Collaborative Information Research Articles

Towards Understanding AI Delegation: The Role of Self-Efficacy and Visual Processing Ability

Recent work has proposed artificial intelligence (AI) models that can learn to decide whether to make a prediction for a task instance or to delegate it to a human by considering both parties’ capabilities. In simulations with synthetically generated or context-independent human predictions, delegation can help improve the performance of human-AI teams—compared to humans or the AI model completing the task alone. However, so far, it remains unclear how humans perform and how they perceive the task when individual instances of a task are delegated to them by an AI model. In an experimental study with 196 participants, we show that task performance and task satisfaction improve for the instances delegated by the AI model, regardless of whether humans are aware of the delegation. Additionally, we identify humans’ increased levels of self-efficacy as the underlying mechanism for these improvements in performance and satisfaction, and one dimension of cognitive ability as a moderator to this effect. In particular, AI delegation can buffer potential negative effects on task performance and task satisfaction for humans with low visual processing ability. Our findings provide initial evidence that allowing AI models to take over more management responsibilities can be an effective form of human-AI collaboration in workplaces. 1

The role of indigenous healers in treating surgical conditions in the rural Eastern Cape of South Africa.

Indigenous knowledge healers (IKHs) provide alternative healthcare to formal health services in rural South Africa, but there is a gap in knowledge regarding their treatment of surgical conditions. This study evaluated IKH surgical care and described their perspective of the dual health system. A cross sectional survey of IKHs in the Madwaleni Hospital catchment of the Eastern Cape, South Africa was conducted. Topics included the training and experience of IKHs, treatment of nine common surgical conditions, referral patterns, disease origin beliefs, benefits and limitations of care, and collaborative opportunities between the two health systems. Thirty-five IKHs completed the survey. IKHs were consulted by persons with all nine surgical conditions. The most common forms of treatment were application of an ointment on the affected site (88%) and oral medication (82%). Operative treatment was only done for abscess. Referrals to the formal healthcare sector were made for all surgical conditions. IKHs reported that they were limited by their lack of training and resources to perform operations. On the other hand, they perceived the treatment of the spiritual aspect of surgical disease as a benefit of their care. Thirty-five (100%) IKHs were interested in closer collaboration with the formal health sector. IKHs treat surgical conditions but refer to the formal health sector when diagnostic and operative services are needed. More research is needed to determine the potential advantages and disadvantages between the formal health sector and IKH collaboration.

Development of a Cloud Computing-Based Collaboration Information System

The rapid advancement of information and communication technology has created a demand for efficient and effective information systems to facilitate collaboration among institutions. This study develops a cloud computing-based collaboration information system designed to enhance real-time communication, data management, and collaboration among users. The system comprises key modules, including collaboration management, document management, and integrated collaboration features. Testing involved various scenarios with 10 to 100 active users simultaneously, revealing that the system maintained stable performance with response times under 3 seconds for each user request. Furthermore, security assessments utilizing encryption protocols and two-factor authentication confirmed that the managed data is protected from external threats. The findings underscore the system's potential to improve collaborative efficiency while ensuring data security, making it a valuable solution for future collaborative initiatives.

Human-AI Collaboration in Cooperative Games: A Study of Playing Codenames with an LLM Assistant

Playing partial information, restricted communication, cooperative (PIRCC) games with humans have proven challenging for AI, due to our reliance on social dynamics and sophisticated cognitive techniques. Yet, recent advances in generative AI may change this situation through new forms of human-AI collaboration. This paper investigates how teams of players interact with an AI assistant in the PIRCC game Codenames and the impact this has on cognition, social dynamics, and player experience. We observed gameplay and conducted post-game focus groups with 54 participants across ten groups. Each group played three rounds of Codenames, with an AI assistant supporting Cluegivers. We found the AI assistant enhanced players' convergent and divergent thinking, but interfered with formation of team mental models, highlighting a tension in the use of AI in creative team scenarios. The presence of the AI challenged many players' understanding of the 'spirit of the game'. Furthermore, the presence of the AI assistants weakened social connections between human teammates, but strengthened connections across teams. This paper provides an empirical account of an AI assistant's effect on cognition, social dynamics, and player experience in Codenames. We highlight the opportunities and challenges that arise when designing hybrid digital boardgames that include AI assistants.

