13 research outputs found
Teachers’ Conceptions of Student Engagement in Learning: The Case of Three Urban Schools
Although student engagement plays a central role in the education process, defining it is challenging. This study examines teachers’ conceptions of the social and cultural dimensions of student engagement in learning at three low-achieving schools located in a low socioeconomic status (SES) urban area. Sixteen teachers and administrators from the three schools participated in two focus group discussions about their definitions of student engagement, indicators of and factors affecting student engagement, and how to facilitate it. The findings indicate that teachers’ conceptions of student engagement have profound ramifications for the ways that they approach their work. Additionally, the teachers recognize that student engagement is a symptom displayed by individuals, but the roots of engagement lay elsewhere. The teachers also described a wide range of strategies to enhance their students' engagement that focused primarily on the student, the teacher and the classroom through improving student-teacher relationships, incorporating out-of-school issues in the curriculum and the classroom, and having teachers show engagement with educational material. We conclude by outlining several implications for practice and policy and by calling for more research on the origins, development and consequences of teachers’ conceptions of student engagement.Alors que l’engagement des élèves joue un rôle central dans le processus éducatif, en définir le sens représente un défi. Cette étude porte sur les conceptions qu’ont les enseignants des dimensions sociales et culturelles de l’engagement des élèves dans trois écoles peu performantes situées dans des régions urbaines à faible statut socioéconomique. Seize enseignants et administrateurs de trois écoles ont participé à des discussions thématiques de groupe pour partager ce qu’ils entendaient par « engagement des élèves », les indicateurs de celui-ci, les facteurs qui l’influençaient et les moyens de le faciliter. Les résultats indiquent que les conceptions qu’ont les enseignants de l’engagement des élèves ont des répercussions profondes sur leur façon d’aborder leur travail. De plus, les enseignants reconnaissent que l’engagement des élèves est un symptôme que manifeste une personne, mais que les racines en sont ailleurs. Les enseignants ont décrit une vaste gamme de stratégies qui visent l’augmentation de l’engagement des élèves, qui sont axées surtout sur l’élève, l’enseignant et la salle de classe, et qui reposent sur l’amélioration du rapport enseignant-élève, l’intégration d’enjeux externes dans le programme d’études et une manifestation d’engagement de la part des enseignants avec la matière à l’étude. Nous concluons en présentant les grandes lignes des incidences de cette étude sur la pratique et la politique, et en réclamant davantage de recherche sur les origines, le développement et les conséquences des conceptions qu’ont les enseignants de l’engagement des élèves.
Exploring the Challenges of Conducting Respectful Research: The Seen and Unforeseen Methodological Factors within Urban School Research.
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Emotion regulation and cognitive function as mediating factors for the association between lifetime abuse and risky behaviors in women of color.
