Mendeley Data Showcase

Pedagogical Approaches for Developing Critical Thinking in Science Education (1987-2025): A Bibliometric and Thematic Analysis

363 The dataset consists of processed public dysgraphia data, expanded into 260 sensor-based features, and incorporates deep learning features for binary (DB2) and multi-class (DB1) classification. Deep learning features were extracted using (a) DenseNet-201, (b) ResNet-50, (c) EfficientNet-B7, (d) ViT, (e) Swin Transformer, and (f) ConvNeXt. The dataset comprises three word levels: easy, difficult, and pseudo-words.

The folder contains all necessary files to reproduce the calculations of the U-shaped concrete element aiming to significantly lowering its deatiled dimensions with the funcionality (and main dimations) kept. There are four optimization methods applied in two variants of the element support side and line support. There are also data necessary to verify the result with the Finite Element Method.

This dataset contains anonymized multidimensional data from 638 preservice physics teachers enrolled in 29 Physics Education Study Programs across 16 provinces in Indonesia. The dataset was developed to examine four interconnected components of the TPACK-PhyLEM evaluation model: Setting, Input, Transaction, and Output (SITO), with particular emphasis on preservice physics teachers’ technological, pedagogical, and content knowledge and their ICT self-efficacy. The dataset includes 2 identification variables, 8 demographic and institutional variables, and 43 retained measurement items. The measurement instrument was initially developed with 52 items, reviewed by five experts for content validity, and empirically validated using data from 270 students representing six Physics Education Study Programs. Following the empirical validation process, 43 items were retained across Setting (6 items), Input (11 items), Transaction (16 items), and Output (10 items). The 43-item instrument uses a five-point semantic differential scale and represents 12 first-order constructs: Environmental and Organizational; Need Assessment and Benefit; Technological Knowledge (TK); Pedagogical Knowledge (PK); Content Knowledge (CK); Technological Pedagogical Knowledge (TPK); Technological Content Knowledge (TCK); Pedagogical Content Knowledge (PCK); TPACK; Application and Software; Searching and Information; and Multimedia. The final dataset is accompanied by a codebook, variable dictionary, metadata description, scoring guide, and validation information to support interpretation, reuse, and further analysis. The dataset is intended for educational researchers, teacher educators, physics education researchers, and researchers studying TPACK, ICT self-efficacy, teacher education, and educational evaluation. It can be used for secondary analysis of preservice physics teachers’ TPACK-related competencies, comparison across institutional and geographical contexts, instrument-related research, and further investigation of technology integration in physics teacher education.

This research work has been carried out in a school in Bhutan consisting of 40 class X students. Thus, it contains datasets of 8 cycle tests scores and, pretest and posttest questionnaires scores over two months. The research is significant at four levels. First, it provides school-level empirical evidence from a Bhutanese multilingual secondary classroom, an environment in which local languages remain central to students’ daily communication while English functions as the principal academic language. Second, the eight-cycle design shows change over time rather than relying only on a single pre-test/post-test comparison. The significant Cycle × Group interaction suggests that the intervention’s advantage accumulated across the intervention period. Third, the findings offer a practical resolution to the common debate between English-only teaching and unrestricted L1 use: the evidence favors managed target-language immersion supported by brief, purposeful L1 scaffolding. Fourth, the study provides an actionable framework for teachers—maintain English as the default, identify moments when L1 genuinely adds value, use it briefly for clarification or planning, and then return students to English production.

This study intends to examine the direct impact of purpose on servant leadership and evaluate the mediating effect of altruism in the association between purpose and servant leadership. This research was conducted on a sample of 400 National Cadet Corps (NCC) cadets from the southern region of India. Mediation analysis results showed that altruism fully mediated the relationship between purpose and servant leadership.

This repository contains the numerical source data and process-model code associated with the manuscript entitled “Antibiotic resistance and changes in microbial arsenic processes through genetic and functional connections in groundwater”. The deposited data include the values underlying the main-text and Supplementary figures and tables. The repository includes: (i) groundwater hydrochemical variables, aqueous As(III) and As(V) concentrations, and antibiotic concentrations; (ii) processed microbial taxonomic profiles and abundances of arsenic-related genes, antibiotic resistance genes and mobile genetic elements used in the reported figures and analyses; (iii) contig-level records of arsenic-related and antibiotic resistance gene co-localisation; (iv) transcript and protein abundance data for arsenic transformation, antibiotic resistance and associated stress-response functions; and (v) measured aqueous arsenic speciation, model inputs, reconstructed endpoints and sensitivity-analysis results. The repository also contains the Python script, fixed parameter settings and software requirements for the exploratory process model of aqueous arsenic speciation. These materials support reproduction of the model’s internal calibration, comparisons among the five predefined configurations and one-at-a-time sensitivity analysis. Raw sequencing reads and mass-spectrometry files are not included in this repository.

This is the data sheet for the focus group discussions.

Results of sequential extraction procedure for trace elements in urban soils

This dataset contains the research data and supporting analytical materials used in the study “Climate-Smart Agriculture and Crop Production in Somalia,” submitted to Cogent Food & Agriculture. The deposited materials are provided to support transparency, verification, and reproducibility of the empirical analysis. They include the raw data, processed data used for econometric estimation, analysis results, and supporting data underlying the tables and figures reported in the manuscript. The study examines the relationship between climate-related and economic factors and crop production in Somalia using annual data covering 1970–2024. The main variables include crop production, gross capital formation, arable land, average temperature, water availability, and precipitation. The empirical analysis applies time-series econometric methods, including unit-root testing, cointegration analysis, and the Autoregressive Distributed Lag (ARDL) framework to examine short-run and long-run associations among the variables. The repository materials are intended to enable editors, reviewers, readers, and researchers to trace the empirical results, tables, and figures reported in the article to the underlying data and analytical outputs. Geographical coverage: Somalia Data frequency: Annual Study period: 1970–2024 Associated journal: Cogent Food & Agriculture