Data-informed decision-making

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Data-informed decision-making (DIDM) gives reference to the collection and analysis of data to guide decisions that improve success. [1] Another form of this process is referred to as data-driven decision-making, "which is defined similarly as making decisions based on hard data as opposed to intuition, observation, or guesswork." [2] DIDM is used in education communities (where data is used with the goal of helping students and improving curricula) and is also used in other fields in which data is used to inform decisions. While "data based decision-making" is a more common term, "data-informed decision-making" is the preferred term, since decisions should not be based solely on quantitative data. [1] [3] Data-driven decision-making is commonly used in the context of business growth and entrepreneurship. [4] [5] Many educators have access to data system for analyzing student data. [6] These data systems present data to educators in an over-the-counter data format (embedding labels, supplemental documentation, and a help system, making key package/display and content decisions) to improve the success of educators' data-informed decision-making. [7] In business, fostering and actively supporting data-driven decision-making in their firm and among their colleagues may be one of the central responsibilities of CIOs (Chief Information Officers) or CDOs (Chief Data Officers). [8]

Assessment in higher education is a form of data-driven decision-making aimed at using evidence of what students learn to improve curriculum, student learning, and teaching. [9] Standardized tests, grades, and student work scored by rubrics are forms of student learning outcomes assessment. Formative assessments, specifically, allow educators to use the data from student performances more immediately in modifying teaching and learning strategies. There are numerous organizations aimed at promoting the assessment of student learning through DIDM including the National Institute for Learning Outcomes Assessment, the Association for the Assessment of Student Learning in Higher Education, and, to an extent, the Association of American Colleges and Universities.

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<span class="mw-page-title-main">Outcome-based education</span> Educational system based on the desired goals

Outcome-based education or outcomes-based education (OBE) is an educational theory that bases each part of an educational system around goals (outcomes). By the end of the educational experience, each student should have achieved the goal. There is no single specified style of teaching or assessment in OBE; instead, classes, opportunities, and assessments should all help students achieve the specified outcomes. The role of the faculty adapts into instructor, trainer, facilitator, and/or mentor based on the outcomes targeted.

<span class="mw-page-title-main">Standardized test</span> Test administered and scored in a predetermined, standard manner

A standardized test is a test that is administered and scored in a consistent, or "standard", manner. Standardized tests are designed in such a way that the questions and interpretations are consistent and are administered and scored in a predetermined, standard manner.

Educational assessment or educational evaluation is the systematic process of documenting and using empirical data on the knowledge, skill, attitudes, aptitude and beliefs to refine programs and improve student learning. Assessment data can be obtained from directly examining student work to assess the achievement of learning outcomes or can be based on data from which one can make inferences about learning. Assessment is often used interchangeably with test, but not limited to tests. Assessment can focus on the individual learner, the learning community, a course, an academic program, the institution, or the educational system as a whole. The word 'assessment' came into use in an educational context after the Second World War.

<span class="mw-page-title-main">No Child Left Behind Act</span> 2002 United States education reform law; repealed 2015

The No Child Left Behind Act of 2001 (NCLB) was a U.S. Act of Congress that reauthorized the Elementary and Secondary Education Act; it included Title I provisions applying to disadvantaged students. It supported standards-based education reform based on the premise that setting high standards and establishing measurable goals could improve individual outcomes in education. The Act required states to develop assessments in basic skills. To receive federal school funding, states had to give these assessments to all students at select grade levels.

Educational evaluation is the evaluation process of characterizing and appraising some aspect/s of an educational process.

Editing technology is the use of technology tools in general content areas in education in order to allow students to apply computer and technology skills to learning and problem-solving. Generally speaking, the curriculum drives the use of technology and not vice versa. Technology integration is defined as the use of technology to enhance and support the educational environment. Technology integration in the classroom can also support classroom instruction by creating opportunities for students to complete assignments on the computer rather than with normal pencil and paper. In a larger sense, technology integration can also refer to the use of an integration platform and application programming interface (API) in the management of a school, to integrate disparate SaaS applications, databases, and programs used by an educational institution so that their data can be shared in real-time across all systems on campus, thus supporting students' education by improving data quality and access for faculty and staff.

