Chemistry laboratory experiments focusing on students’ engagement in scientific practices and central ideas of chemical practices

1.1 Scientific practices

A new vision of science education promotes science learning based on scientific practices (National Research Council, 2012), instead of inquiry, focusing on students’ engagement in eight scientific practices. McNeill and her colleagues (2015) proposed a model of thinking about these practices that is presented in Figure 1. According to their model the three practices: “asking questions” (SP1), “planning and carrying out investigations” (SP2), “using mathematical and computational thinking” (SP3) are in the core of the investigations. “Analyzing and interpreting data” (SP4), “constructing explanations” (SP5), “developing and using models” (SP6) are the sensemaking practices. Finaly, “engaging in argument from evidence” (SP7), and “obtaining, evaluating and communicating information” (SP8) constitutes the critiquing practices (McNeill et al., 2015; National Research Council, 2012; Stephenson et al., 2020). Teaching approaches focus on scientific practices are not significantly different from those based on inquiry (García-Carmona, 2020; Michaels et al., 2008), and there is a dissent about the broadness of the two approaches (Furtak & Penuel, 2019).

Figure 1:

A representation of grouping the National Research Council scientific practices.

1.2 Central ideas of chemical practices

A central challenge in science education is the development of teaching-learning activities that actively and meaningfully engage students in both authentic domain-specific practices, and the specific ways of reasoning, which characterize each scientific domain (Bulte et al., 2006; Talanquer, 2013). In the case of chemistry, those authentic core practices certainly involve the analysis, synthesis, and transformation of chemical substances (Sevian & Talanquer, 2014). Talanquer (2016) proposed a framework that includes six central ideas for practice of chemistry – “substance characterization” (CP1), “structure determination” (CP2), “property prediction” (CP3), “reaction analysis” (CP4), “reaction control” (CP5), and “sustainable action” (CP6) – that interrelate the core disciplinary content, practices, and the goals of the chemical enterprise.

Given the above ideas, the present work has focused on the development of two laboratory experiments centered on sensemaking scientific practices: “analyzing and interpreting data” and “developing and using models”, as well as on central ideas of chemical practices: “substance characterization”, and “property prediction”, which can guide transformations of curriculum, instruction, and assessment in secondary chemistry courses. We used a scientific practices approach instead of the inquiry-based one, because the latter has various definitions that make difficult to assess the results of inquiry-based learning (Cooper, 2015). Table 1 gives brief descriptions of both scientific practices and central ideas of chemical practices that is the focus of the proposed experiments. Descriptions of science practices are adaptations of definitions given in The Framework for K–12 Science Education (McNeill et al., 2015; National Research Council, 2012; Stephenson et al., 2020), and those of chemical ideas for practice are derived from relevant literature (McClary & Talanquer, 2011; Ngai et al., 2014; Sevian & Talanquer, 2014; Talanquer, 2016; Talanquer & Pollard, 2010). These definitions allow us to assess whether students can effectively engage in the practices that proposed experiments focused on.

2.1 Laboratory experiments

Two laboratory experiments entitled (a) Development and Comparison of Different pH Color Scales from Plants (E1), and (b) Using a pH Color Scale Model (E2) were developed. The pH color scales occurred by the natural extracts are presented at Figure 2. The activities and questions included in the laboratory experiments are summarized in Tables 2 and 3. Plant extracts have been proposed as acid-base indicators in secondary laboratory experiments for a long period (e.g., Carvalho et al., 2002; Editorial Staff, 1997; Forster, 1978; Im et al., 2023). They are more friendly in use by students in comparison with chemical indicators that can be toxic, expensive and pollutants for the environment. However, few of the proposed experiments aim to engage students in inquiry (e.g., Im et al., 2023) and none in scientific practices and central ideas of chemical practices.

Figure 2:

pH color scales from plant extracts.

The design of the experiments was accomplished by using as criteria of each scientific practice the learning objectives from K-12 in “Next Generation Science Standards for Scientific Practices” (National Research Council, 2013). Specifically, at E1, students develop three different models by flower plants, radish, and red cabbage and share their data, in order to evaluate the merits and limitations of each model and decide which one is the most appropriate pH indicator (SP6). The students work in six groups and each plant extract is being studied by two groups. Thus, they compare and contrast their data collected in tables in order to discuss similarities and differences in their findings (SP4).

