129 Works
Total skin self-examination at home for people treated for cutaneous melanoma
Peter Murchie & Susan Jane Hall
1. Recordings of interviews with people affected by melanoma to ascertain views on the role of technology in their follow-up. 2. Transcripts of interviews with people affected by melanoma to ascertain views on the role of technology in their follow-up 3. Report of Forres Experience Prototype Lab - May 2013 4. Questionnaire data from participants in ASICA pilot study. 5. Interviews tapes conducted with participants in the ASICA study. 6. Transcript of interviews conducted with...
Editorial: Participation, diversity, involvement and engagement in local and global contexts
Beth Cross, Rachel Shanks & Tuija TurunenEducators’ narratives about belonging and diversity in northern Finland early childhood education
Janna Juutinen & Riikka KessEmbedding and sustaining change in technology-enhanced education: lessons learned from a cross-institutional transformation project
Andrew Comrie, Morag Gray, Terry Mayes & Keith SmythCoping Strategies for Students
Annette MoirLAB studio model: Developing external networks for learning entrepreneurship in higher education
Kari-Pekka Heikkinen, Ulla-Maija Seppänen & Jouko IsokangasOpening Spaces for Indigenous Teaching and Learning through Community-Based Teacher Education
Shelley Tulloch & Sylvia MooreA meditation on what a post-human education might look like: “Touching something beyond myself and my time”
William Boyd & Louise HorstmanshofMAFIO: Model for the Agent-based simulation of Faecal Indicator Organisms
Aaron James Neill
MAFIO is an agent-based model designed to simulate the small-scale behaviour and transport of agents representing faecal indicator organisms (FIOs) in a spatially-distributed, process-based manner, in order to unravel the spatio-temporal dynamics of sources and transfer mechanisms contributing FIOs to streams in agricultural settings. This repository contains the source code for the model, which is written in Python 3.6. It is organised as follows: - ABM_getDirs_V1.py: script containing the locations of various input and output...