Informing Science and Andragogy: A Conceptual Scheme of Client-Side Barriers to Informing University Students

Introduction The teaching of adults, or andragogy, is an important social and economic reality. Colleges and universities are applying andragogical theories to their curriculum in order to tap this rich source of students. Further, the widespread availability of the Internet, combined with the proliferation of computer technology, has heightened interest in andragogy. Burge (1988) noted that, "DL research, as opposed to traditional education research, focuses more on how adults learn. " In the latest figures from the U.S. Department of Education, Institute of Education Sciences, in 2005, 44 percent of American adults aged 17 and older participated in a program, class, or course (U.S. Department of Education, National Center for Educational Statistics, 2007). Because the continuing education of adults increases the private, social, and economic value of our human capital (Lang, 2003), it is important to identify, understand, address, and overcome barriers and biases working against adult learning. In this research, we look to two fields, informing science and education, to aid in this quest. Overview of the Goals and Methodology of this Research This paper does not report upon an empirical study. Rather, our goal is to combine education and informing science research to develop a conceptual model that will assist university professors and students in identifying and overcoming barriers to informing. Since a full study of all barriers, those on the part of the informer, the channel, and the client, would be too extensive for a single paper, we focus in this manuscript on the client-side barriers, i.e., those inherent in the student or the student's immediate situation. In terms of methodology, we look first at informing science research. Then we consider existing education research on teaching at the university level. Thirdly, we use research from both these domains to develop a conceptual scheme of client-side barriers to informing university students. Gill (2011b) noted that the development of a conceptual scheme has as its goal, not representing absolute truth (for that is the job of theory), but rather providing a useful way to conceptualize. Our model is designed to assist faculty and students in conceptualizing barriers to learning at the university level. After developing the model, we evaluate it by using Gill's (2011b) principle that defines usefulness as the intersection of three characteristics: relevant, acceptable, and potentially actionable. Finally, we conclude with a consideration of the contributions, limitations, and future implications of this work. A Note about Terminology While the education literature speaks primarily of barriers, the informing science literature also uses the term filters. Similarly, where the education literature speaks of a teacher, faculty member, or instructor, the informing science literature uses the term informer. Where the education literature speaks of educational technology, learning management systems, and specific methods or pedagogies, the informing science literature refers to channels. Since this research is focused on the intersection of informing science and education, we use these sets of terms interchangeably, relying more on traditional education terminology when discussing education and on informing science terminology when discussing informing science. Background: Barriers in Informing Science Informing science has been defined as "a trans-disciplinary study of systems that employ information to impact clientele" (Gill, 2011a). Note that clientele are not passive recipients of information; as Gill noted in the same address, most informing is both reciprocal and iterative. Nature of Barriers and Bias in Informing Barriers to informing may be defined as anything that leads to misinformation or disinformation. Cohen (2000a) defines four types of errors that lead to failure to inform: data transcription or intentional data misrepresentation, errors in data interpretation, errors related to solving the wrong problem, and filtering errors. …