II.2.2.1 Scientific epistemological beliefs (SEBs) and beliefs on the nature of science (NOS)
Recently, a growing body of research focuses on beliefs about knowledge and knowing within particular disciplines, particular in mathematics and science areas (Hofer, 2000; Muis, 2004). As aforementioned, Hofer and Pintrich (1997) have suggested two general areas representing the core structure of individuals’ personal epistemology: nature of knowledge and nature of knowing. According to Hofer and Pintrich’s (1997) perspective on personal epistemology, the term “scientific
epistemological beliefs” (SEBs) refers to beliefs about knowledge and knowing within science discipline. In other words, scientific epistemological beliefs refer to beliefs about the nature of scientific knowledge and beliefs about the nature of knowing science.
In science education, research on beliefs about “nature of science” (NOS) has received much attention. Although the term “nature of science” has been defined in numerous ways, it most commonly refers to the assumptions, values, and
characteristics of scientific knowledge (Lederman, 1992; Ryan & Aikenhead, 1992;
Tsai & Liu, 2005). Clearly, both “scientific epistemological beliefs” (SEBs) and
“nature of science” (NOS) addresses some common issues, such as the beliefs on the nature of scientific knowledge, but there are also some distinctions between some issues they addressed. For example, only “nature of science” addresses social and culture aspects of scientific knowledge, while “scientific epistemological beliefs” are more concerned with the beliefs on the justification of scientific knowledge.
II.2.2.2 The relationships between students’ scientific epistemological beliefs and science learning
This section will review previous studies regarding the relationships between students’ scientific epistemological beliefs and science learning. Songer and Linn (1991) conducted a study to investigate how middle students’ view of science
influenced knowledge integration. In their study, according to their views of science, the participants were divided into three groups: static, mixed, and dynamic. The results showed that students with dynamic views acquired more integrated
understanding than those with static views. A similar finding is also revealed by Tsai (1998a). Tsai (1998a) explored the interrelationships between 48 eighth graders’
general science achievement, scientific epistemological beliefs and their cognitive structure outcomes derived from the instruction of basic atomic theory. In Tsai (1998a), the participants’ scientific epistemological beliefs were assessed by a Likert-type questionnaire, while their cognitive structures were obtained through interviews. It was found that the students’ scientific epistemological beliefs were significantly correlated with their cognitive structures. Students holding more sophisticated epistemological beliefs toward science tended to display more extended and more integrated cognitive structures. According to the findings derived from Songer and Linn (1991) and Tsai (1998a), students’ scientific epistemological beliefs are correlated with the extent as well as the integratedness of their knowledge
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structures.
Moreover, Tsai (2000a) also examine the relationships between high school students’ scientific epistemological beliefs and perceptions of learning environments.
It was found that students having scientific epistemological beliefs more orientated to the constructivist views of science (as opposed to positivist views about science) tended to perceive that actual learning environments did not provide sufficient opportunities for social negotiations and prior knowledge integration. Tsai (2000a) also found that students holding sophisticated scientific epistemological beliefs showed significantly stronger preferences to learn in the constructivist learning environments. In other words, learners’ scientific epistemological beliefs are also correlated with their preferences of learning environments.
With qualitative analyses, Edmondon and Novak (1993) reported their research findings regarding the interplay between college students’ scientific epistemological views and their learning strategies. They concluded that students’ conceptions of the nature of science influenced the choice of learning strategy. Moreover, Tsai (1998b) conducted a qualitative study to explore the interaction between eighth graders’
scientific epistemological beliefs and learning orientations. This study revealed that students holding constructivist epistemological beliefs about science tended to learn through constructivist-oriented instructional activities and employ more meaningful strategies when leaning science, while those having epistemological beliefs more aligned with empiricism were prone to use more rote-like learning strategies. In addition, students, who were more oriented to hold constructivist epistemological beliefs toward science, were mainly motivated by their interest and curiosity of science, whereas those, who had empiricist scientific epistemological beliefs about science, were mainly motivated by the performance on examinations. In sum, previous studies have suggested the interplay between students’ scientific
epistemological views and their learning orientations, including their learning strategies and motivation.
In his review and discussion, Tsai (2001a) discussed the relationships between epistemological commitments, metaconition, and critical thinking. “Epistemological commitments” refers to evaluative standards an individual employs to judge the merits of knowledge (Tsai, 2001a). Tsai (2001a) has proposed that the
epistemological commitments are highest order beliefs guiding metacognition and critical thinking, and, on the other hand, the practice of metacognition and critical thinking may shape a learner’s epistemological commitments. From his perspective, the possible interaction between learners’ epistemological commitments and their practice of metacognition may exist.
Lin, Chiu and Chou (2004) examined the relationship between 8th graders’
understanding of the nature of science and their problem-solving strategies. The results indicated that students’ understanding of the nature of scientific method was the best predictor for their problem-solving ability.
