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This study developed new measures of the routine and non-routine task contents of managerial, professional, technical, and clerical occupations from a workload perspective. Here, we present a comparative analysis of the workload structures of state and industrial sector employees.

Our method involves detailed descriptions of work processes and an element-wise time study. We collected and analysed data to obtain a workload structure that falls within three conceptual task categories: (i) non-routine analytic tasks, (ii) non-routine interactive tasks and (iii) routine cognitive tasks. A total of 2,312 state and industrial sector employees in Kazakhstan participated in the study. The data were collected using a proprietary web application that resembles a timesheet.

The study results are consistent with the general trend reported by previous studies: the higher the job level, the lower the occupation’s routine task content. In addition, the routine cognitive task contents of managerial, professional, technical, and clerical occupations in the industrial sector are higher than those in local governments. The work of women is also more routinary than that of men. Finally, vthe routine cognitive task contents of occupations in administrative units are higher than those of occupations in substantive units.

Our study sought to address the challenges of using the task-based approach associated with measuring tasks by introducing a new measurement framework. The main advantage of our task measures is a direct approach to assessing workloads consisting of routine tasks, which allows for an accurate estimation of potential staff reductions due to the automation of work processes.

In the era of big data, various industries are generating large amounts of text data every day. Simplifying and summarizing these data can effectively serve users and improve efficiency. Recently, zero-shot prompting in large language models (LLMs) has demonstrated remarkable performance on various language tasks. However, generating a very “concise” multi-document summary is a difficult task for it. When conciseness is specified in the zero-shot prompting, the generated multi-document summary still contains some unimportant information, even with the few-shot prompting. This paper aims to propose a LLMs prompting for multi-document summarization task.

To overcome this challenge, the authors propose chain-of-event (CoE) prompting for multi-document summarization (MDS) task. In this prompting, the authors take events as the center and propose a four-step summary reasoning process: specific event extraction; event abstraction and generalization; common event statistics; and summary generation. To further improve the performance of LLMs, the authors extend CoE prompting with the example of summary reasoning.

Summaries generated by CoE prompting are more abstractive, concise and accurate. The authors evaluate the authors’ proposed prompting on two data sets. The experimental results over ChatGLM2-6b show that the authors’ proposed CoE prompting consistently outperforms other typical promptings across all data sets.

This paper proposes CoE prompting to solve MDS tasks by the LLMs. CoE prompting can not only identify the key events but also ensure the conciseness of the summary. By this method, users can access the most relevant and important information quickly, improving their decision-making processes.

Preservice teachers (PSTs) typically have few opportunities to observe social studies instruction in PSTs' elementary field placements. To practice effective integration as a pathway to include more social studies instruction, PSTs developed a unit plan based on inquiry during an undergraduate methods course. The purpose of this study was to explore what scaffolds were effective in PSTs' development of social studies inquiry projects.

The author used a multiple case study approach, examining initial submissions, feedback and resubmissions as PSTs developed PSTs' inquiry projects. The data were analyzed with an eye on PSTs' ability to plan a unit according to the four dimensions of the C3 Framework's inquiry arc (National Council for the Social Studies [NCSS], 2013).

The author analyzed data related to PSTs’ area of highest need from PSTs' initial submissions: staging the task, formative tasks and resources. PSTs were able to develop inquiry projects after being supported in their (1) organization, (2) clarity, (3) alignment and (4) developmental appropriateness.

This study shows that novice teachers can create high-quality social studies learning experiences in elementary school when provided appropriate supports (in this case, feedback about organization, clarity, alignment and developmental appropriateness). With the tools to develop such projects, new teachers may be able to increase the amount of social studies taught in elementary classrooms.

Despite the technological paradigm shift presented to the architecture, engineering, construction and operations sector (AECO), the full-fledged acceptance of the building information modelling (BIM) methodology has been slower than initially anticipated. Indeed, this study aims to acknowledge the need for increasing supportive technologies enabling the use of BIM, attending to available human resources, their requirements and their tasks.

A complete case study is described, including the development process centred on design science research methodology followed by the usability assessment procedure validated by construction projects facility management operational staff.

Results show that participants could interact with BIM using openBIM processes and file formats naturally, as most participants reached an efficiency level close to that expected for users already familiar with the interface (i.e. high-efficiency values). These results are consistent with the reported perceived satisfaction and analysis of participants’ discourses through 62 semi-structured interviews.

The contributions of the present study are twofold: a proposal for a virtual reality openBIM framework is presented, particularly for the semantic enrichment of BIM models, and a methodology for evaluating the usability of this type of system in the AECO sector.

This article aims to address the confusion related to the meanings of interorganisational cooperation, control, coordination and collaboration in collaborative projects by developing a conceptual framework. From this, the authors aim to describe the links among these concepts in terms of development levels of stakeholder relationships. In addition, the authors aim to identify challenges and preconditions in relation to developing relationships at different levels.

The authors have adopted the directed approach of qualitative content analysis method to validate and extend the conceptual framework of this study. The context of this study is a large hospital construction project located in northern Finland.

The findings of this study suggest that collaboration is a multilevel process of active engagement of multiple stakeholders. These stakeholders must have a high degree of shared understanding in terms of cooperation, control and coordination to achieve the mutually desired outcomes. This study also identifies the challenges that project stakeholders could face in developing collaborative relationships and propose preconditions for the same.

