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Empirical Investigation Strategies

For over a century, learners’ participation in empirical investigations has been integral to science instruction in many types of learning environments. Empirical investigations are a general strategy that includes all sorts of activities and tactics that generally relate to asking questions about, collecting data from, experimenting on and the testing of natural phenomena (National Research Council [NRC], 2012). Traditionally, such empirical investigations have often occurred in settings or classrooms that simulate a laboratory environment (e.g., measuring temperatures of water, contained in a glass beaker, heated through various changes of state; Hofstein & Lunetta, 1982).

Empirical investigations can also include field experiences in the natural environment (e.g., collecting water samples in a creek located near a school). Empirical investigations in laboratory and field settings often involve use and manipulation of equipment and materials via methodologies consistent within a scientific domain (e.g., growing and counting bacteria in a petri dish filled with agar; Hofstein & Lunetta, 2004). In recent decades, empirical investigations also include virtual electronic simulations and environments in which learners collect data and conduct tests and experiments (e.g., observing global temperature changes via computer-based climate change models; Hofstein & Kind, 2012).

Learners’ engagement in empirical investigations can achieve many learning goals. The National Academies of Science released a report in the mid-2000s that said when learners participate in empirical investigations, they may: (a) gain mastery of science content, (b) develop scientific reasoning skills, (c) understand the complexity and uncertainty inherent in empiricism, (d) develop practical skills, (e) understand the characteristic nature of science, (f) cultivate interest in science and interest in learning science, and (g) foster a sense of teamwork (National Research Council, 2007). Inherent within these goals is an assumption that participating in laboratory activities will help learners learn about both the processes of the scientific empiricism (i.e., how to do scientific investigations) and the products of the scientific empiricism (i.e., the knowledge produced from scientific investigations). However, much prior research (see, for example, Driver & Easley, 1978) showed that participation in empirical investigations fell far short of these goals because learners and teachers often relied on a stepwise sequence of procedures to arrive at a predetermined outcome (e.g., the six steps of the so-called “scientific method”: make an observation, generate a question, form a hypothesis, conduct an experiment, analyze the data, and draw a conclusion). Therefore, learners only superficially engaged in this type of learning strategy and would not deeply understand how the stepwise laboratory activity related to fundamental scientific concepts (Lunetta, Hofstein, & Clough, 2007).

Inquiry-based Strategies

Inquiry-based science learning strategies emerged from research about learning via empirical investigations. Researchers proposed the learning cycle to weave development of understanding about scientific concepts with development of more abstract and complex reasoning that is reflected in empirical investigations (Karplus & Butts, 1977; SCIS, 1974). The learning cycle consisted of three phases: (a) exploration, where teachers introduced a scenario requiring science students to interact with phenomenon by encountering a problem, generating questions, observing, measuring, etc.; (b) concept introduction, where science students and teachers made sense of their interactions with the phenomenon of interest in an explanation; and (c) concept application, where students elaborated and extended the explanation to other contexts and phenomena. The developers designed the learning cycle to act as a strategy to help students self-regulate their science learning through a guided process of scientific inquiry, including discovery, explanation, and elaboration (Karplus & Butts, 1977). Although guided inquiry-based science strategies came under criticism for a variety of reasons (e.g., focusing solely on manipulation of materials and pieces of equipment to arrive at a pre-defined solution; see, for example, Tobin, Tippins, & Gallard, 1994), the learning cycle heavily influenced science interventions in the 1990s and early 2000s, including, among others, predict-observe-explain (White & Gunstone, 1992), authentic science tasks (Songer, 1996), and project-based science (Marx, Blumenfeld, Krajcik, & Soloway, 1997). The learning cycle is currently manifest in many science classrooms as the BSCS 5E Instructional Model (Bybee et al., 2006), consisting of five phases: engagement, exploration, explanation, elaboration, and evaluation.

Scientific Expertise Strategies

Engaging learners in inquiry-based instruction is closely related to the notion that developing learners’ scientific expertise is critical for deep science understanding. Strategies for developing expertise aim to develop learners’ thinking skills that reflect the core attributes of authentic scientific reasoning (Chinn & Malhotra, 2002). To develop such expert reasoning, learners need to construct, conceptually organize, and retrieve relevant knowledge about phenomena consistent with scientists who practice within a particular topic domain (Bransford et al., 2000). For example, learners who develop astronomy expertise will be able to construct and relate models of celestial motions that can be accurately applied to astronomical systems at planetary, stellar, and galactic scales. As such, strategies that seek to develop expertise should have students engage in cognitive processes and practices that reflect scientific inquiry (e.g., designing experimental conditions to investigate relations among variables; Kunsting, Wirth, & Paas, 2011) and scientific epistemic beliefs (e.g., coordinate theoretical models with multiple lines of evidence; Chinn & Malhotra, 2002).

Developing such scientific expertise through tasks that engage students in authentic inquiry has proved to be a daunting task for both educators and educational researchers. Chinn and Malhotra (2002) found that many science inquiry-based tasks were rather simplistic, with the potential to reinforce non-scientific epistemic beliefs (e.g., scientific knowledge is simple, certain, and algorithmic). However, to facilitate learners’ development of scientific expertise, learners should engage in tasks that elicit authentic reasoning strategies over sustained periods of time (see, for example, Chen & Wu, 2012). To aid in this sustained strategy of authentic scientific inquiry, the learning sciences and science education research communities called for the development of instructional scaffolds to facilitate cognitive apprenticeship, where “complex tasks can be distributed ... to minimize obstacles and compensate for limitations by providing assistance at opportune moments” (Quintana et al., 2004, p. 340). This call paved the way for contemporary science learning strategies that incorporated argumentation, modeling, and socio-scientific concepts. In fact, a recent report by the NRC (2018) recommended that “science investigation and engineering design should be the [emphasis added] central approach for teaching and learning science and engineering” (p. S-4), with scaffolds needed for learners to develop deep understanding of “phenomena and evidence-based solutions to challenges ... over time” (pp. 3-4).

 
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