Methods based on machine learning have become increasingly popular in many areas as they allow models to be fitted in a highly-data driven fashion and often show comparable or even increased performance in comparison to classical methods. However, in the area of educational sciences, the application of machine learning is still quite uncommon.…

Issue #50 of the Bank Street Occasional Paper Series, "Learning With Treescapes in Environmentally Endangered Times Learning with Treescapes in Environmentally Endangered Times," is intended to be hopeful. Articles in this issue contribute to the envisioning of new practices and to an architecture of knowledge to waymark a more…

The literature provides multiple measures of diversity along a single demographic dimension, but when it comes to studying the interaction of multiple diversity types (e.g. age, gender, and race), the field of useable measures diminishes. We present the use of decision trees as a machine learning technique to automatically identify the…

This article explores a narrative approach adopted by three Taiwanese children's books that feature old trees as storytellers and memory-keepers to address aspects of emotional and psychological adaptation when facing drastic life changes. Although these stories are told from the perspective of old trees, the nostalgic tone serves a specific…

Phylogenetic trees are important tools for teaching and understanding evolution, yet students struggle to read and interpret them correctly. In this study, we extend a study conducted by Catley and Novick (2008) by investigating depictions of evolutionary trees in US textbooks. We investigated 1197 diagrams from 11 German and 11 United States…

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…

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…

It is common in environmental education literature to read about 'transforming' mindsets; for example, moving from humanist to post-humanist viewpoints, or adopting Indigenous Knowledge perspectives. To illustrate how complicated such conceptual shifts are, both philosophically and pedagogically, the paper explores how we come to see and regard…

This study aims to investigate environmentally responsible and sustainable development of 56 pre-service teachers which relevant to framework of sustainable development goals. The qualitative data were collected and analyzed by summarizing general perspectives. The 9 concepts were found and reported. The ways to sustain environments and education…

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…

Contrary to the situation at primary, middle, and secondary school levels, university science courses provide students with very few opportunities to reflect upon the nature of science (NOS). The first goal of this study was to provide evidence that the co-construction of evolutionary trees, an important component of university biology education,…

We perform two approaches of machine learning, logistic regressions and decision trees, to predict student dropout at the Karlsruhe Institute of Technology (KIT). The models are computed on the basis of examination data, i.e. data available at all universities without the need of specific collection. Therefore, we propose a methodical approach…

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…