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The purpose of this study was to identify special education teachers' profiles in relation to their levels of burnout, work engagement and job satisfaction, following a person- oriented approach. This approach was chosen in order to provide cfombinations of attributes that shape high-risk groups of low engagement and high burnout. Additionally, it was examined whether these profiles differed with regard to special education teachers' individual parameters and work-related characteristics, such as age, gender, marital status, number of children in family, level of education, region of employment and teaching experience. The sample included 664 in-service special education teachers (503 females and 161 males) working in primary and secondary schools. Two-step cluster analysis yielded four profiles, entitled: passionate, workaholic, operational and overworked. Differences were also noted among profiles, in terms of participants' age, educational level, region and teaching experience. Findings are discussed with reference to implications for future research in order to early detect and support teachers at risk.

Exploring individual differences and looking beyond averaged parameters of early numeracy in young children with mild intellectual disabilities has become an area of interest to many researchers worldwide. This study aimed to identify the different profiles of early numeracy skills in young children with mild intellectual disabilities. For this purpose, we assessed early numeracy through Utrecht early numeracy test and learning aptitude through Detroit Test, in a sample of 135 children diagnosed with intellectual disabilities. The mean of their mental age was 5:09 (years:months). Two-step cluster analysis identified four homogenous groups of children with distinct early numeracy profiles as follows:C1 were fluent in relational and numerical skills up to 20, C2 were fluent in relational skills and numerical skills up to 10, C3 had basic knowledge of relational skills and inconsistent numerical skills up to 10 and C4 had inconsistent relational skills and numerical skills. Results are discussed with reference to their educational implications.

While open and distance education gains growing recognition over time, it also faces increasing drop-out rates. Consequently, the development of predictive models for early identification of students at-risk for drop-out could be critical to promote ongoing engagement. This study aims to gain insights into the dropout prediction problem in a sample of postgraduate special education students. Therefore, a nonlinear state-space model was employed. An Expectation-Maximization (EM) algorithm that iterates between state estimation (E-step) and parameter estimation (M-step) was retrieved from the existing literature. However, the variables were redefined according to available data. In the dataset a total number of n[subscript 1] = 1337 students were enrolled, attending n[subscript 2] = 7 different modules. Statistical analysis showed that the majority of the students dropped out during the second week. Moreover, an inversely proportional relationship was observed between the dropout rates and the number of weeks that the student has actively engaged in the module. Significant differences across modules were also observed. Results are discussed in terms of their application in the training and education of the collaborating teaching staff working in the HOU. Future work in the field should be expanded in order to investigate students' drop-out in more courses other than special education.

The purpose of this study was to identify special education teachers' profiles in relation to their levels of burnout, work engagement and job satisfaction, following a person- oriented approach. This approach was chosen in order to provide cfombinations of attributes that shape high-risk groups of low engagement and high burnout. Additionally, it was examined whether these profiles differed with regard to special education teachers' individual parameters and work-related characteristics, such as age, gender, marital status, number of children in family, level of education, region of employment and teaching experience. The sample included 664 in-service special education teachers (503 females and 161 males) working in primary and secondary schools. Two-step cluster analysis yielded four profiles, entitled: passionate, workaholic, operational and overworked. Differences were also noted among profiles, in terms of participants' age, educational level, region and teaching experience. Findings are discussed with reference to implications for future research in order to early detect and support teachers at risk. [ABSTRACT FROM AUTHOR]

Exploring individual differences and looking beyond averaged parameters of early numeracy in young children with mild intellectual disabilities has become an area of interest to many researchers worldwide. This study aimed to identify the different profiles of early numeracy skills in young children with mild intellectual disabilities. For this purpose, we assessed early numeracy through Utrecht early numeracy test and learning aptitude through Detroit Test, in a sample of 135 children diagnosed with intellectual disabilities. The mean of their mental age was 5:09 (years:months). Two-step cluster analysis identified four homogenous groups of children with distinct early numeracy profiles as follows:C1 were fluent in relational and numerical skills up to 20, C2 were fluent in relational skills and numerical skills up to 10, C3 had basic knowledge of relational skills and inconsistent numerical skills up to 10 and C4 had inconsistent relational skills and numerical skills. Results are discussed with reference to their educational implications. [ABSTRACT FROM AUTHOR]

This study explored potential factors of numeracy acquisition in young children with intellectual disabilities (IDs). Those factors are determined to assess parents' academic expectations and home practices that they use with their children daily. The sample consisted of 187 Greek-speaking couples, comprising a total number of 374 parents. All of them had a child with mild IDs aged between 4 and 7 years old. Since Greece is placed among European countries with the lowest median disposable income it is significant to assess the potential effects of each family's socioeconomic status. We employed structural equation modeling to identify potential factors affecting a child's with IDs numeracy outcomes. Analysis of moments structures (AMOS) revealed that there is a good fit for the suggested second-order structural equation model. Results are discussed regarding their practical implications., Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.