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This study focuses on leadership in organizations where big data analytics (BDA) is an essential component of corporate strategy. While leadership researchers have conducted promising studies in the field of digital transformation, the impact of BDA on leadership is still unexplored.

This study is based on semi-structured interviews with 33 organizational leaders and subject-matter experts from various industries. Using a grounded theory approach, a framework is provided for the emergent field of BDA in leadership research.

The authors present a conceptual model comprising foundational competencies and higher order roles that are data analytical skills, data self-efficacy, problem spotter, influencer, knowledge facilitator, visionary and team leader.

This study focuses on BDA competency research emerging as an intersection between leadership research and information systems research. The authors encourage a longitudinal study to validate the findings.

The authors provide a competency framework for organizational leaders. It serves as a guideline for leaders to best support the BDA initiatives of the organization. The competency framework can support recruiting, selection and leader promotion.

This study provides a novel BDA leadership competency framework with a unique combination of competencies and higher order roles.

A literature review of 28 data literacy, education articles from 2010 to 2018 was conducted to gain a better understanding of the current state of data literacy research.

A systematic literature review of ERIC, Education Source, and JSTOR was conducted. Articles were included in this literature review if they focused on “data literacy” for K-12 teachers or leaders.

Results demonstrated that the concept of data literacy has become more concrete, but there is still disagreement about the parameters of the construct. While data literacy was shown to be gaining in importance, training from schools of education were focused heavily on assessment literacy. Four recommendations are made as follows: (1) create skill-focused educator prep programs, (2) encourage opportunities for collaboration, (3) model data use from both quantitative and qualitative sources and (4) investigate the role of technology and big data on data literacy.

The scope of this literature review was very narrow and, as such, does not fully encapsulate data-driven decision-making in K-12 education overall.

Data literacy is important for both teachers and leaders, as educational environments strive to better understand individual learners and improve learning outcomes. This literature review looks to pull together the current status of data literacy research with hopes of inspiring more targeted research that influences training practices for both teachers and leaders.

This paper aims to investigate the effectiveness of Language Enhancement Program (LEP) activities in enhancing the oral communication skills of English as a Foreign Language (EFL) students at King Khalid University.

A mixed-method study design was used. Simple random sampling techniques were adopted to recruit the study participants. For the survey, a total of 58 male students were recruited and for interviews, 20 male students were selected. The 58 participants were randomly divided into experimental and control groups. The traditional method was adopted to teach the control group, while LEP activities were conducted to teach the experimental group.

A post-test was conducted to examine the oral communication skills of the participants of the experimental group. The scores of both groups were analyzed using a t-test value at a significant level of 0.05. The content analysis method was adopted to assess the enhancement of the oral communication of the students enrolled in the LEP. The questionnaires and interview results showed that the LEP program has a central focus on improving students' oral communication skills.

It is limited to the EFL students at King Khalid University.

LEP is a good program and can be implemented in Saudi Universities.

Students can interact with one another through the LEP activities that promote their English proficiency as well as their personality characteristics.

The paper spells out the role of LEP activities in improving students' oral communication in English and students' opinions about LEP activities in enhancing their English language in different types of communicative contexts. Further, it suggests some pedagogical implications for overcoming the difficulties faced by EFL students in various communicative contexts.

Analytics technologies are profoundly changing the way in which organizations generate economic and social value from data. Consequently, the professional roles of data scientists and data analysts are in high demand in the labor market. Although the technical competencies expected for these roles are well known, their behavioral competencies have not been thoroughly investigated. Drawing on the competency-based theoretical framework, this study aims to address this gap, providing evidence of the emotional, social and cognitive competencies that data scientists and data analysts most frequently demonstrate when they effectively perform their jobs, and identifying those competencies that distinguish them.

This study is exploratory in nature and adopts the competency-based methodology through the analysis of in-depth behavioral event interviews collected from a sample of 24 Italian data scientists and data analysts.

The findings empirically enrich the extant literature on the intangible dimensions of human capital that are relevant in analytics roles. Specifically, the results show that, in comparison to data analysts, data scientists more frequently use certain competencies related to self-awareness, teamwork, networking, flexibility, system thinking and lateral thinking.

The study was conducted in a small sample and in a specific geographical area, and this may reduce the analytic generalizability of the findings.

The skills shortages that characterize these roles need to be addressed in a way that also considers the intangible dimensions of human capital. Educational institutions can design better curricula for entry-level data scientists and analysts who encompass the development of behavioral competencies. Organizations can effectively orient the recruitment and the training processes toward the most relevant competencies for those analytics roles.

This exploratory study advances our understanding of the competencies required by professionals who mostly contribute to the performance of data science teams. This article proposes a competency framework that can be adopted to assess a broader portfolio of the behaviors of big data professionals.

