Scientific Reasoning
Broadly defined, reasoning skills are considered to be essential to knowledge acquisition, and mark the development of advanced cognition (Koerber, Mayer, Osterhaus, Schwippert, & Sodian, 2015; Koerber, Sodian, Thoermer, & Nett, 2005; Koslowski, 1996; Kuhn, 2011; Lawson, 2004; National Academy of Sciences - National Research Council, 1999; Zimmerman, 2007). There are several definitions of what constitutes scientific reasoning through frameworks of literacy (Dawson & Venville, 2009; Giere, Bickle, & Maudlin, 2006; Romine, Sadler, & Kinslow, 2017), cognitive skills (Klaczynski & Narasimham, 1998; Zeineddin & Abd-El-Khalick, 2010; Zimmerman, 2007), scientific inquiry (Adey & Shayer, 1990; C. W. Beck & Blumer, 2012; Chen & She, 2015; Gerber, Cavallo, & Marek, 2001; Weld, Stier, & McNew-Birren, 2011), and hypothesis testing (Lawson, 2004, 2005; Piekny & Maehler, 2013; Zimmerman, 2007). Also, terms such as critical reasoning, scientific thinking, decision-making skills, and inference skills also appear in relation to scientific reasoning within the literature. Due to the multitude of definitions, it is essential to delineate how scientific reasoning is defined throughout the research literature and how it was defined for this study so that multiple audiences from psychology, education, science, and mathematics can draw connections from this research to the research on scientific reasoning within their own fields.
Several domains and sub-domains of scientific reasoning have been classified in the literature, and include the following: control of variables, proportions and ratios, probability, inductive reasoning, logical reasoning, hypothetical-deductive reasoning, causal reasoning, and correlational reasoning (Bao & Koenig, 2011; Koslowski, 1996; Lawson, 2004; Zimmerman, 2000). Causal and correlational reasoning are critical skills in the laboratory setting and therefore are the focus of this dissertation. These skills are needed to (1) look for patterns in collected data, (2) determine if relationships exist between variables, and (3) identify by what mechanism those variables are related. Understanding how these skills are developed is a predicate task to identifying how laboratory curriculum can best target these skills to aid students in achieving mastery.
Several domains and sub-domains of scientific reasoning have been classified in the literature, and include the following: control of variables, proportions and ratios, probability, inductive reasoning, logical reasoning, hypothetical-deductive reasoning, causal reasoning, and correlational reasoning (Bao & Koenig, 2011; Koslowski, 1996; Lawson, 2004; Zimmerman, 2000). Causal and correlational reasoning are critical skills in the laboratory setting and therefore are the focus of this dissertation. These skills are needed to (1) look for patterns in collected data, (2) determine if relationships exist between variables, and (3) identify by what mechanism those variables are related. Understanding how these skills are developed is a predicate task to identifying how laboratory curriculum can best target these skills to aid students in achieving mastery.
Why are Scientific Reasoning Skills Important?
Educational reforms such as the National Science Education Standards (1996) and the Next Generation Science Standards (2013) stress the need for students to learn not only science content, but to also acquire cognitively advanced and domain transferable scientific reasoning skills (Bybee & Fuchs, 2006; Ding, Wei, & Mollohan, 2016; Kuhn, Iordanou, Pease, & Wirkala, 2008). There is also an increased push from the U.S. government, economists, businesses, and educators for exposure to STEM content to create a more abundant and diverse STEM workforce (Daily & Eugene, 2013; Evans, McKenna, & Schulte, 2013; Hrabowski, 2012; MacIsaac, 2016). In order to prepare such a workforce, various studies have shown that development of such reasoning skills better enabled students to handle open-ended novel situations to solve various scientific, engineering, and social problems that simulate real-world situations (Bao et al., 2009; Bybee & Fuchs, 2006; Coletta & Phillips, 2005; Grapentine, 2012; Iyengar et al., 2008; J. C. Moore & Rubbo, 2012; Schauble, 1996; Zimmerman, 2000).
Unfortunately, according to the National Science Foundation (2012), the United States continues to fall behind other countries regarding student science and mathematical skill performance. The Program for International Student Assessment (PISA) test measures students’ (at age 15) ability to examine, analyze, interpret, and reason through skills-based problems in the domains of mathematics, science, and reading. The United States fell below the scores of 15 OECD countries in 2012, including China, Korea, and Japan. Similarly, on the PISA math test in 2012, the United States was ranked lower than 21 other OECD nations, including the three previously mentioned countries. This stagnation implies that students from the United States are not proficient at scientific and mathematical reasoning in comparison to other OECD countries. Further still, even students in STEM majors show deficits in their scientific reasoning abilities (Boudreaux, Shaffer, Heron, & McDermott, 2008; MacIsaac, 2016), and in particular, causal reasoning (Weinberg, 2012; Zeineddin & Abd-El-Khalick, 2008).
Unfortunately, according to the National Science Foundation (2012), the United States continues to fall behind other countries regarding student science and mathematical skill performance. The Program for International Student Assessment (PISA) test measures students’ (at age 15) ability to examine, analyze, interpret, and reason through skills-based problems in the domains of mathematics, science, and reading. The United States fell below the scores of 15 OECD countries in 2012, including China, Korea, and Japan. Similarly, on the PISA math test in 2012, the United States was ranked lower than 21 other OECD nations, including the three previously mentioned countries. This stagnation implies that students from the United States are not proficient at scientific and mathematical reasoning in comparison to other OECD countries. Further still, even students in STEM majors show deficits in their scientific reasoning abilities (Boudreaux, Shaffer, Heron, & McDermott, 2008; MacIsaac, 2016), and in particular, causal reasoning (Weinberg, 2012; Zeineddin & Abd-El-Khalick, 2008).