References


This page includes the reference material for this module as well as resources for various disciplines related to teaching with spreadsheets. The references and resources are organized by are of discipline.

Jump to: General resources | Economics | Mathematics | Physical sciences | Related SERC modules

General Resources

Abramovich, Sergei; Nikitina, Galina V.; and Romanenko, Vladimir N. (2010) ,Spreadsheets and the development of skills in the STEM disciplines, Spreadsheets in Education 3: 3, Article 5.

Provides evidence that spreadsheets can help teach science, technology, engineering and mathematics more effectively.

ASSUME (Association of Statistics Specialists Using Microsoft Excel)

Provides a very large number of links related to teaching statistics using spreadsheets, but seems to be fading.

Baker, John and Sugden, Stephen J. (2003) Spreadsheets in Education –The First 25 Years, Spreadsheets in Education 1: 1, Article 2.

This article reviews a large number of studies and applications for spreadsheet programs in the classroom for several disciplines. This provides an excellent list of resources.

Beare, R. (1992). Software tools in science classrooms. Journal of Computer Assisted Learning 8, 221—230.

The Boyer Commission on Educating Undergraduates in the Research University (1998) Reinventing Undergraduate Education: A Blueprint for America's Research Universities.

Argues colleges and universities should engage in more hands-on quantitative learning.
Solver.com
The home page for the creators of the optimization software embedded in Excel. Provides support and examples (as well as additional products).

Spreadsheets in Education

A peer-reviewed electronic journal featuring examples and techniques of how spreadsheets may be used in a variety of disciplines, at a variety of levels, with an emphasis on mathematics.

Vockell, E., and van Deusen, R. M. (1989). The computer and higher-order thinking skills. Watsonville, CA, Mitchell Publishing Company.

Argues that spreadsheets (and other computer-based learning technologies) can enhance critical thinking skills.
Wetzel, Laura R. and Whicker, Peter J. (2007) Quick Correct: A Method to Automatically Evaluate Student Work in MS Excel Spreadsheets, Spreadsheets in Education 2:3, Article 1.
Explains how to embed spreadsheet assignments with password protected hidden cells that automatically grade assignments.

Resources related to quantitative literacy

A list of a number of resources related to the promotion and teaching of quantitative literacy.
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Economics and Business

Barreto, Humberto (2006), Intermediate Microeconomics with Microsoft Excel, Cambridge University Press.

Website for textbook that integrates automated Excel spreadsheets with textbook content

Humberto Barreto and Frank Howland (2006), Introductory Econometrics Using Monte Carlo Simulation with Microsoft Excel, Cambridge University Press.

Website for textbook that uses Excel spreadsheet exercises to teach econometrics

Benninga,Simon (2006), Principles of Finance with Excel, Oxford University Press.

Website for textbook that uses Excel spreadsheets to teach basic finance

Berry College, "Using Excel to Teach Economics"

Contains a large number of published and unpublished examples.
Brown, Byron, Problems in Microeconomics
Contains a number of programmed Excel workbooks with on-line questions
Cahill, Miles B. and George Kosicki (2001), "A Framework for Developing Spreadsheet Applications in Economics," Social Science Computer Review, Vol. 19, No. 2 (Summer): pp. 186-200.
This article discusses different ways spreadsheet examples may be constructed to either force students to be involved with spreadsheet construction or concentrate entirely on class content. Similarly, students may either be required to understand the mathematics behind a model or use the spreadsheet to explore properties without needing to understand the technical mathematics. Some practical issues as well as examples from economics courses are provided. Much of the content of this module is derived from this article, especially the discussion about transparency.
Cahill, Miles B. and George Kosicki (2000), "Exploring Economic Models Using Excel," Southern Economic Journal, Vol. 66, No. 3 (January), 2000: pp. 770–792.
This article presents a number of different examples from microeconomics and macroeconomics, detailed instructions on how to use key Excel features, and as some general advice in spreadsheet construction. The article argues that using spreadsheets can expand and deepen the content taught at the intermediate level. Edited and updated versions of these instructions are on the Tools page.

Cahill, Miles B. and George Kosicki (2000), Incorporating neoclassical assumptions into IS-LM, Computers in Higher Education Economics Review (CHEER), 14: 2.

Shows how an Excel IS-LM model can be used to show concepts like the neutrality of money, rational expectations and the permanent income hypothesis.

Computers in Higher Education Economics Review (CHEER)

A peer-reviewed journal featuring spreadsheet applications for use in economics. Contains may useful examples, but does not appear to be active.

Craft, Kim, (2003), Using Spreadsheets to Conduct Monte Carlo Experiments for Teaching Introductory Econometrics, Southern Economic Journal 69: 3 (January), pp. 726–735.

This article argues simulation experiments can be implemented in Excel at a low cost. Stable JSTOR URL

Erfle, Steven (2001), Excel files used in Managerial Economics

Files and text from 2001 Social Sciences Computer Review paper on teaching with Excel.

Guest, Ross (2002), A Simulation Approach to the Taylor-Romer Model of Macroeconomic Stabilization Policy, Computers in Higher Education Economics Review (CHEER), 15:1.

Shows how a sophisticated macroeconomic model can be taught at the principles level with the help of a spreadsheet program.

Hokari, Toru, Masaki Iimura, Seiji Murakoshi and Yoshiko Onuma (2007), [link http://www.economicsnetwork.ac.uk/cheer/ch19/hokari.pdf 'Simulating a Simple Real Business Cycle Model Using Excel," Computers in Higher Education Economics Review (CHEER), 19.

Discusses how a graduate-level topic can be taught to undergraduates using Excel.

