This paper describes a neural network model that can be used to detect at- risk students failing a particular course using only grade book data from a learning management system. By analyzing data extracted from the learning management system at the end of week 5, the model can predict with an accuracy of 88% whether the student will pass or fail…

Advances in data analytics and intelligent technologies are enabling smart learning environments that promote personalized learning. Personalized learning systems where learners engage with information in a manner tailored to their unique needs, goals, and abilities have garnered significant academic research attention. If students can achieve…

Since 2016, the Advanced Distributed Learning (ADL) Initiative has been developing the Total Learning Architecture (TLA), a 4-pillar data strategy for managing lifelong learning. Each pillar describes a type of learning-related data that needs to be captured, managed, and shared across an organization. Each data pillar is built on a set of…

The use of machine learning with educational data mining (EDM) to predict learner performance has always been an important research area. Predicting academic results is one of the solutions that aims to monitor the progress of students and anticipates students at risk of failing the academic pathways. In this paper, we present a framework for…

This paper describes investigations in visualizing logpaths of students in an online calculus course held at Florida State University in 2014. The clickstreams making up the logpaths can be used to visualize student progress in the information space of a course as a graph. We consider the graded activities as nodes of the graph, while information…

With the adoption of Learning Management Systems (LMSs) in educational institutions, a lot of data has become available describing students' online behavior. Many researchers have used these data to predict student performance. This has led to a rather diverse set of findings, possibly related to the diversity in courses and predictor variables…

Individualization of learning through ICT [Information and Communication Technology] allows to students not only the possibility choose the time and place to study, but especially pace adoption of new knowledge on the basis of preferred learning styles. Analysis of learning processes should give the answer to difficult questions from pedagogical…

Annotations play an increasingly crucial role in scientific exploration and discovery, as the amount of data and the level of collaboration among scientists increases. There are many systems today focusing on annotation management, querying, and propagation. Although all such systems are implemented to take user input (i.e., the annotations…

Over the years, companies have relied on On-Line Analytical Processing (OLAP) to answer complex questions relating to issues in business environments such as identifying profitability, trends, correlations, and patterns. This paper addresses the application of OLAP in education and learning. The objective of the research presented in the paper is…

The intention of this qualitative study was to explore the effects that instructional data systems have on a building level leader's capacity to evaluate student growth and inform principal practice. Principal leadership practices were examined through the lens of Kouzes and Postners' five practices of exemplary leadership (Kouzes & Posner,…

Faced with rising demand for information about early childhood programs, states need to find tools and strategies to monitor the progress of and to identify high-quality early childhood programs. In response, REL Mid-Atlantic convened a regional workgroup for state personnel who work with the systems containing early childhood data. The workgroup…

This teaching case discusses the analysis of an electronic voting system. The development of the case was motivated by research into information security and management, but as it includes procedural aspects, organizational structure and personnel, it is a suitable basis for all aspects of systems analysis, planning and design tasks. The material…

Too often computer applications try to supplant rather than augment human capabilities. As a result, there is a gap between the power of the computer and some difficult administrative problems; e.g., longrange planning. However, there is increasing interest in the use of computer simulation in planning. PLANTRAN II represents a completely new…

This paper examines the application of different planning models to the new product development process. Various models are discussed in relation to the four principal stages of the process: product search, project development, market structure analysis, and investment analysis. The authors emphasize that all useful planning models must address a…