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Scott Sinex

Prince George's Community College, Physical Sciences & Engineering, Professor Emeritus

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Latest work has ventured into developing Google Sheets projects that examine large data sets, such as from NASA, with big scatter. A series of YouTube videos were developed to guide users through Google Sheets computations, graphing, mathematical modeling, and adding interactivity and dealing with error analysis for Sheets simulations. See Sites homepage for new GSheets support, data projects (mainly focused on climate change), and new sims!

Efforts over the last decade involve the development of interactive Excel spreadsheets or Excelets to enhance conceptual understanding via mathematical modeling of data, multivariable simulations, and error analysis. Over 240 pre-built Excelets are available covering topics in chemistry, materials science, astronomy, and mathematics. We have also started to have students use Google Sheets to develop online collaboration, data pooling, and computational skills. Google Sheets is very Excel-like with comparable computational capability and somewhat limited in graphical features. Now Sheets has the same regression choices as Excel plus the check box as an interactive on/off switch. See our updated Data Pool in the Cloud website for more information.

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Papers by Scott Sinex

Desmos Penny Circle Activity: Enhanced Analysis and Data Pooling

Electronic Proceedings of the ICTCM Conference, Vol. 36, 11pp., 2025

Two interactive Google Sheets spreadsheets were developed to expand the data analysis of the Desm... more Two interactive Google Sheets spreadsheets were developed to expand the data analysis of the Desmos Penny Circle Activity. Via simple computations, students can examine 2D penny packing models, discover and perform an error analysis, and examine some statistical measures of variability via data pooling. This brings mathematical, statistical, and scientific thinking together around an elegant simple model in Desmos. Plus, students can validate the Desmos simulation!

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Need help: Dealing with Scientific Data in Google Sheets: Data > Model > Simulation
at https://sites.google.com/view/ssinex/home/dealing-with-data-in-gsheets.

Open Educational Resources for Supporting Engineering Education

Proceedings of ASEE Mid-Atlantic Section Spring Conference held at George Washington University, District of Columbia, 2024

Discussion of Open Educational Resources (OER) is often limited to textbook cost but it is the fl... more Discussion of Open Educational Resources (OER) is often limited to textbook cost but it is the flexibility and customizability of OER that makes them a best choice for education. To truly succeed OER projects need to provide not only textbooks but tools and other resources needed today and they need to do so in a way that makes it simple (or as simple as possible) for instructors and students. Platforms for OER must and are becoming educational ecologies with services such as annotation, adaptive homework systems, collaboration tools and more. Engineering and STEM OER has particular demands, including LaTeX equation editing and the ability to execute programs within the textbook. They also must, and are, being extended to be accessible to all, where accessible not only supports those who have difficulty reading, but also those who do not have easy access to devices or the internet. Rather than a loose assembly of EdTech apps, OER system design requires components that support each other. At Prince George's Community College we have built open textbooks for community college engineering, chemistry and physics courses for engineering students using LibreTexts. A major virtue of OER textbooks is that they can be improved formatively as instructors work with their classes. On the technical side, as new components such as a branded school OER commons, a project management app and an online homework system become available they can be integrated to work with the ongoing materials. These textbooks have supported past, current and future curriculum redesign including a new Associate of Science degree in Chemistry and a planned one in Physics.

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For a great interactive example, see Introduction to Engineering for Engineers and Scientists
https://eng.libretexts.org/Bookshelves/Introductory_Engineering/EGR_1010%3A_Introduction_to_Engineering_for_Engineers_and_Scientists

Messy Data and a More Real-World Function Machine

Electronic Proceedings of the ICTCM Conference, Vol. 35, 12pp. , 2024

Authentic, "messy data" contain variability that is derived from a multitude of sources. We will ... more Authentic, "messy data" contain variability that is derived from a multitude of sources. We will examine sources and tweak the function machine to handle multiple variables and errors, a real-world scientific approach dealing with uncertainty. "Messy data" has become a topic in science education and has appeared in the literature. The topic is essentially rediscovering error, both random and systematic, which has been around since measurement appeared. Authentic big data (large data sets) that contains scatter needs more consideration in mathematics and the sciences. Here data from NASA, NOAA, and others with respect to climate change will be used to illustrate "messy" big data via Google Sheets.

