Technology Report pubs.acs.org/jchemeduc
Learning Laboratory Chemistry through Electronic Sensors, a Microprocessor, and Student Enabling Software: A Preliminary Demonstration Qing Zhang, Ly Brode, Tingting Cao, and J. E. Thompson* Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas 79409-1061, United States S Supporting Information *
ABSTRACT: We describe the construction and initial demonstration of a new instructional tool called ROXI (Research Opportunity through eXperimental Instruction). The system interfaces a series of electronic sensors to control software via the Arduino platform. The sensors have been designed to enable low-cost data collection in laboratory courses. Data are collected by a computer and can be displayed or plotted in nearly real time, allowing chemistry to come to life. In addition, student data can be analyzed by the computer automatically and used to provide feedback to assess whether students are analyzing experimental results correctly. Because the computer and software are able to perform all computations and data analysis independently of the student, the software can assess the accuracy of student calculations and even assign grades based upon performance. In addition, since measurement data are logged and plotted, it is possible for the software to assist in assembling laboratory report files that students can print and submit. We envision that the feedback provided to students regarding the accuracy of computations and queries at the conclusion of the experiment can improve laboratory instruction by forcing students to revise or reinforce their mental models at the time of instruction. While this work describes only an initial implementation of the concept, the ROXI platform may ultimately be a powerful mechanism to improve laboratory instruction or serve for administering distance learning laboratory courses. KEYWORDS: Analytical Chemistry, First-Year Undergraduate/General, High School/Introductory Chemistry, General Public, Laboratory Instruction, Hands-On Learning/Manipulatives
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INTRODUCTION According to Kolb’s theory, experiential learning is facilitated by a four-step iterative process:1 1. learner experiences 2. collection of data and observations germane to the experience 3. analysis of data to form abstract concepts and generalizations (e.g., model building) 4. subsequent testing of the model for general robustness Achieving learning requires iterations of this process, actions and observations by the learner, and data and feedback provided to the learner regarding the accuracy of the generalizations drawn. Rapidly providing instruction of such richness can be extremely challenging within a laboratory environment, even for seasoned instructors. In this work, we report the development and initial use of a series of electronic sensors, and command and control software for laboratory instruction with the aim of using technology to assist instruction. We have coined the abbreviation ROXI (Research Opportunity through eXperimental Instruction) to describe the system. The premise of ROXI is illustrated in Figure 1. The general idea is that students can be guided through a hands-on laboratory experience through the use of precisely designed software as an instructional material or guide. The developer crafts a laboratory experience that highlights key learning objectives in a coherent and meaningful way. Providing quality instructional materials is consistent with good practices in © XXXX American Chemical Society and Division of Chemical Education, Inc.
chemical education, as several authors have found quality instructional materials are crucial for student learning.2,3 In addition, the ROXI hardware is used to collect and visualize experimental data by the software during the laboratory experience. Students can view plots of their data stream or extract specific measured values for use in their computations. Because the experimental data are transferred to the digital domain, the software can also analyze the student’s data automatically. If students are prompted to enter results of computations based upon their data, the software can automatically assess the accuracy of computations and provide tailored feedback. The software can be programmed to automatically assign grades based upon measurement accuracy if desired. In addition, the software can be used to ask and grade pre- and postlab questions and even assemble data, plots, computation results, and summary statements into text files that students may submit as laboratory reports. Providing feedback during or at the end of the laboratory session makes possible rapid completion of the fourth step in Kolb’s learning cycle. This may be crucial since Velasco et al.4 suggest providing feedback in the laboratory environment may be the rate-limiting step of the learning cycle. Received: March 2, 2017 Revised: July 10, 2017
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DOI: 10.1021/acs.jchemed.7b00172 J. Chem. Educ. XXXX, XXX, XXX−XXX
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Figure 1. Overview of ROXI approach in the context of Kolb’s theory of experiential learning.
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DESCRIPTION OF THE APPROACH
laboratory exercises or modifying the existing VI requires significant knowledge of the LabVIEW platform.
Sensors
Instructional Aspects of the LabVIEW Software: A Case Study
While a large number of sensors could conceivably be used with the ROXI approach, to date we have developed and/or integrated and tested five sensors common to chemistry experiments. A temperature sensor, gas pressure sensor, spectrophotometer, balance, and commercial pH electrode have been integrated into ROXI. In addition, a fluid dispenser very similar in design to the electronic buret our group has described previously5 is integrated into ROXI. Presenting the specifics of the sensors and their performance within this work would make it prohibitively long. Consequently, sensor designs and results of testing are presented in the Supporting Information (for pH, balance, colorimeter, temperature, and pressure sensors). It should be noted that the sensors themselves generally report analog voltages proportional to the measurement and can be used independently outside of the ROXI environment.
