Data Types
Qualitative and Quantitative Data:
Education schools research and analyze two main types of data: qualitative and quantitative. Scholars typically define their methodology by either of these categories or as a mixed method combining both. Qualitative data tells a story. Such data are non-numerical in nature. They also have a low level of measurability. Qualitative data can include language or opinions. For example, in education, classroom observations or interviews with parents of students regarding family history are qualitative. Quantitative data also tells a story but in a different way. Quantitative data are expressed numerically and possess a high degree of measurability. For instance, quantitative data includes test scores, class rank, and school student populations.
Nominal and Ordinal Data:
Qualitative data can be further subdivided into nominal and ordinal categories. The nominal category labels qualitative data without any inherent rank or order. This would include categorizing students in terms of nationality or gender as well nonbinary pronouns. Ordinal data does possess an innate sense of rank but needs to be converted numerically for quantitative analysis and hence are categorized as qualitative. For example, credit/no-credit grading, class rank, and level of educational attainment are ordinal data.
Discrete and Continuous Data:
Quantitative data is composed of two categories, including discrete and continuous. Discrete data can be measured and counted as finite values assigning to whole numbers or integers that cannot be decomposed into fractions or decimals. Examples are student attendance or number of in-service professional development days for faculty. Continuous data entails information that can be subdivided and assume a value within a range. Test-taking time or GPA are examples of continuous data.
Resources
VISUALIZATION
- ATLAS.tiATLAS.ti supports a wide range of data formats and offers functionalities like coding, annotation, and visualization, enabling researchers to uncover deep insights from textual, graphical, audio, and video data.
- ExcelMicrosoft software spreadsheet tool for data entry, analysis, and presentation.
- Qualtrics(Harvard Key required) Qualtrics is a web-based survey software that allows you to easily create surveys with customizable templates, integrated graphics, and statistical tools; collect, store, and download data in a variety of formats; and produce reports.
- TableauTableau is a data visualization tool that helps in transforming raw data into easily understandable and interactive visual formats.
COMPUTATION
- Express Scribe(Harvard Key required) Tool for transcription encouraged by the Harvard qualitative research support group.
- MATLABIterative analysis and design for creating scripts and combining code.
- MplusStatistical modeling tool for data analysis.
- NVivoNVivo is a qualitative data analysis (QDA) computer software package designed for researchers working with diverse data types such as interviews, social media, surveys, and articles.
- OpenRefineOpenRefine is an open-source tool for cleaning and transforming data. It is useful in handling messy data, allowing users to standardize and clean datasets.
- Python LibrariesThis library reference manual describes the standard library that is distributed with Python. It also describes some of the optional components that are commonly included in Python distributions.
- R PackagesR packages are extensions to the R programming language, consisting of a collection of functions, data, and compiled code, designed to add specific capabilities or perform specialized tasks. Hosted on repositories like CRAN (Comprehensive R Archive Network), these packages cover a wide range of statistical, graphical, and data manipulation functionalities.
- QDA MinerQDA Miner is designed to assist in the analysis of textual data such as interviews, open-ended responses, articles, and reports. It offers tools for coding, annotating, retrieving, and analyzing collections of documents and images.
- SASSAS (Statistical Analysis System) is a robust, enterprise-grade software suite developed by SAS Institute for advanced analytics, multivariate analysis, business intelligence, data management, and predictive analytics.
- SPSSSPSS (Statistical Package for the Social Sciences) offers a range of statistical analysis tools, along with data management and documentation capabilities. SPSS is particularly favored for its user-friendly interface, making complex data analyses more accessible to those without extensive statistical backgrounds, and is extensively used in research, market analysis, health research, and educational sectors.
- STATAData science software package typically used for statistics coursework.
OTHER: INSTRUCTION/ REFERENCES/ CITATIONS/ RESEARCH PROCEDURES
- APA Reference GuidelinesAPA guidelines on citations and references for academic writing.
- Digital Scholarship at HarvardDigital literacy, research support, and teaching support.
- EndnoteSoftware tool for bibliography building and citation.
- IRB and Ethics(Harvard Key required) Harvard resource for IRB approval when working with human subjects in research.
- RefWorksAn internet based reference manager for building bibliographies, formatting, and writing in-line citations (Write-N-Cite).
- ZoteroA research organization tool for references and citations.