Career Adapt-Abilities Scale—Iran Form: Psychometric properties and relationships with career satisfaction and entrepreneurial intentions

This study examined the psychometric properties of a Persian translation of the Career Adapt-Abilities Scale (CAAS—Iran Form) and its relationships with career satisfaction, business opportunity identification, and entrepreneurial intentions. It was hypothesized that career adaptability relates positively to these three outcomes, even when controlling for demographic and employment characteristics. Data were provided by 204 workers from Iran. Results showed that the overall CAAS score and sub-dimension scores (concern, control, curiosity, and confidence) were highly reliable. Moreover, confirmatory factor analyses indicated that the CAAS—Iran Form measures four distinct dimensions that can be combined into a higher-order career adaptability factor. Findings also demonstrated criterion-related validity of the scale with regard to career satisfaction and entrepreneurial intentions. In contrast, overall career adaptability was not significantly related to opportunity identification, while concern related positively, and control related negatively to opportunity identification. Overall, the CAAS—Iran Form has very good psychometric properties and predicts important career outcomes, suggesting that it can be used for career counseling and future research with Persian-speaking workers.

Statistical analysis of spectral data: A methodology for designing an intelligent monitoring system for the diabetic foot

Early detection of (pre-)signs of ulceration on a diabetic foot is valuable for clinical practice. Hyperspectral imaging is a promising technique for detection and classification of such (pre-)signs. However, the number of the spectral bands should be limited to avoid overfitting, which is critical for pixel classification with hyperspectral image data. The goal was to design a detector/classifier based on spectral imaging (SI) with a small number of optical bandpass filters. The performance and stability of the design were also investigated. The selection of the bandpass filters boils down to a feature selection problem. A dataset was built, containing reflectance spectra of 227 skin spots from 64 patients, measured with a spectrometer. Each skin spot was annotated manually by clinicians as "healthy" or a specific (pre-)sign of ulceration. Statistical analysis on the data set showed the number of required filters is between 3 and 7, depending on additional constraints on the filter set. The stability analysis revealed that shot noise was the most critical factor affecting the classification performance. It indicated that this impact could be avoided in future SI systems with a camera sensor whose saturation level is higher than 106, or by postimage processing.

Capacity building of early career researchers through cross-institutional mentoring

Most early career researchers in the first five years following doctoral qualification are faced with research challenges and opportunities, which necessitate the ability to navigate and overcome barriers, and to identify and benefit from possibilities. In this chapter, the authors outline an intentional mentoring initiative aimed at building the capacity of early career researchers within the Excellence in Research in Early Years Education Collaborative Research Network (CRN) in Australia. The initiative involved partnering early career researchers with experienced researchers and the inclusion of an early career representative on the network planning committee. The chapter discusses the many benefits for the mentee arising from the initiative including increased publication, momentum and confidence, as well as exposure to new methodologies, theoretical frameworks, and productive collaborative partnerships. It is hoped, however, that the findings will be of relevance to similar and diverse (funded/unfunded) research programs and collaborative networks wherever mentoring is applied as a capacity building strategy to assist researchers.

The Systems Theory Framework of career development: 20 years of contribution to theory and practice

The development and sustained contribution of the Systems Theory Framework to career development theory and practice is well documented in national and international literatures. In addition to its contribution to theory integration, it has added to the growing literature on connecting career theory and practice, in particular for non-Western populations. In addition, it has been the basis of the development of a broad array of constructivist approaches to career counselling, and indeed specific reflective career assessment activities. This article begins with a brief history of the Systems Theory Framework which is then followed by a rationale for its development. The contribution of the Systems Theory Framework to theory and practice is then described prior to concluding comments by the authors.

The Systems Theory Framework of career development: Applications to career counselling and career assessment

Since its inception, the Systems Theory Framework of career development has afforded ready translation into practice, especially into career counselling and qualitative career assessment. Through its clearly articulated constructs and the clarity of its diagrammatic representation, the Systems Theory Framework has facilitated the development of qualitative career assessment instruments as well as a quantitative measure. This article briefly overviews these practical applications of the Systems Theory Framework as well as its application in career counselling through a story telling approach. The article concludes by offering a synthesis of and considering future directions for the Systems Theory Framework’s practical applications.

Incorporating Career Assessment into Career Counselling

Career assessment has long held a central place in career counselling since the work of Parsons (1909) signalled the birth of a new field of practice, vocational guidance, and its subsequent iterations of career guidance and counselling and more recently life designing.

My System of Career Influences

My System of Career Influences (MSCI) is a qualitative guided reflection process for adolescents and for adults that is based on the Systems Theory Framework (STF; McMahon & Patton, 1995; Patton & McMahon, 1999, 2006, 2014) of career development. Reflective of the trend towards more holistic theories and models of career counselling, the MSCI enables users to identify, prioritise and story their career influences, thus enabling them to contextualise career decisions and career transitions.

A cloud-based intelligent computing system for contextual exploration on personal sleep-tracking data using association rule mining

With the development of wearable and mobile computing technology, more and more people start using sleep-tracking tools to collect personal sleep data on a daily basis aiming at understanding and improving their sleep. While sleep quality is influenced by many factors in a person’s lifestyle context, such as exercise, diet and steps walked, existing tools simply visualize sleep data per se on a dashboard rather than analyse those data in combination with contextual factors. Hence many people find it difficult to make sense of their sleep data. In this paper, we present a cloud-based intelligent computing system named SleepExplorer that incorporates sleep domain knowledge and association rule mining for automated analysis on personal sleep data in light of contextual factors. Experiments show that the same contextual factors can play a distinct role in sleep of different people, and SleepExplorer could help users discover factors that are most relevant to their personal sleep.