This study provides a better understanding for project managers to manage interorganisational collaborative construction projects successfully. The outcome of this research would be beneficial to project management team to deliver dispute-free construction projects.

Existing practical research on the development of relationships at different levels in collaborative construction projects is limited. This study offers a framework for the same which is validated in a real-life project.

This study aimed to investigate the sensemaking strategies employed by early-career employees working within organizationally constrained environments.

Grounded in the sensemaking-as-accomplishment framework, a longitudinal multi-case study was conducted, involving three early-career employees. These participants were interviewed multiple times concerning tasks they themselves identified as anomalous and ambiguous.

The study's findings illuminate how early-career employees utilize sensemaking strategies to accomplish anomalous-ambiguous tasks. These strategies are interwoven with deliberate efforts to mitigate organizational constraints that exist in the organization or arise during the execution of complex tasks.

Notable limitation pertains to the time gap between task completion and the interviews. Conducting real-time interviews concurrently with task execution or immediately afterward was not feasible due to constraints in participant availability. This research has implications for organizational learning initiatives, particularly those encompassing employee-driven self-learning components. Insights derived from studies like this can inform the development of effective self-learning schemes within organizations.

Previous sensemaking research focused on what takes place in high-reliability organizations. This study explored sensemaking strategies in workplaces that are organizationally constrained.

The study consists of a literature study and a case study. The need for a method via which to handle instruction complexity was identified in both studies. The proposed method was developed based on methods from the literature and experience from the case company.

The purpose of the study presented in this paper is to investigate how linking different maintenance domains in a modular maintenance instruction architecture can help reduce the complexity of maintenance instructions.

The proposed method combines knowledge from the operational and physical domains to reduce the number of instruction task variants. In a case study, the number of instruction task modules was reduced from 224 to 20, covering 83% of the maintenance performed on emergency shutdown valves.

The study showed that the other methods proposed within the body of maintenance literature mainly focus on the development of modular instructions, without the reduction of complexity and non-value-adding variation observed in the product architecture literature.

This study aims to adopt a systematic review approach to examine the existing literature on law and LLMs.It involves analyzing and synthesizing relevant research papers, reports and scholarly articles that discuss the use of LLMs in the legal domain. The review encompasses various aspects, including an analysis of LLMs, legal natural language processing (NLP), model tuning techniques, data processing strategies and frameworks for addressing the challenges associated with legal question-and-answer (Q&A) systems. Additionally, the study explores potential applications and services that can benefit from the integration of LLMs in the field of intelligent justice.

This paper surveys the state-of-the-art research on law LLMs and their application in the field of intelligent justice. The study aims to identify the challenges associated with developing Q&A systems based on LLMs and explores potential directions for future research and development. The ultimate goal is to contribute to the advancement of intelligent justice by effectively leveraging LLMs.

To effectively apply a law LLM, systematic research on LLM, legal NLP and model adjustment technology is required.

This study contributes to the field of intelligent justice by providing a comprehensive review of the current state of research on law LLMs.

Recent studies on search-as-learning (SAL) have recognized the significance of identifying users' learning needs as they evolve for acquiring knowledge during the search process. In this study, the authors clarify the extent to which search behaviors reflect the learning outcome and foster the users' knowledge of Chinese art.

The authors conducted an exploratory-sequential mixed-methods approach using simulated work task situations to collect empirical data. The authors used two types of simulated learning tasks for topics related to painting and antique knowledge. A lot of 25 users participated in this evaluation of digital archives (DAs) at the National Palace Museum (NPM) in Taiwan. For each set of topics, a close-ended task related to lower-level learning goals and an open-ended task related to higher-level learning goals.

The learning criteria reflect changes in the users' knowledge structure, revealing the SAL process. Furthermore, users achieved better task performance on the higher-level creative-learning task, which suggests that they met more learning criteria, exhibited a greater variety of search patterns when exploring the topics via interaction with various sources. Finally, there is a close relationship between creative-learning tasks, prior knowledge, keyword search actions and learning outcomes.

The authors discuss implications with respect to the design of DAs in practice and contributions to the body of SAL knowledge in DAs of online museums. For future reference, the authors provide implications for the development of learning measures from the perspective of user search behavior with associated learning outcomes in the context of DAs.

The aim of this study is to empirically explore and analyze the concrete tasks of output measurement and the inherent challenges related to these tasks in a traditional and autonomous professional public work setting – the judicial system.

The analysis of the tasks is based on a categorization of general performance measurement motives (control-motivate-learn) and main stakeholder levels (society-organization-professionals). The analysis is exploratory and conducted as an empirical content analysis on materials and reports produced in two performance improvement projects conducted in European justice organizations.

The identified main tasks in the different categories are related to managing resources, controlling performance deviations, and encouraging improvement and development of performance. Based on the results, key improvement areas connected to output measurement in professional public organizations are connected to the improvement of objectivity and fairness in budgeting and work allocation practices, improvement of output measures' versatility and informativeness to highlight motivational and learning purposes, improvement of professional self-management in setting output targets and producing outputs, as well as improvement of organizational learning from the output measurement.

The paper presents empirically founded practical examples of challenges and improvement opportunities related to the tasks of output measurement in professional public organization.

This paper fulfils an identified need to study how general performance management motives realize as concrete tasks of output measurement in justice organizations.