Judge, Guy (1999), Simple Monte Carlo Simulations on a Spreadsheet Computers in Higher Education Economics Review (CHEER), 13:2.

Shows how a large amount of data may be generated by Excel that can be used to discover estimators and other key statistical concepts.

Lee, Chang Boon Patrick (2005), Teaching spreadsheet proficiency: beyond hitting the keys, International Journal of Human Resources Development and Management, 5:2, pp 218-26.

This article discusses ways spreadsheets can be effectively used in business courses.

McNertney, Edward M. and Robert F. Garnett, Jr. (2006), Using a Simple Simulation Model to Help Students "Think Like Economists" in Intermediate Macroeconomics, Computers in Higher Education Economics Review (CHEER), 18.

Reviews a tool used by Texas Christian University to help drive home key parts of economic analysis.

Mixon, Wilson, Examples tied to Gwartney, Stroup, Sobel, and Macpherson text, Berry College.

Exercises designed to work with this principles text.

Nitkin, Mindell Reiss, An Integrated Approach to Teaching Spreadsheet Skills

This paper suggests strategies for teaching spreadsheets skills with a focus on accounting and management.

Paetow, Holher (1998), [link http://www.economicsnetwork.ac.uk/cheer/ch12_1/ch12_1p02.htm 'Long-Run Dynamic Market Equilibrium Simulation through the Use of Spreadsheets," Computers in Higher Education Economics Review (CHEER), 12:1.

Presents a dynamic microeconomic model with free entry and competition between firms.

Thiriez, H. (2001), Improved OR Education Through the Use of Spreadsheet Models, European Journal of Operational Research, 135: pp. 461—476.

This article argues that spreadsheets are an ideal platform for teaching operations research.

Wabash College, Economics with Microsoft Excel

Contains a large number of Excel exercises for a number of economics courses.
Walbert, Mark, Workbooks for intermediate microeconomics
Contains a number of pre-programmed Excel files on a variety of microeconomics applications.
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Mathematics

Beare, R. (1993), How spreadsheets can aid a variety of mathematical learning activities from primary to tertiary level. Technology in Mathematics Teaching: A Bridge Between Teaching and Learning, B. Jaworski. Birmingham, U.K.: 117—124.

Reviews a number of ways spreadsheets can help teach mathematics at all levels of the curriculum.

Erich Neuwirth, E. and Arganbright, D (2004), The Active Modeler - Mathematical Modeling with Microsoft Excel, Brooks/Cole.

Discusses ways students can be taught to model phenomena using Excel.

Smith, Robert S. (1992), Spreadsheets as a Mathematical Tool, Journal on Excellence in College Teaching, pp. 131-48.

Argues that spreadsheets can enhance interest in mathematics coursework.

Mymathspace Excel resources

Provides examples of teaching mathematics using Excel.

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Physical sciences

Lim, K. (2003). Using spreadsheets in chemical education to avoid symbolic mathematics, Newsletter: Using Computers in Chemical Education, Spring.
This article argues that spreadsheets can help teach concepts in chemistry without formal mathematics.

Webb, Linda (1993) "Spreadsheets in Physics Teaching," Physics Education 28, pp. 77-82.

This article describes some Excel features that can be used in teaching college physics
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Related SERC Modules

Spreadsheets Across the Curriculum provides a number of ready-to-use tutorials with embedded gradable exercises to help students master critical spreadsheet skills. Compiled by Len Vacher at University of South Florida, Tampa.

The What is Excel? page of Mathematics and Statistical Models. This site contains examples and links to understanding the basics of Excel. The site addresses solving relevant equation(s) of a system or characterizing a system based upon its statistical parameters. Compiled by Bob MacKay, Clark College.

Inventing and Testing Models uses Model-Eliciting Activities which are posed as open-ended problems that are designed to challenge students to build models in order to solve complex, real-world problems. Compiled by Joan Garfield, Robert delMas and Andrew Zieffler of the University of Minnesota.

Teaching with Models help students understand the relationships between data and real-world processes. Compiled by Bob MacKay at Clark College.

Teaching Quantitative Reasoning with the News describes how one can use media articles as the main content for a course focused on honing students' ability to critically think about and analyze quantitative information. Compiled by Stuart Boersma, Central Washington University.

Teaching with Data helps faculty find and integrate real data sets into their classes. Compiled by Robert MacKay, Clark College.

Jigsaws are an option when you have several related data sets you would like students to explore. In a jigsaw, each student develops some expertise with one data set, then teaches a few classmates about it (and learns about related data sets from those classmates). Compiled by Barbara Tewksbury, Hamilton College.

Classroom experiments are activities where any number of students work in groups on carefully designed guided inquiry questions. Compiled by Sheryl Ball, Virginia Tech, with assistance from Tisha Emerson, Jennifer Lewis, and J. Todd Swarthout.

Teaching with Data Simulations allows students to visualize probability distributions, which in turn can make the processes associated with probability more concrete. Compiled by Danielle Dupuis, University of Minnesota - Twin Cities.

Teaching with Simulations uses a model of behavior to gain a better understanding of that behavior. Compiled by Betty Blecha, San Francisco State University and refined and enhanced by Mark McBride, Teresa Riley, Katherine Rowell, KimMarie McGoldrick, Mark Maier, and Scott Simkins.

Quantitative Writing engages students with numbers by asking them to analyze and use quantitative data in written reports and arguments. Compiled by John C. Bean, Seattle University.

Assessing learning provides educators with a better understanding of what students are learning and engages students more deeply in the process of learning content. Compiled by William Slattery at Departments of Geological Sciences and Teacher Education, Wright State University, Dayton, Ohio.

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