LabVIEW’s ability to rapidly plot and analyze data and interact with students via switches, gauges, and on-screen buttons is crucial. To demonstrate how we have used the LabVIEW GUI within ROXI, we present one case studyin effect, an experiment that has been completed by students enrolled in a junior-level, nonmajors section of a quantitative analysis course at Texas Tech. The case study is rooted in teaching the concepts of statistical analysis of data sets by weighing pennies minted before and after the year 1982. In this year, the composition of pennies changed, yielding an easily detectable mass difference. The mass of pennies has long served as a convenient means to teach the Gaussian distribution and statistical analysis of data sets.15−18 While we have chosen to focus on the penny statistics laboratory to efficiently communicate the core features of ROXI, experiment modules for a gravimetric titration,19 with potentiometric end-point detection, and spectrophotometry have also been developed for the ROXI system. For the penny statistics lab students are given two containers filled with pennies (those minted prior to 1982 and those minted after 1982), the ROXI apparatus housed in a plastic case, and a laptop personal computer running the software. Figure 2 illustrates the LabVIEW GUI that students interact with. To perform the experiment, the balance is tared (see the Supporting Information for details of balance construction and use). Then, a student types the year of the penny’s mint into a text box within the software. The penny is placed on the ROXI balance pan, and the mass of the penny is recorded electronically when the student clicks on a button within the software user interface. The year and measured mass are automatically sent to one of two data pools (pre-1982 and post-1982) and saved into a text file. The text file is read upon each entry of data, and a histogram of frequency vs penny mass is constructed within the GUI as students are collecting data. The penny weighing process is continued until >80 pennies are present in each of the data sets. This allows students to view histograms that demonstrate the normally distributed data for both pools of pennies. This is a valuable instructional tool because it simplifies understanding of the overlap between distributions (if any exists) and how that relates to the probability of data set statistical similarity.
Interface to Computer
The sensors are interfaced to a personal computer running Microsoft Windows through an Arduino Uno. The Arduino platform has previously received considerable attention within J. Chem. Educ. as an interface to a variety of sensors for chemical measurements due to its user-friendly nature and low cost.6−13 The Arduino Uno microcontroller has a 32 kB onboard memory, 14 digital input/output pins, 6 analog inputs, a 16 MHz quartz crystal oscillator, a USB connection for communications, and a power jack for an AC adaptor. Prior to use, several drivers and programs must be installed and run on the host machine. The Arduino software is free to download and use. However, all machines require the installation of National Instruments Virtual Instrument Software Architecture14 prior to use. A license for NIVISA is available free of charge provided the instructional software is developed on the National Instruments LabVIEW platform. Executable files (.exe) can be compiled from VIs using the LabVIEW Full Development System (approximately $3000 USD). Developing or modifying experiment VIs does require a license to a version of LabVIEW. Further details for the technical implementation of the software can be found in the Supporting Information. At present, end-users may find implementing the software requires a bit of effort and practice to properly install the required files and familiarize themselves with the VI. Writing new B
DOI: 10.1021/acs.jchemed.7b00172 J. Chem. Educ. XXXX, XXX, XXX−XXX
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Figure 2. Screenshots of ROXI software for penny statistics exercise. Within the green box, students enter data. Two histograms are displayed within the red box that illustrate the collected data. Within the blue box, students enter the results of calculations. Students then enter text for the introduction and conclusion sections of the laboratory report before clicking on the action button that generates and grades the report.