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Need help: Dealing with Scientific Data in Google Sheets: Data > Model > Simulation
at https://sites.google.com/view/ssinex/home/dealing-with-data-in-gsheets.

Global Determination of Sea Level Height via Satellite Altimetry

Electronic Proceedings of the ICTCM Conference, Vol. 33, 11pp., 2022

Global mean sea level (GMSL) is critical for addressing climate change. In 1993, NASA started col... more Global mean sea level (GMSL) is critical for addressing climate change. In 1993, NASA started collecting accurate satellite altimetry measurements of sea surface height. We will describe how NASA collects the data and how to analyze a large NASA data set to determine GMSL. Google Sheets will be used here; however, the task could be downloaded into, and accomplished in, Excel.

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Need help: Dealing with Scientific Data in Google Sheets: Data > Model > Simulation
at https://sites.google.com/view/ssinex/home/dealing-with-data-in-gsheets.

Relative Sea Level Change: A Global Problem in Your Backyard

Electronic Proceedings of the ICTCM Conference, Vol. 33, 8pp., 2022

Using authentic mean sea level data for a local site from the PSMSL website, we will use tide gau... more Using authentic mean sea level data for a local site from the PSMSL website, we will use tide gauge data to address the question, "Is sea level changing?" and determine the rate of relative sea level change for the site. Students will need to be able to produce a scatter plot of the data and perform a linear regression and display the equation and r-square on the plot. Google Sheets will be used here; however, the task could be accomplished in Excel.

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Need help: Dealing with Scientific Data in Google Sheets: Data > Model > Simulation
at https://sites.google.com/view/ssinex/home/dealing-with-data-in-gsheets.

Volumetric Measurement of Tumors: Mathematical Models, Assumptions, and Errors

Electronic Proceedings of the ICTCM Conference, Vol. 30, 13pp., 2019

This activity involves the metrology, the science of measurement, of the determination of the vol... more This activity involves the metrology, the science of measurement, of the determination of the volume of tumors by two different methods. Caliper measurements of the dimensions and volume from mass and density are done using a suitable substitute, which allows for a comparison of the two methods; and a number of literature-based ellipsoid models can be evaluated and compared. Google Sheets located in Google Drive, a free cloud-based application, will be used to handle data analysis and simulations of error behavior. Students will discover and explore the propagation of errors for the multivariable ellipsoid model!

Modernizing the Engineering Curriculum: A Community College Approach to Integrate Materials

by Scott Sinex and Scott Johnson

J. Materials Education 40 (3-4), 125-132, 2018

Providing a broad engineering education has become an enormous challenge. Engineering is derived ... more Providing a broad engineering education has become an enormous challenge. Engineering is derived from the basic sciences of physics and chemistry using tools provided by mathematics. With a broad high level introduction an engineer can move to any specialization. We believe that a solution to improving engineering education is to coordinate core engineering courses, calculus, differential equations, physics, chemistry, introductory engineering, materials science, and computer programming so that they support each other. Prince George's Community College has taken a first step in building such a curriculum by creating a new, one semester General Chemistry course specifically designed for engineers. Our collaborators at Howard University have helped in providing an open, online accompanying textbook through the LibreTexts project. Introductory courses are typically taught in isolation of one another without the interconnecting threads that bind topics in different courses together. Community colleges can be less influenced by departmental limits than universities. This freedom allows for greater opportunity for innovation.

Discovering Pi and its Measurement Variation: A Collaborative Cloud Activity

by Scott Sinex and Theodore Chambers

Spreadsheets in Education, 10 (3), Article 4, 2018

Measuring the circumference and diameter of objects, such as coins and lids, allows students to d... more Measuring the circumference and diameter of objects, such as coins and lids, allows students to discover pi from the circumference-to-diameter ratio. From multiple measurements of these two variables and the calculation of the simple ratio, measurement variation can be examined in a variety of numerical and graphical approaches, plus the influence of both random and systematic errors can be explored and percent error using the known value of pi. A best-fit mathematical model can be examined where a plot of circumference as a function of diameter yields the value of pi from its slope. By using a common US standard object (4-inch PVC pipe connector), the accuracy and precision of the measurements can be evaluated. Additionally, utilizing a pre-built Google Sheets spreadsheet (https://goo.gl/oYVQzS), data is collected, graphs produced, and computations performed in a shared environment in the cloud via Google Drive. This allows online collaboration and comparison within the class and between classes and even institutions, all-the-while building a large data set. Since the diameter measurement requires measuring through the center of the object, the diameter measurements could be underestimated which would yield a positive percent error in the determination of pi by this method. Random error should also be minimized as the number of objects measured (sample size) increases as well.

