Middle Grades: Misconceptions in Statistical Thinking

Capraro, Mary Margaret; Kulm, Gerald; Capraro, Robert M.

doi:10.1111/j.1949-8594.2005.tb18156.x

Cited by 38 publications

(40 citation statements)

References 14 publications

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“…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). Moreover, the data revealed inconsistencies between the curve equations created by students and their real life outcomes; these inconsistencies can likely be attributed to an inability to correctly interpret graphics, which itself is rooted in an incomplete understanding of physics and/or statistics and mathematics (McDermott, Rosenquist, & van Zee, 1987;Capraro, Kulm, & Capraro, 2005;Planinić, Milin-Šipuš, Katić, Ivanjek, & Sušac, 2012). An inadequate understating of limits and derivatives were likewise made evident by students' misinterpretations of the graphical data (Bingölbali, 2013;Özmantar & Yeşildere, 2013).…”

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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Section: Discussionmentioning

confidence: 99%

Evaluation of Learning Gains Through Integrated STEM Projects

Çorlu¹,

Aydın²

2016

IJEMST

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“…Transcripts of conversations between, and interviews with, teachers and students who have developed and applied peer-scaffolding approaches however, suggest that rather than encouraging individuals to develop their own understanding, the net effect often reduces to a validation-by-consensus mentality (Capraro, Kulm, & Capraro, 2005;Chin & Chia, 2004;Demirci, 2008;Gautier, Deutsch, & Rebich, 2006;Hamza & Wickman, 2008;Mills et al, 2008;Nehm & Reilly, 2007;Newton & Newton, 2009;Psycharis & Babaroutsis, 2005;Salierno, Edelson, & Sherin, 2005;Settlage, 2007;Smith & Abell, 2008;Stamp, 2007;Stamp & Armstrong, 2005;Wali Abdi, 2006). This does not mean that deployment of peer-scaffolded learning cannot deliver substantial learning gains for individuals.…”

Section: Limitations Of the Sociocultural Discoursementioning

confidence: 99%

Creativity in Science: Tensions between Perception and Practice

Schmidt¹

2011

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Many countries are reviewing science education programmes and implementing new pedagogical paradigms aimed at reversing a trend of declining enrolments. A key factor in this decline is a public perception that science is not a creative endeavour. Attempts to reframe public perception tend to focus on primary and secondary schooling, but do little to address ongoing declines in quality and originality of intellectual output beyond the high-school environment. To overcome systemic devaluation of science requires appreciation of the complex, dynamic, and often stochastic, interplay of sociocultural, psychological and cognitive factors that drive human creativity. Viewing creativity from this perspective reveals tensions between perception and practice that limit opportunities for students, science educators and scientists. Resolving the tension requires integration of developmental, psychometric and sociocultural discourses of creativity in ways that generate opportunities for individuals at all levels of education and practice to: 1) acquire a high level of domain-specific knowledge; 2) practise application of that knowledge in developing solutions to problems across a gradient of difficulty and; 3) be challenged to integrate their knowledge of science with their knowledge of other fields to pursue and solve problems with personal relevance.

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“…We knew that students have difficulties reading and interpreting boxplots, as well as other statistical representations (Biehler 1996;Capraro, Kulm, and Capraro 2005;delMas, Garfield, and Ooms 2005;Friel and Bright 1996;Friel, Curcio, and Bright 2001;Konold et al 1997, Lem et al 2013a, 2013b). One of the major difficulties observed in these studies derives from the fact that boxplots represent the data in an aggregated form.…”

Section: Summary Thoughtsmentioning

confidence: 99%

“…We also want our students to make connections among different representations and use them while conjecturing, reasoning, and solving problems. However, research demonstrates that many students have difficulties in interpreting, reasoning with, and even reading, statistical representations (Biehler 1996;Friel and Bright 1996;Konold et al 1997;Friel, Curcio, and Bright 2001;Ben-Zvi and Garfield 2005;Capraro, Kulm, and Capraro 2005;delMas, Garfield, and Ooms 2005;Lem et al 2013aLem et al , 2013b. delMas, Garfield, and Ooms (2005) discuss students' misconceptions about different statistical representations and conclude that students have many difficulties when reasoning about the graphical representations of data.…”

Section: Introductionmentioning

confidence: 99%

Interpretations of Boxplots: Helping Middle School Students to Think Outside the Box

Edwards

Ozgun-Koca

Barr

2017

Journal of Statistics Education

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Boxplots are statistical representations for organizing and displaying data that are relatively easy to create with a five-number summary. However, boxplots are not as easy to understand, interpret, or connect with other statistical representations of the same data. We worked at two different schools with 259 middle school students who constructed and interpreted boxplots. We observed that even students who were able to create boxplots had difficulty interpreting data represented in a boxplot. After sharing specific difficulties that we observed students having, we discuss ways to help students to make sense of data presented in boxplots.

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Middle Grades: Misconceptions in Statistical Thinking

Cited by 38 publications

References 14 publications

Evaluation of Learning Gains Through Integrated STEM Projects

Evaluation of Learning Gains Through Integrated STEM Projects

Creativity in Science: Tensions between Perception and Practice

Interpretations of Boxplots: Helping Middle School Students to Think Outside the Box

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