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Asia-Pacific Forum on Science Learning and Teaching, Volume 16, Issue 2, Article 6 (Dec., 2015) |
Recent research studies in science education that have investigated the factors influencing science achievement have emphasized some variables such as pre-experiences, individual differences and different assessment techniques. The primary studies focused on the effects of individual differences (especially students’ demographical properties like gender and socio-economic level) on science achievement. In majority of these studies, the effect of gender on science achievement was examined. The results of these studies (Gray, 1981; Kelly, 1988; Karaçam, 2005) showed that males are more successful than girls in science, especially in physics. The gap between males and females’ science achievement has been explained based on the pre-experiences of male and females and the expectations of different assessment techniques. The variation between the achievements of male and female students on different assessment techniques has been explained based on Different Item Functioning Theory (DIF). The results of DIF studies showed that females are more successful in open ended question formats while males are more successful in multiple choice tests (Karaçam, 2005). Thus, it is asserted that there are some variations between male and females’ achievements determined via different assessment techniques due to the different requirements of assessment techniques and the differentiation among abilities of males and females (O’Neil & Brown, 1998). In addition, Johnson (1987) asserted that an important reason of this result is difference between pre-experiences of males and females. According to Johnson, females play with dolls, and are interested in their illnesses and care whereas males generally play with electric circuits and cars, and are interested in motions of things.
Students’ pre-experiences about scientific phenomenon are examined by researchers based on cognitive science. In these studies, researchers have examined mental models and conceptual aspects, especially students’ misconceptions related to scientific phenomenon. According to those researchers, scientific knowledge about electricity includes much more abstract concepts. Since students might intuitively construct far more alternative concepts based on their experiments about abstract concepts than concrete concepts, they are possessed of some alternative concepts in science, and come to courses with those alternative concepts. Alternative concepts have negative effects on students’ learning, and are resistive to altering. Therefore, determining students’ alternative concepts is vital to conceptual understanding about scientific phenomenon.
Based on cognitive science, some cognitive variables like cognitive styles were defined as well. Thus, researchers emphasized the effects of FI/FD cognitive styles and motivational styles on science achievement. Related studies about cognitive styles and motivational styles are provided in the next section.
The Relationship between FD/FI Cognitive Styles and Students’ Achievements
Cognitive styles were defined in different ways by researchers (Witkin, Moore, Goodenough & Cox, 1977; Witkin & Goodenough, 1981; Green, 1985; Saracho, 1997). However, these definitions have a lot in common. For example, Green (1985) defined cognitive styles as the way which is used for thinking, communicating and perceiving by individuals. Witkin, et. al. (1977) described cognitive styles as the individual differences in ways of thinking, learning, perceiving, problem solving and assimilating the new knowledge. Witkin and Goodenough (1981) indicated that cognitive styles exist and affect the ways of learners’ assimilating and processing information and expressing what they know. Saracho (1997) stated that cognitive styles are correlated with attitudes, strategies and preferences that affect individuals’ ways of perceiving, problem solving and recalling.Several researchers have defined cognitive styles with their own perspectives and have improved their own assessment instruments to identify learners’ cognitive styles. In this study, we distinguished students’ cognitive styles based on the Witkin and Goodenough’s (1981) FI/FD dimensions. Learners who are identified as FI/FD cognitive styles have different tendencies about learning, problem solving, perceiving, assimilating the knowledge and recalling. Some characteristics of FI and FD students are presented at Table 1.
Table 1: Some Characteristics of FI/FD Students
Characteristics of FD Characteristics of FI
FD students might recognize only explicit clues in learning or problem solving environment (Dickstein, 1968).
They have a strong tendency towards communicating with people and they are inclined to physical and psychological intimacy. (Witkin ve Goodenough, 1981).
They are inclined to be affected by the people around and prefer getting feedback (Leventhal & Sisco, 1996).
They prefer group works and follow an emotional and critical approach in their social communication (Chinien & Boutin, 1992/1993).
They rely on appearance of the individuals in their social interaction (Riding & Cheema, 1991).FI students might recognize implicit cules as well (Dickstein, 1968).
They aren’t inclined to communicating with people and having physical or psychological intimacy with them (Witkin ve Goodenough, 1981).
They are less effected by the people around and don’t prefer getting feedback (Jones, 1993).
They are competitive and prefer individual study (Lyons-Lawrence, 1994)They rely on emotions and thoughts of the individuals in their social interaction (Riding & Cheema, 1991).
In studies related to FD/FI cognitive styles, researchers aimed examining the effects of FD/FI congnitive styles on students’ achievements in several disciplines. Alamolhodaei (1996) and Donnaruma, Cox and Beder (1980) studied in math, Ziane (1990), Karaçam (2005), Ateş and Çataloğlu (2007) and Çataloğlu and Ateş (2014) studied in physics and Bahar & Hansell (2000) and Danili & Reid (2006) studied in chemistry. Although these studies were conducted in several disciplines, it was showed that FI/FD cognitive styles are one of the important predictors of student achievement.
The first studies in science and math was conducted by Witkin et al. (1977). As a result of their study, Witkin et. al. indicated that there was a significant correlation between FI/FD cognitive styles and science and math achievement and FI students are more successful than their FD peers in both courses. Similarly result was asserted by Ziane (1990) studied in force and motion subjects. Witkin et. al. (1977) and Ziane (1990) emphasized on differences between FD and FI students’ cognitive abilities to explain variation between FI and FD students’ science achievements. According to Witkin et. al. (1977) and Ziane (1990), FI students are more successful than FD counterparts in science and math since FI students are better than FD students about distinguishing relevant clues. But Ateş and Çataloğlu (2007) found that there is no statistically significant difference between FI/FD students’ scores on Force Concept Inventory (FCI). According to Ateş and Çataloğlu one reason of this result is that FCI doesn’t require some skills that favoured FI. Hence, Ateş and Çataloğlu asserted that FCI is not appropriate assessment tool in order to determine the effect of FI/FD cognitive styles due to its structure and style.