Early Childhood Education: Listening to A Child’s Voices Through A/R/Tographic Journey

This inquiry explores the impact of child-led perspectives in art education, using the methodologies of a/r/tography and autoethnography to explore the intersection of artistic practice, personal reflection, and educational theory. The research was inspired by a transformative experience with a 7-year-old child at a spring camp, whose imaginative storytelling of a “tire kingdom”, where car tires live secret lives, reversed traditional adult-child dynamics. The child’s insights redefined my roles as an artist-researcher-teacher/learner, placing him in the role of teacher and myself as the learner. This reversal opened up new pathways for reflection and creativity, as his imaginative exploration became a catalyst for my own artistic practice. I created a series of illustrations based on our stories, which evolved into a picture book that amplifies children’s voices, illustrating the importance of recognizing children’s contributions to educational discourse. Through a/r/tography, which integrates art-making, research, and teaching, alongside autoethnography’s focus on personal and cultural reflection, this inquiry underscores the value of interdisciplinary approaches in understanding the fluid relationships between adult and child, teacher and student. It also highlights the importance of listening to and incorporating children’s imaginative inquiries as a means of enriching educational and artistic practices. By engaging in this child’s world, I not only deepened my own creative and educational practice but also discovered the potential of child-led inquiry to reverse-shape adult learning, fostering reciprocal, inter-generational dialogue and new forms of creative collaboration.

A strategic evaluation of BIM-driven information management in the context of ISO 19650-2 standard

PurposeThis paper presents an in-depth evaluation of BIM-driven information management in the context of ISO 19650-2. The study aimed to understand and evaluate the existing mechanisms and the recommended activities and tasks of collaborative information management, particularly as the Turkish AEC organizations are currently implementing ISO 19650-2.Design/methodology/approachThe study employed a qualitative research design based on information management stages of ISO 19650-2. Semi-structured interviews were conducted with purposefully selected professionals. The framework analyses were made with MAXQDA through conceptual coding to identify current drivers, challenges and incentives for BIM-driven information management. The frequencies of common themes, required tasks and semantic relationships were reported systematically and interpreted to provide a conceptual implementation map, practical insights and actionable recommendations.FindingsThe study results encompass strategies for establishing new tasks and implementation procedures to uphold business value by aligning information management standards with evolving project requirements, providing detailed and responsive EIRs, early use of CDEs, compliant production methods, clarity of roles and responsibilities, increased organizational capacity and capabilities, sustained planning and production quality and leveraging lessons learned.Originality/valueThe study provides evidence-based arguments and strategic insights for BIM-driven information management, focusing on the current implementation compatibilities with ISO 19650-2. Findings and discussions highlight the necessity of industry-wide transformations, reengineered activities/tasks and compliant information flows, which are crucial for adopting ISO 19650-2 and the formulation of national annex documents.

New development: How working from home influences the governance of municipally owned corporations and affects the public interest

IMPACT This article provides important insights for public administration practitioners, particularly those involved in the governance of municipally owned corporations (MOCs). The research highlights how the shift to working from home (WFH) during the Covid 19 pandemic influenced governance practices, with both positive and negative implications for the safeguarding of the public interest. While formal accountability remained strong, reduced trust and less effective informal collaboration emerged as challenges. These findings are particularly relevant for municipal leaders and policy-makers responsible for overseeing MOCs, as well as for those involved in digital transformation and remote work management. The article underscores the need for developing digital skills among civil servants and tailoring governance practices to address the complexities of WFH, which is increasingly becoming the norm. Practitioners in other countries should consider these insights while accounting for differences in governance structures and cultural contexts.

Raising data availability and quality for improved disruption and carbon footprint management through a novel approach to primary data sharing: Virtual Watch Tower / VWT