Algebraic and Scientific Thinking via Spreadsheets: The Unstacking Coins Model

Electronic Proceedings of the ICTCM Conference, Vol. 29, 2018

By starting with a stack of coins and removing four at a time, we construct a model with negative... more By starting with a stack of coins and removing four at a time, we construct a model with negative correlation. This investigation can have the linear regression model with its mathematical nature converted to the scientific nature (physical meaning of variables). Error can be investigated in a spreadsheet simulation to see how it influences results including model predictions. We can validate the model using US Mint data along with pooled group results for some interesting discussion.

Building a Dynamic University-Community College Partnership: The Second Decade of a Broad, Mutually Beneficial Materials Science Collaboration

by Tito Huber, Scott Sinex, and Paul Sabila

MRS Advances 3 (12), 637-642, 2018

Collaborations between community colleges, non-research centered universities and research univer... more Collaborations between community colleges, non-research centered universities and research universities can enrich the flow of students into Science, Technology, Engineering and Mathematics (STEM) majors and careers. The nation is beginning to understand the importance of such interaction especially with under-represented minorities and those with disabilities. For over fifteen years our group has developed new ways to integrate these students and their faculty to the research culture. This will lead to increased diversity and inform research university faculty of the great talent that is latent in these underserved pools.

Online Collaborative-Pair Computational Spreadsheets II: Successive Approximations, Solver, and Learning Spreadsheetese!

by Scott Sinex and Theodore Chambers

Chemical Educator 22, 125-129, 2017

In an effort to enhance online collaboration we show how Google Sheets, a part of Google Drive, c... more In an effort to enhance online collaboration we show how Google Sheets, a part of Google Drive, can be used to familiarize students in introductory courses with the practice of online collaboration and enhance their computational spreadsheet skills by introducing simple numerical methods. Students work in pairs with the instructor serving as a facilitator to aid student pairs by providing formative assessment during spreadsheet development.

Online Collaborative-Pair Computational Spreadsheets: Radioactive Decay

Chemical Educator 22, 12-17, 2017

As engineering, science, and industry in general become increasingly global, online collaboration... more As engineering, science, and industry in general become increasingly global, online collaboration has become a normal part of the professional's workday. It has, however, not been integrated into the US educational system. In this paper we show how Google Sheets, a part of Google Drive can be used to familiarize students in beginning courses with the practice of online collaboration and enhance their computational spreadsheet skills.

Multivariable Spreadsheet Modeling and Scientific Thinking via Stacking Bricks

Electronic Proceedings of the ICTCM Conference, Vol. 28, pp. 381-390, 2017

Students measure the height of a variety of stacks of bricks and construct a mathematical model v... more Students measure the height of a variety of stacks of bricks and construct a mathematical model via a spreadsheet using linear regression. They predict the height of a 100 bricks. Then they go outside and measure brick heights in a real brick wall. Students quickly discover that mortar in between the brick is going to modify their model. They take measurements of bricks plus mortar and produce a second or revised model. Students compare models, consider random and systematic errors using a pre-built spreadsheet simulation, and then develop a model to count the number of bricks in a specified area of a wall (and can verify). From multiple measurements of bricks and mortar joints in a brick wall, students can get a feel for real variation. In the end, a multivariable model is developed and explored as an interactive spreadsheet simulation. A version using Lego bricks and plates (mortar) is also considered.

