Kim Cliett Long
E-learning expands options for teaching and learning using technology. This nomenclature has been solidly in use for the last ten years. The expansive and ever fertile frontier of e-learning—a term used interchangeably with distance and online learning—has become standard fare as an educational delivery solution designed to enhance knowledge and performance. Many educational institutions, corporate enterprises and other entities are utilizing web-based teaching and learning methodologies to deliver education either partially or wholly online using electronic platforms. The learning value chain, including management and delivery, has created multimodal systems, content, and processes to increase accessibility, measurability, and cost effectiveness by infusing advanced learning techniques, such as adaptive learning or communities of practice, among students, employee groups, and lifelong learners. It is interesting to note that e-learning encapsulates internet based courseware and all other asynchronous and synchronous learning, as well as other capabilities for supporting learning experiences.
Student success and advancements in technology are now inextricably linked as a result of higher education institutions embracing and offering e-learning options. The absence of direct instructor guidance makes distance learning particularly difficult for some students. Certain students struggle with the lack of guidance inherent in online learning and the requisite need to work independently. In particular, the lack of high touch strategies in e-learning often leads students to drop or fail courses. While some students struggle to remain engaged in technology-enabled learning, technology is often the vehicle for keeping these same students on task. There are a variety of electronic tools designed to augment online learning and keep online learners on task. Podcasts, for example, can be easily downloaded, then played back on a student’s media player or mobile device at a later date. The student is not tied to a computer, which results in a more comprehensive learning experience.
In many cases, e-learning has become a very lucrative and desirable marketplace for higher education institutions. The business case for e-learning is a clarion call for tight integration among business, human resources, and knowledge and performance management. Hence, it is incumbent upon educational institutions to instill approaches that focus on the learner, learning, and improved performance, more so than the tools and technology. Of further importance is the need for higher education institutions to provide stratagems for developing and supporting caring online relationships, individualized student environments, collaboration, communication, and e-learning culture. Ultimately, institutions should measure not only improved business and performance, but also improved student online learning aptitudes (more self-motivated, self-directed, and self-assessed learning).
In such a complex and well-researched domain as decision support systems (DSS), with a long history of authors making insightful contributions since the 1960’s, it is critical for researchers, especially those less experienced, to have a broad knowledge of the seminal work that has been carried out by prior generations of researchers. This can serve to avoid proposing research questions which have been considered many times before, without having consideration for the answers which have been put forward by previous scholars, thereby reinventing the wheel or “rediscovering” findings about the life of organizations that have been presented long before. The study of human and managerial decision-making is also characterized by considerable depth and seminal research going back to the beginning of the 20th century, across a variety of fields of research including psychology, social psychology, sociology or indeed operations research. Inasmuch as decision-making and decision support are inextricably linked, it is essential for researchers in DSS to be very familiar with both stream of research in their full diversity so they are able to understand both what activity is being supported and how to analyze requirements for developing decision support artefacts. In addition, whilst the area of decision support has sometimes been characterized by technology-based hype, it is critical to recognize that only a clear focus on the thinking and actions of managers can provide decisive directions for research on their decision support needs. In this article, we consider first the characteristics of human cognition, before concentrating on the decision-making needs of managers and the lessons that can be derived for the development of DSS.
A geographic information system (GIS) is a system designed to capture, store, organize, and present spatial data, which is referenced to locations on the Earth. Locational information is of value for a wide range of human activities for decision-making relating to these activities. As spatial data is relatively complex, GIS represents a challenging computer application that has developed later than some other forms of computer systems. GIS uses spatial data for a region of the Earth; such regional data are of interest to a wide range of users whose activities take place in that region, and so many users in otherwise disconnected domains share spatial data. The availability and cost of spatial data are important drivers of GIS use, and the sourcing and integration of spatial data are continuing research concerns. GIS use now spans a wide range of disciplines, and the diversity created is one of the obstacles to a well-integrated research field.
Location analysis is the use of GIS for general-purpose analysis to determine the preferred geographic placement of human activities. Location analytics uses spatial data and quantitative spatial models to support decision-making, including location analysis. The growth of location analytics reflects the increasing amounts of data now available owing to new data collection technologies such as drones and because of the massive amounts of data collected by the use of mobile devices like smartphones. Location analytics allow many valuable new services that play an important role in new developments such as smart cities. Location analytics techniques potentially allow the tracking of individuals, and this raises many ethical questions, however useful the service provided; therefore, issues related to privacy are of increasing concern to researchers.