title: Inclusive education in Fiji: pre-service and in-service primary education teachers’ perspectives and preparedness for inclusive education

authors: Singh, Deepak Sanjay

subjects: Teachers' perspectives and preparedness for Inclusive Education

abstract: Inclusive education is a recent idea of the Ministry of Education Fiji, through which they hope to provide disabled children the opportunity to receive a quality education in mainstream schools. However, are pre-service and in-service primary education teachers in Fiji sufficiently trained to take up the role of an inclusive education teacher? The international literature claims that mainstream teachers, the key people to implement inclusive education, are least prepared and are unwilling to meet the educational needs of disabled children. Is this also true for Fijian teachers? 

The aim of this research study was to gather Fijian pre-service and in-service primary education teachers’ perspectives and preparedness for inclusive education that has begun in some mainstream primary schools in Fiji and will gradually expand to other mainstream primary schools in the country. An interpretive paradigm guided the research methodology, since the purpose was to gather participants’ perspectives and consensus of how prepared they are for inclusive education. A qualitative research approach which utilised a face-to-face semi-structured interview method was used to collect data. Twelve individuals were interviewed comprising of eight final year (Year 3) pre-service primary education teachers from two teacher training institutions, together with one inclusive education and three special education in-service teachers. 

Data gathered from participants reveals that teachers have a positive attitude towards inclusive education in Fiji and are enthusiastic about taking up the role of inclusive education teacher. This positive attitude was native to the understanding that disabled children have rights to a high quality education, and secondly, it was because of the experiences they had with this group of children and adults before, during and, for some, after their initial teacher training. However, all participants also perceive they have insufficient training and limited skills to teach disabled children. In keeping with international findings, this research initiative shows that teachers’ positive attitudes weaken when they face an adverse environment such as large class size and lack of teacher support for daily teaching tasks. 

These findings indicate that all trainee teachers must receive the opportunity to learn about, observe and practice teaching this group of children during their initial teacher training, so that they graduate having adequate skills to teach disabled children. Teachers must also work towards improving their professional skills after initial training, as the data reveals there is high chance that teachers’ attitudes will deteriorate further when they address the challenges of time and classroom management.

text: Inclusive education in Fiji: pre-service and in-service primary education teachers’ perspectives and preparedness for inclusive education Inclusive education is a recent idea of the Ministry of Education Fiji, through which they hope to provide disabled children the opportunity to receive a quality education in mainstream schools. However, are pre-service and in-service primary education teachers in Fiji sufficiently trained to take up the role of an inclusive education teacher? The international literature claims that mainstream teachers, the key people to implement inclusive education, are least prepared and are unwilling to meet the educational needs of disabled children. Is this also true for Fijian teachers? 

The aim of this research study was to gather Fijian pre-service and in-service primary education teachers’ perspectives and preparedness for inclusive education that has begun in some mainstream primary schools in Fiji and will gradually expand to other mainstream primary schools in the country. An interpretive paradigm guided the research methodology, since the purpose was to gather participants’ perspectives and consensus of how prepared they are for inclusive education. A qualitative research approach which utilised a face-to-face semi-structured interview method was used to collect data. Twelve individuals were interviewed comprising of eight final year (Year 3) pre-service primary education teachers from two teacher training institutions, together with one inclusive education and three special education in-service teachers. 

Data gathered from participants reveals that teachers have a positive attitude towards inclusive education in Fiji and are enthusiastic about taking up the role of inclusive education teacher. This positive attitude was native to the understanding that disabled children have rights to a high quality education, and secondly, it was because of the experiences they had with this group of children and adults before, during and, for some, after their initial teacher training. However, all participants also perceive they have insufficient training and limited skills to teach disabled children. In keeping with international findings, this research initiative shows that teachers’ positive attitudes weaken when they face an adverse environment such as large class size and lack of teacher support for daily teaching tasks. 