General Chemistry for Engineers in the 21st Century: A Materials Science Approach

MRS Advances 2 (31-32), 1629-1634, 2017

In the case of General Chemistry, many engineering students only take a one semester class with ... more In the case of General Chemistry, many engineering students only take a one semester class with important topics such as kinetics and equilibrium being given limited coverage. Considerable time is spent covering materials already covered in other courses such as General Physics and Introduction to Engineering. Moreover, most GChem courses are oriented toward health science majors and lack a materials focus relevant to engineering. Taking an atoms first approach, we developed and now run a one-semester course in general chemistry for engineers emphasizing relevant materials topics. Laboratory exercises integrate practical examples of materials science enriching the course for engineering students. First-semester calculus and a calculus-based introduction to engineering course are prerequisites, which enables teaching almost all the topics from a traditional two semester GChem course in this new course with advance topics as well. To support this course, an open access textbook in LibreText, formerly ChemWiki was developed entitled General Chemistry for Engineering. Many of the topics were supported using Chemical Excelets and Materials Science Excelets, which are interactive Excel/Calc spreadsheets. The laboratory includes data analysis and interpretation, calibration, error analysis, reactions, kinetics, electrochemistry, and spectrophotometry. To acquaint the students with online collaboration typical of today's technical workplace Google Drive was used for data analysis and report preparation in the laboratory.

Updated course website: https://sites.google.com/view/ssinex/home/chm-2000-new-stuff

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A follow-up paper, "Modernizing the Engineering Curriculum: A Community College Approach to Integrate Materials", was published in J. Materials Education 40 (3-4), 125-132 (2018).

Oh Sheets!: A Tool for Online Collaboration in the Cloud

Spreadsheets in Education 9 (2), Article 2, 2016

Higher education needs to bring students into the practice of cloud based online collaboration su... more Higher education needs to bring students into the practice of cloud based online collaboration such as they will encounter after graduation. A useful introduction starts with data collecting and pooling with Google Forms followed by real time graphing and computations, easily accomplished in the Excel-like Google Sheets. We find students and in-service teachers are very positive about their experience. Here we review the limited literature and describe how instructors can get their students into cloud based online collaboration using spreadsheets and other powerful collaborative options available via Google Drive.

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Need help: Dealing with Scientific Data in Google Sheets: Data > Model > Simulation
at https://sites.google.com/view/ssinex/home/dealing-with-data-in-gsheets.

Inspiring Online Collaborative STEM Learning

by Scott Sinex and Theodore Chambers

MRS Advances 1 (56), 3727–3733, 2016

Educators are advocating a variety of 21st century technologies to increase student engagement an... more Educators are advocating a variety of 21st century technologies to increase student engagement and prepare them for the modern workplace. As part of this effort this paper describes the development of several introductory laboratory activities which enhance online collaborative skills in the context of group collaborations. The experiments mostly deal with measurement and error in the context of mathematical modeling. They inculcate online collaborative skills including group writing, collection of experimental data, student feedback, and assessment using forms, spreadsheets with data pooling, real-time graphing/computations, and discussions using chat. These are all available in Google Drive, a free cloud-based application. We have also introduced student collaborative pair computational spreadsheet assignments, and results of two projects in general chemistry are presented. Building formative assessment into these activities allows for immediate adjustment to instruction. This approach could be used from middle school through the undergraduate level. It can be implemented both in informal education or formal classroom settings by enhancing interactions with remote partners. Student evaluations have been very positive for the variety of activities, as well as from workshop feedback from high school teachers.

Investigating the Mass-Volume Relationship of Materials from Classic to Collaborative Cloud Experiment

by Scott Sinex and Theodore Chambers

Chem. Educator 20, 48–52, 2015

Determining the density of a solid object by measuring mass and volume by water displacement is a... more Determining the density of a solid object by measuring mass and volume by water displacement is a classic introductory chemistry experiment. In this activity students performed these measurements on a variety of steel bolts to derive density graphically using a collaborative cloud-based application (Google Drive) that has student groups contributing data into a spreadsheet using an online form. The spreadsheet is projected in the laboratory as data is entered; and real-time graphing of the data (mass versus volume) is presented along with computations of the slope (density), y-intercept, and r-squared. Student groups calculate the same information from their individual groups by hand-drawn graphs and using a pre-built spreadsheet. They then compare their data to the larger class set plus standard values. As a post-laboratory assignment, each group of students must prepare a collaborative laboratory report using a pre-designed template addressing further analysis and questions in which each group member contributes.

