Teaching Electrolysis with Guided Inquiry - ACS Publications

Chapter 9

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Teaching Electrolysis with Guided Inquiry John I. Gelder,*,1 Michael R. Abraham,*,2 and Thomas J. Greenbowe*,3 1Department

of Chemistry, Oklahoma State University, Stillwater, Oklahoma 74078 2Department of Chemistry and Biochemistry, 101 Stephenson Pkwy., The University of Oklahoma, Norman, Oklahoma 73019, United States 3Department of Chemistry, University of Oregon, Eugene, Oregon 97403, United States *E-mails: [email protected], [email protected], [email protected]

Inquiry in its modern form has been around since the 1950’s. Its initial emphasis focused on hands-on laboratory investigations. Two National Science Foundation (NSF)-sponsored high school chemistry curriculum development projects; the Chemical Bond Approach (1959) and the Chemical Education Curriculum Study (1959) were early examples of inquiry instruction based on laboratory activities. In the mid 1960’s an NSF funded elementary school project, Science Curriculum Improvement Study (SCIS), introduced another form of inquiry instruction, called the Learning Cycle Approach. This approach divides instruction into three phases: exploration, invention and application. The exploration phase relies on data collection in the laboratory, followed by group discussion to invent the critical concept from the data, and application activities to help deepen understanding of the concept. At about the same time as inquiry instruction was being emphasized, many forms of technology began to appear in the classroom along with activities that used the technology in instruction. However, early use of microcomputers in the classroom, when associated with the laboratory, did not always support an inquiry approach. One of the weaknesses of inquiry instruction based on laboratory activities, which by their very nature presents information at the macroscopic level, was the difficulty of inventing particulate

© 2015 American Chemical Society In Sputnik to Smartphones: A Half-Century of Chemistry Education; Orna, Mary Virginia; ACS Symposium Series; American Chemical Society: Washington, DC, 2015.

level concepts and explanations. With dynamic particulate level simulations, it became possible to investigate conceptual understanding at the particulate level. Written inquiry activities were built to accompany these simulations to allow students to invent concepts based on a particulate level view.


Inquiry as an Instructional Strategy One of the outcomes of the USA/USSR competitive stance of the 1960’s was the push to improve science education through government-supported curriculum development projects. Several of these projects used inquiry as an instructional strategy. Inquiry approaches are usually associated with several instructional characteristics. These include the use of laboratory data to derive concepts, the emphasis on scientific process, the use of questions to guide student learning, the involvement of students in instructional decisions, and the emphasis on evidence in inventing concepts. These characteristics of inquiry instruction have ramifications for how teachers and students interact and what role the various components of instruction play in a unit of instruction. One of these early projects was the Science Curriculum Improvement Study (SCIS), a science curriculum project for elementary school students supported by the National Science Foundation (NSF). The theoretical base for this project was the Learning Cycle Approach (1). The Learning Cycle Approach is an example of an inquiry-oriented instructional strategy that can be used to help students develop concepts and can be used to guide the construction or organization of units of instruction. The Learning Cycle Approach, represented in Table 1, divides instruction into phases, each of which plays a role in instruction.

Table 1. The Learning Cycle and Large Class Instruction Learning Cycle

Role

Activity

Data

Class Organization

Concept Exploration

Introduction to Concept

Data Collection & Analysis

Gathering Data

BCE – Before Class Exploration

Concept Invention

Identification of Concept

Conclusions and Interpretation

Explaining Data

DCI – During Class Invention

Concept Application

Application, Extension, Reinforce, or Modify Concept

Using the Concept in new Applications

Using Data, Provide Evidence

ACA – After Class Application

First, students are exposed to data (called the “Exploration Phase” which demonstrates the concept) from which concepts can be derived (called the “Invention Phase,” which identifies the concept). Students can then apply the concept to other phenomena (called the “Application Phase,” which applies the 142 In Sputnik to Smartphones: A Half-Century of Chemistry Education; Orna, Mary Virginia; ACS Symposium Series; American Chemical Society: Washington, DC, 2015.


