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This study aimed to examine the impact of years of experience and field of expertise on the development of chemistry knowledge structures from STEM experts comprising 103 professors, 10 postdocs, and 146 doctoral students. Of these participants, 127 were specialized in chemistry and the rest were from various science and engineering disciplines. Although most participants were part of a research university located in Northern California, the pool included a small group of experts from different universities and countries. The main source of the data was a Word Association Test generated with 17 keywords that refer to major topics or concepts commonly introduced in the general chemistry curricula. The knowledge structures were examined to determine if the contents and the orientations of the clusters varied between the expert groups. In addition, their analysis was enriched with the consideration of chemistry triplet designations and central terms identified by eccentricity values on each structure. The overall expert knowledge structure generated in this study was also compared to undergraduate structures determined by using the same instrument and methodology. The investigation of the structures revealed several differences between expert groups and provided insight into the transformation of novices into experts. The paper also presents practical suggestions for educators on how to utilize structures while teaching, informing their instructional practices, and reforming teaching materials.
This study aimed to examine the impact of years of experience and field of expertise on the development of chemistry knowledge structures from STEM experts comprising 103 professors, 10 postdocs, and 146 doctoral students. Of these participants, 127 were specialized in chemistry and the rest were from various science and engineering disciplines. Although most participants were part of a research university located in Northern California, the pool included a small group of experts from different universities and countries. The main source of the data was a Word Association Test generated with 17 keywords that refer to major topics or concepts commonly introduced in the general chemistry curricula. The knowledge structures were examined to determine if the contents and the orientations of the clusters varied between the expert groups. In addition, their analysis was enriched with the consideration of chemistry triplet designations and central terms identified by eccentricity values on each structure. The overall expert knowledge structure generated in this study was also compared to undergraduate structures determined by using the same instrument and methodology. The investigation of the structures revealed several differences between expert groups and provided insight into the transformation of novices into experts. The paper also presents practical suggestions for educators on how to utilize structures while teaching, informing their instructional practices, and reforming teaching materials.
Background Electricity is a central concept in science curricula at all levels of education. Nevertheless, its invisible nature makes the concepts associated with it very difficult for students. Moreover, students have many alternative conceptions about concepts related to electrical circuits. This study aims to know the effect of a STEM (Science–Technology–Engineering–Mathematics) approach on students' cognitive structures about the topic of electrical circuits, as revealed through a Word Association Test (WAT). A study following a time series quasi-experimental research design was made to collect information about changes in students’ cognitive structures before and after a learning sequence about electrical circuits. A nonequivalent control group approach was used, and two matching groups of students were used: a control group (N = 317) and an experimental group (N = 321). Students were attending the 9th grade (14–15 years old). Data analysis was made by construction of frequency tables, maps of the cognitive structures, and examination of the sentences written by students. Results The results are indicative that, before the STEM approach, students’ conceptions regarding electrical circuits are mainly related to students’ daily experiences. However, after a STEM approach, the map of students’ cognitive structures from the experimental group is more complex. Furthermore, the quality of the response words is different for each group. In the control group, most of the associations that students made were situated at a phenomenological level. However, in the experimental group, students made many associations related to the curricular contents. Conclusions The STEM approach had a more noticeable effect on the development of students’ cognitive structures on the topic of electrical circuits: based on the results, it can be concluded that this approach allowed students from the experimental group to achieve the learning goals, while students from the control group still retained many ideas that do not meet learning goals. Additionally, WAT has proven to be a suitable diagnostic method, as well as an instrument that can be used to evaluate the accomplishment of students’ learning objectives.
Cognitive structures have attracted the attention of science education researchers because they affect students' learning of new scientific knowledge and play an important role in subsequent learning. According to the researchers, in order to realise meaningful learning in education and training, students' cognitive structures should be determined correctly. Researchers have used techniques such as word association test, flow maps, concept maps, drawing and writing technique, and concept cartoons to determine students' cognitive structures. They analysed the data with methods such as cut-off point technique, coefficient of relatedness formula, response frequencies mapping method, and qualitative analysis. In this study, a) what cognitive structure is; b) the methods, techniques, and tools used to determine cognitive structures; and c) how the data collected was used to determine cognitive structures are analysed and explained with examples of articles. In addition, the results of previous studies on cognitive constructs, especially in the field of science education, are presented.
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