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  2. Data-informed decision-making - Wikipedia

    en.wikipedia.org/wiki/Data-informed_decision-making

    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 ...

  3. Data-driven instruction - Wikipedia

    en.wikipedia.org/wiki/Data-driven_instruction

    Additional problems associated with perceptions of data driven instruction include the limitations of quantitative data to represent student learning, not considering the social and emotional needs or the context of the data when making instructional decisions, and a hyperfocus on the core areas of literacy and mathematics while ignoring the ...

  4. Data-driven model - Wikipedia

    en.wikipedia.org/wiki/Data-driven_model

    Data-driven models encompass a wide range of techniques and methodologies that aim to intelligently process and analyse large datasets. Examples include fuzzy logic, fuzzy and rough sets for handling uncertainty, [3] neural networks for approximating functions, [4] global optimization and evolutionary computing, [5] statistical learning theory, [6] and Bayesian methods. [7]

  5. Data-driven learning - Wikipedia

    en.wikipedia.org/wiki/Data-driven_learning

    Johns (1936 – 2009) pioneered data-driven learning and coined the term. It first appeared in an article, Should you be persuaded: Two examples of data-driven learning (1991). [ 1 ] His paper, From Printout to Handout, [ 2 ] is reprinted and discussed at length in Volume 2 of Hubbard's Computer-Assisted Language Learning . [ 3 ]

  6. Automated decision-making - Wikipedia

    en.wikipedia.org/wiki/Automated_decision-making

    Automated decision-making involves using data as input to be analyzed within a process, model, or algorithm or for learning and generating new models. [7] ADM systems may use and connect a wide range of data types and sources depending on the goals and contexts of the system, for example, sensor data for self-driving cars and robotics, identity data for security systems, demographic and ...

  7. Educational data mining - Wikipedia

    en.wikipedia.org/wiki/Educational_data_mining

    While the analysis of educational data is not itself a new practice, recent advances in educational technology, including the increase in computing power and the ability to log fine-grained data about students' use of a computer-based learning environment, have led to an increased interest in developing techniques for analyzing the large amounts of data generated in educational settings.

  8. P-20 longitudinal data systems - Wikipedia

    en.wikipedia.org/wiki/P-20_longitudinal_data_systems

    Data on students' success in college, including whether they enrolled in remedial courses; Data on whether K-12 students are prepared to succeed in college; A system of auditing data for quality, validity, and reliability; The ability to share data from preschool through post-secondary education data systems.

  9. Student voice - Wikipedia

    en.wikipedia.org/wiki/Student_voice

    Some education agencies engage students as staff in programs where they make decisions about grant making, school assessment, and other areas. [20] Students are also participating in decision-making by establishing and enforcing codes of conduct and in personal education decision-making, such as choosing classes and deciding whether to attend ...