These findings indicate that all trainee teachers must receive the opportunity to learn about, observe and practice teaching this group of children during their initial teacher training, so that they graduate having adequate skills to teach disabled children. Teachers must also work towards improving their professional skills after initial training, as the data reveals there is high chance that teachers’ attitudes will deteriorate further when they address the challenges of time and classroom management.

year: 2018

title: Random Relational Rules

authors: Pfahringer, Bernhard

subjects: computer science

abstract: Exhaustive search in relational learning is generally infeasible, therefore some form of heuristic search is usually employed, such as in FOIL[1]. On the other hand, so-called stochastic discrimination provides a framework for combining arbitrary numbers of weak classifiers (in this case randomly generated relational rules) in a way where accuracy improves with additional rules, even after maximal accuracy on the training data has been reached. [2] The weak classifiers must have a slightly higher probability of covering instances of their target class than of other classes. As the rules are also independent and identically distributed, the Central Limit theorem applies and as the number of weak classifiers/rules grows, coverages for different classes resemble well-separated normal distributions. Stochastic discrimination is closely related to other ensemble methods like Bagging, Boosting, or Random forests, all of which have been tried in relational learning [3, 4, 5].

text: Random Relational Rules Exhaustive search in relational learning is generally infeasible, therefore some form of heuristic search is usually employed, such as in FOIL[1]. On the other hand, so-called stochastic discrimination provides a framework for combining arbitrary numbers of weak classifiers (in this case randomly generated relational rules) in a way where accuracy improves with additional rules, even after maximal accuracy on the training data has been reached. [2] The weak classifiers must have a slightly higher probability of covering instances of their target class than of other classes. As the rules are also independent and identically distributed, the Central Limit theorem applies and as the number of weak classifiers/rules grows, coverages for different classes resemble well-separated normal distributions. Stochastic discrimination is closely related to other ensemble methods like Bagging, Boosting, or Random forests, all of which have been tried in relational learning [3, 4, 5].

year: 2006

title: Wearable technology for hazardous remote environments: Smart shirt and Rugged IoT network for forestry worker health

authors: Hinze, Annika

subjects: software engineering

abstract: This paper introduces the architecture and details of our wearable IoT solution for workplace health and safety in rugged outdoor environments. We focus on the specific requirements defined by the New Zealand forestry environment as it is the industry with the most fatalities and highest accident rate in New Zealand. Neither consumer-level products nor professional wearables have been found to be suitable for forestry conditions. Furthermore, forestry workplaces cannot rely on existing networking infrastructure, and due to their remote and rugged nature, no permanent setup is possible.

We describe the Hakituri project in which we integrate wearable devices, networking, data analytics, and a buddy system into a novel monitoring solution for worker health and safety. Our wearable IoT solution includes a dynamic network set-up, wearables suitable for forestry conditions, contextual rule-based data analytics, and real-time alerts. A wearable smart shirt carries sensors for collecting personal data from forestry workers, while further environmental sensors capture contextual data. The IoT network is set up for communication in unreliable and rugged outdoor environments. We explore a variety of setups to achieve the best quality outcomes for health and safety in the forestry domain.

text: Wearable technology for hazardous remote environments: Smart shirt and Rugged IoT network for forestry worker health This paper introduces the architecture and details of our wearable IoT solution for workplace health and safety in rugged outdoor environments. We focus on the specific requirements defined by the New Zealand forestry environment as it is the industry with the most fatalities and highest accident rate in New Zealand. Neither consumer-level products nor professional wearables have been found to be suitable for forestry conditions. Furthermore, forestry workplaces cannot rely on existing networking infrastructure, and due to their remote and rugged nature, no permanent setup is possible.

We describe the Hakituri project in which we integrate wearable devices, networking, data analytics, and a buddy system into a novel monitoring solution for worker health and safety. Our wearable IoT solution includes a dynamic network set-up, wearables suitable for forestry conditions, contextual rule-based data analytics, and real-time alerts. A wearable smart shirt carries sensors for collecting personal data from forestry workers, while further environmental sensors capture contextual data. The IoT network is set up for communication in unreliable and rugged outdoor environments. We explore a variety of setups to achieve the best quality outcomes for health and safety in the forestry domain.

year: 2022