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The purpose of this paper is to propose a knowledge extraction framework to extract knowledge, including entities and relationships between them, from unstructured texts in digital humanities (DH).

The proposed cooperative crowdsourcing framework (CCF) uses both human–computer cooperation and crowdsourcing to achieve high-quality and scalable knowledge extraction. CCF integrates active learning with a novel category-based crowdsourcing mechanism to facilitate domain experts labeling and verifying extracted knowledge.

The case study shows that CCF can effectively and efficiently extract knowledge from multi-sourced heterogeneous data in the field of Tang poetry. Specifically, CCF achieves higher accuracy of knowledge extraction than the state-of-the-art methods, the contribution of feedbacks to the training model can be maximized by the active learning mechanism and the proposed category-based crowdsourcing mechanism can scale up the effective human–computer collaboration by considering the specialization of workers in different categories of tasks.

This research proposes CCF to enable high-quality and scalable knowledge extraction in the field of Tang poetry. CCF can be generalized to other fields of DH by introducing domain knowledge and experts.

The extracted knowledge is machine-understandable and can support the research of Tang poetry and knowledge-driven intelligent applications in DH.

CCF is the first human-in-the-loop knowledge extraction framework that integrates active learning and crowdsourcing mechanisms; he human–computer cooperation method uses the feedback of domain experts through the active learning mechanism; the category-based crowdsourcing mechanism considers the matching of categories of DH data and especially of domain experts.

The purpose of this paper is to focus on assessing individuals’ problems in learning groups/teams and should lead to the assessment of the group/team itself as a learning entity.

In this paper, an extension of the IMS-Learning Design (IMS-LD) meta-model is proposed in order to support the assessment of collaborative activities in e-learning. Besides, the software architecture which consists of a set of components forming a web wizard to create, track and assess the collaborative assessment processes is described as to support that extension of the IMS-LD meta-model.

With the proposed solution we can: make assessment fairer using individual and collective assessment indicators to assign final scores to learners; make an assessment step by step for better individual and collective monitoring activities; and divide the assessment into lighter phases for the correctors. Consequently, the evaluator will have more detailed information about his/her students and the quality of judgment will be better. This could also be useful for the evaluator in order to plan further examinations.

Further experimentations are necessary to test the effectiveness of the proposed system in order to analyze its performances under a massive usage. In addition, the authors plan to use a survey to collect learners’ opinions to know the effectiveness of the proposal in terms of fairness in the assessment of collaborative activities in an online community.

This paper addresses important issues in the educational area, especially assessment of collaborative activities. In fact, to reduce subjectivity and increase fairness in assessing learners in collaborative work, for example, using the peer assessment, in order to try reducing subjectivity and fairly assessing learners. However, while assessing group work, the same mark is attributed for all group members and authors have concluded that it is not the right approach to make a fair and more objective assessment.

Telepresence robots (TPRs) are an emerging field of application and research that have received attention from various disciplines, including computer science, telehealth and education. The purpose of this study is to conduct a bibliometric analysis of publications on TPR in the Web of Science database from 1980 to 2022 to gain a better understanding of the state of research on TPRs and explore the role of pedagogical and psychological aspects in this research.

The analysis of research publications on TPRs was made on the basis of papers published in the Web of Science database from 1980 to 2022. The following research questions were proposed: What are the main tendencies in publication years, document types, countries of origin, source titles, publication authors, affiliations of authors and the most cited articles related to TPRs? What are the main topics discussed in the publications from the perspective of psychology? What are the main topics discussed in the publications from the perspective of educational sciences?

The results indicate that it is in the computer science where most of the existing research has been conducted, whereas the interest in the psychology and educational science has been relatively low. The greatest regional contributor has been the USA, whereas the effort in the European Union lags behind. Research publications in psychology in the Web of Science database related to TPRs can be grouped into three broad thematic categories: features of TPRs, degree of social presence compared to physical presence or other mediated technologies and opportunities for using TPRs. The results suggest that from the perspective of psychology, TPRs are one of the approaches that could enable greater social presence in remote communication. Most of the analysed papers in educational sciences investigated the opportunities of using TPRs in various educational fields. However, while the findings of the studies indicated significant potential of TPRs for education, their acceptance for wider use is still challenged.