concept). In contrast to traditional instructional approaches, this inquiry-oriented approach uses data to derive concepts rather than to verify concepts. This difference has several consequences for the role played by various instructional activities. Laboratory and other data generating activities play a more central role in introducing concepts. Instruction can be said to be data driven. The data that are obtained by the students can be used as the evidence to make claims. Classroom discussions are focused on using data to generate or invent concepts rather than informing students of the concepts. Textual materials are used to apply, reinforce, review, and extend concepts rather than introduce concepts. This approach encourages more active learning by students. There are several characteristics which, when used in combination, establish the Learning Cycle Approach as a distinct inquiry-oriented instructional strategy. The most important of these is the presence of the three phases of instruction in a specific sequence, “exploration - concept invention - concept application” (E > I > A). This sequence has a number of logical consequences. The “Exploration Phase” coming first implies that learners will use the information exposed by the learning activity inductively during the “Invention Phase.” The key to this instructional approach is that learners derive the concept from their observations of the behavior of an experimental system. In this way, data plays a central role in instruction. In the “Application Phase,” learners use the invented concept to verify and modify their ideas through a deductive process. The Learning Cycle Approach has advantages over other instructional strategies because it takes into account both inquiry and exposition; that is, it requires the learner to use both inductive and deductive logical processes. There has been a large amount of research concerning the Learning Cycle Approach since its origins in the 1960s. Most of the research supporting the Learning Cycle Approach is discussed in detail in Lawson, Abraham, & Renner (2). A summary of this research supports the conclusion that the Learning Cycle Approach can result in greater achievement in science, better retention of concepts, improved attitudes toward science and science learning, improved reasoning ability, and superior process skills than would be the case with traditional instructional approaches (3–8). This is especially true with intermediate level students when instructional activities have a high level of intellectual demand (9).

Inquiry and Laboratory Historically the data source used to generate concepts in inquiry approaches was hands-on laboratory activities. This emphasis on laboratory data was mirrored by the two main NSF supported high school chemistry projects, the Chemical Bond Approach (CBA) and ChemStudy. The Chemical Bond Approach was a project aimed at college bound high school students. A group of high school and college faculty met in 1958 and 1959 to develop the course materials. The approach in this project was to provide opportunities to connect theory and experiment so students could experience the process of inquiry. 143 In Sputnik to Smartphones: A Half-Century of Chemistry Education; Orna, Mary Virginia; ACS Symposium Series; American Chemical Society: Washington, DC, 2015.


The ChemStudy project began organizing in 1960, again with a group of high school and college faculty. The goals of this project focused on building content knowledge and exposure to current scientific research for the high school teacher and to prepare high school students with an interest in science, as well as students who were not going to pursue a scientific career (10).While the ChemStudy group planned to develop a textbook, a laboratory manual, and films, they first focused on what content was important to cover with the project materials. It was also decided that the laboratory would be used to introduce each course topic. In the laboratory students would generate experimental data as evidence to support the development of principles. Demonstrations by the teacher and experiments that were presented on film were also used as data sources for experiments that did not lend themselves for the high school classroom. Effort was made to limit the concepts that were covered in the course to those that could be developed from experimental evidence. At the same time that the two high school chemistry projects were getting started, the National Academy of Sciences organized a meeting, held at Woods Hole, Massachusetts, as a response to the Soviet Union’s launch of the Sputnik series of satellites, to identify the problems of science education and to recommend solutions. Representatives from a wide range of academic disciplines, science, and mathematics, but also education, history and psychology, attended. The report from this meeting emphasized discipline based education, conceptual learning, and inquiry-oriented instruction (11).

Inquiry’s Influence Overall, the national curriculum reform efforts had an impact. During the 1976 – 77 academic year, 15% of high schools were using the CHEM Study materials. Physics had similar percentage usage of the Physical Science Study Committee (PSSC) and the Harvard Project Physics materials. In biology, 43% of schools were using Biological Sciences Curriculum Study (BSCS) materials. It was believed that as a result of these projects that the chemistry curriculum reflected more current chemical knowledge, better reflected what happens in the research laboratory, and communicated how concepts and models are based on evidence (12). The inquiry approach continues to be recognized as an important approach to teaching and learning from early 60’s to today. Experimentation to generate data, along with the practice of making claims based on evidence, has continued to be emphasized. Through the latter part of the 20th century an emphasis on scientific processes developed. The elementary science program Science - A Process Approach that had its origins in the 1960’s had described 14 different science processes (see Table 2) to be part of instruction (13). The Process Oriented Guided Inquiry Learning (POGIL) project uses cooperative learning and the Learning Cycle Approach in a lecture-less environment to teach process skills and introductory chemistry content (14).

