Coaching and Embedding in Early Childhood

Coaching and embedding has become an increasingly popular service delivery model in early childhood and has led to higher developmental outcomes for children and increased caregiver confidence and competence in working with their children with delays or disabilities. Coaching and embedding is an evidence based practice and considered a recommended practice by the Division for Early Childhood of the Council for Exceptional Children as a service delivery model for early intervention. Coaching involves many strategies and can be delivered through a variety of modalities including in-person or virtual services. This project includes a review of literature on coaching and embedding in early childhood, development of three coaching videos, a summary reflection on the process for developing coaching videos and next steps for implementation with families, and the outcomes of early intervention. Key words: early intervention, coaching, embeddin

Tagtmeier, Daniel - Covid-19 Journal

EIU student, Daniel Tagtmeier writes about the effect of the pandemic on his learning and homelife, particularly his relationship with his grandmother and the inability to see her in the early stages of the pandemic

Microblogging as a mechanism for human–robot interaction

This article has been made available through the Brunel Open Access Publishing Fund.This paper presents a novel approach to social data analysis, exploring the use of microblogging to manage interaction between humans and robots, and presenting and evaluating an architecture that extends the use of social networks to connect humans and devices. The approach uses natural language processing - in the form of simple grammar-based techniques - to extract features of interest from textual data retrieved from a microblogging platform in real-time and generate appropriate executable code for the robot. The simple rule-based solution exploits some of the 'natural' constraints imposed by microblogging platforms to manage the potential complexity of the interactions and create bi-directional communication. In order to evaluate the developed system, an analysis of real-time, user-generated social media data is presented. The analysis demonstrates the feasibility of producing programmes from the social media data which lead to executable actions by a front-end application - an approach of immediate relevance to web-based systems, like question-answering engines, personal digital assistants, and smart home/office devices