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Agley, Jon; Tidd, David; Jun, Mikyoung; Eldridge, Lori; Xiao, Yunyu; Sussman, Steve; Jayawardene, Wasantha; Agley, Daniel; Gassman, Ruth; Dickinson, Stephanie L. – Educational and Psychological Measurement, 2021
Prospective longitudinal data collection is an important way for researchers and evaluators to assess change. In school-based settings, for low-risk and/or likely-beneficial interventions or surveys, data quality and ethical standards are both arguably stronger when using a waiver of parental consent--but doing so often requires the use of…
Descriptors: Data Analysis, Longitudinal Studies, Data Collection, Intervention
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Juho Kahila; Henriikka Vartiainen; Matti Tedre; Eetu Arkko; Anssi Lin; Nicolas Pope; Ilkka Jormanainen; Teemu Valtonen – Informatics in Education, 2024
The integration of artificial intelligence (AI) topics into K-12 school curricula is a relatively new but crucial challenge faced by education systems worldwide. Attempts to address this challenge are hindered by a serious lack of curriculum materials and tools to aid teachers in teaching AI. This article introduces the theoretical foundations and…
Descriptors: Personal Autonomy, Data, Children, Creativity
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Lee, Victor R.; Drake, Joel; Cain, Ryan; Thayne, Jeffrey – Cognition and Instruction, 2021
Given growing interest in K-12 data and data science education, new approaches are needed to help students develop robust understandings of and familiarity with data. The model of the "quantified self"--in which data about one's own activities are collected and made into objects of study--provides inspiration for one such approach. By…
Descriptors: Statistics Education, Familiarity, Self Concept, Prior Learning