scholarly journals The impacts of supervisor – PhD student relationships on PhD students’ satisfaction: A case study of Vietnamese universities

2021 ◽  
Vol 18 (4) ◽  
pp. 269-285
Author(s):  
Mai Le ◽  
◽  
Long Pham ◽  
Kioh Kim ◽  
Nhuong Bui ◽  
...  

This study focuses on investigating impact of supervisor – PhD student relationship on PhD students’ satisfaction with their supervisors’ supervisory styles and their skill development. A survey was conducted among 430 respondents who both finished or were doing their doctoral study at universities in Northern, Central and Southern cities in Vietnam in social science, economics and business management majors. Findings revealed that the leadership, helping, understanding and responsibility relationship between supervisors and PhD students were positively associated with PhD students’ satisfaction with supervisors’ supervisory style while the uncertain, dissatisfied and admonishing types of relationships were negatively associated with PhD students’ satisfaction. The strict relationship did not negatively affect PhD students’ satisfaction with their supervisors’ supervisory styles. Furthermore, PhD students’ satisfaction with their supervisors’ supervisory styles positively influenced their satisfaction with academic skill development during their PhD candidature. Implications and future research directions were then discussed.

Author(s):  
Agnes Kukulska-Hulme ◽  
Chris Jones

Focusing on intermediate and institutional levels of design for learning, this chapter explores how institutional decisions relate to design, using recent experience at The Open University as a case study. To illuminate the relationship between institutional decisions and learner-focused design, we review and bring together some of the research on learner practices in mobile and networked learning. We take a critical stance in relation to the concept of generation, which has been applied to understanding learners of different ages using terms such as net generation and digital natives. Following on from this, we propose an integrated pedagogical design approach that takes account of learner practices, spaces for learning, and technologies. The chapter also proposes future research directions focused on the changing context for learning, a distinction between place and space and an understanding of how the different levels of educational systems interact with mobile and networked technologies.


Author(s):  
Iain Doherty

The purpose of this chapter is to examine the challenges of achieving systemic change in the teaching culture of a research-intensive university. The chapter makes use of a teaching improvement case study to identify both the challenges and the solutions to engaging academics in a research-intensive university with educational professional development. Ongoing issues are identified and future research directions are presented.


Author(s):  
Peggy Lynn Semingson ◽  
Pete Smith

This chapter provides a case study example using cross-case analysis (Merriam, 2001) of digital mentoring within an online Master's level literacy course at a large public university in the Southwest United States. Two mentors provided individualized video conference sessions, using Blackboard Collaborate™ to 28 students (mentees). Data included written reflections from students as well as transcripts from selected videoconference sessions. Structured synchronous mentoring sessions provided a predictable framework for students and mentors alike. This chapter provides an analysis of the students' perceptions of the conferences, the types of discourse patterns and language analysis of the conferences, as well as description of themes and trends across the data. Suggestions on the usefulness of the conferences as well as the structure of mentoring sessions are described in the chapter. Established and emerging models of mentorship and e-development are outlined and utilized to frame the analyses and future research directions.


Author(s):  
Álvaro Fernández ◽  
Camino Fernández ◽  
José-Ángel Miguel-Dávila ◽  
Miguel Á. Conde

Abstract The integration of a Supercomputer in the educational process improves student’s technological skills. The aim of the paper is to study the interaction between science, technology, engineering, and mathematics (STEM) and non-STEM subjects for developing a course of study related to Supercomputing training. We propose a flowchart of the process to improve the performance of students attending courses related to Supercomputing. As a final result, this study highlights the analysis of the information obtained by the use of HPC infrastructures in courses implemented in higher education through a questionnaire that provides useful information about their attitudes, beliefs and evaluations. The results help us to understand how the collaboration between institutions enhances outcomes in the education context. The conclusion provides a description of the resources needed for the improvement of Supercomputing Education (SE), proposing future research directions.


2019 ◽  
Vol 50 (5) ◽  
pp. 572-597 ◽  
Author(s):  
Hajime Mizuyama ◽  
Seiyu Yamaguchi ◽  
Mizuho Sato

Background. Knowledge sharing among the members of an organization is crucial for enhancing the organization’s performance. However, knowing how to motivate and direct members to effectively and efficiently share their relevant private knowledge concerning the organization’s activities is not entirely a straightforward matter. Aim. This study aims to propose a gamified approach not only for motivating truthful sharing and collective evaluation of knowledge among the members of an organization but also for properly directing those actions so as to maximize the usefulness of the shared knowledge. A case study is also conducted to understand how the proposed approach works in a live business scenario. Method. A prediction market game on a binary event on whether the specified activity will be completed successfully is devised. The game utilizes an original comment aggregation and evaluation system through which relevant knowledge can be shared verbally and evaluated collectively by the players themselves. Players’ behavior is driven toward a desirable direction with the associated incentive framework realized by three game scores. Results. The proposed gamified approach was implemented as a web application and verified with a laboratory experiment. The game was also played by four participants who deliberated on an actual sales proposal in a real company. It was observed that the various valuable knowledge elements that were successfully collected from the participants could be utilized for refining the sales proposal. Conclusions. The game induced motivation through gamification, and some of the designed game scores worked in directing the players’ behavior as desired. The players learned from others’ comments, which brought about a snowball effect and enriched collective knowledge. Future research directions include how to transform this knowledge into an easy-to-comprehend representation.


2021 ◽  
Vol 51 (1) ◽  
pp. 57-71
Author(s):  
Alicja Dąbrowska ◽  
Robert Giel ◽  
Sylwia Werbińska-Wojciechowska

Abstract During the robot's operational tasks, a key issue is its reliability in the aspect of human safety providing. Currently, there are a number of methods used to detect people, and their selection most often depends on the type of process carried out by robots. Therefore, the article is focused on the development of a comparative analysis of selected methods of human detection in the storage area. The main aspect in the context of which these systems were compared concerned the safety of robotic systems in the space of human occurrence. Main advantages and drawbacks of the methods in various applications were presented. The detailed analysis of the achievements in this area gives the possibility to identify research gaps and possible future research directions when using these tools in autonomous warehouses designing processes.


2021 ◽  
Vol 9 ◽  
pp. 1061-1080
Author(s):  
Prakhar Ganesh ◽  
Yao Chen ◽  
Xin Lou ◽  
Mohammad Ali Khan ◽  
Yin Yang ◽  
...  

Abstract Pre-trained Transformer-based models have achieved state-of-the-art performance for various Natural Language Processing (NLP) tasks. However, these models often have billions of parameters, and thus are too resource- hungry and computation-intensive to suit low- capability devices or applications with strict latency requirements. One potential remedy for this is model compression, which has attracted considerable research attention. Here, we summarize the research in compressing Transformers, focusing on the especially popular BERT model. In particular, we survey the state of the art in compression for BERT, we clarify the current best practices for compressing large-scale Transformer models, and we provide insights into the workings of various methods. Our categorization and analysis also shed light on promising future research directions for achieving lightweight, accurate, and generic NLP models.


2020 ◽  
Vol 28 (2) ◽  
pp. 101-110
Author(s):  
Andrea Gelei ◽  
Imre Dobos

This paper focuses on forecasting of products with sporadic demand. The demand for such products is not continuous but diffused seemingly at random, with a large proportion of zero values in the analyzed time series. The sporadic character of demand patterns actually means that the information available on the demand for previous selling periods is patchy, resulting in lower quality of data available. Under such circumstances demand forecasting is a challenging task. We present the results of a case study, where forecasting practice of a pharmaceutical wholesaler firm –we call it Pharma– is analyzed and developed. We present state-of-the-art knowledge related to demand forecasting of sporadic products and test suggestions related to them. We show that these suggestions can only partly be backed. We extend therefore the suggested product classification scheme and recommend using the concept of demand data aggregation. This will reduce sporadicity and result in higher quality forecasting. Aggregation also helps to specify the recommended forecast period, the length of time recommended to calculate the forecast for. The managerial consequences of these suggestions are also discussed, and future research directions are highlighted.


2020 ◽  
Vol 14 (1) ◽  
pp. 3-17
Author(s):  
Angela Yung Chi Hou ◽  
Sheng-Ju Chan ◽  
Lily Lin ◽  
Zoe Hu

PurposeTransnational learning has become a mainstream issue in recent years due to the rise of global education. There are many kinds of overseas learning, including degree-seeking, joint/double degree, student exchange, internship, service learning and so on. The scope of learning may involve research, teaching/learning and community service. The purpose of the case study is to investigate how the Taiwanese students participating in an international internship project of the US–Taiwan Partnerships for International Research and Education (PIRE) acquire professional knowledge and soft skills, including cross-cultural awareness, interdisciplinary communication, skill development and social networking. It also explores how a joint research project contributes into a collaborative educational program.Design/methodology/approachTo better understand participants' experiences in the PRIE, this study held three focus groups and seven in-depth interviews on the students, faculty members and project managers for data collection.FindingsThree major findings are shown in the study. First, participants agreed that the overall learning experiences in knowledge acquisition or skill development have been positive. Second, participants obviously expressed their greater interests in intercultural interaction with the locals, which did not happen quite often during the internship. Third, the extent of interest in applying for the PIRE deg ree program after the internship program is escalating year by year.Research limitations/implicationsMore investigation into participants’ social and cultural engagement in similar project will be needed for future research.Practical implicationsThe results will be implicated into other cross-border education project evaluation.Originality/valueThis study manages to investigate the cross-border research initiative from different participants' perspectives and received comprehensive feedbacks.


2019 ◽  
Vol 18 (4) ◽  
pp. 300-318 ◽  
Author(s):  
Isabella Marker ◽  
Peter J. Norton

Recent meta-analytic findings have revealed that the addition of motivational interviewing (MI) to cognitive behavior therapy (CBT) for anxiety disorders improves treatment outcome. However, for the most part, previous research has limited MI as a prelude to CBT. This article explored the benefits and complications of a more integrated approach by adapting and examining an already established transdiagnostic CBT protocol to include intermittent MI strategies. The presented protocol is described and illustrated using a case study of a woman meeting criteria for four anxiety disorder diagnoses. This study presents session-by-session treatment accounts, as well as pre, post, and follow-up data. Results indicated clinically significant improvement, supporting the utility of intermittent MI strategies within CBT. Implementation recommendations and future research directions are discussed.


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