Experiments’ activities also provide students an opportunity to apply two of the central ideas for chemical practices: (CP1) and (CP3) to answer the corresponding questions (Table 2). The criteria of each central idea of chemical practices that used for the experiments’ design emerged from the related literature (McClary & Talanquer, 2011; Ngai et al., 2014; Talanquer, 2016; Talanquer & Pollard, 2010). In particular, based on experimental data, the differentiating properties of a substance can be used to detect and/or identify it, in each system (CP1) (McClary & Talanquer, 2011; Ngai et al., 2014; Talanquer, 2016; Talanquer & Pollard, 2010). Thus, at E1, students measure the pH of the plant extracts with the “universal indicator paper” and the collected data enable them to characterize the plant extracts as acids. Likewise, at E2, they identify an unknown detergent as basic solution based on experimental data gathered by the “red cabbage color pH meter” model.

Classification is conceptualized as a powerful tool for properties prediction. For example, the classification of acids based on the observable (macroscopic) properties such as the sour taste, metals’ corrosion, and change the color of litmus paper to red. Scientific models of acids can also be used to predict the properties of acids. In the context of the Arrhenius model, acids can be considered as the substances that decrease the pH when dissolved in either water or an aqueous solution, and ‘acidity’, in turn, as an intrinsic property of a substance. Consequently, the examination of how the observable (macroscopic) and/or measurable properties can provide information for properties prediction based on either experimental data or models and representations or both (CP3) (McClary & Talanquer, 2011; Ngai et al., 2014). Students engage in this practice, when they are asked to predict (a) the acid properties of the CO₂ produced by the reaction between vinegar and baking soda either by using the “red cabbage color pH meter” model or by recalling the known properties of CO₂ or by combining experimental data and model; (b) the properties of the CO₂ when produced by different reagents (E2BQ4); and (c) the effect of atmospheric CO₂ to the pH of the rain (E2).

The proposed experiments should be done sequentially to emphasize the “developing and using models”. The concentration of hydrogen ions (H⁺) or pH is a measure of the acidity of an aqueous solution. Acid–base indicators are substances that change color in various concentrations of hydrogen ions (H⁺). Therefore, the use of indicators for pH measurements is a model based on color changes that can be utilized to drive conclusions concerning the acidity of a solution without directly measuring the concentration (or amount) of hydrogen ions (H⁺).

Hazards: Students should wear gloves. The basic and acidic solutions are to be collected in the appropriate waste containers and neutralized before disposal. The plant extracts can discolor clothing and/or skin, so students should be careful.

2.2 Implementation of the experiments

The experiments presented here were implemented in (a) a teacher training course entitled “Chemical laboratory in Formal and Informal Education” at the Department of Chemistry of National and Kapodistrian University of Athens, and (b) a laboratory course at an upper secondary school in Athens to gather students’ data from their engaging in the activities.

3.1 Results from teachers’ implementation

Most of the 23 teachers identified the “analyzing and interpreting data” (19 teachers-E1, 20 teachers-E2), while only 3 (in E1) and 2 (in E2) teachers recognized “developing and using models” as the practices in which students could be engaged. On the other hand, fewer teachers chose the experiments as appropriate to engage students in “analyzing and interpreting data” (13 teachers-E1, 14 teachers-E2). This difference is due to several challenges faced by teachers while teaching scientific practices. Lack of time, large class sizes, and inadequate equipment are reported as the main teachers’ constraints to incorporate inquiry or scientific practices in school laboratory experiments (Crawford, 2014). Teachers showed difficulties regarding the recognition of scientific practices, and especially the “development and using model” practice, which is the main aim for these experiments. It seems that although there is a wide agreement that models are important elements in scientific practice, no unique definition of a model is established (Oh & Oh, 2011). Moreover, previous research mentioned a wide range of interpretations of the scientific practices given by teachers (Dalvi et al., 2021; Kite et al., 2021). Finally, science and chemistry teachers often focus on teaching techniques (like measurement of pH) without emphasizing the underlying models (McNeill et al., 2018).