Materials, Measurement, and Error: Comparative Class Data and Scientific Argumentation via a Cloud-based Application

by Scott Sinex and Theodore Chambers

Mater. Res. Soc. Symp. Proc. Vol. 1657, 2014

The Next Generation Science Standards make scientific discourse a vital part of the classroom and... more The Next Generation Science Standards make scientific discourse a vital part of the classroom and arguing with evidence needs to become a common practice for students. Analysis and interpretation of data are an integral part as well. We present an approach using 21st-century technology combined with collection of laboratory data that is suitable for middle school through college. In an experiment using common nuts and bolts first semester chemistry students form six groups and determine a bolt mass indirectly. They collect mass data; then enter the data into an online form that compiles the data into a spreadsheet in Google Drive, a free cloud-based application. Once all the groups have submitted their data, they access the spreadsheet online and start an emulated online discussion in the laboratory as if the groups were globally dispersed using the chat feature available in Google Drive. Each group is identified by a group number having a unique group email address so there is a semi-anonymous sense among the members that allows for a fairly free discussion among students.

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This is the follow-up discussion of the online chat from our earlier paper, "Developing Online Collaboration Skills in the General Chemistry Laboratory" in J. Chem. Educ. 2013, 90, 1244−1246.

Developing Online Collaboration Skills in the General Chemistry Laboratory

by Scott Sinex and Theodore Chambers

J. Chem. Educ. 2013, 90, 1244−1246

Online collaboration is a vital 21st-century technology skill. So how can online collaboration be... more Online collaboration is a vital 21st-century technology skill. So how can online collaboration be incorporated into general chemistry? We are using Google Drive spreadsheets and forms to develop online collaboration skills in students. The forms capability allows easy collection of data for class comparison and student feedback. The information collected in a spreadsheet can be projected for class discussion, or can easily be downloaded and analyzed in Excel. This is an eﬀective way to gather class statistics on experimental data. We have started to use the Google chat feature to promote discussion in the laboratory of class data, such as looking for uniformity in data or analyzing errors across groups. This is done by posting a link to the form to enter data for student groups and then the link to the spreadsheet of data (which only instructors can edit) and having students open it in the lab. With multiple openings the chat feature is enabled. Any discussion is anonymous unless students or lab groups identify themselves (students are not signed into Google Drive). These mock online collaborations are a valuable start and demonstrate the ease and power of the technology. Collaborative group projects or reports are a logical next step, which would require students to have a Google account.

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Further discussion of results can be found in a later paper "Materials, Measurement, and Error: Comparative Class Data and Scientific Argumentation via a Cloud-based Application" in Mater. Res. Soc. Symp. Proc. Vol. 1657 (2014).

Investigating and Visualizing Measurement Error for Novice "STEM" Learners

ASEE Mid-Atlantic Spring Conference 2013 Proceedings

At some point students reach the course that addresses the propagation of errors after answering ... more At some point students reach the course that addresses the propagation of errors after answering the question “What errors influence your results?” in umpteen different experiments plus maybe a few percent error calculations. Dealing with error is a mindset that requires developing over time. Why not start the process as soon as measurement occurs? This is in line with the Analyzing and Interpreting Data section of the Next Generation Science Standards. To study errors, the novice learner needs to make experimental errors in relatively simple situations that allow comparison to near errorless situations. Now students can discover the influence of the error and study its behavior by further numerical experimentation.

Over the last decade as mathematical modeling of data has become a larger part
of the scientific experience for students, more investigation of errors has been
incorporated. The approach includes both actual experimentation with analysis
and the use of simulations. The tool of choice for modeling data and constructing interactive animated simulations is the spreadsheet. A variety of discovery-learning tools to examine random and systematic errors have been developed. Students gain hands-on experience with a number of experiments and subsequent data analysis. Then they extend their experience using prebuilt interactive animated simulations to enhance their conceptual understanding and foster deeper learning of multivariable systems.

How do instructors change their pedagogical approach? They learn how the
spreadsheet simulations can be used to explore and discover concepts, enhance
science process, and foster higher-order thinking. Instructors can convert a
classic lecture into a discussion using dynamic spreadsheet simulations and
asking “what if” questions. Students experience a predict-test-analyze cycle
where they must explain what they observe with instructor guidance. The
simple computational mechanics of inducing the various errors and how they
influence linear models are discussed. Students deal with errors in a large
variety of situations including error simulations and analysis for numerous
topics.

All materials and numerous other prebuilt spreadsheets plus instructions for
developing interactive Excel spreadsheets available free to download are
accessible at https://academic.pgcc.edu/~ssinex/excelets/matsci_excelets.htm.