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Dvir, Michal; Ben-Zvi, Dani – Instructional Science: An International Journal of the Learning Sciences, 2023
Estimating and accounting for statistical uncertainty have become essential in today's information age, and crucial for cultivating a sound decision making citizenry. Engaging with statistical uncertainty early on can support the gradual development of uncertainty-related considerations that are often challenging to foster at any age. Statistical…
Descriptors: Learning Processes, Computation, Numeracy, Attitudes
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Samuele Maccioni; Cristiano Ghiringhelli; Edoardo Datteri – Learning Organization, 2024
Purpose: The purpose of this paper is to explore the phenomenon of organizational unlearning with a focus on challenging path dependence and its implications on the organizational change field. By generating a taxonomy of unlearning definitions and examining the dimensions, actors and processes involved, the authors aim to offer a holistic…
Descriptors: Organizational Change, Organizational Learning, Taxonomy, Outcome Measures