Abstract The global supply chain and logistics industry is a self-organizing ecosystem consisting of numerous actors that work together to move goods from end to end. The different stakeholders involved are usually interdependent organizations, like freight forwarders, carriers, terminals, and homeland security agencies and information exchange between them is required to coordinate the activities along the individual transport chains. However, the exchange of information has often been analog, flawed, late, and incomplete. New circumstances, like unprecedented supply chain disruptions, new regulatory requirements around greenhouse gas (GHG) emissions, and generally growing shipper expectations create an urgent need for improved data sharing between actors. New technologies, like digital platforms, networks, and architectures as well as social media, mobile, analytics, cloud, and internet of things (SMACT) have brought some improvements, but not the required holistic digital perspective required or expected. Averages and approximations are usually insufficient to close data gaps, e.g., only primary data allows for accurate GHG emission calculations. Primary data sharing is widely seen as the missing piece of the puzzle. Primary data is data from the source providing an accurate state and picture of a situation. Primary data sharing at scale requires a new form of digital collaboration. We propose a rethink of digital collaboration as a means for broader primary private data sharing for complete end-to-end datasets and data quality, particularly focusing on the sharing of data associated with both transport plans and progress made in the respective movements of goods for more better disruption and carbon footprint management through more accurate calculations of estimated times of arrival (ETA) and GHG emissions. We introduce an example for digital collaboration in end-to-end supply chains that is focusing specifically on primary data sharing. The new thinking around digital collaboration manifests itself in the Virtual Watch Tower / VWT initiative (www.virtualwatchtower.org). In 2022, RISE and Singapore Maritime Institute signed a collaboration agreement focused on innovation in shipping. The VWT initiative is the first collaborative project under the umbrella of this partnership. The VWT is led by RISE, A*STAR, and VTT. VWT is a community-driven, digitally empowered initiative, a cargo owner-driven, and terminal-centric approach for improved supply chain management. It is the users themselves who co-create and co-evolve the solution that they need. The initiative aims to create a community that shapes the digital tool (VWTnet) they need to reach the required higher levels of visibility. This, through primary data sharing across the supply chain ecosystem and between actors (VWT Users) participating in individual end-to-end transports (VWT Shipments). The VWT serves as an object of research to hone the new thinking and understand the implications of its implementation.

Team-centered IDAC: Modeling and simulation of operating crew in complex systems – Part 1: Team model and fundamentals

Operation of highly complex systems such as Nuclear Power Plants (NPPs) generally require highly trained professional operating teams. Factors associated with teamwork, such as ineffective communication and coordination, can be important contributing factors to accidents and unsafe behavior. The impact of crew interactions on team effectiveness and, consequently, on the entire system, has not been fully and quantitatively explored in high-risk environments such as NPPs. Since a team is an interactive social system, team-specific issues must be studied and evaluated from a “team perspective”—based on team dynamics and processes. This paper is part of a two-papers series that presents a simulation-based Team Model for NPP control room operations. The current paper, Part 1, describes the theoretical fundaments of the model and details its elements. The accompanying paper describes the simulation aspects, and a full application of the method to a pipe break accident in a four- four-loop steam generator feedwater system. The proposed model is based on the IDAC (Information, Decision, and Action in Crew context) cognitive model framework. The resulting model, Team-centered IDAC (Tc-IDAC), examines the team activities “Collaborative information collection,” “Shared decision making,” and “Distributed action execution” through specific modules for Team Error Management. These modules include error detection, error indication and error correction, and team performance shaping factors.

A theoretical framework for human-centered intelligent information services: A systematic review

Intelligent Information Services (IIS) employ Artificial Intelligence (AI)-based systems to provide information that matches the user's needs in diverse and evolving environments. Acknowledging the importance of users in AI-empowered IIS success, a growing number of researchers are investigating AI-empowered IIS from a user-centric perspective, establishing the foundation for a new research domain called “Human-Centered Intelligent Information Services” (HCIIS). Nonetheless, a review of user studies in AI-empowered IIS is still lacking, impeding the development of a clear definition and research framework for the HCIIS field. To fill this gap, this study conducts a systematic review of 116 user studies in AI-empowered IIS. Results reveal two primary research themes in user studies in AI-empowered IIS: human-IIS interaction (including user experience, system quality, user attitude, intention and behavior, information quality, and individual task performance) and IIS ethics (e.g., explainability and interpretability, privacy and safety, and inclusivity). Analyzing research gaps within these topics, this study formulates an HCIIS research framework consisting of three interconnected elements: human values and needs, environment, and service. The interconnections between each pair of elements identify three key research domains in HCIIS: interaction, ethics, and evolution. Interaction pertains to the facilitation of human-IIS interaction to meet human needs, encompassing topics including human-centered theory, evaluation, and the design of AI-empowered IIS interaction. Ethics emphasize ensuring AI-empowered IIS alignment with human values and norms within specific environments, covering topics like general and context-specific AI-empowered IIS ethical principles, risk assessment, and governance strategies. Evolution focuses on addressing the fulfillment of human needs in diverse and dynamic environments by continually evolving intelligence, involving the enhancement of AI-empowered IIS environmental sensitivity and adaptability within an intelligent ecosystem driven by technology integration. Central to HCIIS is co-creation, situated at the intersection of interaction, evolution, and ethics, emphasizing collaborative information creation between IIS and humans through hybrid intelligence. In conclusion, HCIIS is defined as a field centered on information co-creation between IIS and humans, distinguishing it from IIS, which focuses on providing information to humans.

