Research is a process of systematic inquiry that entails collection of data; documentation of critical information; and analysis and interpretation of that data/information, in accordance with suitable methodologies set by specific professional fields and academic disciplines. Show
Research is conducted to...
If you would like further examples of specific ways different schools at Hampshire think about research, see: School Definitions of Research » What is "research" that needs to be reviewed and approved by the Institutional Review Board at Hampshire before proceeding? In reviewing such research, the IRB is concerned with the methodology of data collection in the "field" (e.g. collection, experimentation, interview, participant observation, etc.) and the use of the data. The broader validity of the hypotheses or research questions, and the quality of inferences that may result (unless, of course, the research methodologies severely compromise the data collection and data usage directly), is not something they will be evaluating. What if I am using information that is already available?If you are doing research that is limited to secondary analysis of data, records, or specimens that are either publicly available, de-identified, or otherwise impossible to be linked to personal identities, you may still need IRB approval to do your project. Sometimes a data use agreement between the researcher and the data custodian may still be required to verify that the researcher will not have access to identifying codes. This "de-linking" of data from personal identifiers allows the IRB to make this determination. Regardless, you should submit an IRB proposal so the IRB can determine whether your project needs IRB review, and if so, the type of review required. For specifics of what research should be reviewed by the IRB and the category of review required, see the flow chart and examples provided. Author: Victor Piercey, Ferris State University In our increasingly data-rich information age, people need the ability to critically read and construct meaning from numerical information. From public discussions concerning scientific matters such as climate change, to interpreting research evidence assessing the performance of a business, there is a need to not only understand the meaning behind the numbers but to critically think about the interpretation of them. This ability to interpret numbers, make judgments from data, and make arguments based on numerical evidence are skills that are needed for democratic participation in the 21st Century as well as for professionals in all manner of disciplines. This ability, sometimes called “numeracy,” or “quantitative literacy,” is a skill that must be specifically addressed in curriculum so that today’s college graduates are comfortable working with, understanding, and making arguments based on numbers. The Association of American Colleges & Universities (AAC&U) describes quantitative literacy as one of their essential outcomes. According to the AAC&U, quantitative literacy is much more than just knowing how to make computations. The emphasis is on solving real-world problems by use of numerical information. It includes comfort and skill in interpreting data, recognizing when numerical manipulation is useful, being competent to make computations when needed, using numbers to solve problems, and the ability to present information to others that involves numerical data (see instructional resource 1) Numerical information is everywhere, including in those fields of study we might not typically think of as being mathematical (see the plethora of data in the Association of Religion Data Archives for instance). Consequently, quantitative literacy is something that should be addressed in a wide range of disciplines. See, e.g. (8) and (9). The National Numeracy Network (instructional resource 7) is an organization dedicated to spreading quantitative literacy across disciplines and publishes its own journal,Numeracy. Beyond ensuring that students in a particular discipline have numerical skills sufficient to accomplish the tasks they need to in their field, quantitative literacy broadly applies to an individual’s ability to use numbers in any situation from personal to professional. Quantitative literacy, then, is an essential quality of an educated person and is a skill needed to manage one’s personal and professional life. It is important to avoid assuming that quantitative literacy and mathematics are the same. In Mathematics and Democracy: The Case for Quantitative Literacy, Steen wrote:
Steen’s reference to seeing the world through a mathematician’s eyes involve identifying patterns, asking questions about the interpretation of the data, questioning the methodology with which the data was collected, and being skeptical of arguments using data that appear to be one-sided. Paulos’ A Mathematician Reads the Newspaper (14) illustrates this disposition. Steen further broke quantitative literacy down into its “elements” listed here in no particular order since all are of equal importance (15, pgs. 8 – 9):
The difference between quantitative literacy and mathematics can be summarized by considering the following problem solving cycle for any problem that involves data. This should be viewed as a “cycle.” We start with observations and questions. We then determine what data will help us answer those questions and collect that data, then process that information with appropriate calculations. Finally, we interpret the results within the context of our original questions. Typically, the data and the interpretation will raise new questions, beginning another phase of the cycle. Most mathematics courses focuses only on the middle step in the cycle: “compute.” Quantitative literacy involves a focus on the entirety of the cycle, often allowing technology to handle the computations.Ensuring that students are quantitatively literate may require instructors in fields beyond mathematics to more fully consider what quantitative skills should be taught in their courses and design deliberate learning and assessment activities directed at quantitative skills. The cycle above could be mimicked with data