensions of math anxiety: A cross-national study. Journal For Research In Mathematics Education, 31(3), 362-379.
  • Kahveci, M. & Imamoglu, Y. (2014). Re-analysis of PISA 2003 data about students’ mathematics anxiety, self-efficacy, and motivation. Journal of Research in Education and Society (JRES), 1(1), 1-22.
  • Li, Q., Ma, X. (2010). A meta-analysis of the effects of computer technology on school students' mathematics learning. Educational Psychology Review, 22(3), 215-243.
  • Ma, X., & Kishor, N. (1997). Assessing the relationship between attitude toward mathematics and achievement in mathematics: A meta-analysis. Journal For Research in Mathematics Education, 28(1), 26-47.
  • Ma, X., & Xu, J. M. (2004). The causal ordering of mathematics anxiety and mathematics achievement: a longitudinal panel analysis. Journal Of Adolescence, 27(2), 165-179.
  • Meece, J. L., Wigfield, A., & Eccles, J. S. (1990). Predictors Of Math Anxiety And Its Influence On Young Adolescents Course Enrollment Intentions And Performance In Mathematics. Journal of Educational Psychology, 82(1), 60-70.
  • OECD. (2003). The PISA 2003 Assessment Framework: Mathematics, Reading, Science and Problem Solving Knowledge and Skills. Paris: OECD Publications.
  • OECD. (2005a). PISA 2003 data analysis manual: SPSS users. Paris: OECD.
  • OECD. (2005b). PISA 2003 technical report: Programme for International Student Assessment. Paris: Organization for Economic Co-operation and Development.
  • Pamuk, S., Peker, D. (2009) Turkish pre-service science and mathematics teachers' computer related self-efficacies, attitudes, and the relationship between these variables. Computers and Education, 53, 454-461.
  • Plumm, K.M. (2008). Technology in the classroom: Burning the bridges to the gaps in gender- bias education? Computers and Education, 50, 1052-1068.
  • Polya, G. (1945). How to Solve It: A New Aspect of Mathematical Method. Pinceton, NJ: Princeton University Press.
  • Roschelle, J. M., Pea, R. D., Hoadley, C. M., Gordin, D. N., & Means, B. M. (2000). Changing how and what children learn in school with computer-based technologies. Future of Children, 10(2), 76-101.
  • Sainz, M. & Lopez-Saez, M. (2010). Gender differences in computer attitudes and the choice of technology-related occupations in a sample of secondary students in Spain. Computers and Education, 54, 578-587.
  • Sanchez, J. C., Encinas, L. H., Fernandez, R. L., & Sanchez, M. R. (2002). Designing hypermedia tools for solving problems in mathematics. Computers & Education, 38(4), 303-317.
  • Teo, T. (2008). Assessing the computer attitudes of students. Computers in Human Behavior, 24, 1634-1642.
  • Tondeur, J., van Braak, J. & Valcke, M. (2007). Towards a topology of computer use in primary education. Journal of Computer Assisted Learning, 23, 197-206.

USE of TECHNOLOGY and ATTITUDES towards TECHNOLOGY: An INTERNATIONAL ANALYSIS of the PISA 2003

Yıl 2014, Cilt: 1 Sayı: 1, 45 - 64, 01.12.2014

Öz

The aim of this study is to analyze the use of computers and attitudes towards computers with respect to gender, geographical regions and socioeconomic status. The sample includes 15-year old students, who have participated in the international PISA 2003 study. Significant differences are found in the variables of availability of a computer to use, experience of computer use, frequency of computer use for different purposes, and attitudes towards computers. Connections with mathematics anxiety are also discussed. Results indicate that boys have more positive attitude towards computers and they tend to use computers more frequently. While socioeconomic level increases, experiences in computer use and Internet use and positive attitudes towards computers increase