The purpose of this paper is to explore the key ingredients that people analytics teams require to contribute to organizational performance. As the information that is currently available is fragmented, it is difficult for organizations to understand what it takes to execute people analytics successfully.

To identify the key ingredients, a narrative literature review was conducted using both traditional people analytics and broader business intelligence literature. The findings were summarized in the People Analytics Effectiveness Wheel.

The People Analytics Effectiveness Wheel identifies four categories of ingredients that a people analytics team requires to be effective. These are enabling resources, products, stakeholder management and governance structure. Under each category, multiple sub-themes are discussed, such as data and infrastructure; senior management support; and knowledge, skills, abilities and other characteristics (KSAOs) (enablers).

Many organizations are still trying to set up their people analytics teams, and many others are struggling to improve decision-making by using people analytics. For these companies, this paper provides a comprehensive overview of the current literature and describes what it takes to contribute to organizational performance using people analytics.

This paper is designed to provide organizations and researchers with a comprehensive understanding of what it takes to execute people analytics successfully. By using the People Analytics Effectiveness Wheel as a guideline, scholars are now better equipped to research the processes that are required for the ingredients to be truly effective.

Human resource analytics (HRA) is an HR activity that companies and academics increasingly pay attention to. Existing literature conceptualises HRA mostly from an objectivist perspective, which limits understanding of actual HRA activities in the complex organisational environment. This paper therefore draws on the practice-based approach, using a novel framework to conceptualise HRA-as-practice.

The authors conducted a systematic literature review of 100 academic and practitioner-oriented publications to analyse existing HRA literature in relation to practice theory, using the “HRA-as-practice” frame.

The authors identify the main practices involved in HRA, by whom and how these practices are enacted, and reveal three topics in nomological network of HRA-as-practice: HRA technology, HRA outcomes and HRA hindrances and facilitators, which the authors suggest might actualize enactment of HRA practices.

The authors offer HR function and HR professionals a basic ground to evaluate HRA as a highly contextual activity that can potentially generate business value and increase HR impact when seen as a complex interaction between HRA practices, HRA practitioners and HRA praxis. The findings also help HR practitioners understand multiple factors that influence the practice of HRA.

This systematic review differs from the previous reviews in two ways. First, it analyses both academic and practitioner-oriented publications. Second, it provides a novel theoretical contribution by conceptualising HRA-as-practice and comprehensively compiling scattered topics and themes related to HRA.

This paper aims to examine the actions lecturers, universities and their administrators can take in improving and making political science undergraduate degrees more relevant in the twenty-first century. This paper will reflect on specific measures undertaken by institutions globally to equip students with unique skills to enhance the value and relevance of their programmes in the context of an increased technologically driven environment.

This paper uses a qualitative approach to the review of the literature with implications for practice in examining how universities globally are applying strategies in raising students’ skill levels to enhance future workplace value. A review of select institutions obtained from the Times Higher Ranked (2019) universities was used in identifying best practices to prepare a political science student for better employability.

Contrary to prevailing opinions, a huge skills gap exists for filling the demand for twenty-first century political science-related careers in the public and private sector. The attainment of twenty-first century skill sets and the deployment of technology-driven teaching and learning methods are vital elements in unlocking the value of political science education and providing students with opportunities to advance their professional and career objectives.

Higher education institutions need to reconsider their strategies in the delivery of political science degrees, bearing in mind the increased use of technology and innovative teaching practices. This paper offers insight into how to tailor an exciting and relevant political science programme for the future of work.

Drawing on Bandura’s social learning theory (SLT), the purpose of this paper is to investigate, analytically, the impact that after-training skills level (i.e. perceived skill match) has on change self-efficacy. Moreover, this research also aims to identify which specific skills sets (if any) act as a protective factor during organizational change, supporting the change confidence (CC) level of the people involved.

Quantitative research was carried out on a sample of 200 workers in the bank sector.

Findings of this study suggest that skill match has a significant impact on the CC level. Furthermore, this study demonstrates that, even in front-office jobs, a perceived skill match of soft skills does not have a significant impact on staff CC, unlike that suggested by common sense and by literature.

Future research should investigate if and how a training process enables change self-efficacy over time or instead shows its utility only when it is relating to a specific and limited period.

This study suggests that in designing training, top and middle management should pay specific attention to change recipients’ needs by adopting a bottom-up approach. Moreover, to improve training effectiveness, it would be advisable to also train change recipients’ supervisors.

This study has social implications in suggesting how to foster the adaptive capabilities of change recipients in current turbulent times. In doing so, it suggests how to prevent some undesirable change consequences such as anxiety, intention to quit, work-related stress and change cynicism.

This paper shows that, from a methodological point of view, it is necessary to evaluate training effectiveness at the level of a specific skill area and not simply by comparing the trained/not trained people, as typically practiced until now.