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The purpose of this paper is to develop a holistic model for educational purposes using data‐mining techniques for exploring the effects of probable changes in processes related to admissions, course delivery and recruitments.

The paper proposes a framework for an effective educational process using data‐mining techniques to uncover the hidden trends and patterns and making accuracy based predictions through a higher level of analytical sophistication in the process of counselling students.

Data‐mining tools are used in academia for capitalizing on the advances of information technology. This process improves research and academic decision making through uncovering hidden trends and patterns that predict using a combination of explicit knowledge base, sophisticated analytical skills and academic domain knowledge.

The paper presents a model using a data‐mining approach for academics.

The purpose of this paper is to demonstrate the utility of combining event-centred and variable-centred approaches when analysing big data for higher education institutions. It uses a large, university-wide data set to demonstrate the methodology for this analysis by using the case study method. It presents empirical findings about relationships between student behaviours in a learning management system (LMS) and the learning outcomes of students, and further explores these findings using process modelling techniques.

The paper describes a two-year study in a Chilean university, using big data from a LMS and from the central university database of student results and demographics. Descriptive statistics of LMS use in different years presents an overall picture of student use of the system. Process mining is described as an event-centred approach to give a deeper level of understanding of these findings.

The study found evidence to support the idea that instructors do not strongly influence student use of an LMS. It replicates existing studies to show that higher-performing students use an LMS differently from the lower-performing students. It shows the value of combining variable- and event-centred approaches to learning analytics.

The study is limited by its institutional context, its two-year time frame and by its exploratory mode of investigation to create a case study.

The paper is useful for institutions in developing a methodology for using big data from a LMS to make use of event-centred approaches.

The paper is valuable in replicating and extending recent studies using event-centred approaches to analysis of learning data. The study here is on a larger scale than the existing studies (using a university-wide data set), in a novel context (Latin America), that provides a clear description for how and why the methodology should inform institutional approaches.

Purpose – This paper aims to describe the process and the outcome of a situation in which a professor of anatomy and physiology made supplemental use of a course management system (CMS) to assist with the instruction of 242 students. The purpose of this instructor's use of WebCT was to: increase student autonomy and improve access to information; improve student learning and achievement through the expert use of student “Self‐Tests”, which are an ungraded, interactive tutoring/quizzing feature; create a more active, student‐centered learning environment. Design/methodology/approach – Features that were provided in the WebCT site include: student self‐tests are ungraded, but act as a basic form of expert system or informative tutor by providing very specific feedback to answers students selected in this multiple choice experience. The feedback to each question was designed by the instructor, who advised students to use the system as a tutor by clicking on a variety of possible answers to gather new information. Comments on answers were designed to demonstrate to the student the “way of thinking” of a professional in the field. Current grade information for individual students. Schedule‐related information on labs, due dates, etc. syllabus lecture audio. Findings – Findings suggest that the implementation of the WebCT self‐tests contributed to the substantial increase in student test scores. Research limitations/implications – The implications are very exciting and far‐reaching in that – through a fairly unobtrusive course re‐design – the use of a CMS yielded a measurable improvement in student achievement. Practical implications – The use of these expert‐system‐like self‐tests, gradebooks, and other CMS features has the potential to improve teaching and learning in all manner of courses, including those that are on‐ground, blended, and fully online. Originality/value – This paper uses concrete data to demonstrate how a course management system was used to re‐design traditional courses and how this re‐design resulted in improved student achievement.

Artificial intelligence (AI) refers to a type of algorithms or computerized systems that resemble human mental processes of decision-making. This position paper looks beyond the sensational hyperbole of AI in teaching and learning. Instead, this paper aims to explore the role of AI in educational leadership.

To explore the role of AI in educational leadership, I synthesized the literature that intersects AI, decision-making, and educational leadership from multiple disciplines such as computer science, educational leadership, administrative science, judgment and decision-making and neuroscience. Grounded in the intellectual interrelationships between AI and educational leadership since the 1950s, this paper starts with conceptualizing decision-making, including both individual decision-making and organizational decision-making, as the foundation of educational leadership. Next, I elaborated on the symbiotic role of human-AI decision-making.