instructional goal is use of the Student’s t-test to assess the statistical similarity of the data pools (pre- and post-1982
After collecting data, students are prompted to complete calculations based on their measurements. The ultimate C
DOI: 10.1021/acs.jchemed.7b00172 J. Chem. Educ. XXXX, XXX, XXX−XXX
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pennies). The students are asked to compute the mean and standard deviation of each data set, the number of points, number of degrees of freedom, 95% confidence intervals, pooled standard deviation, and calculated t-statistic and must find the tabular t-statistic from a table reproduced in the software. Students enter the results of each calculation into text boxes within the LabVIEW GUI. Separate text entry boxes are available for students to enter text for an introduction section and conclusion section of their lab report. These entries are openended, requiring students to demonstrate organization and a coherence of thought in crafting replies. After completing the entries, students can click a button within the GUI to finish the experiment. Clicking the button generates a Microsoft Word file on the computer’s hard drive that contains the introductory statement, the data collected within a table, the histograms, the results of the student’s computations, and the conclusion section. An example of the automatically generated lab report file is available in the Supporting Information. Alternate user-interface buttons can be added to provide formative assessments to students, if desired. In addition to simply reporting results, the LabVIEW software also checks the accuracy of student computations and questions directly posed to the students. The accuracy assessment is possible because the measurement data are logged in the LabVIEW programming environment. It is relatively straightforward to compare the correctly computed statistical values with the typed answers from the end-user. In this work, we allowed for a ±0.7% deviation between the studentcomputed result and the true result to allow for rounding differences. This value corresponds to the expected tolerance of the balance used when weighing a 2 g object such as a penny. A higher (or lower) standard can be employed if warranted, and the exact tolerance chosen was not made known to students. Feedback is shown to students as “correct” or “incorrect” in the lab report. The correct answer is also provided to the user. This element of the ROXI software provides rapid feedback and summative assessment on mental models that students have constructed and therefore contributes to step 4 of Kolb’s experiential learning theory.
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Figure 3. Summary of student opinions regarding ROXI. For these data, N = 9 students. A copy of the survey instrument is included in the Supporting Information.
ROXI units might be rented as a course material or used in a portable fashion for distance learning applications sometime in the future (scores > 4.2/5.0 for all themes). In addition to the numerical scaled responses, students completing the survey also had the ability to offer opinions of ROXI in a free-response format. Here, we summarize opinions expressed; however, all student responses have been reproduced within the Supporting Information. In general, students appreciated the automation that ROXI offered, whether this was for collection of data into a computer file, formatting data, or generation of the lab report. Students recognized the ROXI approach as being faster, and potentially portable. Caveats included the precision of the scale, the visual appearance of the automatically generated lab report, and the perception that the sensors could easily be broken if students were not careful. One specific area that received comments was the rapid feedback function that ROXI provides. Students mentioned that the rapid feedback on whether calculations are correct or not was very helpful to them to evaluate their work. Again, this allows students the ability to quickly test their mental models as in step 4 of Kolb’s experiential learning theory. Unwittingly, a student demonstrated an appreciation for Kolb’s learning model by remarking that “It’s possible for the student to check his own work and learn it all by himself.”
SUMMARY OF USER EXPERIENCES
Student Opinions of ROXI
During the Fall 2016 semester, students enrolled in a quantitative analysis laboratory used the ROXI apparatus to complete the penny statistics laboratory. Upon completion of the exercise, students were given the option to complete a survey about their experience with ROXI. The survey instrument used is provided in the Supporting Information, and results of the opinion survey are presented in Figure 3. As observed, students were generally receptive of the ROXI platform. The apparatus and software both received scores above 4.5/5.0. Results seem to reflect students were happy with the ease of use of the system and the simplicity with which data management and reporting took place. The ROXI apparatus received the lowest ratings (near 4.0/5.0) for accuracy of the ROXI sensors and when compared to traditional measurement devices. These results represent reality. The limit of detection for the ROXI balance used in this experiment is about 12 mg, much higher than traditional analytical balances. The ROXI balance must also be tared frequentlya feature that slowed experimental progress. The ROXI balance is a low-cost, lowprecision device, and this is accurately reflected in survey results. However, students remained generally receptive to the idea that
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SUMMARY A series of electronic sensors have been designed, constructed, and interfaced to a computer via an Arduino Uno A/D interface. Software has been written within the LabVIEW GUI that guides students through experiments, collects and logs sensor data, creates visual displays of the data, prompts students to perform calculations, automatically checks the accuracy of resultant calculations, provides near-real-time feedback to students on the accuracy of their mental models, and automatically generates laboratory reports. The integrated ROXI system maintains the experiential learning environment of the laboratory classroom, is capable of providing well-produced course materials and guidance through the software, and feedback provided by the software during the laboratory class completes Kolb’s experiential learning cycle. The ROXI apparatus is portable and easy to use. The design is also potentially compatible with distance learning applications. D
DOI: 10.1021/acs.jchemed.7b00172 J. Chem. Educ. XXXX, XXX, XXX−XXX
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(12) Famularo, N.; Kholod, Y.; Kosenkov, D. Integrating Chemistry Laboratory Instrumentation into the Industrial Internet: Building, Programming, and Experimenting with an Automatic Titrator. J. Chem. Educ. 2016, 93 (1), 175−181. (13) Mabbott, G. A. Teaching Electronics and Laboratory Automation Using Microcontroller Boards. J. Chem. Educ. 2014, 91 (9), 1458−1463. (14) National Instruments VISA: What Is VISA? National Instruments. https://www.ni.com/visa/ (accessed July 2017). (15) Stolzberg, R. J. Do New Pennies Lose Their Shells? Hypothesis Testing in the Sophomore Analytical Chemistry Laboratory. J. Chem. Educ. 1998, 75 (11), 1453. (16) Richardson, H. Reproducible Bad Data for Instruction in Statistical Methods. J. Chem. Educ. 1991, 68 (10), 310. (17) Harris, D. C. Penny Statistics. Experiments To Accompany Exploring Chemical Analysis, 4th ed.; W. H. Freeman: New York, 2008; http://bcs.whfreeman.com/webpub/Chemistry/ExploringChem5e/ Lab_Experiments/5e-Expts_for_Web_Nov_2011.pdf (accessed July 2017). (18) Bularzik, J. The Penny Experiment Revisited: An Illustration of Significant Figures, Accuracy, Precision, and Data Analysis. J. Chem. Educ. 2007, 84 (9), 1456. (19) Thompson, J. E.; Brode, L. My Dear Buret, Your Time Has Indeed Come! J. Chem. Educ. 2016, 93 (6), 988−989.