Meta-Analyzing the Trust-Performance Link in Collaboration: Moderating Effects of Conceptual and Contextual Factors

Trust is vital for effective collaboration, but its impact on collaboration performance has produced inconsistent findings. This study examines the trust-collaboration performance link by testing the moderating effects of diverse conceptual and contextual factors. Through a comprehensive meta-analysis of 31 empirical studies, we synthesize siloed findings and offer a systematic and evidence-based examination of the trust-collaboration performance link. Our findings show that the trust-collaboration performance relationship is positive and stronger when trust is cognition-based rather than affect-based, when performance content focuses on process and outcomes, and when performance is subjectively measured. In addition, trust is more important in low generalized trust countries and in cross-sectoral or nonprofit collaboration. These moderation effects manifest differently in different collaboration forms, with trust playing a less salient role in contracting. These findings unravel the nuanced dynamics of trust within collaboration and have substantial implications for scholars and practitioners in collaborative governance and network management.

The Hong Kong Shue Yan University Social Work Research Center—A Case Analysis

Hong Kong Shue Yan University (HKSYU) Center for Social Work Research and Practice was established in 2015, aspiring to collaborate with industry partners to conduct research that enhance the industry's understanding of social issues and develop quality services for the community. HKSYU is a self-financing university without direct subsidies from the HKSAR Government to the Center. In the last couple of years, the Center has implemented 11 research and training projects, jointly organizing with local and overseas universities. Two of them adopted the interdisciplinary approach, collaborating with health and nursing disciplines. Using the extended case method, the Center was found to be aligned with the principles of evidence-based practice and research-mindedness in social work. Moreover, the Center normally adopted the “Translational form of collaboration,” coproducing research projects with industry partners. Upon reflection, the Center should maximize its involvement with social work practitioners to promote research-mindedness in the practice environment.

Clustering scRNA-seq data with the cross-view collaborative information fusion strategy.

Single-cell RNA sequencing (scRNA-seq) technology has revolutionized biological research by enabling high-throughput, cellular-resolution gene expression profiling. A critical step in scRNA-seq data analysis is cell clustering, which supports downstream analyses. However, the high-dimensional and sparse nature of scRNA-seq data poses significant challenges to existing clustering methods. Furthermore, integrating gene expression information with potential cell structure data remains largely unexplored. Here, we present scCFIB, a novel information bottleneck (IB)-based clustering algorithm that leverages the power of IB for efficient processing of high-dimensional sparse data and incorporates a cross-view fusion strategy to achieve robust cell clustering. scCFIB constructs a multi-feature space by establishing two distinct views from the original features. We then formulate the cell clustering problem as a target loss function within the IB framework, employing a collaborative information fusion strategy. To further optimize scCFIB's performance, we introduce a novel sequential optimization approach through an iterative process. Benchmarking against established methods on diverse scRNA-seq datasets demonstrates that scCFIB achieves superior performance in scRNA-seq data clustering tasks. Availability: the source code is publicly available on GitHub: https://github.com/weixiaojiao/scCFIB.

A Recommendation System for Trigger-Action Programming Rules via Graph Contrastive Learning.

Trigger-action programming (TAP) enables users to automate Internet of Things (IoT) devices by creating rules such as "IF Device1.TriggerState is triggered, THEN Device2.ActionState is executed". As the number of IoT devices grows, the combination space between the functions provided by devices expands, making manual rule creation time-consuming for end-users. Existing TAP recommendation systems enhance the efficiency of rule discovery but face two primary issues: they ignore the association of rules between users and fail to model collaborative information among users. To address these issues, this article proposes a graph contrastive learning-based recommendation system for TAP rules, named GCL4TAP. In GCL4TAP, we first devise a data partitioning method called DATA2DIV, which establishes cross-user rule relationships and is represented by a user-rule bipartite graph. Then, we design a user-user graph to model the similarities among users based on the categories and quantities of devices that they own. Finally, these graphs are converted into low-dimensional vector representations of users and rules using graph contrastive learning techniques. Extensive experiments conducted on a real-world smart home dataset demonstrate the superior performance of GCL4TAP compared to other state-of-the-art methods.

