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251.
Mohammad Khaled Al-Shboul 《The Journal of Academic Librarianship》2014,40(5):500-509
A persona represents a group of target users that share common behavioural characteristics. The personas method, an approach to systems design, has been receiving significant attention from practitioners. However, only anecdotal evidence currently exists for the effectiveness of personas and there have been criticisms about its validity as a scientific approach to research. This paper attempts to demonstrate how incorporating personas may lead to better understand the information needs of humanities scholars. Humanities scholars in an advanced ICT environment in the Hashemite Kingdom of Jordan are sampled as a case. Previous studies show that the humanities scholars have a significant negative relation with ICT use; they are using it less than scientists and social scientists, and they demonstrate a significantly higher use of library facilities than other academics. There is also a lack of up-to-date international research on the humanities scholars' information needs that takes into account recent rapid increases in the availability of ICT infrastructure, especially the Internet. As such, the objective of this study is to understand the information needs of humanities scholars and the effect of the electronic environment on their information seeking behaviour using personas. This study is conducted within a conceptual framework based on an integration of existing models of information-seeking behaviour, along with additional new elements representing the information context environment, such as languages, decision to seek and format of information resources. The four personas that were uncovered in this study may be able to effectively communicate the actual information needs of the humanities scholars through the personal narrative, name, and face, which continuously will remind the academic library of what their users really want and need from their services. This study also lays the foundation for future research by identifying variables of interest, and building construct validity through the themes of information needs that emerged. 相似文献
252.
Neda Nasiri Ahmad Fakharian Mohammad Bagher Menhaj 《Journal of The Franklin Institute》2021,358(10):5185-5212
This paper presents a novel combined State Dependent Riccati Equation (SDRE) / Function Approximation Technique (FAT)-based control design for nonlinear uncertain systems. The SDRE is employed to construct an optimal controller and the function approximation technique is utilized to estimate time-varying disturbances and uncertainties. Moreover, a robust term in the proposed control law compensates for the truncation error. The closed-loop stability and boundedness of the tracking error and FAT weights approximation error are proved in the sense of Lyapunov, with consideration of truncation error. Due to the great importance of the adequate performance of transient response from practical point of view, performance evaluation has been accomplished. The proposed scheme is computationally simple due to utilizing the FAT to represent uncertainties and disturbances as a function of time. Compared with the SDRE based SMC, the proposed controller is superior in terms of capability to track a fast and highly complicated trajectory and no need to determine time-varying disturbances and uncertainties bounds. The case study is a Selective Compliant Articulated Robot for Assembly (SCARA) flexible joint manipulator as a representative of highly nonlinear, coupled, large robotic systems. Simulation results easily verify the effectiveness and superiority of the proposed controller. 相似文献
253.
An evaluation of traditional admission standards in predicting Kuwait University students' academic performance 总被引:1,自引:0,他引:1
The purpose of this study was to evaluate the usefulness of the traditional admission standards utilized by Kuwait University in predicting students' academic performance. It was found that the established practice of using students' score in standardized secondary school examinations and branch of study (i.e. sciences or arts emphasis) to be highly predictive of their college cumulative grade point average. Moreover, it was established that students' secondary school scores reflect intellective as well as the non-intellective factors pertaining to students' background. 相似文献
254.
The present study investigated English as a foreign language (EFL) teachers’ attributions of success and failure. It also set out to investigate whether these attributions vary by teachers’ age, teaching experience, gender and educational level. To do so, 200 EFL teachers were selected according to convenience sampling among EFL teachers teaching English in Language Institutes in Mashhad and Tehran, two cities in Iran. The participants completed the language teacher attribution scale measuring four attributions: teaching competency (TC), teacher effort (TE), student effort (SE) and institution supervision (IS). The present study yielded mixed results regarding English language teachers’ attributions of success and failure events. It was also found that these attributions vary by their age, teaching experience and educational level, but not by gender. The discussion and implications of the research are further presented with reference to the earlier findings. 相似文献
255.
Qinyi Liu Mohammad Khalil 《British journal of educational technology : journal of the Council for Educational Technology》2023,54(6):1715-1747
The field of learning analytics has advanced from infancy stages into a more practical domain, where tangible solutions are being implemented. Nevertheless, the field has encountered numerous privacy and data protection issues that have garnered significant and growing attention. In this systematic review, four databases were searched concerning privacy and data protection issues of learning analytics. A final corpus of 47 papers published in top educational technology journals was selected after running an eligibility check. An analysis of the final corpus was carried out to answer the following three research questions: (1) What are the privacy and data protection issues in learning analytics? (2) What are the similarities and differences between the views of stakeholders from different backgrounds on privacy and data protection issues in learning analytics? (3) How have previous approaches attempted to address privacy and data protection issues? The results of the systematic review show that there are eight distinct, intertwined privacy and data protection issues that cut across the learning analytics cycle. There are both cross-regional similarities and three sets of differences in stakeholder perceptions towards privacy and data protection in learning analytics. With regard to previous attempts to approach privacy and data protection issues in learning analytics, there is a notable dearth of applied evidence, which impedes the assessment of their effectiveness. The findings of our paper suggest that privacy and data protection issues should not be relaxed at any point in the implementation of learning analytics, as these issues persist throughout the learning analytics development cycle. One key implication of this review suggests that solutions to privacy and data protection issues in learning analytics should be more evidence-based, thereby increasing the trustworthiness of learning analytics and its usefulness.
Practitioner notes
What is already known about this topic- Research on privacy and data protection in learning analytics has become a recognised challenge that hinders the further expansion of learning analytics.
- Proposals to counter the privacy and data protection issues in learning analytics are blurry; there is a lack of a summary of previously proposed solutions.
- Establishment of what privacy and data protection issues exist at different phases of the learning analytics cycle.
- Identification of how different stakeholders view privacy, similarities and differences, and what factors influence their views.
- Evaluation and comparison of previously proposed solutions that attempt to address privacy and data protection in learning analytics.
- Privacy and data protection issues need to be viewed in the context of the entire cycle of learning analytics.
- Stakeholder views on privacy and data protection in learning analytics have commonalities across contexts and differences that can arise within the same context. Before implementing learning analytics, targeted research should be conducted with stakeholders.
- Solutions that attempt to address privacy and data protection issues in learning analytics should be put into practice as far as possible to better test their usefulness.