"Curriculum integration with the use of technology involves the infusion of technology as a tool to enhance the learning in a content area or multidisciplinary setting... Effective technology integration is achieved when students can select technology tools to help them obtain information on time, analyze and synthesize it, and present it professionally to an authentic audience. Technology should become an integral part of how the classroom functions—as accessible as all other classroom tools. The focus in each lesson or unit is the curriculum outcome, not the technology."

Formative assessment, formative evaluation, formative feedback, or assessment for learning, including diagnostic testing, is a range of formal and informal assessment procedures conducted by teachers during the learning process in order to modify teaching and learning activities to improve student attainment. The goal of a formative assessment is to monitor student learning to provide ongoing feedback that can help students identify their strengths and weaknesses and target areas that need work. It also helps faculty recognize where students are struggling and address problems immediately. It typically involves qualitative feedback for both student and teacher that focuses on the details of content and performance. It is commonly contrasted with summative assessment, which seeks to monitor educational outcomes, often for purposes of external accountability.

<span class="mw-page-title-main">Commission on the Future of Higher Education</span>

The formation of a Commission on the Future of Higher Education, also known as the Spellings Commission, was announced on September 19, 2005, by U.S. Secretary of Education Margaret Spellings. The nineteen-member commission was charged with recommending a national strategy for reforming post-secondary education, with a particular focus on how well colleges and universities are preparing students for the 21st-century workplace, as well as a secondary focus on how well high schools are preparing the students for post-secondary education. In the report, released on September 26, 2006, the Commission focuses on four key areas: access, affordability, the standards of quality in instruction, and the accountability of institutions of higher learning to their constituencies. After the report's publication, implementation of its recommendations was the responsibility of U.S. Under Secretary of Education, Sara Martinez Tucker.

A strategic technology plan is a specific type of strategy plan that lets an organization know where they are now and where they want to be some time in the future with regard to the technology and infrastructure in their organization. It often consists of the following sections.

<span class="mw-page-title-main">Evidence-based education</span> Paradigm of the education field

Evidence-based education (EBE) is the principle that education practices should be based on the best available scientific evidence, rather than tradition, personal judgement, or other influences. Evidence-based education is related to evidence-based teaching, evidence-based learning, and school effectiveness research. For example, research has shown that spaced repetition "leads to more robust memory formation than massed training does, which involves short or no intervals".

Value-added modeling is a method of teacher evaluation that measures the teacher's contribution in a given year by comparing the current test scores of their students to the scores of those same students in previous school years, as well as to the scores of other students in the same grade. In this manner, value-added modeling seeks to isolate the contribution, or value added, that each teacher provides in a given year, which can be compared to the performance measures of other teachers. VAMs are considered to be fairer than simply comparing student achievement scores or gain scores without considering potentially confounding context variables like past performance or income. It is also possible to use this approach to estimate the value added by the school principal or the school as a whole.

Teacher quality assessment commonly includes reviews of qualifications, tests of teacher knowledge, observations of practice, and measurements of student learning gains. Assessments of teacher quality are currently used for policymaking, employment and tenure decisions, teacher evaluations, merit pay awards, and as data to inform the professional growth of teachers.

<span class="mw-page-title-main">Open educational practices</span>

Open educational practices (OEP) are part of the broader open education landscape, including the openness movement in general. It is a term with multiple layers and dimensions and is often used interchangeably with open pedagogy or open practices. OEP represent teaching and learning techniques that draw upon open and participatory technologies and high-quality open educational resources (OER) in order to facilitate collaborative and flexible learning. Because OEP emerged from the study of OER, there is a strong connection between the two concepts. OEP, for example, often, but not always, involve the application of OER to the teaching and learning process. Open educational practices aim to take the focus beyond building further access to OER and consider how in practice, such resources support education and promote quality and innovation in teaching and learning. The focus in OEP is on reproduction/understanding, connecting information, application, competence, and responsibility rather than the availability of good resources. OEP is a broad concept which can be characterised by a range of collaborative pedagogical practices that include the use, reuse, and creation of OER and that often employ social and participatory technologies for interaction, peer-learning, knowledge creation and sharing, empowerment of learners, and open sharing of teaching practices.

<span class="mw-page-title-main">Wisconsin Center for Education Research</span>

Wisconsin Center for Education Research (WCER), located in Madison, Wisconsin, is an education research center founded in 1964 as a branch of the School of Education at the University of Wisconsin–Madison. WCER currently has extramural funding of approximately $40 million, and is home to over 500 faculty, staff, graduate and undergraduate students who are engaged in more than 100 research projects that investigate a variety of topics in education.

