A Comprehensive Survey of Artificial Intelligence Techniques for Talent Analytics

In today's competitive and fast-evolving business environment, it is a critical time for organizations to rethink how to make talent-related decisions in a quantitative manner. Indeed, the recent development of Big Data and Artificial Intelligence (AI) techniques have revolutionized human resource management. The availability of large-scale talent and management-related data provides unparalleled opportunities for business leaders to comprehend organizational behaviors and gain tangible knowledge from a data science perspective, which in turn delivers intelligence for real-time decision-making and effective talent management at work for their organizations. In the last decade, talent analytics has emerged as a promising field in applied data science for human resource management, garnering significant attention from AI communities and inspiring numerous research efforts. To this end, we present an up-to-date and comprehensive survey on AI technologies used for talent analytics in the field of human resource management. Specifically, we first provide the background knowledge of talent analytics and categorize various pertinent data. Subsequently, we offer a comprehensive taxonomy of relevant research efforts, categorized based on three distinct application-driven scenarios: talent management, organization management, and labor market analysis. In conclusion, we summarize the open challenges and potential prospects for future research directions in the domain of AI-driven talent analytics.Comment: 30 pages, 15 figure

Proceedings of the 4th Workshop on Awareness and Reflection in Technology Enhanced Learning. In conjunction with the 9th European Conference on Technology Enhanced Learning: Open Learning and Teaching in Educational Communities

Awareness and reflection can be viewed from the differing perspectives of the disciplines informing Technology-Enhanced Learning, such as Psychology, Educational and Learning Sciences, or Computer Science. A common denominator can be identified, though, and enhancing ’awareness’ of learners and other participants involved in learning processes by technology means augmenting formal or informal learning experiences, typically in real-time, with information on progress, presence, outcomes, workspace, and the like. Supporting ’reflection’ then means enabling learners to capture, adapt, re-evaluate, and share experience in anticipation of future situations it will prove relevant to. Reflection supported digitally is a creative act, adding sense and meaning to experiences made. Combining support for 'awareness' and 'reflection' bears huge potential for improving the learning and training with respect to utility, self-regulation, usability, and user experience. The ARTEL workshop series brings - for the 4th time in 2014 - together researchers and professionals from different backgrounds to provide a forum for discussing the multi-faceted area of awareness and reflection. For this year 2014, the workshop organizes discussion and meta-reflection amongst researchers around the application of awareness and reflection in practice, its impact on learners and questions of feasibility, and sustainability for awareness and reflection in education and work. This year's workshop theme is: How does computer-support for awareness and reflection need to be embedded into practical (working or learning) contexts in order for learners to benefit from such computer support

Academic Librarians with Disabilities: Job Perceptions and Factors Influencing Positive Workplace Experiences

Although there has been increasing attention to diversity in librarianship, little attention has been paid to librarians with disabilities. This study uses a mixed method approach, using results from a survey and in-depth follow-up interviews, to investigate some of the characteristics of Canadian university librarians with disabilities, their job satisfaction, their perceptions of their workplace climate for diversity and accessibility, and the factors that influence their workplace perceptions. Although librarians with disabilities report a generally high level of job satisfaction, they are less satisfied with some areas related to workplace stress and job flexibility than librarians without disabilities. Librarians with disabilities also report less confidence that their workplace is inclusive, values diversity, and is understanding of disability-related issues. Factors influencing the work experience of university librarians with disabilities include a collegial environment, supportive colleagues and supervisors, job flexibility and autonomy, clear priorities and reporting structures, reasonable expectations about workload, time pressures and short deadlines, effective structures and processes to ensure accessibility, an accessible physical environment, and, most importantly, an understanding of disability and awareness of disability-related workplace issues

Personal Profile Monitoring

Employees are the human capital which, to a great extent, contributes to the success and development of high-performance and sustainable organizations. In a work environment, there is a need to provide a tool for tracking and following-up on each employees' professional progress, while staying aligned with the organization’s strategic and operational goals and objectives. The research work within this Thesis aims to contribute to improve employees' selfawareness and auto-regulation; two predominant research areas are also studied and analyzed: Visual Analytics and Gamification. The Visual Analytics enables the specification of personalized dashboard interfaces with alerts and indicators to keep employees aware of their skills and to continuously monitor how to improve their expertise, promoting simultaneously behavioral change and adoption of good-practices. The study of Gamification techniques with Talent Management features enabled the design of new processes to engage, motivate, and retain highly productive employees, and to foster a competitive working environment, where employees are encouraged to be involved in new and rewarding activities, where knowledge and experience are recognized as a relevant asset. The Design Science Research was selected as the research methodology; the creation of new knowledge is therefore based on an iterative cycle addressing concepts such as design, analysis, reflection, and abstraction. By collaborating in an international project (Active@Work), funded by the Active and Assisted Living Programme, the results followed a design thinking approach regarding the specification of the structure and behavior of the Skills Development Module, namely the identification of requirements and the design of an innovative info-structure of metadata to support the user experience. A set of mockups were designed based on the user role and main concerns. Such approach enabled the conceptualization of a solution to proactively assist the management and assessment of skills in a personalized and dynamic way. The outcomes of this Thesis aims to demonstrate the existing articulation between emerging research areas such as Visual Analytics and Gamification, expecting to represent conceptual gains in these two research fields

Five Potential Barriers to LMS Usage

This paper began as a needs assessment investigating low Learning Management System (LMS) usage at a worldwide technology corporation. Subsequently, the company in question underwent a number of personnel changes and decide to forgo the needs assessment. As such, this paper became a review of research literature related to LMS usage barriers, with the intentions of identifying potential causes of low LMS usage in corporate environments. The review of the existing literature identified five major potential barriers to LMS usage. Because of the nature of the process, these are generalized broad barriers that can easily be identified and discovered in diverse scenarios. It posits that all five of the issues need to be resolved before a robust learning environment can be established. Any one barrier is significant enough to create usage issues. Generalized recommendations are made, but a needs assessment should be run before any real-world action is taken to resolve similar issues. Broad barriers consequently generate broad recommendations; any organization seeking to resolve similar issues will need to customize their solutions accordingly

Prerequisite-aware course ordering towards getting relevant job opportunities

Adapting learning experience according to the rapidly-changing job market is essential for students to achieve fruitful learning and successful career development. As building blocks of potential job opportunities, we focus on “technical terminologies” which are frequently required in the job market. Given a technical terminology, we aim at identifying an order of courses which contributes to the acquisition of knowledge about the terminology and also follows the prerequisite relationships among courses. To solve the course ordering problem, we develop a two-step approach, in which course-terminology relatedness is first estimated and then courses are ordered based on the prerequisite relationships and the estimated relatedness. Focusing on the second step, we propose a method based on Markov decision process (MDPOrd) and compare it with three other methods: (1) a method that orders courses based on aggregated relatedness (AggRelOrd), (2) a method that topologically sorts the courses based on personalized PageRank values (PageRankTS), and (3) a method that greedily picks courses based on the average relatedness (GVPickings). In addition to evaluating how the order prioritizes the related courses, we also evaluate from pedagogical perspectives, namely, how the order prioritizes specifically/generally fundamental courses, and how it places courses close to their prerequisites. Experimental results on two course sets show that MDPOrd outperforms the other methods in prioritizing related courses. In addition, MDPOrd is effective in ordering courses close to their prerequisites, but does not work well in highly ranking fundamental courses in the order