This paper examines ways in which the ethics of data-driven technologies might be (re)politicised, particularly where educational institutions are involved. The recent proliferation of principles, guidelines, and frameworks for ethical 'AI' (artificial intelligence) have emerged from a plethora of organisations in recent years, and seem poised to…

Selecting undergraduate majors or specializations is a crucial decision for students since it considerably impacts their educational and career paths. Moreover, their decisions should match their academic background, interests, and goals to pursue their passions and discover various career paths with motivation. However, such a decision remains…

Statewide longitudinal data systems (SLDSs) can enable researchers, policymakers, and practitioners to identify and understand important relationships and trends across the education-to-workforce continuum. A well-developed SLDS can increase state and territory governments' ability to establish more informed and equitable policies, enable agency…

This paper describes an innovative approach for teaching the challenges in the management of data warehouse development. The approach contains lecture material providing conceptual background about the management of data warehouse development, a simulation game supporting experiential learning, and a post-play debriefing to support synthesis of…

Educational Data Mining is an emerging discipline which seeks to develop methods to explore large amounts of data from educational settings, in order to understand students' behavior, interests and results in a better way. In recent years there have been various works related to this specialty and multiple data mining techniques derived from this…

Data-informed instructional methods offer tremendous promise for increasing the effectiveness of teaching, learning, and schooling. Yet-to-be-developed data science approaches have the potential to dramatically advance instruction for every student and to enhance learning for people of all ages. Next steps that emerged from a recent National…

Purpose: The purpose of the paper is to provide a thorough analysis of the concepts of business intelligence (BI), knowledge management (KM) and analytical CRM (aCRM) and to establish a framework for integrating all the three to each other. The paper also seeks to establish a KM and aCRM based framework using data mining (DM) techniques, which…

Academic standards and performance outcomes are a major focus of the current Cycle 2 Australian Universities Quality Agency (AUQA) audits. AUQA has clearly stated that universities will need to provide "evidence of setting, maintaining, and reviewing institutional academic standards and outcomes" (2010, p. 27). To do this, universities…

The Hint Factory is an implementation of our novel method to automatically generate hints using past student data for a logic tutor. One disadvantage of the Hint Factory is the time needed to gather enough data on new problems in order to provide hints. In this paper we describe the use of expert sample solutions to "seed" the hint generation…

Despite all the speeches, articles, and meetings about data-based instructional decision making, the author's observation after more than 20 years of working with middle and high school teams is that teachers and administrators often make important instructional decisions on the basis of historical precedent, anecdotal information, experience, or…

In building intelligent tutoring systems, it is critical to be able to understand and diagnose student responses in interactive problem solving. However, building this understanding into a computer-based intelligent tutor is a time-intensive process usually conducted by subject experts. Much of this time is spent in building production rules that…

In this dissertation we develop a framework that combines data mining, statistics and operations research methods for improving real-time decision support systems in healthcare. Our approach consists of three main concepts: data gathering and preprocessing, modeling, and deployment. We introduce the notion of offline and semi-offline modeling to…

A study was conducted to propose a research-based model for a longitudinal data research system that addressed recommendations from a synthesis of literature related to: (1) needs reported by the U.S. Department of Education, (2) the twelve mandatory elements that define federally approved state longitudinal data systems (SLDS), (3) the…

A management information system (MIS) is a systems approach to data processing. It provides relevant, timely, and accurage data to decisionmakers, as well as information storage, retrieval, and transfer functions through the use of computers. Educational administrators have been slow to implement computerized data processing either because they…

Discusses the objectives in constructing a centralized and computerized data bank for a school system and the uses to which such a bank could be put. (LS)