Kautish / Dutta / Nagpal Data-Informed Leadership in Higher Education: An Executive Playbook for Institutional Excellence

1. Auflage 2025
ISBN: 979-8-89881-126-6
Verlag: Bentham Science Publishers
Format: EPUB
Kopierschutz: 0 - No protection

E-Book, Englisch, 255 Seiten

Reihe: Advances in Data Science Driven Technologies

Advances in Data Science Driven Technologies (Volume 5): Data-Informed Leadership in Higher Education is an executive playbook for institutional excellence. It demonstrates how purposeful faculty development, human-centred design, and data-informed leadership transform technology investments into improved learning outcomes, equity, and graduate success. Spanning thirteen chapters, the book moves from people to platforms-building the educator's toolkit, embedding analytics-driven quality assurance, and integrating immersive technologies such as virtual reality. Case studies, policy-aligned frameworks, and implementation playbooks equip readers with a roadmap to redesign curricula, elevate student experience, and lead sustainable digital transformation. Key Features Upskills faculty and leaders with evidence-based frameworks. Guides faculty developers in the redesigning of courses and programmes with structured approaches. Provides toolkits for data-driven decision-making and student-success analytics. Translates strategy into classroom practice through reviews and case studies. Enables readers to implement and scale innovations with practical checklists and plans.

Autoren/Hrsg.

Kautish, Sandeep

Dutta, Pushan Kumar

Nagpal, Namrata

Leseproben

Data-Informed Leadership in Higher Education Institutions for Improved Decision-Making in a Digital Era

M. Arun1, *, C. Prajitha2

1 Department of Mechanical Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Thandalam-602105 India

2 Department of Electronics and Communication Engineering/Centre for Interdisciplinary Research, Karpagam Academy of Higher Education, Coimbatore, India

Abstract

Transformational leadership in higher education emphasizes collaborative responsibility-sharing among faculty with diverse expertise, enabling effective responses to the multifaceted challenges of academic leadership. The article emphasizes the necessity of data-informed leadership for decision-making tools in higher education institutions (HEIs) to foster sustainable development and boost academic performance. Methods of data analytics, such as learning analytics, transformational leadership, business intelligence, and educational data mining, should be used by educational institutions to extract valuable insights and information from educational data. Since universities are still not using decision support systems to their full potential, despite providing several benefits, they need more study and implementation of these systems. The purpose of this research is to analyze this matter by describing the benefits of data-informed leadership for decision-making at higher education institutions (HEIs) and evaluating a variety of tools and frameworks, like an academic prediction model and a course recommendation system, based on their capacity to support educational decision-making. These resources are designed to help define educational theories, frameworks, and phenomena so that we may identify the most essential aspects of learning and use that information to design more effective learning systems. Companies and placement agencies may use these technologies to find people who might be good trainers or hires. Helping students make more well-informed course choices and improving the effectiveness of educational administration are possible outcomes of their work.

Keywords: Digital era, Decision-making, Data analytics methods, Data-informed leadership, HEI.

* Corresponding author M. Arun: Department of Mechanical Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Thandalam- 602105, India;
E-mail: [e-mail]

INTRODUCTION

In the face of global competition, universities are adopting innovative leadership approaches to foster sustainable growth. Unlike other industries, higher education occupies a distinctive role as a hub for knowledge creation and dissemination, driving human capital development and addressing societal challenges. To contribute to the growth of almost every economic sector, universities produce competent human capital by leading research initiatives that bring many institutions' attention to societal weaknesses and unsolved challenges. Consequently, for universities to succeed, they need academic administrators who can carry out their responsibilities with the highest level of competence, integrity, and moral fiber. Research, supervision, administration, job placement, event planning, and extracurricular activities are just a few of the numerous tasks that fall on the bears of education leaders. Demand for higher education is changing, which requires long-term beliefs about the institution's ideal management and leadership structures and its role in society and the world. Leadership in universities is seen as a shared responsibility in the conventional university model, characterized by a community of academics with an extremely democratic and decentralized decision-making progression. On the other hand, institutional or entrepreneurial leadership and management methods are becoming more common in universities. Leadership styles in higher education have been the subject of recent research on the effects on quality, effectiveness, hard work, citizenship, perceptions of organizational support, and task satisfaction. All higher education institutions aim to provide high-quality education. Many HEIs get financing based on student enrollment and research [1]. This requires ongoing monitoring of HEI operations and management choices that ensure excellent education. HEI management must make everyday choices to follow strategy and meet objectives [2]. This higher education management setting demands solid assistance for management choices [3]. Higher education management increasingly values reliable and accessible data for fundamental operations and strategic planning [4]. Many contemporary institutions seek solutions to better their conventional management procedures and overcome their issues [5].

HEIs have relied more on data gathering, storage, and processing. Modern HEIs use student data systems, human resource systems, learning management systems, scientific actions reporting systems, and rich datasets from exterior systems to support management decisions and enhance ongoing procedures [6]. If HEI leadership does not see the strategic importance of data and use it to make data-informed choices, the data is useless. With so many systems, HEI executives struggle to get the right information for decision-making [7]. Data gathering and analysis need human resources and laborious reading of endless data streams. The data supplied does not reflect the HEI's present state of play and must be reanalyzed if the management wants updated data [8]. This increases HEI leadership's interest in utilizing gathered and processed data for decision-making. They are applying new policies and solutions to extract data from software systems and turn it into knowledge that helps process management, optimization, and development in all key areas and informs strategic decisions at all organizational levels [9]. It is recommended that investments be made in technologies such as learning analytics, educational data mining, business intelligence, academic analytics, and semantic and linked-data technologies to support all management activities.

Data analysis tools automatically extract, analyze, and classify data from various systems [10]. They enable HEI leadership to watch and analyze trends and Key Performance Indicators (KPI) performance using straightforward dashboards that provide summary data in graphical form and discover hidden patterns, trends, and anomalies [11]. HEI leadership uses the data to manage the institution better, assess the effectiveness of its activities, make strategic choices to improve procedures, and gather evidence for decision-making [12]. Higher education institutions (HEIs) may benefit from these technologies by monitoring student progress, enrollment patterns, academic output, professional growth, financial management, regulatory compliance, research, and other continuous activities related to education and research [13].

This paper contributes to better insight and control over operations, less chance of damage from mistakes, more valid management decisions that contribute to HEIs' sustainable development, and time and money saved by not having to employ specialists to find pertinent information as ways software solutions can improve decision-making for HEI managers. In higher education, decision-making systems reduce time and money spent on problem identification and optimal decision-making. Using a data-informed leadership framework and decision-making systems, the higher education system may save time and money by describing problems more precisely and finding the most effective solutions.

Related Work

When adopting a data-driven culture, companies are said to undergo a cultural shift toward a more business-oriented model. Firms' product and process improvements are believed to benefit significantly from it. Several companies have recently enhanced their performance using various business analytics (BA) products, including innovative technologies [14]. Once again, businesses have been able to investigate the possibility of using BA tools with artificial intelligence because of advancements in information and communication technology. Because of this, there has been an enormous change in the corporate culture that helps companies make better decisions, boosting their creativity and productivity. Background research, a resource-based perspective model, and several theories have established a conceptual model. With the help of several business analytics tools, suitable replies were collected from workers of various organizations, validating the conceptual model. According to the report, product and process innovation are boosted by a data-driven culture, which makes the company more competitive. The study's moderators include a data-driven culture and strong leadership, whereas the control variables are company age, size, and industry.

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