How do secondary school science students interpret and construct scientific graphs?

Tairab, Hassan; Al-Naqbi, Ali Khalfan

doi:10.1080/00219266.2004.9655920

Cited by 46 publications

(35 citation statements)

References 7 publications

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“…In the other studies conducted about graphics (Bruno and Espinel, 2009;Capraro et al, 2005;Lee and Meletiou, 2003;Tairab and Al-Naqbi, 2004), it was seen that bar graph and histogram were used instead of each other without considering the differences between them, similar to the results obtained from the research. It was concluded that institutional infrastructure of education situations given to individuals about histogram is an important factor in the learning of the individuals.…”

Section: Discussionsupporting

confidence: 74%

“…In this direction, it is thought that pre-service teachers confuse bar and line graph. In the conducted studies, it was stated that the confusing of bar and line graph originates from not paying attention to the differences between these two graphs (Capraro et al, 2005;Tairab and A-Naqbi, 2004). As seen from the histogram drawn, histogram resembles bar graph structurally.…”

Section: Individual Recognitions Of Pre-service Elementary Mathematicmentioning

confidence: 97%

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Anthropological analysis of content knowledge of pre-service elementary mathematics teachers on graphs

Ã–vez¹,

Akar²

2018

Educ. Res. Rev.

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The purpose of this study is to analyse the content knowledge on graphs of pre-service elementary mathematics teachers from an anthropological perspective. 112 pre-service elementary mathematics teachers participated in the study. Concentric mixed pattern research method has been used in the study. The data was collected through Graphic Content Knowledge Scale and interview method in order to examine the content knowledge of primary school math teacher candidates related to graphics anthropologically. This scale which was developed within the frame of determined institutional recognitions includes graphic concept and its usage conditions, graphic types and different display forms, making proper transformations between graphics related to a given context, graphic reading, graphic interpreting and graphic drawing skills. In addition, for the purpose of having a more detailed review of the individual recognitions of the 10 participants, a semi-structured interview scale has been developed and used during the interviews. Data acquired have been analysed by using ecologic and praxiologic approach suggested within the framework of Anthropological Theory of the Didactic. The knowledge scale and interview data have been subjected to content analysis and descriptive analysis to interpret the individual recognitions of the pre-service teachers within the scope of institutional recognitions. As a result, it has been observed that the individual recognitions of pre-service teachers related to column, circle and line graphs conform to the institutional recognitions, however in institutional recognitions the techniques specified for column graphs are being used for histogram, hence they have difficulties in comprehending the differences between histogram and column graph. It has also been concluded that they were not aware of a theory based on graph knowledge.

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Section: Discussionsupporting

confidence: 74%

Section: Individual Recognitions Of Pre-service Elementary Mathematicmentioning

confidence: 97%

Anthropological analysis of content knowledge of pre-service elementary mathematics teachers on graphs

Ã–vez¹,

Akar²

2018

Educ. Res. Rev.

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“…A similar distinction can be made with regard to students' interpretations of the graphs (i.e., a quantitative versus qualitative understanding). The approaches observed during the investigative projects suggest an inadequate qualitative understanding of the cause and effect relationship between independent and dependent variables (Özgün-Koca, 2013;Tairab & Khalaf Al-Naqbi, 2004). Although students were relatively successful in carrying out the experimental design's mechanical requirements (e.g., placing data onto measurement tables and graphs), they were unable to identify the best-fitting equations or interpret the R-squared error values (Aydin & Delice, 2005).…”

Section: Discussionmentioning

confidence: 99%

Evaluation of Learning Gains Through Integrated STEM Projects

Çorlu¹,

Aydın²

2016

IJEMST

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New approaches to instruction are needed in all educational levels in order to develop the skills suited to the twenty-first century (i.e., inquiry, problem solving, innovation, entrepreneurship, technological communication, experimental design, and investigativeness). This research evaluated the outcomes of an approach aiming to develop such skills based on students' assessments of themselves and their peers with regard to investigative projects and course grades. The study is chiefly based on a quantitative paradigm with a multi-method approach. Data were primarily collected using a form to evaluate scientific investigation skills and learning gains; students' project reports and examination papers were the other data sources, which were evaluated both quantitatively and qualitatively. The results revealed a low-to-moderate level of improvement in skills. In addition, the authors discovered that students were overestimating their gains, and that peer-evaluations seemed to function better than self-evaluations.

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“…Taken together, these results amplify the importance of procedural knowledge (Aberg- Bengtsson & Ottosson, 2006;McKenzie & Padilla, 1986;Tairab & Khalaf Al-Naqbi, 2004).…”

Section: Mathematical Knowledgementioning

confidence: 54%

“…This perspective is predominantly found in the psychological and mathematics education research literature (e.g., Friel, Curcio, & Bright, 2001;Leinhardt, Zaslavsky, & Stein, 1990;Parmar & Signer, 2005) with several key pieces found in the science education literature (e.g., McKenzie & Padilla, 1986;Shah & Hoeffner, 2002). Unfortunately, most research on graphing in science in the psychological tradition has assessed only math skills and knowledge using tests and surveys, requiring no formal science skills and background knowledge to obtain high scores (e.g., McKenzie & Padilla, 1986;Tairab & Khalaf Al-Naqbi, 2004).…”

Section: Psychological and Sociocultural Literaturesmentioning

confidence: 99%

Assessing and Understanding Line Graph Interpretations Using a Scoring Rubric of Organized Cited Factors

Boote

2014

Journal of Science Teacher Education

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This study examined how 12-and 13-year-old students' mathematics and science background knowledge affected line graph interpretations and how interpretations were affected by graph question levels. A purposive sample of 14 students engaged in think aloud interviews while completing an excerpted Test of Graphing in Science. Data were collected and coded using a rubric of previously cited factors, categorized by Bertin's (1983) theory of graph interpretation. Data analysis revealed responses varied by graph question level. Across levels, students interpreted graphs in one or more of three ways: mathematical word problems (focusing on an algorithm), science data to be analyzed (incorporating science knowledge), or no strategy. Although consistently used across levels, the frequency and usefulness of approaches varied by question level.

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How do secondary school science students interpret and construct scientific graphs?

Cited by 46 publications

References 7 publications

Anthropological analysis of content knowledge of pre-service elementary mathematics teachers on graphs

Anthropological analysis of content knowledge of pre-service elementary mathematics teachers on graphs

Evaluation of Learning Gains Through Integrated STEM Projects

Assessing and Understanding Line Graph Interpretations Using a Scoring Rubric of Organized Cited Factors

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