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Interdisciplinary PhD programs can be challenging as the vital information needed by students may not be readily available; it is scattered across the university’s websites, while tacit knowledge can be obtained only by interacting with people. Hence, there is a need to develop a knowledge management model to create, query and maintain a knowledge repository for interdisciplinary students. This study aims to propose a knowledge graph containing information on critical categories (faculty, classes, dissertations, etc.) and their relationships, extracted from multiple sources, essential for interdisciplinary PhD students. This study evaluates the usability of a participatory-designed knowledge graph intended to facilitate information exchange and decision-making.

The authors used data from multiple sources (such as university websites, faculty profiles, publication and dissertation metadata and crowdsourced data) to generate a knowledge graph in the Neo4J Bloom platform. The authors recruited 15 interdisciplinary PhD students using convenience sampling from the University of Hawaiʻi at Mānoa at various PhD stages to design and populate the knowledge graph. Next, the authors conducted a mixed methods study to perform its usability evaluation. First, the authors engaged the students in a participatory design workshop to identify relevant graph queries. Second, the authors conducted semi-structured interviews to determine the usability of the knowledge graph and rate the queries. Each interview was coded with structural and thematic codes and was further analyzed using sentiment analysis in R programming language.

The usability findings demonstrate that interaction with this knowledge graph benefits PhD students by notably reducing uncertainty and academic stress, particularly among newcomers. Knowledge graph supported them in decision-making, especially when choosing collaborators (e.g. supervisor or dissertation committee members) in an interdisciplinary setting. Key helpful features are related to exploring student–faculty networks, milestones tracking, rapid access to aggregated data and insights into crowdsourced fellow students’ activities. However, they showed concerns about crowdsourced data privacy and accessibility. Although participants expressed the need for more qualitative data in the graph, they noted it helped identify people to talk to about the topics of their interest.

The knowledge graph provides a solution to meet the personalized needs of doctoral researchers and has the potential to improve the information discovery and decision-making process substantially. It also includes the tacit knowledge exchange support missing from most current approaches, which is critical for this population and establishing interdisciplinary collaborations. This approach can be applied to other interdisciplinary programs and domains globally.

In academia, assessment is often narrow in its focus on research productivity, its application of a limited number of standardised metrics and its summative approach aimed at selection. This approach, corresponding to an exclusive, subject-oriented concept of talent management, can be thought of as at odds with a broader view of the role of academic institutions as accelerating and improving science and scholarship and its societal impact. In recent years, open science practices as well as research integrity issues have increased awareness of the need for a more inclusive approach to assessment and talent management in academia, broadening assessment to reward the full spectrum of academic activities and, within that spectrum, deepening assessment by critically reflecting on the processes and indicators involved (both qualitative and quantitative). In terms of talent management, this would mean a move from research-focused assessment to assessment including all academic activities (including education, professional performance and leadership), a shift from focus on the individual to a focus on collaboration in teams (recognising contributions of both academic and support staff), increased attention for formative assessment and greater agency for those being evaluated, as well as around the data, tools and platforms used in assessment. Together, this represents a more inclusive, subject-oriented approach to talent management. Implementation of such changes requires involvement from university management, human resource management and academic and support staff at all career levels, and universities would benefit from participation in mutual learning initiatives currently taking shape in various regions of the world.

Research excellency has long been the dominant paradigm in assessing academic quality and hence a prime determinant of academic careers. Lately, this approach to academic performance has come under higher scrutiny for its narrow focus on the individual, promoted an exclusive, performance-oriented talent management and inhibiting collaboration, transparency and societal involvement.

As a response to the limitations of the excellency policy, this chapter examines the emergence of open science as a transformative force in the academic world. Open science represents a paradigm shift, emphasizing the importance of transparency, and increased societal engagement in the academic process. It opens up the possibility to include the context dimension, multiple stakeholders and a more diverse set of development and performance indicators.

This chapter stresses the urgent need to realign our system of recognition and rewards with the premise of open science and with talent management. By highlighting the disconnect between current recognition mechanisms and the values of universities, this chapter emphasizes the necessity of transformative changes at institutional and systemic levels.

To provide concrete insights into the implementation of these changes, this chapter explores a case study of Utrecht University. This specific example showcases how strategic decisions at an institute level allow navigation of the complexities of recognizing and rewarding open science practices. The Utrecht University case study serves as an inspiration for other institutions seeking to embrace open science and adapt their policies and practices accordingly.

Post-COVID-19, public K–12 schools are still facing the consequences of the years of interrupted learning. Schools serving minoritized students are particularly at risk for facing challenges with academics, behavior and student social emotional health. The university counseling programs are in positions to build capacity in urban schools while also supporting counselors-in-training through service-learning opportunities.

The following conceptual manuscript demonstrates how counselor education counseling programs and public schools can harness the capacity-building benefits of university–school partnerships. While prevalent in fields like special education, counselor educators have yet to heed the hall to participate in mutually beneficial partnership programs.

Using the multi-tiered systems of support (MTSS) and the components of the university–school partnerships, counselor educators and school stakeholders can work together to support student mental health, school staff well-being and counselor-in-training competence.

