Social scientists under threat: Resistance and self-censorship in Turkish academia

Attacks on academic freedom in Turkey have become increasingly systematic in recent years and thousands of academics have been dismissed. This study reflects on the effects of this worsening repression through interviews with academics in the social sciences, both those dismissed and those still active in their profession. Although the dismissed academics are socially in a very precarious position, they are continuing their scholarly activities in alternative, underground forms. This resistance stands in contrast to the accommodation and self-censorship that seem, according to the interviewees, to prevail in university departments.     

Equity for English Learners: Evidence from Four Years of California’s Local Control Funding Formula

This study examined evidence of equity for English Learners-one of the three targeted student groups–in the early implementation of California’s Local Control Funding Formula (LCFF) across data sets from seven studies. We used social justice inquiry methods and data integration analytic approaches that included purposeful sampling of districts’ Local Control and Accountability Plans (LCAPs), and data integration analyses of interviews with education leaders to examine how equity was advanced for English Learners. Our findings reveal that the quest for equity for English Learners is elusive and requires multilevel efforts to reverse the national, state, and local histories of unequal treatment, deficit orientations, socio-political dynamics, and legacies of unequal funding that still permeate many schools. Further advances in equity will require greater systemic coherence that sharpens the focus on educational outcomes for English Learners. California’s most recent policy shifts–including the passage of Proposition 58 and the English Learner Roadmap–show promise of systemic coherence and alignment to an assets-based approach for English Learners in the state and nation, as tangible evidence of equity in services and outcomes are still works in progress.     

Models for antecedents of turnover intention and behavior among Brazilian employees

International Journal for Educational and Vocational Guidance - Studies indicate that the costs resulting from voluntary turnover range from 93 to 200% of the annual salary for a single position,...     

Designing instruction for complex learning: 4C/ID in higher education

Objectives‐based instructional design approaches break down tasks into specific learning objectives and prescribe that instructors should choose the optimal instructional method for teaching each respective objective until all objectives have been taught. This approach is appropriate for many tasks where there is little relation between the objectives, but less effective for teaching complex professional tasks that require the integration of knowledge, skills, and attitudes and the coordination of different skills. For the latter, a task‐centred approach that starts designing instruction from whole, real‐life tasks, is more appropriate. This article describes one task‐centred instructional design model, namely the Four‐Component Instructional Design (4C/ID) model and illustrates its application by reflecting on three educational programs in higher education designed with 4C/ID. The first case presents a design for a course that focuses on the development of mobile apps at the Amsterdam University of Applied Sciences in the Netherlands. The second case illustrates the integration of information problem‐solving skills at Iselinge University of Professional Teacher Education, a teacher training institute in the Netherlands. The third case is an example from general practice education at the KU Leuven, Belgium. Future developments and issues concerning the implementation of task‐centred educational programmes are discussed.     

Vocation in Theology and Psychology: Conflicting Approaches?

ABSTRACT

Recent contributions in the fields of psychology, sociology, and theology reveal opposing attitudes about the subject of calling or vocation with regard to one's work. Whereas psychologists have rediscovered the concept, theologians increasingly show reluctance to accept a vocational view of work. In offering an alternative perspective, this article argues that an approach to calling from biblical theology is capable of inspiring Christian workers in a psychologically meaningful way, while avoiding the inadequacies of the understanding that “work is vocation” that was developed during the Protestant Reformation. In a biblical-theological approach, work is not equated with calling. Rather, it is perceived as practicing the love command and hope for a restoration of God's intentions for creation, emanating from the call into fellowship with Christ and a vision for the kingdom of God.     

Assistant principals in high-stakes accountability environments: The effects of job attributes and school characteristics

This study addressed the topic of job specifications and school characteristics since there is a shortage of quality AP applicants in high-stakes accountability environments. It is important to learn about allocation of duties from educational administrators with on-the-job experience as well as to learn why current APs would consider applying for other AP positions. The purpose of this study was to investigate the impact of job attributes (instruction, discipline), school level (elementary, middle, high), and school achievement (in-need-of-assistance, progressing, meets goal) on applicant’s rating of an AP position. This research study used an experimental design. A main effect for job attributes indicated that instruction was significantly higher than discipline when attracting assistant principals. Implications for practice and research are discussed.     

Preface-Special Part-issue of the International Symposium on Robotics and Mechatronics(ISRM 2009)

The International Federation for the Promotion of Mechanism and Machine Science(IFToMM)held the International Symposium on Robotics and Mechatronics(ISRM 2009)as the first in a series of conference events promoting robotics and mechantronics in the Asian IFToMM community.The first event was held in Hanoi University of Technology on Sept.21-23.2009.     

Noninvasive physicochemical characterization of two 19th century English ferrotypes

The present work was one of the first attempts to analyze the conservation status of two ferrotypes, ancient photographic plates realized on a support made of iron. The photographic material was constituted of collodion as binder for the photosensitive silver halides grains. The two ferrotypes studied belonged to a private collection of a family from Durham, UK, and were made at the end of the 19th century. The analytical techniques used for the morphological and physicochemical characterization were noninvasive. The surface morphology was studied by means of optical microscopy (OM) and environmental scanning electron microscopy (ESEM) coupled with an energy dispersive X-rays (EDX) system for the elemental analysis. These techniques, together with microreflectance Fourier transform infrared spectroscopy (μ-FTIR) and contact angle, allowed to obtain information on both the chemical – elemental – composition of the materials constituting the ferrotypes, and the conservation status of these photographic plates. The study showed that the physicochemical diagnostics allowed to characterize the two ferrotypes that, despite their similar age and provenance, showed different conservation status, surface properties, and elemental composition.     

Human resources for Big Data professions: A systematic classification of job roles and required skill sets

The rapid expansion of Big Data Analytics is forcing companies to rethink their Human Resource (HR) needs. However, at the same time, it is unclear which types of job roles and skills constitute this area. To this end, this study pursues to drive clarity across the heterogeneous nature of skills required in Big Data professions, by analyzing a large amount of real-world job posts published online. More precisely we: 1) identify four Big Data ‘job families’; 2) recognize nine homogeneous groups of Big Data skills (skill sets) that are being demanded by companies; 3) characterize each job family with the appropriate level of competence required within each Big Data skill set. We propose a novel, semi-automated, fully replicable, analytical methodology based on a combination of machine learning algorithms and expert judgement. Our analysis leverages a significant amount of online job posts, obtained through web scraping, to generate an intelligible classification of job roles and skill sets. The results can support business leaders and HR managers in establishing clear strategies for the acquisition and the development of the right skills needed to leverage Big Data at best. Moreover, the structured classification of job families and skill sets will help establish a common dictionary to be used by HR recruiters and education providers, so that supply and demand can more effectively meet in the job marketplace.