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Ferguson, Joseph Paul; Tytler, Russell; White, Peta – International Journal of Science Education, 2022
Reporting on a Grade 4 teaching and learning sequence, we highlight foundational constructs of measurement and data modelling which are fundamental to competence development in both science and mathematics. The sequence involved students generating and representing measures of their teacher's arm-span, with a focus on the invention and refinement…
Descriptors: Aesthetics, Data Analysis, Educational Philosophy, Teaching Methods
Cheng, Kun-Hung; Hou, Huei-Tse – Technology, Pedagogy and Education, 2015
Previous research regarding peer assessment has investigated the relationships between peer feedback and learners' performance. However, few studies investigate in-depth learning processes during technology-assisted peer assessment activities, particularly from affective, cognitive, and metacognitive perspectives. This study conducts a series of…
Descriptors: Behavior Patterns, Student Behavior, Metacognition, Peer Evaluation
Hsieh, Ya-Hui; Lin, Yi-Chun; Hou, Huei-Tse – Educational Technology & Society, 2015
Unlike most research, which has primarily examined the players' interest in or attitude toward game-based learning through questionnaires, the purpose of this empirical study is to explore students' engagement patterns by qualitative observation and sequential analysis to visualize and better understand their game-based learning process. We…
Descriptors: Elementary School Students, Learner Engagement, Educational Games, Teaching Methods
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection

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