An introduction to using SPSS to analyze complex survey data is given. Key features of complex survey design are described briefly, including stratification, clustering, multiple stages, and weights. Then, annotated SPSS syntax for complex survey data analysis is presented to demonstrate the step-by-step process using real complex samples data.

How science and technology attitudes vary across the United States, China, South Korea and Japan - all of which top Bloomberg's list of high-tech centralization - is explored through data from the sixth wave of the World Values Survey (2010-2014). The following study examines the presence of different types of attitudinal groups using latent profile analysis. Not only do unique attitudinal groups exist in each country, but each group is uniquely influenced by select demographic characteristics, including education, age, gender, religiosity, employment status and individual interaction with technology. The findings provide insight into public attitudes towards science and technology across social and cultural contexts and generate nuanced understandings of similar and different attitudinal groups in East Asia and the United States.

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Research priority setting, an element of knowledge mobilization, makes knowledge users integral to the development of research agendas. To date, the use of research priority setting in educational research has been minimal. The purpose of this study was to explore educational leaders’ perspectives on research priorities in special education. We conducted a cross-sectional research priority setting survey with educational leaders from 60 public school districts in British Columbia, Canada. Seventy-one participants completed the survey. Results of a pre-set list of questions indicated that the top three research priorities were: grade-to-grade transitions, high school graduation, and time to designation. In terms of designation, or student categorization, participants were most interested in “Intensive Behaviour Interventions/Severe Mental Illness.” When asked about other priorities, participants identified research on types of support/interventions. These results have implications for developing a research agenda that can support informed decision-making around policy-development and programming for students with special needs.

A paucity of population-based research explores the prevalence and sociodemographic characteristics of high school students with varieties of special needs and disabilities. Utilising a population-based sample of self-reported data collected in British Columbia, Canada, we investigated the scope and sociodemographic characteristics of adolescents between and within multiple categories of physical, mental, emotional and behavioural needsincluding those with two or more conditions and no conditions. First, we computed the most commonly occurring and least commonly occurring special needs categories. Second, we created profiles of the broad sociodemographic characteristics of adolescents in each special needs category. Finally, we determined whether the profiles indicated statistically significant between-and withincategory heterogeneity. We found that over onequarter of adolescents had one or more special needs, while nearly three-quarters of the special needs subpopulation had only three of the nine special needs tracked. Also, whether adolescents with a given special need were compared to those from different categories or those within the same category, there was considerable diversity in their sociodemographic attributes. Our study is one of the first to describe adolescents with special needs in this population-based fashion. We hope that our findings may guide programme and policy development in British Columbia and around the world.