Science education requires learning resources that connect scientific knowledge with contextual problem solving, environmental responsibility, and learners’ cultural experiences. This study aimed to determine the validity and practicality of the Pancaniti ethnoscience-based UA-EVAA (Understanding, Awareness, Evidence-Based Reasoning, Value-Based Action, and Authentic Truth) Digital Science Module for junior secondary science. The study employed a Research and Development approach structured using the ADDIE model, with the present investigation focusing on formative product evaluation. Expert validation involved six validators who assessed 44 sub-indicators across content, presentation, language, and graphic feasibility using Aiken’s V. Practicality was evaluated through a 40-item questionnaire in a small-scale trial involving 15 students and three teachers, followed by a large-scale trial involving 100 students and 10 teachers. Expert validation yielded an overall Aiken’s V of 0,861, with dimension means of 0,891 for content, 0,844 for presentation, 0.839 for language, and 0,847 for graphics. Item-level coefficients ranged from 0,708 to 1,000, identifying specific priorities for formative revision despite adequate overall feasibility. Small-scale practicality scores reached 86,30% for students and 87,67% for teachers. Large-scale evaluation produced scores of 83,44% and 86,60%, respectively, with satisfactory internal consistency for both groups. These findings demonstrate that the UA-EVAA module has adequate expert-supported validity and positive user practicality, providing a sound basis for subsequent effectiveness testing of students’ problem-solving skills and environmental awareness.
Supporting data, adapters, predictions and code for the article *Low-Cost LoRA Fine-Tuning of Small Language Models for Multi-Step Arithmetic Reasoning* by Jake O'Grady, Asena Isik Gürhan, Chee Fong Ting and Effirul Ramlan (University of Galway). We generated 20,000 GSM8K-derived arithmetic problems with step-by-step s...
O'Grady, Jake, Gürhan, Asena Isik, Chee, Fong Ting et al.· Zenodo (CERN European Organi...· 465 citations
The results are packaged in the Greenfield Startup Model (GSM), which explains the priority of startups to release the product as quickly as possible, and the need to shorten time-to-market, by speeding up the development through low-precision engineering activities.
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A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
Microsoft Research Blog· microsoft.comOct 15, 2026
Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.