Influence of students' background and perceptions on science attitudes and achievement

Abstract

The purpose of the study was to investigate the influence of students' background and perceptions on science attitude and achievement. The data analysed came from Booklet 4 given to 17‐year‐olds during the 1976–1977 National Assessment of Educational Progress (NAEP) survey. Causal modeling procedures were used to analyze the data. In particular, the LISREL method which underlies the LISREL IV computer program, (Jöreskog and Sörbom, 1978) was employed. The influence of five background variables (sex, race, home environment, amount of homework, and parents' education) on three dependent variables (student perception of science instruction, student attitudes, and student achievement) was examined. Sex, race, and the home environment were shown to have substantial influence on student achievement in science. Further, two different models were tested: a model in which attitudes influence achievement and its converse (achievement influences attitudes). The data supported the first model, that is, attitudes influence achievement.

Attitudes toward chemistry among 11th grade students in high schools in Greece

“…The majority of studies demonstrate that boys record a more positive attitude toward science than girls (Francis & Greer, 1999;Jones, Howe, & Rua, 2000;O'Brien & Porter, 1994;Schibeci & Riley, 1986;Simpson & Oliver, 1985). On the other hand, Greenfield (1996) found no gender differences in science-related attitudes between boys and girls.…”

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“…It has often been argued that students' views about knowing and learning science are major determinants of their achievement in science courses (Baker & Piburn 1991;Reif & Larkin 1991;Schibeci & Riley 1986;Songer & Linn 1991;Tobias 1990). VASS results support this view.…”

“…Research suggests that: (a) students are often encumbered with views about the nature of science and learning science that are at odds with the views of scientists, and (b) these views may significantly affect what students learn in science courses (Aikenhead 1987;Baker & Piburn 1991;Cobern 1993;Edmondson & Novak 1993;Meichtry 1993;Reif & Larkin 1991;Schibeci & Riley 1986;Songer & Linn 1991). There is a need for valid and reliable instruments to help teachers evaluate instruction in these respects.…”

Modeling Course Achievements of Elementary Education Teacher Candidates with Artificial Neural Networks

“…Numerous studies exist in predicting science achievement of teacher candidates as well as students, showing that variables such as attitudes towards science and technology, parental education level, socio-economic level, and scientific process skills are related to science achievement and that they have an important effect in predicting the science achievement of students (Berberoğlu, Çelebi, Özdemir, Uysal, & Yayan, 2003;Fleming & Malone, 1983;Germann, 1994;Schibeci & Riley, 1986)..…”