The state of higher education leadership development program evaluation: A meta-analysis, critical review, and recommendations

Building Leadership Service Academies to Institutionalize a Strategic Leadership Development Focus

In this article, we propose a strategic view of leadership development, by defining a Leadership Service Academy (LSA) construct. The LSA represents a strategic approach that enables an organization and its leaders to institutionalize its own theory of leadership, narrative, models, learning methodologies, practices, and evaluation methods for determining the impact of investing in developing leadership. The LSA construct represents a shift in strategic thinking that involves moving beyond focusing on individual leader development training programs used for satisfying current role-requirements or tactical succession planning, to adopting a systemic view of leadership development aligned with the organization's strategic objectives, mission, values, and culture. Most leadership development research has focused on examining the efficacy of training methodologies linked to individual leadership models and modalities and has produced promising results. However, the narrow focus on individual leadership development has excluded the full spectrum of leadership development interventions from being explored and analyzed. Our primary goal here is to explore a comprehensive strategy for building a sustainable, multi-level leadership development system firmly anchored in both science and practice.

Influence Mechanism of Educational Leadership on Environmental Accounting Based on Big Data Algorithm

Over the last 20 years, big data techniques in teaching have been overgrown. Making educational decisions now includes information knowledge as a crucial component. This started a trend for using big data algorithms strategically. Technological advances have been used to analyze the enormous amount of information and develop strategic judgments. The current study aims to address issues with the conventional instructional, administrative management solution focused on manual rule formulation in big data storage and interpretation and has poor efficiency in analyzing big data and lacking value in developing education leadership qualities. The study suggests an educational leadership model based on big data algorithm (ELM-BDA) to explore the student leadership performance that relies on cooperative filtration and fuzzy C-means (FCM) and big data. The different influencing mechanisms and factors directly linked to educational leadership were also analyzed using a big data algorithm. To build an intelligent institutional administrative system, the research also exposes it to organizational studies. By evaluating the big data research already in existence, this study emphasizes the expanding significance of big data. Additionally, this study explores the effects of big data analytics on educational leadership qualities by utilizing an FCM. A scoring system is designed to predict the student's leadership level, and using the big data algorithms, the students are motivated and trained to improve their skills. The education and learning method can be enhanced at educational institutions through better decision-making to use this big data for leadership development. Big data facilitates efficient educational decision-making by merging various data and telecommunications technologies. Using big data in schooling will increase—leadership quality among students. To effectively use big data for decision-making, academic leaders must create new types of learning and monitoring systems.

Walking Our Evidence-Based Talk: The Case of Leadership Development in Business Schools

Academics have lamented that practitioners do not always adopt scientific evidence in practice, yet while academics preach evidence-based management (EBM), they do not always practice it. This paper extends prior literature on difficulties to engage in EBM with insights from behavioral integrity (i.e., the study of what makes individuals and collectives walk their talk). We focus on leader development, widely used but often critiqued for lacking evidence. Analyzing 60 interviews with academic directors of leadership centers at top business schools, we find that the selection of programs does not always align with scientific recommendations nor do schools always engage in high-quality program evaluation. Respondents further indicated a wide variety of challenges that help explain the disconnect between business schools claiming A but practicing B. Behavioral Integrity theory would argue these difficulties are rooted in the lack of an individually owned and collectively endorsed identity, an identity of an evidence-based leader developer (EBLD). A closer inspection of our data confirmed that the lack of a clear and salient EBLD identity makes it difficult for academics to walk their evidence-based leader development talk. We discuss how these findings can help facilitate more evidence-based leader development in an academic context.

Toward Optimized Effectiveness of Employee Training Programs

Abstract. Although organizations invest heavily on employee training, the effectiveness of employee training programs has not been well-established. In the current study, we examine the training delivery features of employee training programs to derive a better understanding of features that may be of best benefit in the improvement of employee affective outcomes. Specifically, and via the use of meta-analysis ( k = 79 studies totaling 107 independent effect sizes), we focus on two broad classes of affective employee training outcomes including attitudinal and motivational outcomes. Results evidence support for the effectiveness of employee workplace training interventions and indicate that employee training programs associated with attitudinal versus motivational outcomes require different features while being delivered to reach optimal effectiveness.

Motivation and Evaluation in Education from the Sustainability Perspective: A Review of the Scientific Literature

(1) Background: This paper outlines the results of a literature review of meta-analyses published on motivation and evaluation in the last five years. (2) Methods: A systematic review of three educational databases (WoS, SCOPUS and ERIC) was conducted following the PRISMA and PICO approaches. A total of 54 peer-reviewed meta-analysis papers were selected, analysed and compared. (3) Results: A significant number and variety of meta-analyses have been conducted: motivation meta-analyses focus primarily on contextual variables, self-regulation and students’ academic performance, and evaluation meta-analyses examine the effectiveness of the teaching intervention, the use of teaching methodologies and technological resources for learning. (4) Conclusions: There are two important absences: on the one hand, it is necessary to develop meta-analyses that combine motivation and evaluation, also measuring their interaction, from the perspective of sustainability, and not only of educational improvement, and on the other hand, it is necessary to perform meta-analyses on the effectiveness of the formative and shared evaluation of the sustainability of learning processes.