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• 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.
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• 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.
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• 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.
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