Once the decisionmakers and stakeholders have considered the types of questions an LDS can answer, the organization should assess what data it has and what it will need to answer the questions they deem most useful. Most agencies already have a large amount of data, especially if they are collecting and maintaining data on individual students. However, while more is not necessarily better, the data currently maintained may not be sufficient to answer questions stakeholders have determined are important. This section offers some data an education agency may need to achieve its goals.
Your data may be stored in a central data warehouse, or in many separate data stores. Likely source systems include the
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After taking an inventory of what data it has, cataloguing all current and planned data collections, and identifying where data items are housed (and which system is the authoritative source for each data element), an agency should determine if it should collect any additional data.
While the education community often focuses on student traits and learning outcomes, truly informative education research also requires context—the students' learning opportunities and learning climate. In addition to outcomes, therefore, data users should look at information on the inputs and processes that contribute directly and indirectly to student learning. For instance, in which programs does the student participate? Who are the student's teachers? What classroom strategies are used? Are there differences in student learning opportunities by race, sex, and/or socioeconomic status (e.g., representation in special education and non-college-preparatory tracks, teacher experience levels, resources, expectations)? What are the local financial and hiring practices?
Keep in mind that while individual data items about students and staff are extremely valuable in efforts to monitor and understand student experiences, deeper analysis will view certain data elements in concert (as "derived" data elements, indexes, or indicators) and track them longitudinally. Doing so allows data users to examine the relationships between various aspects of reality and illuminates the trends that occur over time, showing what educational inputs contribute to what kinds of results for which students. For instance, when evaluating the success of a particular program, researchers may look at more than the participating student performance on assessments. The relative effectiveness of a particular instructional strategy, or strategies, may also depend on context and input variables such as the background and preparation of the teachers implementing the program, how closely the program is implemented, and the characteristics of the students receiving the instruction. And a fair evaluation of the program will look at a host of discrete measures of success in addition to year-end summative test scores. Such holistic methodologies that combine a range of relevant data can generate powerful guidance and help educators more effectively meet individual student needs.
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When identifying new data for collection, overarching goals should be used as a framework for selecting new elements and education agencies should collect and store only those data that will benefit the enterprise. Elements that stakeholders think would be nice to have, but which do not lend themselves to achieving stated goals, should be avoided. In addition, the data collected should capture the appropriate level of detail. For instance, when collecting data on attendance, should you collect by day, by period, or by some other unit of time? If attendance by day is sufficient, an agency may not want to burden staff further (National Forum on Education Statistics 2009). Also, widely accepted standards and definitions should be followed so that the records are consistent and comparable to other agencies' data.
Table 4 presents many of the key types of data that may be contained in a P–12 LDS and used for longitudinal analyses, but it is not exhaustive. Appendix C offers sources of more detailed and exhaustive data. Ultimately, agencies should collect all other data required for state and federal reports, as well as other key data necessary to answer its stakeholders' questions.