Introduction of Research Framework

Author(s):  
Yuka Kaneko
Keyword(s):  
2020 ◽  
Vol 1 (2) ◽  
pp. 192-207
Author(s):  
Juliette Barbera

For decades, both incarceration and research on the topic have proliferated. Disciplines within the Western sciences have studied the topic of incarceration through their respective lenses. Decades of data reflect trends and consequences of the carceral state, and based on that data the various disciplines have put forth arguments as to how the trends and consequences are of relevance to their respective fields of study. The research trajectory of incarceration research, however, overlooks the assumptions behind punishment and control and their institutionalization that produce and maintain the carceral state and its study. This omission of assumptions facilitates a focus on outcomes that serve to reinforce Western perspectives, and it contributes to the overall stagnation in the incarceration research produced in Western disciplines. An assessment of the study of the carceral state within the mainstream of American Political Development in the political science discipline provides an example of how the research framework contributes to the overall stagnation, even though the framework of the subfield allows for an historical institutionalization perspective. The theoretical perspectives of Cedric J. Robinson reveal the limits of Western lenses to critically assess the state. The alternative framework he provides to challenge the limits imposed on research production by Western perspectives applies to the argument presented here concerning the limitations that hamper the study of the carceral state.


Author(s):  
Sindhu Madhuri G. ◽  
Indira Gandhi M P

Image is a basic and fundamental data source for the digital image processing. This image data source is required to be processed into information or intelligence and further to knowledge levels where it is required to understand and migrate into knowledge economy systems. Image registration is one of such key and most important process already identified in the digital image processing domain. Image registration is a process of bringing the reference image and sensed image into a common co-ordinate system, and application of complex transformation techniques for necessary comparison of reference with sensed images obtained from different - views, times, spaces, etc., in order to extract the valuable information and intelligence embedded in them. Due to the complexity of overall image registration process, it is difficult to suggest a single transformation technique even for a specific application. In addition, it is highly impossible to suggest one single transformation technique for comparison of various sensed images with a reference image during the image registration process. This research gap calls for the development of new image registration techniques for the application of more than one transformation technique during the image registration process for the necessary comparisons with reference image & sensed images, those are obtained from the available heterogeneous sources or sensors, based on the requirement. In addition, it is a basic need to attempt for the measurement of effectiveness of the image registration process also. Therefore, a research framework is developed for image registration process and attempted for the measurement of its effectiveness also. This new research area is a novel idea, and is expected to emerge as a provision for the knowledge computations with creative thinking through the embedded intelligence extraction during the complex image registration process.


Author(s):  
Marry Mdakane ◽  
Christo J. Els ◽  
A. Seugnet Blignaut

Student satisfaction, as a key psychological-affective outcome of tertiary education, is a direct measure of the success of Open Distance Learning (ODL). It is therefore vital for ODL Higher Education Institutions to assess and improve student satisfaction constantly. Existing theories on student satisfaction are mostly derived from deductive research, i.e. from research that considers the existing body of knowledge, followed by an investigation of a specific aspect or component, in order to reach a specific conclusion. We, however, maintain the inductive stance that a research framework for student satisfaction in ODL should be derived from students themselves. Accordingly, we purposively collected qualitative data from N=34 South African postgraduate ODL students, representative of various cultural language groups, with regard to student satisfaction. Supported by Atlas.ti, we composed an integrated dataset comprised of students’ responses to two focus-group interviews, as well as students’ written narratives in response to qualitative questions. Through meticulous qualitative data-analysis, we detected data categories, sub-categories, patterns and regularities in the integrated dataset. Theories and findings from the existing corpus of knowledge pertaining to student satisfaction in ODL illuminated our qualitative findings. This paper reports on the knowledge we gained from our participants pertaining to their student satisfaction with the Higher Education (HE) environment, the first of three main research components of an inductively derived research framework for student satisfaction in ODL.


Sign in / Sign up

Export Citation Format

Share Document