title: AI augmented approach to identify shared ideas from large format public consultation

authors: Weng, Min-Hsien

subjects: software engineering

abstract: Public data, contributed by citizens, stakeholders and other potentially affected parties, are becoming increasingly used to collect the shared ideas of a wider community. Having collected large quantities of text data from public consultation, the challenge is often how to interpret the dataset without resorting to lengthy time-consuming manual analysis. One approach gaining ground is the use of Natural Language Processing (NLP) technologies. Based on machine learning technology applied to analysis of human natural languages, NLP provides the opportunity to automate data analysis for large volumes of texts at a scale that would be virtually impossible to analyse manually. Using NLP toolkits, this paper presents a novel approach for identifying and visualising shared ideas from large format public consultation. The approach analyses grammatical structures of public texts to discover shared ideas from sentences comprising subject + verb + object and verb + object that express public options. In particular, the shared ideas are identified by extracting noun, verb, adjective phrases and clauses from subjects and objects, which are then categorised by urban infrastructure categories and terms. The results are visualised in a hierarchy chart and a word tree using cascade and tree views. The approach is illustrated using data collected from a public consultation exercise called “Share an Idea” undertaken in Christchurch, New Zealand, after the 2011 earthquake. The approach has the potential to upscale public participation to identify shared design values and associated qualities for a wide range of public initiatives including urban planning.

text: AI augmented approach to identify shared ideas from large format public consultation Public data, contributed by citizens, stakeholders and other potentially affected parties, are becoming increasingly used to collect the shared ideas of a wider community. Having collected large quantities of text data from public consultation, the challenge is often how to interpret the dataset without resorting to lengthy time-consuming manual analysis. One approach gaining ground is the use of Natural Language Processing (NLP) technologies. Based on machine learning technology applied to analysis of human natural languages, NLP provides the opportunity to automate data analysis for large volumes of texts at a scale that would be virtually impossible to analyse manually. Using NLP toolkits, this paper presents a novel approach for identifying and visualising shared ideas from large format public consultation. The approach analyses grammatical structures of public texts to discover shared ideas from sentences comprising subject + verb + object and verb + object that express public options. In particular, the shared ideas are identified by extracting noun, verb, adjective phrases and clauses from subjects and objects, which are then categorised by urban infrastructure categories and terms. The results are visualised in a hierarchy chart and a word tree using cascade and tree views. The approach is illustrated using data collected from a public consultation exercise called “Share an Idea” undertaken in Christchurch, New Zealand, after the 2011 earthquake. The approach has the potential to upscale public participation to identify shared design values and associated qualities for a wide range of public initiatives including urban planning.

year: 2021

title: Space speaks: A portrait of an early childhood centre and the affordances provided by the learning environment

authors: McChesney, Katrina

abstract: The quality of early childhood education and care fundamentally depends on teachers’ wise practice. However, the environments in which that education and care occur can influence, inform, and shape teachers’ practice, and children’s and families’ experiences. This article draws on a written “portrait” of the learning environment created at one New Zealand early childhood education (ECE) centre, capturing both physical and non-physical aspects of the environment and highlighting the affordances the environment offered to children and families/whānau. A Reggio Emilia lens is used to inform analysis of the learning environment and the associated affordances. The portrait (McChesney, 2020) and this article may support practitioners by providing a vision of what can be in terms of early childhood learning environments, and by providing a possible framework for self-review and inquiry.

text: Space speaks: A portrait of an early childhood centre and the affordances provided by the learning environment The quality of early childhood education and care fundamentally depends on teachers’ wise practice. However, the environments in which that education and care occur can influence, inform, and shape teachers’ practice, and children’s and families’ experiences. This article draws on a written “portrait” of the learning environment created at one New Zealand early childhood education (ECE) centre, capturing both physical and non-physical aspects of the environment and highlighting the affordances the environment offered to children and families/whānau. A Reggio Emilia lens is used to inform analysis of the learning environment and the associated affordances. The portrait (McChesney, 2020) and this article may support practitioners by providing a vision of what can be in terms of early childhood learning environments, and by providing a possible framework for self-review and inquiry.

year: 2020

title: "It's about empowering the whānau": Māori adult students succeeding at university

authors: Williams, Daphne Christina (Tina)

subjects: māori academic success

abstract: A large number of studies have demonstrated that Māori students are not performing well in education. The literature in the general area of Māori education paints a very grim picture that demonstrates a clear preoccupation with failure and underachievement. These studies often overlook the experiences of Māori adult students who return to study long after leaving school and experience considerable success. This paper focuses on the academic success of 16 indigenous students at a New Zealand university. It is based on the findings of a qualitative investigation that explored the experiences of Māori adult students who entered university with very few formal school qualifications and then went on to attain undergraduate degrees. This paper pays particular attention to the role of the whānau in facilitating Māori educational success at university.

text: "It's about empowering the whānau": Māori adult students succeeding at university A large number of studies have demonstrated that Māori students are not performing well in education. The literature in the general area of Māori education paints a very grim picture that demonstrates a clear preoccupation with failure and underachievement. These studies often overlook the experiences of Māori adult students who return to study long after leaving school and experience considerable success. This paper focuses on the academic success of 16 indigenous students at a New Zealand university. It is based on the findings of a qualitative investigation that explored the experiences of Māori adult students who entered university with very few formal school qualifications and then went on to attain undergraduate degrees. This paper pays particular attention to the role of the whānau in facilitating Māori educational success at university.

year: 2011