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Achieving continuous innovation performance still poses a major challenge to established companies as it requires high flexibility and adaptability in usually efficiently structured organisations. One way to tackle this challenge lies in establishing effective behaviours to successfully establish and apply innovation leadership mechanisms in an organisation. The emerging agile leadership style could provide such effective behaviours, as it addresses the demand for flexibility and adaptability on the organisational level. Despite these clear parallels research on the link between agile leadership and innovation leadership, and their possible combined contribution to drive continuous innovation performance is still in its infancy. Accordingly, the present study examines the behaviours of agile leaders to promote continuous innovation in established companies. It applies a discovery-driven research process of agile leaders to derive and categorise their behaviours. The subsequent comparison of the identified agile leadership behaviours with innovation leadership mechanisms from existing literature leads to eight specific, combined agile leadership principles within the three categories empowerment, performance enhancement, and support for continuous innovation. Eventually, this basis allows the conceptualisation of a first exploratory framework with the identified behaviours as possible enablers, and innovation leadership mechanisms as possible mediators for the continuous innovation performance, subject to test. These findings enhance existing theory by clarifying a possible link between agile leadership and continuous innovation. That way, practitioners can profit from concrete principles for agile leaders to inspire and enable continuous innovation in individuals and teams.

This study explores the determinants of police officer support for pre-arrest/booking deflection programs that divert people presenting with substance use and/or mental health disorder symptoms out of the criminal justice system and connect them to supportive services.

This study analyzes responses from 254 surveys fielded to police officers in Delaware. Questionnaires asked about views on leadership, approaches toward crime, training, occupational experience and officer’s personal characteristics. The study applies a new machine learning method called kernel-based regularized least squares (KRLS) for non-linearities and interactions among independent variables. Estimates from a KRLS model are compared with those from an ordinary least square regression (OLS) model.

Support for diversion is positively associated with leadership endorsing diversion and thinking of new ways to solve problems. Tough-on-crime attitudes diminish programmatic support. Tenure becomes less predictive of police attitudes in the KRLS model, suggesting interactions with other factors. The KRLS model explains a larger proportion of the variance in officer attitudes than the traditional OLS model.

The study demonstrates the usefulness of the KRLS method for practitioners and scholars seeking to illuminate patterns in police attitudes. It further underscores the importance of agency leadership in legitimizing deflection as a pathway to addressing behavioral health challenges in communities.

This study reports on changes made within the study, plan, teach and reflect steps of lesson study with pre-service teachers who were learning to teach within a disciplinary literacy course.

Using methods associated with formative experiments and design-based research, this study gathered data over four iterations of the disciplinary literacy course. Data included the course materials, pre-service teachers’ written work, observational notes from research lessons, transcripts of post-lesson discussions and teacher-educators’ analysis sessions and pre-service teachers’ post-program interviews. Data were analyzed within and across iterations.

Initial adjustments to the lesson study process focused on the reflect step, as we learned to better scaffold pre-service teachers sharing of observational data from research lessons. Later adjustments occurred in the study and plan steps, as we refined the design of four-day lesson sequences that better supported pre-service teachers’ attention to disciplinary literacy while providing room for their instructional mentors to provide specific team-based feedback. Adjustments to the teach step included reteaching and more explicit attention to literacy objectives.

This paper contributes to the literature by explicitly applying formative experiment and design-based research methods to the implementation of lesson study with pre-service teachers. Furthermore, it contributes examples of lesson study within a disciplinary literacy context, expanding the examples of lesson study’s applicability across content areas.

This study aims to uncover the ongoing discourse on generative artificial intelligence (AI), literacy and governance while providing nuanced perspectives on stakeholder involvement and recommendations for the effective regulation and utilization of generative AI technologies.

This study chooses generative AI-related online news coverage on BBC News as the case study. Oriented by a case study methodology, this study conducts a qualitative content analysis on 78 news articles related to generative AI.

By analyzing 78 news articles, generative AI is found to be portrayed in the news in the following ways: Generative AI is primarily used in generating texts, images, audio and videos. Generative AI can have both positive and negative impacts on people’s everyday lives. People’s generative AI literacy includes understanding, using and evaluating generative AI and combating generative AI harms. Various stakeholders, encompassing government authorities, industry, organizations/institutions, academia and affected individuals/users, engage in the practice of AI governance concerning generative AI.

Based on the findings, this study constructs a framework of competencies and considerations constituting generative AI literacy. Furthermore, this study underscores the role played by government authorities as coordinators who conduct co-governance with other stakeholders regarding generative AI literacy and who possess the legislative authority to offer robust legal safeguards to protect against harm.