A STEM education program entitled "Come rain or shine" implemented in a primary rural school in southern Greece as part of the "Diffusion of STEM (DI-STEM)" project and the results of its implementation are presented in this paper. The educational program deepened in weather education and intended to develop eight scientific…

When learning about scientific phenomena, students are expected to "mechanistically" explain how underlying interactions produce the observable phenomenon and "conceptually" connect the observed phenomenon to canonical scientific knowledge. This paper investigates how the integration of the complementary processes of designing…

Increasingly, learning in science and mathematics is considered in terms of induction into the multimodal language practices of the disciplinary community. A strong strand of research in this tradition has involved students being challenged to invent multimodal language forms, and their ideas refined through structured guidance. Often, however,…

Purpose: Drawing from the equitable education fund (EEF) launching 6Qs innovation in the teacher school quality program (TSQP) for small and medium schools, this research aims to analyze the effect size of the ordinary national educational test (O-NET) scores between TSQP schools that implement 6Qs innovation and non-TSQP schools and explain the…

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…

This article is a presentation of a three-day sequence of lessons that engaged fifth-grade students in an exploration following the activities of scientists. From asking questions and analyzing data, to engaging in scientific modeling, to defending their theories to the scientific (classroom) community, these fifth graders were mirroring how…

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…

The increasing use of educational technologies in classrooms is producing vast amounts of process data that capture rich information about learning as it unfolds. The field of educational data mining has made great progress in using log data to build models that improve instruction and advance the science of learning. Thus far, however, the…

Research in computer-based learning environments has long recognized the vital role of adaptivity in promoting effective, individualized learning among students. Adaptive scaffolding capabilities are particularly important in open-ended learning environments, which provide students with opportunities for solving authentic and complex problems, and…

This paper focuses on one Grade 5 class (9 females; 9 males) who worked in student-pairs to view five digital learning object (DLO) lessons created by the authors and meant to introduce students to the nature of models, the particle nature of matter, and physical change. Specifically, the paper focuses on whether DLO design elements could assist…

This applied dissertation was designed to provide perceptual teacher data as well as summative testing data to educational leaders concerning the effects of implementing Investigations in Number, Data, and Space® (Investigations) in three Title I elementary school settings, two Title I schools, and one non-Title I school. Data collected during…

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…

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…

The purposes of this research are: (1) description of reading skill the students who join in CIRC learning model, Jigsaw learning model, and STAD learning model; (2) finding out the effective of learning model cooperative toward a reading comprehensions between the students who have high language logic and low language logic; and (3) finding out…

This longitudinal study of 78 Canadian English-speaking students examined the applicability of the stability, cumulative, and compensatory models in reading comprehension development. Archival government-mandated assessments of reading comprehension at Grades 3, 6, and 10, and the Canadian Test of Basic Skills measure of reading comprehension…