In addition, some studies have also investigated the relationship between
students’ beliefs on NOS and their informal reasoning on socio-scientific issues. For example, Zeidler et al. (2002) explored 9th -12th graders’ decision-making on animal rights, and found that students’ views of NOS were related to their decision-making on this issue. Bell and Lederman (2003) investigated the relationship between university faculties’ understanding of the nature of science and their decision-making on environmental issues. In addition, Sadler et al. (2004) examined the relationship between high school students’ informal reasoning and their beliefs on NOS.
The results derived from these shows that students’ informal reasoning on
socio-scientific issues is related to certain aspects of beliefs about NOS, such as social embeddedness of science and tentativeness (Sadler et al., 2004; Zeidler et al., 2002),
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but learners’ differences in views on NOS may not lead to different decision-making on a socio-scientific issue (Bell & Lederman, 2003).
To sum up, the literature review in this section suggests that students’ scientific epistemological beliefs are correlated with their science learning in many aspects, including knowledge structure, problem-solving ability, informal reasoning on socio-scientific issues (SSI), learning orientations, preferences of learning
environments, and metacognition. As shown in Figure 2.2, these aspects can be categorized into three domains: cognitive domain, metacognitive domain, and emotional and motivational domain.
Figure 2.2: Students’ scientific epistemological beliefs and their science learning
Problem-
on SSI Cognitive domain
Emotional and
II.3. Exploration of cognitive structures II.3.1 Cognitive structure and its dimensions
Understanding how learners acquire knowledge is always an important issue in science education. In the last three decades, the perspectives of constructivism on learning and teaching have been strongly advocated by science educators and researchers. The view of constructivism on learning highlights the significance of the individual learner’s pre-acquired knowledge (i.e., their prior knowledge) in subsequent learning (Ausubel, 1968; Driver & Bell, 1986; Bischoff & Anderson, 2001). Educators and cognitive scientists have tried to represent pre-acquired knowledge in terms of “cognitive structure” (Pines, 1985; West, Fensham & Garrard, 1985).
A cognitive structure is a hypothetical construct showing the extent of concepts and their relationships in a learner’s long-term memory (Shavelson, 1974). From its literal meaning, cognitive means “of the mind, having the power to know, recognize, and conceive, concerning personally acquired knowledge”; therefore cognitive structure concerns individual’s ideas, meanings, concepts, and so on (Pines, 1985).
Structure refers to the form, the arrangement of elements or parts of anything; the emphasis here is not on the element, but on the way these elements are bounded together (Pines, 1985). Therefore, there are, at least, two important aspects for describing cognitive structure: the knowledge bit it contains and how knowledge is organized (West et al., 1985). In addition, Tsai and Huang (2002) have also argued that the information processing strategies individuals use to organize concepts within their cognitive structures should be also viewed as one of the important component of their cognitive structures (e.g., Tsai, 2002). Therefore, there are three aspects in describing cognitive structure: the concepts or ideas contained, the connections among
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concepts, and the information processing strategies.
Three sets for representing the dimensions of cognitive structure have been proposed by educators. West et al. (1985) proposed five dimensions of cognitive structure: integration of propositional knowledge, differentiation of propositional knowledge, differentiation of skills/examples knowledge, articulated propositional relatedness, and depth of propositional knowledge. Also, White (1985) proposed nine dimensions of cognitive structures: extent, precision, internal consistency, accord with reality or generally accepted truth, variety of types of element (including
propositions, intellectual skills, images, and episodes), variety of topics, shape, ratio of internal to external associations, and availability. Tsai and Huang (2002) also suggested five variables for assessing cognitive structures:
(1) Extent: the numbers of concepts or ideas contained in one’s cognitive structure.
(2) Correctness: the number of alternative conceptions shown in one’s cognitive structure, or the number of correct conceptions.
(3) Integratedness: the connection of concepts within one’s cognitive structure.
(4) Availability: the availability of one’s cognitive structure can be represented by his/her information retrieval rate.
(5) Analyses of information processing strategies: by means of content analyses of cognitive structure, researchers can investigate an individual’s information processing operations.
Clearly, among the aforementioned three sets of dimensions (or variables) of cognitive structure, only what proposed by Tsai and Huang (2002) can provide
relevant information regarding the information processing strategies individuals used.
Besides, West (1985) has also advocated the following three tests for the appropriateness of a set of dimensions of cognitive structure:
(1) Practicality: it must be possible to convert interview protocols to score on them.
(2) Robustness: it must be robust against circumstances.
(3) Creativity: it enables people to invent new method for probing cognitive structure.
According to the three tests advocated by West (1985), it seems that the variables suggested by Tsai and Huang (2002) outperform the other two sets of dimensions of cognitive structure (i.e., West et al. [1985] and West [1985]) in its practicality and creativity. Therefore, the variables suggested by Tsai and Huang (2002) are more suitable for describing individuals’ cognitive structures.