Preventing Corruption in Bali’s Customary Villages: How Do Regional Institutions Play a Role?

Customary villages are traditional institutions in Bali that have existed for centuries. The village has autonomy when it comes to managing its customary arrangements based on local traditions and wisdom, meaning that it does not have a hierarchical relationship with the government based on the state structure of the Republic of Indonesia. The Bali Province Government, a second-layer hierarchical government structure in Indonesia, applies a unique approach to performing relationships with customary villages in Bali as it has regularly supported the existence and activities of customary villages, including providing funding assistance. Unfortunately, several cases have shown the misuse of government funds. This article, therefore, identifies the practice of fraud and corruption in customary villages in Bali. Second, it analyses the role of the Customary Community Development Agency (DPMA) of the Bali Province Government in supervising the financial management of Bali's customary villages. Lastly, it supports the synergy between DPMA and the Representative Office of the Financial and Development Supervisory Agency (BPKP) of Bali Province in preventing corruption cases in the customary villages. The article applies empirical legal research, which involves collecting primary and secondary data and analyzing them using statutory, factual, and legal concept analysis approaches. The research suggests that fraud and corruption cases in customary villages cause a loss of government funds, harming the financial management of Village Credit Institutions (LPD), and involving the misuse of power. The provincial regulation authorizes DPMA to address this issue by monitoring how customary villages use the Bali Province Government grants. This paper then argues that the DPMA’s role would be more effective if it adopted a more formal collaboration with the Representative BPKP in Bali Province through various joint programs that support the comprehensive efforts to prevent corruption in customary villages in Bali.

Analyzing knowledge integration in convergence research

A pragmatic concern guides this perspective piece: How might researchers charged with leading convergence research better plan, design, implement, and evaluate the integrative processes and products of their research? We use a self-evaluation approach to assess the integrative processes and products of the first two years of a five-year National Science Foundation Growing Convergence Research project on addressing inland freshwater salinization. To examine the linkages between integration approaches and products, we analyzed the integrative qualities of fifteen research products and the collaborative processes used to generate these products. We found that large, heterogeneous teams with a broad mix of disciplines and professional expertise produced more interdisciplinary research products, but they relied on skilled integration by the leader, more intensive forms of collaboration, and inclusive problem framing. Teams that relied on deliberation by experts and used more consultative or cooperative mechanisms for engagement produced research that was more uni- or multi-disciplinary. We consider the efficacy of the various knowledge integration approaches used in this research and share empirically derived recommendations for designing, implementing, and evaluating convergence research. Our findings and lessons provide researchers at the helm of large-scale convergence and transdisciplinary research projects that address complex socio-environmental problems guidance on: (1) the planning and designing of projects with the explicit goal of knowledge integration; (2) the selection and implementation of appropriate knowledge integration approaches and tools; and (3) how knowledge integration can be conceptualized and evaluated for socio-environmental problems.

Teachers’ daily positive and negative affect and their relationship with teachers’ emotion regulation strategies and daily work engagement – results of a diary study among team teachers

AbstractTeam teaching as a close form of teacher collaboration entails frequent interactions between the team-teaching partners in the classroom. During these interactions, the team teachers experience a variety of positive and negative emotions, triggered by their team partner. The teachers may express or suppress these emotions, depending on their habitual use of these emotion regulation strategies. In turn, the teachers’ daily emotions may be related to an important facet of teacher well-being, namely their daily work engagement. This study aims to investigate the related factors (habitual emotion regulation, daily work engagement) of team teachers’ daily positive and negative emotions triggered by the team partner in the classroom. Forty-seven Austrian team teachers working in secondary education completed a daily diary study, consisting of 15 diary entries, measuring their habitual emotion expression and suppression strategies, their daily positive and negative affect and daily work engagement. Multilevel regression analyses were conducted. Results show that positive and negative affect and work engagement vary substantially within and between team teachers. Random-intercept fixed-slope multilevel models indicate that the habitual use of authentic display of positive emotions is associated with daily positive affect, and teachers’ daily positive and negative affect significantly relate to their daily work engagement both on the within- and between-person level. This study underscores the important role that team teachers’ emotional experiences play regarding their work engagement. We draw theoretical and practical implications for the role of emotions during team-teaching practices.

