Even highly urban environments are settings for outdoor learning of local biodiversity, for they contain easily accessible street tree diversity that students walk pass daily. This study uses pre/post assessments and a tree observation curriculum grounded in scientific observation practice to understand the everyday and scientific tree observation…

This paper reports on progress in the development of a teaching module on machine learning with decision trees for secondary-school students, in which students use survey data about media use to predict who plays online games frequently. This context is familiar to students and provides a link between school and everyday experience. In this…

Mobile geospatial technologies enable high school students to engage in authentic scientific data collection and analysis that promote spatial-thinking and reasoning skills, as well as problem-solving in a school's local environment. We developed and implemented an Ecological Services investigation aligned to the Next Generation Science Standards…

In this study, classifications were made from the data obtained from the Health-Related Physical Fitness Report cards and BMIs of students through data mining methods, artificial neural networks, and decision trees models. Then the classification performances of both models were compared. The body weight and height measurements of the students in…

Detecting wheel-spinning behaviors of students who interact with an Intelligent Tutoring System (ITS) is important for generating pertinent and effective feedback and developing more enriching learning experiences. This analysis compares decision tree and bagged tree models of student productive persistence (i.e., mastering a skill) using the…

In educational and psychological research, it is common to use latent factors to represent constructs and then to examine covariate effects on these latent factors. Using empirical data, this study applied three approaches to covariate effects on latent factors: the multiple-indicator multiple-cause (MIMIC) approach, multiple group confirmatory…

A wealth of evidence shows that exposure to the natural environment and nature-based learning can benefit children's physical, mental, social, and emotional health. Despite this, children are spending less time in nature and nature-based learning remains an underutilised pedagogical tool. Several barriers are frequently reported by teachers,…

The purpose of this study is to compare decision trees obtained by data mining algorithms used in various areas in recent years according to different criteria. In the study, similar and different aspects of the decision trees obtained by different methods for classifying the students as successful and unsuccessful in terms of science literacy…

This study aims to compare the performances of the artificial neural network, decision trees and discriminant analysis methods to classify student achievement. The study uses multilayer perceptron model to form the artificial neural network model, chi-square automatic interaction detection (CHAID) algorithm to apply the decision trees method and…

Statistical modeling continues to gain prominence in the secondary curriculum, and recent recommendations to emphasize data science and computational thinking may soon position algorithmic models into the school curriculum. Many teachers' preparation for and experiences teaching statistical modeling have focused on probabilistic models.…

The purpose of this work is to identify contextual variables that help to explain the occupational aspirations of Spanish 15-year-old students. This is done by performing a secondary analysis of the PISA2018 test. Data have been analysed using decision trees introducing the students' expected occupational status as a dependent variable (DV), and…

The purpose of this research was to determine classification accuracy of the factors affecting the success of students' reading skills based on PISA 2018 data by using Artificial Neural Networks, Decision Trees, K-Nearest Neighbor, and Naive Bayes data mining classification methods and to examine the general characteristics of success groups. In…

This study examines modelling with machine learning. In the context of a yearlong data science course, the study explores how upper secondary students apply machine learning with Jupyter Notebooks and document the modelling process as a computational essay incorporating the different steps of the CRISP-DM cycle. The students' work is based on a…

Considering the critical need to support students' mental health and wellbeing, this article outlines a standards-based approach that integrates flourishing within a high school English/Language Arts classroom and supports clinical practice and professional development in a professional development school (PDS). Using the book, "The Bean…

This article reports on a short film being made for the Edge Foundation by the author. It records the innovative approach to learning taken by two comprehensive schools serving areas of high deprivation. Work in these schools integrates knowledge and skills, and offers a context in which all students, whatever their perceived 'ability', make…