in any field and any course in which numerical information is involved. Teaching This ObjectiveAs you are teaching this objective, it is important to appreciate the students’ need for understanding why this is valuable. The experience that many students have in mathematics is one in which they memorized what to them were meaningless, computational algorithms and tried to match the memorized algorithm with each problem they confronted. Don’t treat quantitative literacy as something to be addressed at the end of a unit “if time permits.” Instead, start with the numerical questions inherent in the content and use them as motivation to use quantitative skills to find answers. In addition, it is helpful for students if you are sensitive to the prevalence of math anxiety. There are exercises that can be used for students overwhelmed by a phobia of mathematics. See (17) and (18) for these resources. To begin preparing a lesson addressing quantitative literacy, identify realistic scenarios requiring numerical information. Look at your own life and your profession. Many of us pay taxes – how do we fill out a tax form? Once it is completed, how can we analyze the data on the form to make decisions for next year? Professionally, when do you use data? Here are some examples in different disciplines: Political Science/Law: What does it mean for a law to have a “disparate impact” on different populations (such as African Americans) and what does evidence of a disparate impact look like? Education: How does one analyze standardized test results? What is the difference between normative and positive data? How do you make decisions based on this information? History: What does the Russian census of 1897 tell you about Russian society on the eve of the revolution? How does that play into the way the Bolshevik regime evolved according to different scholars? Music: What are the ratios among the frequencies of various pitches in the 12-note scale? Mathematics: Why does our progressive tax code set marginal rates instead of average rates? What does this have to do with continuity? Health Professions: What are the advantages and disadvantages of asking a patient to rate their pain on a scale of 1 to 10? Business: How did Enron misuse its data and why did that lead to its collapse? What role did Arthur Andersen play in the misuse of data? Assumptions
Communication
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Collection Methods
Data vs Modeling: Not a Zero-Sum Game
If it fits within your instructional context, include numerical and quantitative matters in active learning activities. We want our students to appreciate and develop a disposition for using quantitative information, so embedding numerical work in our active learning activities and case studies has the potential make progress toward this goal. Within the mathematical community, Yoshinobu and Jones (19) argue that the benefits of active learning outweigh the costs of content coverage, while Kohen and Laursen (12) document the benefits of active learning in a systematic study. Finally, consider the appropriate type of technology for your learning goals and your students’ abilities. Graphing calculators are powerful but may not be used by those in a particular profession. Alternatively, spreadsheets are commonplace and useful both professionally and personally. See instructional resource 6 below for best practices in using spreadsheets. Assessing This Learning ObjectiveThe Quantitative Literacy and Reasoning Assessment (10) is a scientifically constructed instrument used for assessment purposes. This assessment is a standardized multiple choice test with 20 items as well as demographic questions. The instrument includes benchmarks that are disaggregated for different types of institutions. There is also a “promptless” quantitative literacy habits of mind assessment that involves reading a carefully selected news article (4). Students respond to questions that don’t direct them to the data in the article (hence “promptless”), and the response is measured by how much the student refers to the data on their own. Beyond standardized tests, the AAC&U promotes “grounding assessment in authentic artifacts of student work” evaluated using the VALUE rubric (instructional resource 1) to assess student progress (6). One way to collect those artifacts is to have students deposit them into an online portfolio that can be evaluated by whoever is appropriate at your institution (7). This is particularly useful for assignments that involve quantitative literacy in classes outside of the traditional general education coursework. This could also include work done in capstone courses, internships, or other types of “signature work” completed at the end of a program (2). What is important is that following the assessment, we “close the loop” by discussing the findings and using the results to improve our courses. (1) Resources
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What do you call the process of collecting analyzing and interpreting information?A survey is the process of collecting, analysing and interpreting data from many individuals. It aims to determine insights about a group of people. A survey goes much deeper than a questionnaire and often involves more than one form of data collection.
What is the systematic process of collecting and analyzing information to increase our understanding of the phenomena under study?Research as it was defined by Leedy and Ormond (2010) it is the systematic process of collecting and analyzing information to increase our understanding of the phenomenon under study.
Is the process of interpreting the information or data?Data interpretation refers to the process of using diverse analytical methods to review data and arrive at relevant conclusions. The interpretation of data helps researchers to categorize, manipulate, and summarize the information in order to answer critical questions.
What do we call a person who collects organizes analyzes and interprets a data?A data scientist is a professional responsible for collecting, analyzing and interpreting extremely large amounts of data.
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