The continuous development of Educational Data Mining (EDM) and Learning Analytics (LA) technologies has provided more effective technical support for accurate early warning and interventions for student academic performance. However, the existing body of research on EDM and LA needs more empirical studies that provide feedback interventions, and…

The purpose of this study was to analyze the activities in the Problem-Based Learning (PBL) methodology among high school students when solving problems related to the field of plane figures, both in extra-mathematical and intra-mathematical environments. The research was qualitative and constituted a case study. The technique used to select the…

Prospective longitudinal data collection is an important way for researchers and evaluators to assess change. In school-based settings, for low-risk and/or likely-beneficial interventions or surveys, data quality and ethical standards are both arguably stronger when using a waiver of parental consent--but doing so often requires the use of…

This paper addresses how students explore, construct, validate and use statistical models when facing situations designed from a socio-critical perspective. The case study used is a statistics lesson designed by a statistics teacher and a researcher. The lesson centers on nutritional information and was implemented in a 7th-grade classroom at a…

Our research aims to predict students' academic performance by considering the variables affecting academic performance in science courses using the deep learning method from machine learning algorithms and to determine the importance of independent variables affecting students' academic performance in science courses. 445 students from 5th, 6th,…

The pervasiveness of racism in the U.S. and its negative relations with key development outcomes has led researchers to uncover mediators, of which this article argues efficacy should be considered. Self-efficacy, one's belief in their capability to accomplish a task or goal, can be measured in multiple domains of functioning and contexts to…

In this study, we investigated how sixth and seventh grade students used CODAP to make sense of roller coaster data while engaged in Exploratory Data Analysis (EDA). Using instrumentation theory, we examined students' instrumentation approaches, as well as the types of instrumental orchestration utilized by teachers as they interacted with student…

Energy is a central concept across the sciences and an important goal of science education is to support all students so that they develop a full understanding of the energy concept. However, given the abstract and complex nature of the energy concept, only a few students develop an understanding so that they can use energy ideas to make sense of…

Well-designed digital games hold promise as effective learning environments. However, designing games that support both learning and engagement without disrupting flow is quite tricky. In addition to including various game design features (e.g., interactive problem solving, adaptive challenges, and player control of gameplay) to engage players,…

Adaptive Learning Technologies (ALT) and Learning Analytics (LA) are expected to contribute to the customisation and personalisation of pupil learning by continually calibrating and adjusting pupils' learning activities towards their skill and competence levels. The overall aim of the study presented in this paper was to obtain a comprehensive…

Statistical literacy is a skill that will be required by all students, but only limited insights exist into how it can be developed in middle schools. Research is required that identifies design principles and provides didactic materials for developing statistical literacy in actual middle school classrooms, meaning classrooms in which statistics…

Within the last decade, different educational data mining techniques, particularly quantitative methods such as clustering, and regression analysis are widely used to analyze the data from educational games. In this research, we implemented a quantitative data mining technique (clustering) to further investigate students' feedback. Students played…

Data reasoning and digital literacy skills, especially the ability to find, represent, and accurately interpret the relevant data, are critical in workplaces and lifetime experiences. Given the importance of developing data reasoning skills from learners' experiences, this article aims to describe teacher and student actions that contributed to…

Research has begun to show that certain schoolwide characteristics--such as student-centered learning environments, leadership, and safety--can be important for improving student outcomes. In keeping with these insights, school improvement efforts around the country are becoming less narrowly focused on the performance of individual students and…

Purpose: In an era of unprecedented student measurement and emphasis on data-driven educational decision making, the full potential for using data to target resources to students has yet to be realized. This study explores the utility of machine-learning techniques with large-scale administrative data to identify student dropout risk. Research…