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Kirkup, Les; Frenkel, Bob – Physics Education, 2020
When the relationship between two physical variables, such as voltage and current, can be expressed as y = bx where b is a constant. b may be estimated by least squares, or by averaging the values of b obtained for each x-y data pair. We show for data gathered in an experiment, as well as through Monte Carlo simulation and mathematical analysis,…
Descriptors: Comparative Analysis, Least Squares Statistics, Monte Carlo Methods, Physics
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Chng, J. J. Kenneth; Patuwo, Michael Yudistira – Journal of Chemical Education, 2021
We described and ran a lesson plan for a build-your-own visible-range spectrophotometer undergraduate project as inspired by the research of Bougot-Robin, Imperial College London. Students were required to improve a basic Raspberry Pi spectrophotometer design and evaluate their improvements. Students learned firsthand how to manage instrumental…
Descriptors: Lesson Plans, Chemistry, Science Instruction, Spectroscopy
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Sideridis, Georgios D.; Tsaousis, Ioannis; Alamri, Abeer A. – Educational and Psychological Measurement, 2020
The main thesis of the present study is to use the Bayesian structural equation modeling (BSEM) methodology of establishing approximate measurement invariance (A-MI) using data from a national examination in Saudi Arabia as an alternative to not meeting strong invariance criteria. Instead, we illustrate how to account for the absence of…
Descriptors: Bayesian Statistics, Structural Equation Models, Foreign Countries, Error of Measurement
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Ryoo, Ji Hoon; Tai, Robert H.; Skeeles-Worley, Angela D. – Research in Science Education, 2020
In longitudinal studies, measurement invariance is required to conduct substantive comparisons over time or across groups. In this study, we examined measurement invariance on a recently developed instrument capturing student preferences for seven instructional strategies related to science learning and career interest. We have labeled these seven…
Descriptors: Guidelines, Longitudinal Studies, Comparative Analysis, Error of Measurement