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Erik Eliassen; Ragnhild Eek Brandlistuen; Mari Vaage Wang – European Early Childhood Education Research Journal, 2024
Many studies have linked quality in early childhood education and care [ECEC] to school performance, but the mechanisms of how ECEC process quality affects children in ways that lead to improved school performance is unclear. In this study on 7431 children in Norway, we test the hypothesis that the relation between process quality in ECEC and…
Descriptors: Early Childhood Education, Academic Achievement, Foreign Countries, Interpersonal Competence
Gabrielle Oslington; Joanne Mulligan; Penny Van Bergen – Mathematics Education Research Journal, 2024
In this exploratory descriptive study, changes in one cohort's responses to an authentic statistical investigation at the commencement of years 3 and 4 were analysed. Forty-four students made predictions by interpreting a data table of historical monthly temperatures, represented these data and explained their reasoning. An Awareness of…
Descriptors: Mathematics Instruction, Mathematical Logic, Tables (Data), Prediction
Oslington, Gabrielle Ruth; Mulligan, Joanne; Van Bergen, Penny – Mathematics Education Research Group of Australasia, 2021
This longitudinal study aimed to determine changes in students' predictive reasoning across one year. Forty-four Australian students predicted future temperatures from a table of maximum monthly temperatures, explained their predictive strategies, and represented the data at two time points: Grade 3 and 4. Responses were analysed using a…
Descriptors: Foreign Countries, Thinking Skills, Prediction, Grade 3
Kazak, Sibel; Pratt, Dave; Gökce, Rukiye – ZDM: The International Journal on Mathematics Education, 2018
We explore 11-12-year-old students' emerging ideas of models and modelling as they engage in a data-modelling task involving inquiry based on data obtained from an experiment. We report on a design-based study in which students identified what and how to measure, decided how to structure and represent data, and made inferences and predictions…
Descriptors: Data, Models, Grade 6, Mathematics Instruction
Wright, Suzie; Watson, Jane; Smith, Caroline; Fitzallen, Noleine – Teaching Science, 2021
Life would not be possible without plants. Plants supply food to many organisms (including people), produce oxygen, absorb carbon dioxide from the air, provide products for human use, and homes for many other living things. It is not surprising, therefore, that plant growth is a familiar topic in the primary school science curriculum. This paper…
Descriptors: Science Instruction, Plants (Botany), Grade 6, STEM Education
Fancsali, Stephen E.; Li, Hao; Sandbothe, Michael; Ritter, Steven – International Educational Data Mining Society, 2021
Recent work describes methods for systematic, data-driven improvement to instructional content and calls for diverse teams of learning engineers to implement and evaluate such improvements. Focusing on an approach called "design-loop adaptivity," we consider the problem of how developers might use data to target or prioritize particular…
Descriptors: Instructional Development, Instructional Improvement, Data Use, Educational Technology
Bush, Sarah B.; Albanese, Judith; Karp, Karen S. – Mathematics Teaching in the Middle School, 2016
Historically, some baby names have been more popular during a specific time span, whereas other names are considered timeless. The Internet article, "How to Tell Someone's Age When All You Know Is Her Name" (Silver and McCann 2014), describes the phenomenon of the rise and fall of name popularity, which served as a catalyst for the…
Descriptors: Mathematics Instruction, Grade 6, Prediction, Data Collection
Bosch, Nigel – Journal of Educational Data Mining, 2021
Automatic machine learning (AutoML) methods automate the time-consuming, feature-engineering process so that researchers produce accurate student models more quickly and easily. In this paper, we compare two AutoML feature engineering methods in the context of the National Assessment of Educational Progress (NAEP) data mining competition. The…
Descriptors: Accuracy, Learning Analytics, Models, National Competency Tests
Zhang, Xiuyuan; Patel, Priyank; Ewing, Maureen – College Board, 2015
Historically, AP Potential™ correlations and expectancy tables have been based on 10th-and 11th-grade PSAT/NMSQT® examinees and 11th-and 12th-grade AP® examinees for all subjects (Zhang, Patel, & Ewing,2014; Ewing, Camara, & Millsap, 2006; Camara & Millsap, 1998). However, a large number of students take AP European History and AP…
Descriptors: Grade 4, Scores, Prediction, European History
Rønneberg, Vibeke; Torrance, Mark – Reading and Writing: An Interdisciplinary Journal, 2019
Spelling accuracy and time course was investigated in a sample of 100 Norwegian 6th grade students completing a standardized spelling-to-dictation task. Students responded by keyboard with accurate recordings of response-onset latency (RT) and inter-keypress interval (IKI). We determined effects of a number of child-level cognitive ability…
Descriptors: Spelling, Grade 6, Nonverbal Ability, Short Term Memory
Hourigan, Mairéad; Leavy, Aisling – Teaching Statistics: An International Journal for Teachers, 2016
As part of Japanese Lesson study research focusing on "comparing and describing likelihoods", fifth grade elementary students used real-world data in decision-making. Sporting statistics facilitated opportunities for informal inference, where data were used to make and justify predictions.
Descriptors: Foreign Countries, Elementary School Students, Grade 5, Statistics
Olsen, Jennifer K.; Aleven, Vincent; Rummel, Nikol – Grantee Submission, 2015
Student models for adaptive systems may not model collaborative learning optimally. Past research has either focused on modeling individual learning or for collaboration, has focused on group dynamics or group processes without predicting learning. In the current paper, we adjust the Additive Factors Model (AFM), a standard logistic regression…
Descriptors: Educational Environment, Predictive Measurement, Predictor Variables, Cooperative Learning
Olsen, Jennifer K.; Aleven, Vincent; Rummel, Nikol – International Educational Data Mining Society, 2015
Student models for adaptive systems may not model collaborative learning optimally. Past research has either focused on modeling individual learning or for collaboration, has focused on group dynamics or group processes without predicting learning. In the current paper, we adjust the Additive Factors Model (AFM), a standard logistic regression…
Descriptors: Educational Environment, Predictive Measurement, Predictor Variables, Cooperative Learning
English, Lyn; Watson, Jane – Mathematics Education Research Group of Australasia, 2014
Students explored variation and expectation in a probability activity at the end of the first year of a 3-year longitudinal study across grades 4-6. The activity involved experiments in tossing coins both manually and with simulation using the graphing software, "TinkerPlots." Initial responses indicated that the students were aware of…
Descriptors: Foreign Countries, Elementary School Mathematics, Elementary School Students, Grade 4
Jeffrey Steven Chenier – ProQuest LLC, 2012
Federal and state initiatives (No Child Left Behind, 2001) require schools and districts to set high standards for student growth and achievement. Currently, student growth and progress are measured in Louisiana via statewide achievement tests. In 4th and 8th grades these assessments are considered to be 'high-stakes', as promotion and retention…
Descriptors: Educational Legislation, Federal Legislation, Data Use, Academic Achievement
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