Educator effectiveness is a United States K-12 school system education policy initiative that measures the quality of an educator performance in terms of improving student learning. It describes a variety of methods, such as observations, student assessments, student work samples and examples of teacher work, that education leaders use to determine the effectiveness of a K-12 educator.

Data based decision making or data driven decision making refers to educator’s ongoing process of collecting and analyzing different types of data, including demographic, student achievement test, satisfaction, process data to guide decisions towards improvement of educational process. DDDM becomes more important in education since federal and state test-based accountability policies. No Child Left Behind Act opens broader opportunities and incentives in using data by educational organizations by requiring schools and districts to analyze additional components of data, as well as pressing them to increase student test scores. Information makes schools accountable for year by year improvement various student groups. DDDM helps to recognize the problem and who is affected by the problem.

Data-driven instruction is an educational approach that relies on information to inform teaching and learning. The idea refers to a method teachers use to improve instruction by looking at the information they have about their students. It takes place within the classroom, compared to data-driven decision making. Data-driven instruction works on two levels. One, it provides teachers the ability to be more responsive to students’ needs, and two, it allows students to be in charge of their own learning. Data-driven instruction can be understood through examination of its history, how it is used in the classroom, its attributes, and examples from teachers using this process.

Assessment in higher education was a reform movement that emerged in the United States in the early 2000s to spur improved learning in higher education through regular and systematic measurement. The campaign was a higher education corollary to the standardized testing required in K-12 schools by the No Child Left Behind Act. By the latter 2010s the bureaucratic demands of assessment advocates were being reconsidered in higher education even by some of those who had played a major part in promoting them.

<span class="mw-page-title-main">Large-scale learning assessments</span>

Large-scale learning assessments (LSLAs) is defined as a form of national or cross-national standardized testing that provide a snapshot of learning achievement for a group of learners in a given year and in a limited number of learning domains.

<span class="mw-page-title-main">Learning engineering</span> Interdisciplinary academic field

Learning Engineering is the systematic application of evidence-based principles and methods from educational technology and the learning sciences to create engaging and effective learning experiences, support the difficulties and challenges of learners as they learn, and come to better understand learners and learning. It emphasizes the use of a human-centered design approach in conjunction with analyses of rich data sets to iteratively develop and improve those designs to address specific learning needs, opportunities, and problems, often with the help of technology. Working with subject-matter and other experts, the Learning Engineer deftly combines knowledge, tools, and techniques from a variety of technical, pedagogical, empirical, and design-based disciplines to create effective and engaging learning experiences and environments and to evaluate the resulting outcomes. While doing so, the Learning Engineer strives to generate processes and theories that afford generalization of best practices, along with new tools and infrastructures that empower others to create their own learning designs based on those best practices.

References

  1. 1 2 U.S. Department of Education Office of Planning, Evaluation and Policy Development (2009). Implementing data-informed decision making in schools: Teacher access, supports and use. United States Department of Education (ERIC Document Reproduction Service No. ED504191)
  2. "Data-Driven Decision Making: 5 Essentials". Ohio University. 2019-12-02. Retrieved 2022-02-28.
  3. Knapp, M. S., Swinnerton, J. A., Copland, M. A., & Monpas-Hubar, J. (2006). Data-informed leadership in education. Seattle, WA: Center for the Study of Teaching and Policy.
  4. "Data-Driven Decision Making: A Primer for Beginners". Northeastern University Graduate Programs. 2019-08-22. Retrieved 2022-02-28.
  5. "Three Examples of How Companies Make Data-Driven Decisions". Utica University. 2019-11-25. Retrieved 2022-02-28.
  6. Aarons, D. (2009). Report finds states on course to build pupil-data systems. Education Week, 29(13), 6.
  7. Rankin, J. (2013, March 28). How data Systems & reports can either fight or propagate the data analysis error epidemic, and how educator leaders can help. Archived 2019-03-26 at the Wayback Machine Presentation conducted from Technology Information Center for Administrative Leadership (TICAL) School Leadership Summit.
  8. Delort P. 2012. ICCP Technology Foresight Forum - "Harnessing data as a new source of growth: Big data analytics and policies" . OECD, 2012
  9. Flaherty, Colleen. "Large-Scale Assessment Without Standardized Tests". Inside HigherEd. Retrieved 24 February 2017.