By the end of 1990’s, researchers began to examine the effect of FI/FD cognitive styles on science achievement based on DIF (Karaçam, 2005; Danili and Reid, 2006; Çataloğlu and Ateş, 2014). The results of these studies indicated that there are relationships among FI/FD cognitive styles, science achievement and format and content of assessment techniques. Karaçam (2005) investigated the effects of FI/FD cognitive styles on students’ conceptual understandings about force and motion laws measured by multiple choice, open ended tests and structured communication grid. Karaçam showed that there was a statistically significant mean difference between FD and FI students’ conceptual understanding levels about force and motion when they were assessed by using a multiple choice test. On the other hand, there was no statistically significant mean difference between FD and FI students’ conceptual understanding levels when they were assessed through an open ended test and structural communication grids. Çataloğlu and Ateş (2014) examined the effect of FI/FD cognitive styles on freshman students’ performances related to applications of degrees of naïve impetus theory. Two tier and multiple choice tests were used to determine students’ application degrees of naïve impetus theory. When data was analysed, it was found that there were statistically significant correlations between FI/FD cognitive styles and students’ application degrees of naïve impetus theory, and that FI students’ application degrees were higher than FD students’ in both tests. From these findings Çataloğlu and Ateş asserted that some of the factors that affect pupils’ performance might be: (a) the content and presentation of the test, (b) the format of the test, and (c) the cognitive difference of the individual like FI/FD (Danili and Reid, 2006).
The Relationship between Motivational Styles and Science Achievement
Some of researchers (Adar, 1969; Hofstein & Kempa, 1985; Kempa & Diaz, 1990a, 1990b; Al-Naeme, 1991; Solomon, 1996) emphasized the importance of the affective dimension, especially motivational style, in terms of individual differences. There are many categorizations about motivation style in the literature. Some of these categorizations have the same dimensions including need and readiness (Bahar, 2002). As an example of these, Adar (1969) categorized students according to their motivational styles based on the predominance of the following needs; i) the need to achieve, ii) the need to satisfy one’s curiosity, iii) the need to discharge a duty, and iv) the need to affiliate with other people. Adar referred to the four motivational styles of students as achiever, curious, conscientious and social respectively and described the four groups as follows: Achievers have a distinct preference for an expository method of teaching to enable themselves to achieve well. They compete to be top and get pleasure from excelling. Conscientious students want to be told exactly what to do and enjoy clearly stated objectives. Curious students keep asking why. They have a distinct preference for discovery learning and problem solving activities. Social students enjoy their opinions being heard. They conform to everything easily and like working in groups. They like studying and discussing problems with their friends.There are some studies based on Adar’s categorization of motivational styles (Hofstein & Kempa, 1985; Kempa & Diaz 1990a, 1990b; Johnstone & Al-Naeme, 1995). However, the studies on motivational styles are very limited. Some of these studies (Kempa & Diaz 1990a, 1990b; Bahar, 2003b) emphasized the interaction between gender and motivational styles. Results of these studies generally showed that whereas boys are achiever, girls are conscious.
Another group of studies (Hofstein & Kempa, 1985; Al-Naeme, 1991; Johnstone & Al-Naeme, 1995; Bahar, 2003b) emphasized the effects of motivational styles on students’ achievement. The results of these studies asserted that motivational style is one of the important factors affecting students’ learning and performance. Hofstein and Kempa (1985) postulated that there are a number of relationships between students’ motivational characteristics and their preferences for particular modes of instruction in science education. Similarly Al-Naeme (1991) looked into the influence of motivational styles on the performance of students in some creative practical problem solving tasks in chemistry, which are termed mini projects at the bench. His findings demonstrated that motivation factor was an important factor which affects students’ achievement. Moreover, Al-Naeme showed that the curious groups were the best and the conscientious groups were the poorest in terms of their performance in problem solving tasks.
Rationale of This Study
One of the most important areas of physics education is electricity. Therefore, researchers have emphasized on determining students’ misconceptions about DC circuits and revising those misconceptions. In the studies about misconceptions, it was stated that since electricity subject area consists of several abstract concepts, students have a number of misconceptions (Choi & Chang, 2004). Students construct misconceptions based on their pre-experiences about electricity (Duit & von Rhöneck, 1998). Thus, they come to learning environments with misconceptions about electricity phemenon (Treagust & Duit, 2008). However, misconceptions have adverse effects on students learning (Hammer, 1996). Moreover, they are more resistant to change, so it is difficult to revise with traditional learning approaches (Eryılmaz, 2002). In this view, several researchers have examined alternative learning approaches to revise students’ misconceptions about electricity phenomenon. The effects of analogies (Chiu and Lin, 2005), learning cycle strategy (Ateş, 2005), simulations based on conceptual change (Başer, 2006), virtual laboratory experiments (Zacharia, 2007), computer supported inquiry learning (Başer and Durmuş, 2010) and conceptual change strategy (Taşlıdere, 2013) on students’ misconceptions have already examined. However, there is no study that has aimed to determine the effects of FI/FD cognitive style and motivational styles on students’ conceptual understandings about direct current circuits. Thus, the aim of this study was to investigate the effects of FI/FD cognitive styles and motivational styles on students’ conceptual understandings about direct electric circuit. Based on this goal, the research questions of this study are as follows:
- Is there a statistically significant difference between FI and FD students in terms of their conceptual understandings about direct current circuit concepts?
- Is there statistically significant difference among students who have different motivational styles with respect to their conceptual understanding of direct current circuit concepts?
