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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.

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.

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.

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.

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.

Using a qualitative inquiry approach, 93 line-level hospitality employees were surveyed online regarding their experiences about the characteristics of good managers.

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.

This study advanced the literature on managerial characteristics by confirming several existing categories from the viewpoint of hospitality industry employees.

Human resource managers should be considerate of these findings in terms of recruitment, hiring, and training, development, and promotion of employees in their companies.

This is one of the first studies to analyze the perceived reasons behind the development of these characteristics.

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.

It has been shown that the graphical evolutionary game theory (EGT) is a very efficient method to study this problem.

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.

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.

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?

The study is a quantitative research approach based on survey data.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

This paper presents a pioneer study on keyword extraction on MOOC resources and obtains some new findings.

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.

“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.

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.

The study is based on expert opinions as such there is a limitation of how much it is of a true consensus.

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.

The purpose of this paper is to report the change in students' STEM perceptions in two different informal learning environments: an online STEM camp and a face-to-face (FTF) STEM camp.

For this quasi-experimental study, 26 students participated in an online STEM summer camp and another 26 students participated in the FTF STEM camp. Students from each group took the same pre- and post-STEM Semantics Survey documenting their perceptions of the individual STEM fields and of STEM careers. Wilcoxon Signed-Rank tests, Mann–Whitney U tests and corresponding effect sizes were used to compare the pre- and post-scores within and between the camps.

Results indicate that both camps produce similar outcomes regarding STEM field and career perceptions. However, analysis of all statistical values indicates that the online STEM camp can produce a larger positive influence on STEM field perceptions and the FTF camp can produce a larger positive influence on STEM career perceptions.

This suggests that STEM camps, both online and in-person, can improve students' perceptions of the STEM fields and of STEM careers. Implications from this study indicate that modifications of informal learning environments should be based on the type of learning environment.

This manuscript discusses the development and impact of an online STEM camp to accommodate for the sudden onset of the COVID-19 pandemic and the inability to hold an in-person STEM camp. These results may influence the curriculum and organization of future online and FTF STEM camps.