자연주의적 탐구조사(Naturalistic Inquiry)

Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Machine learning

Lincoln, Yvonna, and Egon Guba, "Postpositivism and the Naturalist Paradigm," pp. 14-46 in Yvonna Lincoln and Egon Guba, Naturalistic Inquiry . Beverly Hills, CA: Sage, 1985.*

Reflexive methodology - new vistas for qualitative research: Media Reviews

Justice and the Politics of Difference

This paper is concerned with research into early school leaving. A narrative interview approach was used to document and analyse the experiences, processes and decisions that a small sample of boys made prior to leaving school, in this case, before completing Year 10 and 11. Data collected in 2004 indicate that schools along with students co-construct the decisions and educational pathways that many students find themselves on, pathways which sometimes lead to withdrawal, disengagement, and, finally, leaving school. On the surface, it can appear as though early school leaving is an individualised and rational phenomenon, associated perhaps with easy-to-define events that precipitate the action of leaving school. This paper suggests that early school leaving has contradictory and institutionalised histories, and that ‘winnowing’ may be an apt metaphor to describe this process.

Towards a More Telling Way of Understanding Early School Leaving.

Student views of their teachers and schooling can influence motivation and interest in schooling as well as their approach to learning. This paper describes the results of an investigation of rural adolescents' views of their schooling. A total of 240 students from government and non-government schools in the South West of Western Australia were interviewed in small groups. They offered a diversity of responses and insights related to their views of teachers and teaching. Results indicate that what these young people needed from their schools was enough flexibility and choice to cater for this diversity, not only in terms of curriculum, but in the methods of teaching, and the scope of future potentials made available for them. Students were able to offer a range of thoughtful, clear descriptions of what worked and did not work for them at school and what needed to happen to make school meaningful and relevant to their lives and needs.

/pdf/good-teachers-bad-teachers-how-rural-adolescent-students-1d9lyl93ft.pdf

Good Teachers / Bad Teachers: How Rural Adolescent Students’ Views of Teachers Impact on Their School Experiences

Approaches to curriculum design often occur at the unit or course level within social work education. Only rarely have ‘whole of curriculum’ approaches been discussed in the literature. This paper describes the creation of a ‘whole of curriculum approach’ to social work teaching and learning within an Australian University. The project involved the creation of a methodology and conceptual framework to map assessment across an entire social work curriculum. In doing so, the mapping exercise provided a way to evaluate the sequencing and integration of assessment tasks across the four-year degree pathway, and judge the effectiveness that such assessments fit with theories and research on assessment more broadly, and with the graduate outcomes for a social work degree. This paper outlines the background to the 2013 assessment project and its alignment to the curriculum mapping. It argues and explains how a systematic approach to mapping and improving social work curriculums can be achieved.

Whole Curriculum Mapping of Assessment: Cartographies of Assessment and Learning

In this paper I outline an approach towards policy analysis that takes governmentality as its point of theoretical orientation and begin to apply this approach to my research into the recently raised compulsory school‐leaving age in Western Australia. I aim to demonstrate the methodological potentials of this approach by giving examples of the thinking and practices that shape and condition the policy. I commence by situating the school‐leaving age policy within a broader field of reforms occurring under the general banner of neoliberalism and argue that the policy is primarily concerned with the conduct of students classified at ‘educational risk’, and with transforming these students to become more visible, participative and engaged in their schooling. By focusing on the policy rationalities and technologies, and drawing on Foucault’s notion of governmentality, I explore the forms of knowledge and practical strategies that are deployed in this policy field. I contend that this particular deployment narr...

Policy rationalities and policy technologies: a programme for analysing the raised school‐leaving age in Western Australia

The examination of a PhD thesis marks an important stage in the PhD student journey. Here, the student’s research, thinking and writing are assessed by experts in their field. Yet, in the early sta...

https://journals.sagepub.com/doi/pdf/10.1177/1469787417742020

David Hodgson

Papers

Towards a More Telling Way of Understanding Early School Leaving.

Good Teachers / Bad Teachers: How Rural Adolescent Students’ Views of Teachers Impact on Their School Experiences

Whole Curriculum Mapping of Assessment: Cartographies of Assessment and Learning

Policy rationalities and policy technologies: a programme for analysing the raised school‐leaving age in Western Australia

Helping doctoral students understand PhD thesis examination expectations: A framework and a tool for supervision: