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1 – 10 of over 3000Zhengfa Yang, Qian Liu, Baowen Sun and Xin Zhao
This paper aims to make it convenient for those who have only just begun their research into Community Question Answering (CQA) expert recommendation, and for those who are…
Abstract
Purpose
This paper aims to make it convenient for those who have only just begun their research into Community Question Answering (CQA) expert recommendation, and for those who are already concerned with this issue, to ease the extension of our understanding with future research.
Design/methodology/approach
In this paper, keywords such as “CQA”, “Social Question Answering”, “expert recommendation”, “question routing” and “expert finding” are used to search major digital libraries. The final sample includes a list of 83 relevant articles authored in academia as well as industry that have been published from January 1, 2008 to March 1, 2019.
Findings
This study proposes a comprehensive framework to categorize extant studies into three broad areas of CQA expert recommendation research: understanding profile modeling, recommendation approaches and recommendation system impacts.
Originality/value
This paper focuses on discussing and sorting out the key research issues from these three research genres. Finally, it was found that conflicting and contradictory research results and research gaps in the existing research, and then put forward the urgent research topics.
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Keywords
Trishna G. Mistry, S. Kyle Hight, Fevzi Okumus and Abraham Terrah
The purpose of this study was to empirically investigate the characteristics of good hospitality managers and the core causes that lead to developing such characteristics.
Abstract
Purpose
The purpose of this study was to empirically investigate the characteristics of good hospitality managers and the core causes that lead to developing such characteristics.
Design/methodology/approach
Using a qualitative inquiry approach, 93 line-level hospitality employees were surveyed online regarding their experiences about the characteristics of good managers.
Findings
The research findings revealed five key themes of good managerial characteristics, including interpersonal skills, communication skills, supervisory skills, leadership skills, and positive personality and professionalism. Additionally, the root causes of these managerial characteristics were also analyzed. The good managerial characteristics were perceived to have developed from having worked under either a great manager or a terrible manager.
Research limitations/implications
This study advanced the literature on managerial characteristics by confirming several existing categories from the viewpoint of hospitality industry employees.
Practical implications
Human resource managers should be considerate of these findings in terms of recruitment, hiring, and training, development, and promotion of employees in their companies.
Originality/value
This is one of the first studies to analyze the perceived reasons behind the development of these characteristics.
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Keywords
Hangjing Zhang, Yan Chen and H. Vicky Zhao
The purpose of this paper is to have a review on the analysis of information diffusion based on evolutionary game theory. People now get used to interact over social networks, and…
Abstract
Purpose
The purpose of this paper is to have a review on the analysis of information diffusion based on evolutionary game theory. People now get used to interact over social networks, and one of the most important functions of social networks is information sharing. Understanding the mechanisms of the information diffusion over social networks is critical to various applications including online advertisement and rumor control.
Design/methodology/approach
It has been shown that the graphical evolutionary game theory (EGT) is a very efficient method to study this problem.
Findings
By applying EGT to information diffusion, the authors could predict every small change in the process, get the detailed dynamics and finally foretell the stable states.
Originality/value
In this paper, the authors provide a general review on the evolutionary game-theoretic framework for information diffusion over social network by summarizing the results and conclusions of works using graphical EGT.
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Keywords
Patrick Schweighofer, Doris Weitlaner, Martin Ebner and Hannes Rothe
The literature includes several studies that define different critical success factors (CSF) which have to be considered to support the implementation of technology-enhanced…
Abstract
Purpose
The literature includes several studies that define different critical success factors (CSF) which have to be considered to support the implementation of technology-enhanced learning (TEL) approaches. An analysis of such studies revealed that (1) regional differences seem to determine the CSF for TEL approaches, (2) certain CSF are relevant for TEL approaches in general, and (3) professionals in higher education determine which influential factors they consider when implementing TEL approaches. Thus, the question arises: in general, which influential factors do professionals in Austrian and German institutions of higher education actually consider when implementing TEL approaches?
Design/methodology/approach
The study is a quantitative research approach based on survey data.
Findings
The results show that certain influential factors seem to be generally important, such as the factors of respecting learning success or motivation. However, the outcome of the study also indicated that different moderating variables like experiences and personal relevance affect the professionals’ choices.
Originality/value
The originality and value are in the approach to identify generally important influential factors for the implementation of TEL approaches in Austrian and German institutions of higher education.
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Keywords
Salla-Riikka Kuusalu, Päivi Laine, Minna Maijala, Maarit Mutta and Mareen Patzelt
This study aims to explore how university language students evaluate different sustainability themes and examine the overall relevance of ecological, social, cultural and economic…
Abstract
Purpose
This study aims to explore how university language students evaluate different sustainability themes and examine the overall relevance of ecological, social, cultural and economic sustainability dimensions in language education.
Design/methodology/approach
A questionnaire was designed to study Finnish university language students’ (n = 55) order of priority for sustainability dimensions and their sub-themes and the justifications for the priority orders using a mixed methods design. Qualitative content analysis was conducted using NVivo software, and weighted rankings were used to analyse the quantitative data.
Findings
The findings of the study showed that language students evaluated the social and cultural dimensions as the most relevant in language teaching. In all dimensions, students approached sustainability mainly by prioritising larger issues and advancing towards smaller ones. Most non-directional responses appeared in the economic dimension. In addition, individual prioritising and justification approaches varied between different sustainability dimensions.
Originality/value
To the best of the authors’ knowledge, no previous studies have examined language students’ evaluations of and justifications for all four sustainability dimensions. The results highlight the need to use multiple, holistic approaches and systems thinking to incorporate education for sustainable development.
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Gamification is a booming motivational approach in information systems. Leaderboards play a key role in gamification; however, there are mixed findings regarding the heterogeneous…
Abstract
Purpose
Gamification is a booming motivational approach in information systems. Leaderboards play a key role in gamification; however, there are mixed findings regarding the heterogeneous motivational impacts of leaderboard positions. This study aims to clarify the motivational effects of high and low leaderboard positions by assembling diverse behavioral measures and self-reports. The measures used in this study shed a light on the quantitative and qualitative dynamics of motivation facilitated by leaderboard positions. The authors inspect motivation in relation to satisfaction and frustration of competence need.
Design/methodology/approach
The authors conducted an online experiment set in a crowdsourcing context, asking the participants to compete in an image tagging game. Participants' leaderboard positions were manipulated to be either high or low for five consecutive rounds. The number of clicks, tags, duration of tagging and persistence on the task were measured as indicators of motivation.
Findings
High ranks on leaderboards induced complacent behaviors choosing easy ways to maintain their positions, while low ranks led the participants to stick to the right process of the task with intensified motivation round after round. However, neither of the motivations seemed to be of intrinsic nature.
Originality/value
The present study provides conclusive evidence on the varying motivational impact of leaderboard positions. The authors also demonstrate how the “needs-as-motive” model (Sheldon and Gunz, 2009) applies to gamification. Its implications in self-determination theory and gamification literature are discussed.
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Cheri Macleod and Paula Hayden
The learning skills used by students at a technical college to fully participate in their classes were the focus of this investigation. Researchers shadowed two full-time students…
Abstract
The learning skills used by students at a technical college to fully participate in their classes were the focus of this investigation. Researchers shadowed two full-time students for one full day as they each went to their classes in a technical college in Qatar. An observation schedule was used to record what students did in their classes (for example: solve problems, listen to the teacher, ask questions). At the end of the day students were interviewed and asked to comment on the importance of the learning skills that they used, how they built the skills they needed and how to become a better student. It was found that students used a variety of learning skills throughout a typical day and that they had their own ideas about learning. The learning skills the two students used most during their classes were not the same, owing partly to the format of the courses and partly to personal learning approach. The four learning skills students identified as most important were: understand and apply concepts to current work; concentrate and maintain focus; follow written instructions; and ask questions. The information gathered in this investigation can be used to inform students, instructors and course planners about the skills students need to be active participants in their classes and to ensure that educators support the development of required learning skills.
Zhuoxuan Jiang, Chunyan Miao and Xiaoming Li
Recent years have witnessed the rapid development of massive open online courses (MOOCs). With more and more courses being produced by instructors and being participated by…
Abstract
Purpose
Recent years have witnessed the rapid development of massive open online courses (MOOCs). With more and more courses being produced by instructors and being participated by learners all over the world, unprecedented massive educational resources are aggregated. The educational resources include videos, subtitles, lecture notes, quizzes, etc., on the teaching side, and forum contents, Wiki, log of learning behavior, log of homework, etc., on the learning side. However, the data are both unstructured and diverse. To facilitate knowledge management and mining on MOOCs, extracting keywords from the resources is important. This paper aims to adapt the state-of-the-art techniques to MOOC settings and evaluate the effectiveness on real data. In terms of practice, this paper also tries to answer the questions for the first time that to what extend can the MOOC resources support keyword extraction models, and how many human efforts are required to make the models work well.
Design/methodology/approach
Based on which side generates the data, i.e instructors or learners, the data are classified to teaching resources and learning resources, respectively. The approach used on teaching resources is based on machine learning models with labels, while the approach used on learning resources is based on graph model without labels.
Findings
From the teaching resources, the methods used by the authors can accurately extract keywords with only 10 per cent labeled data. The authors find a characteristic of the data that the resources of various forms, e.g. subtitles and PPTs, should be separately considered because they have the different model ability. From the learning resources, the keywords extracted from MOOC forums are not as domain-specific as those extracted from teaching resources, but they can reflect the topics which are lively discussed in forums. Then instructors can get feedback from the indication. The authors implement two applications with the extracted keywords: generating concept map and generating learning path. The visual demos show they have the potential to improve learning efficiency when they are integrated into a real MOOC platform.
Research limitations/implications
Conducting keyword extraction on MOOC resources is quite difficult because teaching resources are hard to be obtained due to copyrights. Also, getting labeled data is tough because usually expertise of the corresponding domain is required.
Practical implications
The experiment results support that MOOC resources are good enough for building models of keyword extraction, and an acceptable balance between human efforts and model accuracy can be achieved.
Originality/value
This paper presents a pioneer study on keyword extraction on MOOC resources and obtains some new findings.
Details
Keywords
Sharon Slade, Paul Prinsloo and Mohammad Khalil
The purpose of this paper is to explore and establish the contours of trust in learning analytics and to establish steps that institutions might take to address the “trust…
Abstract
Purpose
The purpose of this paper is to explore and establish the contours of trust in learning analytics and to establish steps that institutions might take to address the “trust deficit” in learning analytics.
Design/methodology/approach
“Trust” has always been part and parcel of learning analytics research and practice, but concerns around privacy, bias, the increasing reach of learning analytics, the “black box” of artificial intelligence and the commercialization of teaching and learning suggest that we should not take stakeholder trust for granted. While there have been attempts to explore and map students’ and staff perceptions of trust, there is no agreement on the contours of trust. Thirty-one experts in learning analytics research participated in a qualitative Delphi study.
Findings
This study achieved agreement on a working definition of trust in learning analytics, and on factors that impact on trusting data, trusting institutional understandings of student success and the design and implementation of learning analytics. In addition, it identifies those factors that might increase levels of trust in learning analytics for students, faculty and broader.
Research limitations/implications
The study is based on expert opinions as such there is a limitation of how much it is of a true consensus.
Originality/value
Trust cannot be assumed is taken for granted. This study is original because it establishes a number of concerns around the trustworthiness of learning analytics in respect of how data and student learning journeys are understood, and how institutions can address the “trust deficit” in learning analytics.
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