144 In Sputnik to Smartphones: A Half-Century of Chemistry Education; Orna, Mary Virginia; ACS Symposium Series; American Chemical Society: Washington, DC, 2015.

Table 2. Scientific Processes Processes


Grades K – 3rd

Observing, measuring, using number relationships, using space/time relationships, classifying, inferring, predicting and communicating

4th – 6th

Formulating hypotheses, controlling variables, experimenting, defining operationally, formulating models, interpreting data

The Challenges of Inquiry Although inquiry approaches have been shown to have many educational benefits, there are weaknesses that must also be taken into account. The data sources to support concept development in inquiry approaches have traditionally come from hands-on laboratory activities. Demonstrations or films were also used, but the laboratory was always considered an environment where an inquiry approach was a best fit. All of these sources provide macroscopic data. But many explanations for chemical behavior are based on what atoms and molecules are doing. We want students to think about what is happening at the submicroscopic level. How can the macroscopic data be used in an inquiry approach to address the submicroscopic? Another issue is that although inquiry has been shown to be an effective instructional strategy in small classroom settings, it has been difficult to introduce into large lecture environments. The lengthy process of gathering data used to invent a concept proves problematic in a 50-minute class. Furthermore, relegating the data-gathering phase to the laboratory can also be problematic because laboratory sections are usually distributed throughout the week making coordination of data with concept invention difficult. Also, with a limited number of laboratory experiments in the semester, only a small number of concepts can be addressed compared to the total number of concepts in the curriculum. Teacher-to-student and student-to-student interactions are also awkward in large class settings. Inquiry uses questions in the classroom to guide students to invent ideas. Regardless of the setting, instructors need to ensure all students are paying attention to answering questions. When using a series of questions in an instructional setting, many students are not fully aware of the complete meaning of the question and are not able to construct a meaningful response without some degree of facilitation by the instructor. It is also difficult to react to a student’s response in a meaningful way when it includes misconceptions or incorrect answers. When an instructor hears a student’s answer, the instructor may not be able to immediately address the misconceptions embedded in the student’s response other than merely correcting the answer. The instructor typically must re-state the student’s response using words more appropriate to cover any of these misconceptions. Trying to make up a tactic to address student misconceptions in real-time can be challenging for any instructor. 145 In Sputnik to Smartphones: A Half-Century of Chemistry Education; Orna, Mary Virginia; ACS Symposium Series; American Chemical Society: Washington, DC, 2015.

To encourage greater participation by students, Clicker Questions can be presented to students who provide an answer using a Personal Response System (15). However, the kinds of questions typically asked in the classroom are generally the short answer type as it is too difficult and time-consuming to have students work a challenging problem.


Addressing the Challenges An approach to address the above challenges of implementing inquiry and the Learning Cycle Approach in the large lecture classroom is being developed (16). This approach is based on activities that students complete before, during and after each class. These activities are based on the three phases in the Learning Cycle Approach: exploration, invention and application (see Table 1). These phases are referred to as the Before Class Exploration (BCE), the During Class Invention (DCI), and After Class Application (ACA). Before Class Explorations have students go to an assigned web site to collect data using a simulation or animation, and/or to answer a set of five to seven scaffolding questions to assess what the student knows or think they know about the concept being studied. Simulations can include molecular animations or molecular representations that allows students to analyze and explain chemical behavior at the particulate level. Student responses to the BCEs are collected in a relational database that can be accessed by the instructor, and can be used to develop charts and/or graphs of student-generated observations/data. Since the BCEs are data-driven, they can be used as a component of the Exploration Phase of a learning cycle. Typically, the Before Class Exploration (BCE) requires only 10 to 15 minutes of a student’s time to complete. BCEs can be used to: pool data to invent concepts in lecture, identify student misconceptions and false ideas to be addressed in lecture, and review concepts needed as prerequisite knowledge for a lecture topic. The goals of BCEs are to encourage all students to come to the lecture already thinking about the topic to be discussed and/or to generate data to support concepts to be developed in class. BCEs are one method for more actively involving students in the learning process. The BCE is not intended to replace any part of the lecture presentation or laboratory experience. In fact, BCEs expand the number of concepts addressed by an instructional unit. In turn, having students analyze charts, graphs, or data displayed in tables can be used in the Concept Invention Phase of a learning cycle. The instructor can use the responses to customize his/her lecture presentation and to address any specific student misconceptions, or review prerequisite knowledge. The During Class Invention (DCI) develops/invents the concepts or ideas introduced by the BCE. The DCI poses questions/problems that are focused on a course learning objective and are designed to be done by small cooperative groups in a class setting (17). The questions/problems are presented in a handout or as a class presentation by the instructor (see for example: Landis, Ellis, Lisensky, Lorenz, and Wamser (18); Mazur (19)). When the questions are in a multiple-choice format the answer choices will have been developed from responses to open-ended questions 146 In Sputnik to Smartphones: A Half-Century of Chemistry Education; Orna, Mary Virginia; ACS Symposium Series; American Chemical Society: Washington, DC, 2015.