The limitations of this research are that this study only analysed research papers in the Web of Science database and therefore only covers a limited number of scientific papers published in the field of psychology and educational sciences on TPRs. In addition, only publications with the term “telepresence robots” in the topic area of the Web of Science database were analysed. Therefore, several relevant studies are not discussed in this paper that are not reflected in the Web of Science database or were related to other keywords.

The field of TPRs has not been explored using a bibliographic analysis of publications in the Web of Science database from the perspective of psychology and educational sciences. The findings of this paper will help researchers and academic staff better understand the state of research on TPRs and the pedagogical and psychological aspects addressed in this research.

The purpose of this paper is to analyse the relationship between on-the-job learning and information and communication technology (ICT).

Action research methodology was applied to study 62 small- and medium-sized corporations, and to interview over 200 knowledge workers and managers. The qualitative, textual data collected were transformed into 16 variables and analysed by multidimensional scaling.

The paper provides insights into the optimal use of ICT in intra-organizational knowledge transfer and learning. We found that it is essential to use the right combination and number of technologies, aligned with the organization’s internal processes. Four different types of organizations with sub-optimal usage of ICT and possible strategies for them to reach the optimal zone were identified. For successful organizational learning, however, more is needed: the individual must also understand the value of learning and must be motivated to take part in it.

On-the-job-learning can be facilitated with ICT tools but only if the organization invests in the right levels of ICT. Too much technology can be as destructive to on-the-job learning as too little. Future research should look at other contexts (size, age, industry, etc.) to validate these findings.

The paper demonstrates the effective use of ICT in knowledge transfer and on-the-job learning.

The paper extends our understanding of human–computer collaboration. It highlights that finding the optimal level of ICT is essential for successful knowledge transfer and on-the-job learning.

The paper aims to clarify the importance of the psychological processing of contextual cues in the mining of individual attention resources. In recent years, the research of more open spatial perspective, such as spatial and scene perception, has gradually turned to the recognition of contextual cues, accumulating rich literature and becoming a hotspot of interdisciplinary research. Nevertheless, besides the fields of psychology and neuroscience, researchers in other fields lack systematic knowledge of contextual cues. The purpose of this study is to expand the research field of contextual cues.

We retrieved 494 papers on contextual cues from SCI/SSCI core database of the Web of Science in 1992–2019. Then, we used several bibliometric and sophisticated network analysis tools, such as HistCite, CiteSpace, VOSviewe and Pajek, to identify the time-and-space knowledge map, research hotspots, evolution process, emerging trends and primary path of contextual cues.

The paper found the core scholars, major journals, research institutions, and the popularity of citation to be closely related to the research of contextual cues. In addition, we constructed a co-word network of contextual cues, confirming the concept of behavior implementation intentions and filling in the research gap in the field of behavior science. Then, the quantitative analysis of the burst literature on contextual cues revealed that the research on it that focused more on multi-objective cues. Furthermore, an analysis of the main path helped researchers clearly understand and grasp in the development trend and evolution track of contextual cues.

Given academic research usually lags behind management practice, our systematic review of the literature to a certain extent make a bridge between theory and practice.

Digital humanities research platform for biographies of Malaysia personalities (DHRP-BMP) was collaboratively developed by the Research Center for Chinese Cultural Subjectivity in Taiwan, the Federation of Heng Ann Association Malaysia, and the Malaysian Chinese Research Center of Universiti Malaya in this study. Using The Biographies of Malaysia Henghua Personalities as the main archival sources, DHRP-BMP adopted the Omeka S, which is a next-generation Web publishing platform for institutions interested in connecting digital cultural heritage collections with other resources online, as the basic development system of the platform, to develop the functions of close reading and distant reading both combined together as the foundation of its digital humanities tools.

The results of the first-stage development are introduced in this study, and a case study of qualitative analysis is provided to describe the research process by a humanist scholar who used DHRP-BMP to discover the character relationships and contexts hidden in The Biographies of Malaysia Henghua Personalities.

