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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
*
SSupporting 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
■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 general-
izations (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
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’sdata
automatically. If students are prompted to enter results of
computations based upon their data, the software can automati-
cally 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
Published: July 24, 2017
Technology Report
pubs.acs.org/jchemeduc
© 2017 American Chemical Society and
Division of Chemical Education, Inc. 1562 DOI: 10.1021/acs.jchemed.7b00172
J. Chem. Educ. 2017, 94, 1562−1566
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■DESCRIPTION OF THE APPROACH
Sensors
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 previously
5
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 measure-
ment and can be used independently outside of the ROXI
environment.
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 Architecture
14
prior to use. A license for NI-
VISA 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
laboratory exercises or modifying the existing VI requires
significant knowledge of the LabVIEW platform.
Instructional Aspects of the LabVIEW Software: A Case
Study
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
withinROXI,wepresentonecasestudyin 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 potentio-
metric 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.
Figure 1. Overview of ROXI approach in the context of Kolb’s theory of experiential learning.
Journal of Chemical Education Technology Report
DOI: 10.1021/acs.jchemed.7b00172
J. Chem. Educ. 2017, 94, 1562−1566
1563
After collecting data, students are prompted to complete
calculations based on their measurements. The ultimate
instructional goal is use of the Student’st-test to assess the
statistical similarity of the data pools (pre- and post-1982
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.
Journal of Chemical Education Technology Report
DOI: 10.1021/acs.jchemed.7b00172
J. Chem. Educ. 2017, 94, 1562−1566
1564
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 open-
ended, 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 student-
computed 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.
■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 frequentlyafeaturethatslowed
experimental progress. The ROXI balance is a low-cost, low-
precision device, and this is accurately reflected in survey results.
However, students remained generally receptive to the idea that
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
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 experi-
ential learning cycle. The ROXI apparatus is portable and easy to
use. The design is also potentially compatible with distance
learning applications.
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.
Journal of Chemical Education Technology Report
DOI: 10.1021/acs.jchemed.7b00172
J. Chem. Educ. 2017, 94, 1562−1566
1565
■ASSOCIATED CONTENT
*
SSupporting 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)
■AUTHOR INFORMATION
Corresponding Author
*E-mail: jon.thompson@ttu.edu.
ORCID
J. E. Thompson: 0000-0003-1550-2823
Notes
The authors declare no competing financial interest.
■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) Kubínova
,S
.; Sle
gr, J. ChemDuino: Adapting Arduino for Low-
Cost 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.
(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.
Journal of Chemical Education Technology Report
DOI: 10.1021/acs.jchemed.7b00172
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