Kaynakça

  • schoolwork. Hence affective factors such as anxiety and motivation are likely to have a role in
  • frequency of use as well as socioeconomic factors. In fact, in a previous study on the same
  • sample (Kahveci & Imamoglu, 2014), researchers found that mathematics anxiety follows a
  • similar trend: medium socioeconomic level students have the highest anxiety, whereas very
  • high and very low socioeconomic level students have lowest mathematics anxiety. Another
  • possible explanation may be that students who do not use computer programs frequently for
  • academic purposes tend to have higher anxiety (in other subjects as well as mathematics).
  • Results for attitudes towards computers also reveal significant mean differences with respect to
  • gender, geographical regions and socioeconomic status. Males have more positive attitudes
  • compared to females. This may be a reason to the result that males use Internet and software
  • programs more frequently. Southeast Mediterranean countries have the most positive attitude
  • towards computers, while Oceania has the lowest. This is opposite to the other findings where
  • Oceania has the highest computer availability of computers, experience and internet use. It also
  • has high scores in self-efficacy, self-concept and motivation, and low mathematics anxiety
  • scores ( Kahveci & Imamoglu, 2014). Southeast Mediterranean countries, on the other hand,
  • have the least computer availability but they are most frequent program users. In addition, they
  • have high mathematics anxiety scores. These results should further be investigated. There is a
  • significant linear relationship between attitudes towards computer use and socioeconomic
  • status, however, the line is close to horizontal, meaning that attitudes towards computer do not
  • show big changes with respect to socioeconomic status. Mathematics anxiety with respect to
  • socioeconomic status does not show a similar trend. Further research can be conducted to
  • investigate direct relationship between math anxiety and attitudes towards computers.
  • Adiguzel, T., & Akpinar, Y. (2004). Improving school children's mathematical word problem solving skills through computer-based multiple representations (ERIC Number: ED485024) (p. 10). Presented at the Association for Educational Communications and Technology, Chicago.
  • Ashcraft, M. H. (2002). Math anxiety: Personal, educational, and cognitive consequences. Current Directions In Psychological Science, 11(5), 181-185.
  • Bovée, C., Voogt, J., & Meelissen, M. (2007). Computer attitudes of primary and secondary students in South Africa. Computers in Human Behavior, 23(4), 1762–1776. doi:10.1016/j.chb.2005.10.004
  • Baloglu, M., & Kocak, R. (2006). A multivariate investigation of the differences in mathematics anxiety. Personality and Individual Differences, 40(7), 1325-1335.
  • Baylor, A. L., Shen, E., & Warren, D. (2004). Supporting learners with math anxiety: the impact of pedagogical agent emotional and motivational support, International Conference on Intelligent Tutoring Systems (Vol. 2006). Maceió, Brazil.
  • Chang, K. E., Sung, Y. T., & Lin, S. F. (2006). Computer-assisted learning for mathematical problem solving. Computers & Education, 46(2), 140-151.
  • Ho, H. Z., Senturk, D., Lam, A. G., Zimmer, J. M., Hong, S., Okamoto, Y., et al. (2000). The affective and cognitive dimensions of math anxiety: A cross-national study. Journal For Research In Mathematics Education, 31(3), 362-379.
  • Kahveci, M. & Imamoglu, Y. (2014). Re-analysis of PISA 2003 data about students’ mathematics anxiety, self-efficacy, and motivation. Journal of Research in Education and Society (JRES), 1(1), 1-22.
  • Li, Q., Ma, X. (2010). A meta-analysis of the effects of computer technology on school students' mathematics learning. Educational Psychology Review, 22(3), 215-243.
  • Ma, X., & Kishor, N. (1997). Assessing the relationship between attitude toward mathematics and achievement in mathematics: A meta-analysis. Journal For Research in Mathematics Education, 28(1), 26-47.
  • Ma, X., & Xu, J. M. (2004). The causal ordering of mathematics anxiety and mathematics achievement: a longitudinal panel analysis. Journal Of Adolescence, 27(2), 165-179.
  • Meece, J. L., Wigfield, A., & Eccles, J. S. (1990). Predictors Of Math Anxiety And Its Influence On Young Adolescents Course Enrollment Intentions And Performance In Mathematics. Journal of Educational Psychology, 82(1), 60-70.
  • OECD. (2003). The PISA 2003 Assessment Framework: Mathematics, Reading, Science and Problem Solving Knowledge and Skills. Paris: OECD Publications.
  • OECD. (2005a). PISA 2003 data analysis manual: SPSS users. Paris: OECD.
  • OECD. (2005b). PISA 2003 technical report: Programme for International Student Assessment. Paris: Organization for Economic Co-operation and Development.
  • Pamuk, S., Peker, D. (2009) Turkish pre-service science and mathematics teachers' computer related self-efficacies, attitudes, and the relationship between these variables. Computers and Education, 53, 454-461.
  • Plumm, K.M. (2008). Technology in the classroom: Burning the bridges to the gaps in gender- bias education? Computers and Education, 50, 1052-1068.
  • Polya, G. (1945). How to Solve It: A New Aspect of Mathematical Method. Pinceton, NJ: Princeton University Press.
  • Roschelle, J. M., Pea, R. D., Hoadley, C. M., Gordin, D. N., & Means, B. M. (2000). Changing how and what children learn in school with computer-based technologies. Future of Children, 10(2), 76-101.
  • Sainz, M. & Lopez-Saez, M. (2010). Gender differences in computer attitudes and the choice of technology-related occupations in a sample of secondary students in Spain. Computers and Education, 54, 578-587.
  • Sanchez, J. C., Encinas, L. H., Fernandez, R. L., & Sanchez, M. R. (2002). Designing hypermedia tools for solving problems in mathematics. Computers & Education, 38(4), 303-317.
  • Teo, T. (2008). Assessing the computer attitudes of students. Computers in Human Behavior, 24, 1634-1642.
  • Tondeur, J., van Braak, J. & Valcke, M. (2007). Towards a topology of computer use in primary education. Journal of Computer Assisted Learning, 23, 197-206.
Toplam 45 adet kaynakça vardır.

Ayrıntılar

Diğer ID JA89PH65RP
Bölüm Makaleler
Yazarlar

Murat Kahveci Bu kişi benim

Yeşim İmamoğlu Bu kişi benim

Yayımlanma Tarihi 1 Aralık 2014
Gönderilme Tarihi 1 Aralık 2014
Yayımlandığı Sayı Yıl 2014 Cilt: 1 Sayı: 1

Kaynak Göster

APA Kahveci, M., & İmamoğlu, Y. (2014). TEKNOLOJİ KULLANIMI VE TEKNOLOJİYE KARŞI TUTUM: PISA 2003 VERİSİNİN ULUSLARARASI ANALİZİ. Eğitim Ve Toplum Araştırmaları Dergisi, 1(1), 45-64.