collected from previous students’ work on quizzes and exam problems. During class, students are given questions to answer. They might work individually or have a small group discussion and come to a consensus response to the questions/problems. Students can then report their individual and or consensus response using a personal response system (15) and/or by turning in a written response. A class discussion can then be based on the DCI. The After Class Application (ACA) is a web-based set of questions enabling students to apply their knowledge and/or practice using concepts introduced by the BCE and invented by the DCI. Questions on the ACA can be conceptual or algorithmic or a combination of both. Problems requiring students to use what they have learned in a slightly different setting can be part of an Application Phase of a learning cycle. Students are expected to spend approximately 15 minutes answering the ACA questions. As with the BCE, after submitting their responses to the ACA questions, students receive an electronic response page that juxtaposes the student’s response to each question with an expert’s response. These responses can be used as the basis for a grade. Both the BCE and ACA are web-based and student responses are stored in a relational database to allow the instructor and students to review at any time.

A Sample Data Driven BCE/DCI/ACA That Uses a Computer Simulation Because the BCEs are used to generate data that is used to invent a concept some mechanism for generating the data is needed. A series of interactive simulations that produce data and help student’s gain an understanding of concepts from a macroscopic, particulate and symbolic levels have been developed (20). In addition four “Next Generation” Simulations: Electrolysis; Stoichiometry; Calorimetry; and Gas Laws and Kinetic Molecular Theory instructional units have been or are being developed. These simulations are being developed in collaboration with an instructional development team that includes artists and computer programmers funded by Pearson Education. As part of an NSF project accompanying sets of instructional activities for each simulation done by students “before”, “during”, and “after” class meetings are also being developed (16). Figure 1 shows a screen shot from the electrolysis computer simulation (21) [Additional molecular level simulations (MoLES) are also available from a previous NSF sponsored project (20). To view the computer simulation on electrolysis, access the URL: http://media.pearsoncmg.com/bc/bc_0media_chem/chem_sim/electrolysis_fc1_ gm_11-26-12/main.html. (Here is a tiny URL http://tinyurl.com/n2282kh). Scroll to Unit 14 - Electrochemistry and click on the link. On the new page that appears scroll to the Electrolysis BCE (BCE69), DCI (DCI69) and ACA (ACA77) and click on the appropriate link. Once the simulation is loaded, users can select the type of metal electrodes, the type of aqueous solution, select the current, and the time. When the simulation is operating, users have the option of viewing particulate nature of matter animations of what occurs in the solution, at the surface of each electrode, and the flow of 147 In Sputnik to Smartphones: A Half-Century of Chemistry Education; Orna, Mary Virginia; ACS Symposium Series; American Chemical Society: Washington, DC, 2015.


electrons within the electrodes and wires. Figure 2 shows a screen shot of an animation sequence of the reduction process at the particulate nature of matter view at the copper cathode in an electrolysis experiment.

Figure 1. Sample screen shot from the Electrolysis Computer Simulation. (20).

Figure 2. A screen shot of an animation sequence at the particulate nature of matter level. (20). 148 In Sputnik to Smartphones: A Half-Century of Chemistry Education; Orna, Mary Virginia; ACS Symposium Series; American Chemical Society: Washington, DC, 2015.