With its efficiency in collecting, processing, analyzing data and providing real-time or near real-time results, AI can bring in analytical efficiency to assist educational leaders in making data-driven, evidence-informed decisions. However, AI-assisted data-driven decision-making may run against value-based moral decision-making. Taken together, both leaders' individual decision-making and organizational decision-making are best handled by using a blend of data-driven, evidence-informed decision-making and value-based moral decision-making. AI can function as an extended brain in making data-driven, evidence-informed decisions. The shortcomings of AI-assisted data-driven decision-making can be overcome by human judgment guided by moral values.

The paper concludes with two recommendations for educational leadership practitioners' decision-making and future scholarly inquiry: keeping a watchful eye on biases and minding ethically-compromised decisions.

This paper brings together two fields of educational leadership and AI that have been growing up together since the 1950s and mostly growing apart till the late 2010s. To explore the role of AI in educational leadership, this paper starts with the foundation of leadership—decision-making, both leaders' individual decisions and collective organizational decisions. The paper then synthesizes the literature that intersects AI, decision-making and educational leadership from multiple disciplines to delineate the role of AI in educational leadership.

Government administrative data have enormous potential for public and individual benefit through improved educational and health services to citizens, medical research, environmental and climate interventions and better use of scarce energy resources. The purpose of this study (part of the Administrative Data Research Centre in England, ADRC-E) was to examine perspectives about the sharing, linking and re-use (secondary use) of government administrative data. This study seeks to establish an analytical understanding of risk with regard to administrative data.

This qualitative study focused on the secondary use of government administrative data by academic researchers. Data collection was through 44 semi-structured interviews plus one focus group, and was supported by documentary analysis and a literature review. The study draws on the views of expert data researchers, data providers, regulatory bodies, research funders, lobby groups, information practitioners and data subjects.

This study discusses the identification and management of risk in the use of government administrative data and presents a risk framework.

This study will have resonance with records managers, risk managers, data specialists, information policy and compliance managers, citizens groups that engage with data, as well as all those responsible for the creation and management of government administrative data.

First, this study identifies and categorizes the risks arising from the research use of government administrative data, based on policy, practice and experience of those involved. Second, it identifies mitigating risk management activities, linked to five key stakeholder communities, and it discusses the locus of responsibility for risk management actions. The conclusion presents the elements of a new risk framework to inform future actions by the government data community and enable researchers to exploit the power of administrative data for public good.

Educational management's main task is to achieve learning quality outcomes in acquiring knowledge, scientific skills and social values. This study aims to provide a background on Egyptian thought development in educational management from 1990 to 2020.

In this study, we used the descriptive method to collect and interpret data. This method aims to describe an object of phenomena after data collection, analyze it, identify the conditions and relationships between variables and monitor the challenges arising from Egypt's educational system's problems.

The results showed the following: (1) the trend toward decentralization of educational management is not fulfill during that period and (2) the district and directorate administration continued to receive administrative instructions from the managerial ladder's highest authorities. The Ministry of Education was in control of policy decision-making processes and administrative and financial responsibilities. Many decisions and laws hinder decentralization, such as centralizing examinations, curricula and teachers' recruitment and transfer.

The challenges of developing educational management are related to the shortage of modern management methods in administrative leadership, organizational behavior and decision-making, such as human relations and decentralized administration. Also, the insufficient material resources, managerial competencies and educational, intellectual stagnation among many leaders and administrators.

The information age is upon us. In schools across the country, administrators are making important decisions about how best to employ computer technology. This case study of an expert educational administrator looks at computer use from a problem‐solving perspective, focusing on the relationship between how this school leader thinks about and acts on technological capacity. It examines the personal attributes and perceptions that underlie his effective application of technology and finds them interwoven with the same cognitive and behavior skills he employs across his problem solving. It explores the connections he makes between school and community and between administrative and instructional technology.

What do school administrators do when discharging their administrative responsibilities? How do they spend their days? Their weeks? Their years? What constitutes the basic content of their administrative behavior? Despite decades of research in educational administration, we are unable to answer these deceptively simple, but fundamental questions. This lacuna in the literature provided encouragement for pursuing this present study as a relatively untapped approach to describing and analysing the administrative behavior of school superintendents. The central problem of the study was to observe and describe the actual on‐the‐job behavior of the superintendent of schools so as to develop a composite view of his administrative behavior.