Collaborative Policymaking: a qualitative systematic review of advice for policymakers

Background Complex policy problems are not amenable to simple solutions by a few powerful policy actors in one central government. They require collaboration across government and between actors inside and outside of government. However, this requirement for collaboration is no guarantee of collective action. Further, it is difficult to know how to collaborate effectively. We searched the academic and grey literature for advice on how to foster collaborative policymaking. Methods We conducted a qualitative systematic review (2024) of peer reviewed journal articles (Web of Science) and grey literature reports (Policy Commons). Each article or report had to inform advice on collaborative policymaking. We used an immersive and inductive approach to identify key themes and relate the results to well-established insights from policy theories. Results 86 texts meet the inclusion criteria (49 Web of Science, 37 Policy Commons). Most provide broad definitions of collaborative policymaking, which are similar to definitions of collaborative governance (and connected aims such as policy co-creation). Many assert or assume that greater collaboration, across and inside/outside of government, will improve policymaking and policy. Few individual studies give advice on how to collaborate effectively, but they combine to identify common features of collaboration. Conclusions We synthesise the available advice to identify five main features of collaborative policymaking: plan and prepare to collaborate, such as by designing rules and allocating resources; create a sense of collective purpose, such as by setting a boundary around the collaboration and co-producing a common vision; foster creative methods to visualise collaboration and design policy; create new forums to supplement formal collaboration; and clarify the roles and skills essential to each collaborative task.

Meta concept recommendation based on knowledge graph

Massive Open Online Courses (MOOCs) are playing a key role in improving educational ways. Abundant learning resources make it difficult for online users to find suitable learning content. The current personalized service in the field of online education relies more on course recommendations. However, coarse-grained recommendations cannot help users discover the defects of their knowledge network effectively. In this paper, we propose a Knowledge-Aware Meta-Concept (KAMC) framework to provide fine-grained recommendation services. We innovatively incorporate Knowledge Graph (KG) into the field of educational recommendation to provide abundant auxiliary information. However, simply combining knowledge graphs with educational recommender systems cannot improve the performance of existing recommendation models, and may even weaken the performance of the models. Because the modeled KG ignores the enhancements on the user side and only considers the enhancements on the item side. We further propose to enrich the semantic representation of users with collaborative information in user-item interactions, and at the same time enrich the semantic representation of items with information in KG. Furthermore, to provide users with more accurate and fine-grained personalized recommendation services, we propose a user-based attention mechanism to capture users’ fine-grained semantic information. Our method is experimentally validated on three real-world datasets. In the three datasets, KAMC’s AUC evaluation index is 6.2%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$6.2\\%$$\\end{document}, 6.9%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$6.9\\%$$\\end{document}, and 2.2%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$2.2\\%$$\\end{document} higher than the latest baseline method (KGAN), respectively. Experimental results show that the KAMC method outperforms the current state-of-the-art baseline methods.

LOOK, THATS HOW I DO IT! TRY IT!

In Hungary, children and pupils with special educational needs are those who, on the basis of a diagnostic assessment by a committee of educational experts, are entitled to additional support for their development. Today, they are often placed in inclusive or integrative kindergartens and schools, where they learn with other children and are assisted in their development by a special needs teacher. Several studies have looked at the role of special needs teachers in inclusive education. Other approaches emphasise collaboration between professionals, and some forms of collaboration are seen as teamwork. Although these collaborations are necessary to achieve the best possible developmental outcomes, they are difficult to achieve for a number of reasons. This paper presents an action research project in which teamwork, i.e. case discussion, solution finding and knowledge transfer, took the form of online collaboration. The methodological framework was participatory action research. Although this form of collaboration was created out of necessity in the institution, the positive feedback and results from the participants show the need for activities and collective learning adapted to the knowledge level and needs of teachers, which help them to deal with everyday tasks and problems with more confidence and self-efficacy.