The following provides an example of how the simulation can be used in a lesson that is based on the learning cycle. The lesson is designed to guide students to determine the relationship between the change in mass at an electrode and the current, time and metal ions in solution; and also to invent Faraday’s Constant (22).


Exploration Phase: Before Class Activity In the BCE students are instructed to open the Electrolysis simulation and open the Demonstration Mode to become familiar with the experimental setup. Next students are asked to set up experiments based on the experimental conditions set forth in the BCE. It is important to note that in this particular BCE any one of six pairs of experiments (see Table 3) can be randomly generated to produce the data necessary to invent the relationship between time, current, and charge on the metal ion being reduced.

Table 3. Sets of Experiments That Are Randomly Generated in the BCE Set

Experiment

Metal Electrode

Metal Electrode

Time (min)

Amps

1

1

Fe

Fe

5.00

3.00

1

2

Zn

Zn

5.00

3.00

2

1

Fe

Fe

10.00

3.00

2

2

Fe

Fe

10.00

2.00

3

1

Zn

Zn

10.00

3.00

3

2

Zn

Zn

10.00

2.00

4

1

Zn

Zn

10.00

3.00

4

2

Zn

Zn

5.00

3.00

5

1

Ag

Ag

10.00

3.00

5

2

Ag

Ag

5.00

3.00

6

1

Fe

Fe

10.00

2.00

6

2

Ag

Ag

10.00

2.00

Students are asked several questions addressing both macroscopic and microscopic observations that they should make during the experiment. Each student’s set of responses, and data collected in the experiment are stored in a database the instructor can access. Students receive feedback in the form of an expert’s response after submitting their BCE responses. The instructor can access all of his/her student’s responses to extract the data for classroom discussion and to determine how much prior knowledge students are bringing to the classroom. Students are expected to bring his/her data to lecture. 149 In Sputnik to Smartphones: A Half-Century of Chemistry Education; Orna, Mary Virginia; ACS Symposium Series; American Chemical Society: Washington, DC, 2015.


Table 4. Data Table with Response Cells from the BCE

Concept Invention Phase: During Class Inventions To invent the relationships between current, time and number of electrons transferred, the instructor has several resources available to use in lecture: a PowerPoint presentation and a student handout. Both of these resources are available on the project website (22). For this discussion the focus will be on the activity. Students would work through the activity in small groups. In the activity, the first question asks students to complete a data table based on the BCE experiment completed before class. Depending on the size of the class students could be assigned to locate other students with different experimental data to complete the table, or for a large class students could be invited to complete a data table projected on a screen for everyone to see. While data were entered, other students could verify that data. After pooling the data, students are expected to construct a table (see Table 5). Once the data table is completed, students are asked to describe any patterns they see in the data. They are then asked to write a mathematical equation that would represent the relationship between mass plated out and time, and mass plated out and current. Based on the experiments the students completed in the BCE, two observations should be evident; 1) That doubling the time doubles the mass of metal produced; 150 In Sputnik to Smartphones: A Half-Century of Chemistry Education; Orna, Mary Virginia; ACS Symposium Series; American Chemical Society: Washington, DC, 2015.

2) That increasing the amps by a factor of 1.5 increases the mass produced by a factor of 1.5; (we expect that most students will only recognize that increasing the amps increases the mass produced); The two mathematical relationships the student should write are:


1) Moles α time 2) Moles α current

Table 5. Summary Data Table for the Electrolysis Simulation Current (amps)

Time (sec)

