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Garcia Moreno-Esteva, Enrique; Kervinen, Anttoni; Hannula, Markku S.; Uitto, Anna – Education Sciences, 2020
In this article we discuss, as a proof of concept, how a network model can be used to analyse gaze tracking data coming from a preliminary experiment carried out in a biodiversity education research project. We discuss the network model, a simple directed graph, used to represent the gaze tracking data in a way that is meaningful for the study of…
Descriptors: Biology, Science Instruction, Biodiversity, Networks
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Siemsen, Hayo – Science & Education, 2011
Where does Finnish science education come from? Where will it go? The following outside view reflects on relations, which Finns consider "normal" (and thus unrecognizable in introspection) in science education. But what is "normal" in Finnish culture cannot be considered "normal" for science education in other…
Descriptors: Foreign Countries, Epistemology, Science Education, Comparative Analysis
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Loukomies, Anni; Juuti, Kalle; Lavonen, Jari – International Journal of Science Education, 2015
Pupils' interest has been one of the major concerns in science education research because it can be seen as a gateway to more personalised forms of interest and motivation. However, methods to investigate situational interest in science teaching and learning are not broadly examined. This study compares the pupils' observed situational interest…
Descriptors: Elementary School Students, Science Instruction, Teaching Methods, Student Interests
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Nieminen, Pasi; Savinainen, Antti; Viiri, Jouni – Physical Review Special Topics - Physics Education Research, 2010
This study investigates students' ability to interpret multiple representations consistently (i.e., representational consistency) in the context of the force concept. For this purpose we developed the Representational Variant of the Force Concept Inventory (R-FCI), which makes use of nine items from the 1995 version of the Force Concept Inventory…
Descriptors: Foreign Countries, Science Tests, Reliability, Validity
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Chow, Angela; Salmela-Aro, Katariina – International Journal of Behavioral Development, 2011
This study examined what kinds of groups can be identified according to students' task-values across four subject domains (languages, math and science, social sciences, practical subjects) and the related gender differences using a person-centered approach. Latent class analysis was applied to classify 638 students (mean age = 15) into four…
Descriptors: Females, Compulsory Education, Social Sciences, Gender Differences
Achieve, Inc., 2010
In response to concerns over the need for a scientifically literate workforce, increasing the STEM pipeline, and aging science standards documents, the scientific and science education communities are embarking on the development of a new conceptual framework for science, led by the National Research Council (NRC), and aligned next generation…
Descriptors: Science Instruction, Science Education, Academic Standards, National Standards
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Johnston, Jane; Ahtee, Maija – Teaching & Teacher Education: An International Journal of Research and Studies, 2006
This research explores and compares primary student teachers' attitudes, subject knowledge and pedagogical content knowledge (PCK) in physics in two institutions in England and Finland, using a practical physics activity and questionnaire. Teaching of physics activities was rated unpopular both in Finland and England, although English students…
Descriptors: Pedagogical Content Knowledge, Student Teacher Attitudes, Foreign Countries, Physics
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