The benefits and opportunities within the university–school partnerships are well documented. However, few researchers have described a model to support partnerships between the university counseling programs and urban elementary schools. We provide a best practice model using the principles of university–school partnerships and a school’s existing MTSS framework.

The purpose of this co-produced research project was to conduct interviews with people working in, volunteering with and accessing Canadian recovery colleges (RCs) to explore their perspectives on what an evaluation strategy for RCs could look like.

This study used a participatory action research approach and involved semistructured interviews with 29 people involved with RCs across Canada.

In this paper, the authors share insights from participants about the purposes of RC evaluation; key elements of evaluation; and the most applicable and effective approaches to evaluation. Participants indicated that RC evaluations should use a personalized, humanistic and accessible approach. The findings suggest that evaluations can serve multiple purposes and have the potential to support both organizational and personal-recovery goals if they are developed with meaningful input from people who access and work in RCs.

The findings can be used to guide evaluations in which aspects that are most important to those involved in RCs could inform choices, decisions, priorities, developments and adaptations in RC evaluation processes and, ultimately, in programming.

A recent scoping review revealed that although coproduction is a central feature of the RC model, coproduction principles are rarely acknowledged in descriptions of how RC evaluation strategies are developed. Exploring coproduction processes in all aspects of the RC model, including evaluation, can further the mission of RCs, which is to create spaces where people can come together and engage in mutual capacity-building and collaboration.

The purpose of this study is to test whether equity theory (ET) – which posits that individuals compare their outcome/input ratio to the ratio of a “comparison other” and classify individuals as Benevolent, Equity Sensity, and Entitled – applies to the modern workplace of global virtual teams (GVT), where work is mostly intellectual, geographically dispersed and online, making individual effort nearly impossible to observe directly.

Using a sample of 1,343 GVTs comprised 6,347 individuals from 137 countries, this study tests three ET’s predictions in the GVT context: a negative, linear relationship between Benevolents’ perceptions of equity and job satisfaction in GVTs; an inverted U-shaped relationship between Equity Sensitives’ perceptions of equity and job satisfaction in GVTs; and a positive, linear relationship between Entitleds’ perceptions of equity and job satisfaction in GVTs.

Although the second prediction of ET is supported, the first and third have statistically significant opposite signs.

The research has important ramifications for management studies in explaining differences in organizational behavior in GVTs as opposed to traditional work settings.

The authors conclude that the main novelty with ET in GVTs is that GVTs are an environment stingy with satisfaction for “takers” (Entitleds) and generous in satisfaction for “givers” (Benevolents).

The objective of this study was to develop wearable suit platforms with various anchoring structure designs with the intention of improving wearability and enhancing user satisfaction.

This study selected fabrics and materials for the suit platform through material performance tests. Two anchoring structure designs, 11-type and X-type are compared with regular clothing under control conditions. To evaluate the comfort level of the wearable suit platform, a satisfaction survey and electroencephalogram (EEG) measurements are conducted to triangulate the findings.

The 11-type exhibited higher values in comfort indicators such as α, θ, α/High-β and lower values in concentration or stress indicators such as β, ϒ, sensorimotor rhythm (SMR)+Mid-β/θ, and a spectral edge frequency of 95% compared to the X-type while walking. The 11-type offers greater comfort and satisfaction compared to the X-type when lifting based on the EEG measurements and the participants survey.

It is recommended to implement the 11-type when designing wearable suit platforms. These findings offer essential data on wearability, which can guide the development of soft wearable robots.

This paper aims to identify and classify the parameters that construct the input, processes, output, productivity and outcome variables that affect performance. These parameters are used in the evaluation model to measure research performance in universities so that they can be used as the basis for making leadership policies both at the national and institutional levels.

The design of this research is a quantitative research method using a survey questionnaire that was sent to the heads of research institutions at universities in Indonesia. To obtain these parameters, a test for determining the value of the loading factor was used.

The authors found that input variable parameters consisted of 10 parameters; process variable consisted of 22 parameters; output variable parameters consisted of 8 parameters; productivity variable consisted of 4 parameters; and outcome variable parameters consisted of 10 parameters.

One approach to obtain parameters is through systems theory, where every element that makes up the organization contributes to the achievement of goals. This study attempted to develop parameters in the performance appraisal model of systems theory-based research institutions that are adapted to trends in the direction of research in universities. These parameters are based on aspects of input, process, output, productivity and outcome.

The new concept of corporate social innovation (CSI) has witnessed a steady growth in the business and management academic world over the past 20 years. Yet its adoption by corporations has been notably slow. This paper aims to operationalize the concept and develop a research agenda for CSI.

A systematic review of the current literature in the recent past (1999–2020) has been embraced in this research. The review is based on 40 articles and offers a descriptive and a thematic analysis of the literature.

The authors demonstrate the development of the concept over time and identify 12 themes to assist in the institutionalization of CSI.

To the best of the authors’ knowledge, this study is the first to provide an enhanced overview of the current state of CSI. The paper shows how a variety of different definitions of corporate social innovation have been used in the business and management literature. The findings provide a unique conceptual framework and a detailed research agenda for scholars seeking to examine CSI.