Mass of Zn (g)deposited

Mass of Fe (g) deposited

Mass of Ag (g) deposited

3 amp

600

0.60 g

0.52 g

2.01 g

3 amp

300

0.31 g

0.26 g

1.00 g

2 amp

600

0.41 g

0.35 g

1.34 g

The next portion of the activity (beginning with question 4) is designed to guide students to discovering the relationship between moles of metal plated on the electrode and the number of electrons transferred. This is a much more subtle connection to discover, so scaffolding questions are asked that involve reviewing the microscopic videos included in the simulation, writing half-reactions, and calculating the number of atoms plated out at the electrode. To get started Question 4 asks if the mass plated out depends on whether the metal is zinc, iron or silver. The answer would be yes, but exactly what the relationship is, is not obvious. To further guide the student to the next relationship Question 5 asks for the chemical equations (half-reactions) that describe what happens when each of the metals plates out on the electrode. By writing the half-reaction and focusing on what is similar and what is different about the half-reactions, it is hoped that students will make two observations: 1) that when using chemical equations the amount of substance should be expressed in moles; and 2) for both zinc and iron 2 moles of electrons are transferred per mole plated out, while for silver 1 mole of electrons are transferred per mole of metal plated. To further emphasize the mole issue in Question 6 parts a through c, students are asked to calculate how many atoms of zinc, iron and silver were plated out in the experiments. By filling out the new data table in Question 7 students should arrive at the third and final relationship between the amount of metal plated (now in moles of the metal) and the number of electrons transferred. In question 8, Question 4 is re-stated asking for the mathematical relationship that is evident in the data. The relationship is;


Also students can re-state the original two relationships in terms of moles in Question 9: 1) Moles α time (sec) 2) Moles α current (amps)


Further a mathematical relationship can now be written combining all three of the variables, current, time and the number of electrons transferred. The new combined mathematical relations involving all three variable is,

If any of the data from the data table are substituted into the mathematical relationship 4) above it is clear that the moles of metal plated out do not equal . To convert the proportionality to an equality we must introduce a proportionality constant. Now whether the proportionality constant is in the numerator or the denominator is the next issue. Students can do the calculation on their own and then polled as to the magnitude of the constant. The value calculated from this data is either 1.035 x 10-5 or 96,640. The value used has been established by convention as 96,500. The units on the number are amp·sec mol-1. That constant when placed in the denominator is 96,500 and is called the Faraday. Eventually the set of experiments invents the relationship that:

Concept Application Phase: After Class Application After class students are again directed to the web site (22) to answer a series of questions based on their concept invention. In the ACA students are asked to list the variable that can affect the amount of metal plated out. Students are asked to predict the time or current required to plate out a specific mass of a metal given the current or the time. So the student would be expected to rearrange the equation that was invented in the DCI to solve for time, calculate that time in minutes and then use the simulation to verify their prediction. Finally two conceptual questions are asked that require the students to think more deeply about the mathematical relationship they invented in the DCI and what is happening at the electrode where the metal is plating out.

Discussion The Learning Cycle Approach had its origins in late 1950’s and early 1960’s as an inquiry-oriented instructional strategy. It remains in use today. However, with the availability of new technologies, it may be possible to use 152 In Sputnik to Smartphones: A Half-Century of Chemistry Education; Orna, Mary Virginia; ACS Symposium Series; American Chemical Society: Washington, DC, 2015.


Learning Cycles in exciting new ways. We believe that using Before, During and After Class activities provides several ways to integrates technology into the Learning Cycle Approach to help students practice using science reasoning, and to practice a process approach to developing concepts that are taught in introductory chemistry. Many concepts that are taught in introductory chemistry lend themselves to collecting data, controlling variables, looking for patterns, and developing mathematical relationships. When students are given a directed data-gathering task that uses a simulation (in a BCE), the instructor can bring that data to class, and the class as a whole can explore that data. The instructor can, by asking questions guide students towards finding patterns, and developing relationships. This is important because introductory chemistry students do not demonstrate they are able to control variables and find relationships between dependent and independent variables. Additionally, when the simulations that are used in the data-gathering task, provide dynamic particulate level models that represent the changes that are occurring students can make important connections between the sensory level and the particulate level. The example we have developed in this chapter, and other sets of Before, During and After Class activities we have developed based on the Learning Cycle Approach are intended to engage students in a data driven experience to invent concepts. We can use technology to change the way we do things. If we want to make instruction inquiry oriented there are ways to take advantage of technology to accomplish this change. The focus of the before, during, after guided-inquiry approach is the use of questions to guide students to inventing ideas. We are not using computer simulations to substitute for a regular hands-on laboratory experiments. We are representing chemical reactions at the particulate level. We can distinguish between strategies and tactics that have been shown to be more effective at gaining students interest and are more effective in helping students learn and retain knowledge.

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Teaching Electrolysis with Guided Inquiry - ACS Publications

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