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Structured classroom observation protocols provide instructors with data about their teaching practices, but instructors may not meaningfully engage with those data without guidance. To facilitate instructor reflection, educational developers from the Centers for Teaching and Learning (CTLs) and educational researchers from STEM departments across three campuses collaborated to design and implement a novel faculty professional development program that would promote reflection on teaching using instructors’ Classroom Observation Protocol for Undergraduate STEM (COPUS; Smith et al., 2013) data—a program we call data-informed professional development (DIPD). The program involved faculty completion of/participation in a teaching reflection, structured classroom observations from two course sessions, at least one meeting with CTL staff, an exit interview, and an opportunity to update their original teaching reflection. Through qualitatively coding the post-DIPD exit interviews, we found that instructors primarily reflected on their COPUS data with a desire to increase student engagement. Instructors also described being more open to making small changes to their courses, feeling supported to make changes to their teaching, and feeling that there was an important element of community-building in the DIPD program. And finally, instructors described how the DIPD experience was beneficial for promoting reflection on teaching practices, but the meeting portion was critical–providing data from the structured observations alone was not sufficient for a variety of reasons. Our study can serve as a teaching professional development model for how educational developers and education researchers can collaborate to prompt instructors to critically reflect on their teaching practices using structured observation protocols.

Describe a multilevel, community-based participatory process to recruit diverse Lewy Body Dementia (LBD) family caregivers into a nationwide, virtual, randomized controlled trial (RCT, NCT06389032).

Background: Suspected transient ischaemic attack is a diagnostic challenge, yet requires timely diagnosis for secondary stroke prevention. Aims: To understand variability of organisational processes, roles, education and clinical decision making in the UK's transient ischaemic attack services. Methods: Healthcare professionals were surveyed online in 2021 with descriptive data analysis. Interviews were conducted with a purposive sample. Three researchers thematically analysed interview data. Findings: Survey responses were received from 43 transient ischaemic attack services. 70% conducted remote consultations, 28% face-to-face, and 2% mixed. Clinicians with varying roles, skills and experience provided transient ischaemic attack services. All services involved a consultant physician with experience in stroke. Ten interviews confirmed the survey results and highlighted variability regarding clinical decision making, service composition, resources, learning opportunities and mode of consultation. Conclusions: Variability in transient ischaemic attack service workforce and service organisation influenced diagnostic decisions. The possible impact of such variability on clinical outcomes and approaches to reducing it require further research.

Virtual reality (VR) simulations have shown promise in helping students learn abstract concepts and visualize 3D objects at scale. While VR is useful for teaching subjects in science, technology, engineering, and mathematics (STEM) topics, early research has focused more on efficacy than instructional design. Understanding the factors that contribute to VR educational outcomes is increasingly important, particularly how to integrate instructional design into creating custom implementations. This paper presents the design and development of a VR application for teaching crystalline structures in undergraduate physics courses. Utilizing the SAMR model of technology integration, this study explores how collaboration with instructors can integrate VR into various class components, each requiring different VR features. Key features include visualizing, constructing, and manipulating crystal structures for instruction, assignments, and assessment. The application includes tools for generating atoms, creating lattice frames, and building composite structures to enhance comprehension of geometric arrangements and theoretical rules. Applying instruction design theories to VR in STEM education has implications for future applications, as successful VR educational tools depend on practical considerations, instructor goals, and implementation factors.

The impact of every crisis has the potential to cascade throughout an organisation’s operations, supply chain and market ecosystem. To properly understand and mitigate this ripple of dynamic risk, business continuity, security and risk management leaders need to know where to focus their attention. Looking at historical threat data provides a clearer picture of the risk landscape, helping leaders better anticipate and plan for the future. To date, however, there have been challenges in this process. As the volume of data about critical events continues to grow at an alarming rate, sifting manually through data puts organisations — and business continuity — in jeopardy. This paper discusses the value of historical threat data and innovations in data-mining technology that can unlock the true power of historical data for informed, strategic decision-making and better outcomes during a crisis.

<p>Graduate students commonly experience isolation and estrangement when conducting their final research projects, which can contribute to difficulties in completion. A creative and socially beneficial way to offset academic isolation is for graduate students to engage in participatory and action-oriented research projects with local communities. Facilitating a research study with a local partner can be a richly rewarding experience. This article argues that students who enjoy working in collaborative environments and want their final research projects to lead to beneficial social change can find fulfillment in action research (AR) methodologies. Critiqued by some for its lack of tangible and practical methods and its over-reliance on ideology, others, including the author, argue that the benefits of participatory research far outweigh the challenges.</p> <p> </p>

<p>Graduate students commonly experience isolation and estrangement when conducting their final research projects, which can contribute to difficulties in completion. A creative and socially beneficial way to offset academic isolation is for graduate students to engage in participatory and action-oriented research projects with local communities. Facilitating a research study with a local partner can be a richly rewarding experience. This article argues that students who enjoy working in collaborative environments and want their final research projects to lead to beneficial social change can find fulfillment in action research (AR) methodologies. Critiqued by some for its lack of tangible and practical methods and its over-reliance on ideology, others, including the author, argue that the benefits of participatory research far outweigh the challenges.</p> <p> </p>

Students’ sense of belonging is associated with successful transition into higher education and a range of positive outcomes including enhanced learning, well-being, and demonstrated achievement. The COVID-19 pandemic underscored the importance of belonging as the shift to online learning highlighted the challenges of supporting and monitoring student belonging. Attending to belonging is not simple, however; students’ experiences with belonging are complex, dynamic, and contextual. In creating a new agenda connecting the fields of belonging and learning analytics, we propose the idea of “belonging analytics” to address the challenge of supporting and tracking students’ belonging. In this paper, we discuss how the understanding of belonging may be enhanced through learning analytics. Advancements in learning analytics, such as digital trace data, narratives, textual data, or a combination, may be harnessed to gain insights into ongoing experience of belonging, and consequently to support belonging. We conclude with a set of open questions to interested researchers and practitioners, to advance the field of belonging analytics. LIFT Learning: The authors recently presented on the topic of Belonging Analytics at Indiana University’s 5th International Learning Analytics Summit. Engage with part of this discussion through this article’s companion LIFT Learning site where the authors describe their proposition and lay out the key concepts and challenges associated with belonging. As part of this, the authors discuss the case study presented in the article in greater detail, and provide additional contextual information that enhances the reader’s understanding of the proposal. The LIFT Learning site is available at https://apps.lift.c3l.ai/learning/course/course-v1:LEARNINGLETTERS+0104+2023