Regarding the central ideas of chemical practices, most teachers recognized that students could engage in “substance characterization” (21 teachers-E1 and 19 teachers-E2), and in “property prediction” (20 teachers-E1 and 19 teachers-E2). A similar number of teachers (21-E1 and 17-E2) chose both experiments as appropriate to engage students in “substance characterization” but fewer (15-E1 and 15-E2) in “property prediction” practices.

The difference between teachers’ choices is due to their poor knowledge about scientific practices. If teachers do not know what the scientific and/or chemical practices exactly mean, they do not feel comfortable to choose experiments that aim to them (Crawford & Capps, 2018). Research about classroom implementation of scientific practices suggests that teachers interpret disciplinary practices by adapting them to fit within their existing set of goals and expectations (Berland et al., 2016).

3.2 Results from students’ implementation

Students’ engagement in each scientific and chemical practice is denoted by the categories resulting from their responses’ analysis. Each of these categories corresponds to a rationale of students’ answers, depending on the questions’ context and on students’ understandings.

For example, responding to E1Q4, a question that aims to engage students in “developing and using models” practice, 15 students chose the red cabbage extract, and 10 students chose the radish extract (1 without rationale) as the most appropriate pH indicator. The “intensity of change”, “rate of change”, and “connection of change with pH” are categories of rationale refered to how the students evaluated the merits and limitations for each from the three developed models and decided which one is the most appropriate pH indicator.

The “intensity of change” category resulted from students’ responses such as “We chose red cabbage due to strong color change”, “We thought the purple (red cabbage) because the changes were more obvious,” and “The radish because the change is more intense.” “Rate of change” category was revealed by students’ responses such as “The red cabbage because the changes were faster”, and “The red cabbage because it was changing color more easily.” Finally, “connection of change with pH” category refers to students’ responses such as “The radish extract because the change of color was according to the change of the pH,” “The purple (red cabbage) because the changes of color were more characteristics for the changes of pH”, and “The radish because it’s closer to 7 that is neutral.” These statements were used by students to justify their decision about the most appropriate indicator.

The distribution of categories per chosen plant extract is provided in Figure 3. Figure shows that students, who chose the red cabbage extract as the most appropriate pH indicator, justify their decision mainly based on either the observed changes or the rate of those changes. On the other hand, students, who chose the radish extract, justify their decision largely based on connections of observed changes with pH.

Figure 3:

The distribution of categories (intensity of change, rate of change, connection of change with pH) per chosen plant extract (red cabbage or radish).

While secondary chemistry teachers had difficulties to recognize the “development and use models” practice in the proposed experiments, all the students developed three color models for pH measurements in the first experiment and they chose one of them as an indicator in the second. However, they used different criteria to evaluate the limitations of each model and decide which one is the most appropriate. It is remarkable that the choice of the best model does not indicate scientific reasoning, because the majority of students, who chose the red cabbage extract as the suitable color model, used the “the more A-the more of B” intuitive rule of reasoning (Stavy & Tirosh, 1996), as the more intensive or the faster change means the more appropriate indicator. Teachers’ difficulties to recognize the “development and use models” are likely to relate to a lack of knowledge about this practice (Crawford & Capps, 2018).

Students’ implementation provides positive feedback about their effective engagement in the intended scientific and chemical practices using different rationale. The evaluation of their rationales depends on the content and the context of the relate practice (Talanquer, 2018; 2021). The diversity of students’ rationales and the classroom discussion related to the selection of the best model based on specific criteria promote the students critical thinking (Crawford & Capps, 2018). Science education research indicates that a scientific practices-based teaching that requires students to develop and use models is related to both the improvement of students’ understanding of the science content and the development of epistemic knowledge (Crawford, 2014). The proposed experiments focused on analyzing and interpreting data, in contrast to confirmatory experiments, develop students’ competencies to justify their observations and the best interpretation, as well as to summarize the main patterns of the data. Thus, the high advantage of teaching scientific practices is the empowerment of students’ higher-order thinking skills and their scientific literacy (OECD, 2017).