Close reading provided by DHRP-BMP was able to support humanities scholars on comprehending full text contents through a user-friendly reading interface while distant reading developed in DHRP-BMP could assist humanities scholars on interpreting texts from a rather macro perspective through text analysis, with the functions such as keyword search, geographic information and social networks analysis for humanities scholars to master on the character relationships and geographic distribution from personality biographies, thus accelerating their text interpretation efficiency and uncovering the hidden context.

At present, a digital humanities research platform with real-time characters’ relationships analysis tool that can automatically generate visualized character relationship graphs based on Chinese named entity recognition (CNER) and character relationship identification technologies to effectively assist humanities scholars in interpreting characters’ relationships for digital humanities research is still lacking so far. This study thus presents the DHRP-BMP that offers the key features that can automatically identify characters’ names and characters’ relationships from personality biographies and provide a user-friendly visualization interface of characters’ relationships for supporting digital humanities research, so that humanities scholars could more efficiently and accurately explore characters’ relationships from the analyzed texts to explore complicated characters’ relationships and find out useful research findings.

Collaboratively annotating digital texts allow users to add valued information, share ideas and create knowledge. Most importantly, annotated content can help users obtain a deeper and broader understanding of a text compared to digital content without annotations. This work proposes a novel collaborative annotation system (CAS) with four types of multimedia annotations including text annotation, picture annotation, voice annotation and video annotation which can embedded into any HTML Web pages to enable users to collaboratively add and manage annotations on these pages and provide a shared mechanism for discussing shared annotations among multiple users. By applying the CAS in a mashup on static HTML Web pages, this study aims to discuss the applications of CAS in digital curation, crowdsourcing and digital humanities to encourage existing strong relations among them.

This work adopted asynchronous JavaScript (Ajax) and a model-view-controller framework to implement a CAS with reading annotation tools for knowledge creating, archiving and sharing services, as well as applying the implemented CAS to support digital curation, crowdsourcing and digital humanities. A questionnaire survey method was used to investigate the ideas and satisfaction of visitors who attended a digital curation with CAS support in the item dimensions of the interactivity with displayed products, the attraction and the content absorption effect. Also, to collect qualitative data that may not be revealed by the questionnaire survey, semi-structured interviews were performed at the end of the digital curation exhibition activity. Additionally, the effects of the crowdsourcing and digital humanities with CAS support on collecting and organizing ideas and opinions for historical events and promoting humanity research outcomes were considered as future works because they all need to take a long time to investigate.

Based on the questionnaire survey, this work found that the digital curation with CAS support revealed the highest rating score in terms of the item dimension of attraction effect. The result shows applying CAS to support digital curation is practicable, novel and interesting to visitors. Additionally, this work also successfully applied the developed CAS to crowdsourcing and digital humanities so that the two research fields may be brought into a new ground.

Based on the CAS, this work developed a novel digital curation approach which has a high degree of satisfaction on attraction effect to visitors, an innovative crowdsourcing platform that combined with a digital archive system to efficiently gather collective intelligence to solve the difficult problems of identifying digital archive contents and a high potential digital humanity research mode that can assist humanities scholars to annotate the texts with distinct interpretation and viewpoints on an ancient map, as well as discuss with other humanities scholars to stimulate discussion on more issues.

In a variety of domains, teams represent the main mechanism for dealing with change, complexity, and uncertainty in organizations. Consequently, teams need to be able to adapt and effectively use shared and complementary cognitive processing while collaborating to deal with these challenges.

A conceptual review is provided that addresses this type of complex collaborative cognition via discussion of macrocognition and the processes contributing to effective team problem-solving.

Despite extensive research on problem-solving, research and theories regarding how problem-solving changes over time as teams develop is missing. With this review, we extend research on team problem-solving and team development through integration of existing theory and concepts from the team literature.

This review provides a theoretical foundation for understanding and studying the developmental dynamic of team problem-solving.

A team problem-solving development model is described which outlines the degree to which the primary elements of team development are likely to affect macrocognitive processes within problem-solving phases. A set of propositions is offered in order to guide research on team development in collaborative problem-solving.