ASSOCIATED CONTENT
S Supporting Information *
The Supporting Information is available on the ACS Publications website at DOI: 10.1021/acs.jchemed.7b00172. Sample lab report generated by the software (PDF) Survey instrument (PDF) Description of pH sensor (PDF, DOCX) Description of balance sensor (PDF, DOCX) Description of colorimeter sensor (PDF, DOCX) Description of temperature sensor (PDF, DOCX) Description of pressure sensor (PDF, DOCX) Initialization sketch for the Arduino and associated description (PDF, DOCX) LabVIEW VI for penny statistics lab (ZIP) Instructions for technical implementation of the software (PDF, DOCX)
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AUTHOR INFORMATION
Corresponding Author
*E-mail:
[email protected]. ORCID
J. E. Thompson: 0000-0003-1550-2823 Notes
The authors declare no competing financial interest.
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ACKNOWLEDGMENTS The Arduino logo is reprinted with permission from Arduino Store USA. REFERENCES
(1) Kolb, D. A.; Fry, R. Toward an Applied Theory of Experiential Learning. In Theories of Group Process; Cooper, C., Ed.; John Wiley & Sons: London, 1975. (2) Hofstein, A.; Lunetta, V. N. The Laboratory in Science Education: Foundations for the Twenty-First Century. Sci. Educ. 2004, 88 (1), 28− 54. (3) Xu, H.; Talanquer, V. Effect of the Level of Inquiry on Student Interactions in Chemistry Laboratories. J. Chem. Educ. 2013, 90 (1), 29− 36. (4) Velasco, J. B.; Knedeisen, A.; Xue, D.; Vickrey, T. L.; Abebe, M.; Stains, M. Characterizing Instructional Practices in the Laboratory: The Laboratory Observation Protocol for Undergraduate STEM. J. Chem. Educ. 2016, 93 (7), 1191−1203. (5) Cao, T.; Zhang, Q.; Thompson, J. E. Designing, Constructing, and Using an Inexpensive Electronic Buret. J. Chem. Educ. 2015, 92 (1), 106−109. (6) Grinias, J. P.; Whitfield, J. T.; Guetschow, E. D.; Kennedy, R. T. An Inexpensive, Open-Source USB Arduino Data Acquisition Device for Chemical Instrumentation. J. Chem. Educ. 2016, 93 (7), 1316−1319. (7) Kubínová, Š.; Šlégr, J. ChemDuino: Adapting Arduino for LowCost Chemical Measurements in Lecture and Laboratory. J. Chem. Educ. 2015, 92 (10), 1751−1753. (8) Urban, P. L. Open-Source Electronics As a Technological Aid in Chemical Education. J. Chem. Educ. 2014, 91 (5), 751−752. (9) McClain, R. L. Construction of a Photometer as an Instructional Tool for Electronics and Instrumentation. J. Chem. Educ. 2014, 91 (5), 747−750. (10) Walkowiak, M.; Nehring, A. Using ChemDuino, Excel, and PowerPoint as Tools for Real-Time Measurement Representation in Class. J. Chem. Educ. 2016, 93 (4), 778−780. (11) Meloni, G. N. Building a Microcontroller-Based Potentiostat: An Inexpensive and Versatile Platform for Teaching Electrochemistry and Instrumentation. J. Chem. Educ. 2016, 93 (7), 1320−1322. E
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