BackgroundThe relationship between lifetime abuse (i.e., childhood abuse, intimate partner violence) and risky behaviors is well established. One proposed mechanism is poor emotion regulation and executive functioning, as a potential mechanism that may explain the relationship between lifetime abuse and risky behaviors. However, research on executive functioning and emotion regulation as mediators of this relationship has been limited. In the present study, we examined this association. We hypothesized that lifetime abuse would be significantly associated with executive function and emotion regulation which in turn would be associated with greater alcohol use and risky sex.MethodsThis cross-sectional study included 150 women with a history of lifetime abuse who were assessed for hazardous alcohol use using the AUDIT Score; emotion regulation was measured using the Difficulties with Emotion Regulation Scale (DERS); risky sex was measured using the question: "in the last 90 days, how many people did you have anal or vaginal sex without using a condom? Executive function was assessed using the NIH Toolbox.ResultsThe mediation model followed the self-regulation theory, which proposes executive function as the higher-order cognitive process. Results showed that executive function deficit and poor emotion regulation significantly mediated the relationship between lifetime abuse and hazardous alcohol use (indirect effect = .097, SE .031, 95% CI = .035 to .158).ConclusionOur findings suggest a higher-order cognitive process with executive function promoting emotion regulation as a potential mechanism for alcohol problems in women of color who experienced lifetime abuse
JuliaGPU/AMDGPU.jl: v0.7.4
<h2>AMDGPU v0.7.4</h2>
<p><a href="https://github.com/JuliaGPU/AMDGPU.jl/compare/v0.7.3...v0.7.4">Diff since v0.7.3</a></p>
<p><strong>Merged pull requests:</strong></p>
<ul>
<li>Update preconditioners.jl (#533) (@amontoison)</li>
<li>[rocSPARSE] Interface the generic routines (#535) (@amontoison)</li>
<li>Defer freeing hostcall buffers & add 1.10 CI (#538) (@pxl-th)</li>
<li>Have separate <code>free!</code> method for hostcalls (#539) (@pxl-th)</li>
<li>Switch to artifact device libraries if ROCm 5.5+ is detected (#540) (@pxl-th)</li>
<li>Fix artifact discovery in global project (#541) (@pxl-th)</li>
</ul>
<p><strong>Closed issues:</strong></p>
<ul>
<li>Investigate GPUArrays tests suite error (#515)</li>
<li>Multiple workers hang test suite on Julia 1.10 (#521)</li>
<li>[rocSPARSE] ILU(0) and IC(0) preconditioners are not working (#532)</li>
<li>Hostcall tests hang (#537)</li>
</ul>
JuliaGPU/AMDGPU.jl: v0.8.1
<h2>AMDGPU v0.8.1</h2>
<p><a href="https://github.com/JuliaGPU/AMDGPU.jl/compare/v0.8.0...v0.8.1">Diff since v0.8.0</a></p>
<p><strong>Merged pull requests:</strong></p>
<ul>
<li>Implement device-side RNG (#380) (@utkarsh530)</li>
<li>Fix path detection in ubuntu like systems (#545) (@gbaraldi)</li>
<li>Simplify ROCm discovery (#548) (@pxl-th)</li>
<li>[rocSPARSE] Add new constructors (#550) (@amontoison)</li>
<li>Check context is valid before freeing streams, arrays. (#552) (@pxl-th)</li>
<li>[rocSPARSE] Update helpers.jl (#554) (@amontoison)</li>
<li>Use Atomix.jl for atomics (#555) (@pxl-th)</li>
<li>Reset exception holder immediately after exception (#556) (@pxl-th)</li>
<li>Fix exception reporting (#557) (@pxl-th)</li>
<li>Cleanup (#559) (@pxl-th)</li>
</ul>
<p><strong>Closed issues:</strong></p>
<ul>
<li>Implement sparse BLAS routines (#15)</li>
<li>Implement iterative solvers (#13)</li>
<li>Create a Docker image for AMDGPU.jl (#33)</li>
<li>Implement batched off-thread HSA signal waiting (#128)</li>
<li>HSA_STATUS_ERROR_INVALID_CODE_OBJECT on gfx803 (#192)</li>
<li><code>hsa_executable_freeze</code> can hang during high GPU load (#208)</li>
<li>Implement copy!() (#218)</li>
<li>ROCM/Hip not downloading (?) when ]added (#230)</li>
<li>mapreducedim! is not implemented for AnyROCArray Types (#234)</li>
<li>Test of AMDGPU fails on 5900HX - hipErrorNoBinaryForGpu (#244)</li>
<li>Don't disable ROCm external library type definitions when non-functional (#350)</li>
<li>AMDGPU.jl doesn't seem to work with 7900 series GPUs (#371)</li>
<li>Support for rand from Julia Base on device code (#378)</li>
<li>Detect hardware queue limit and use to limit queue pool size (#403)</li>
<li>AMDGPU on windows (#465)</li>
<li>Rely on Atomix.jl for atomics (#547)</li>
</ul>
JuliaGPU/AMDGPU.jl: v0.8.4
<h2>AMDGPU v0.8.4</h2>
<p><a href="https://github.com/JuliaGPU/AMDGPU.jl/compare/v0.8.3...v0.8.4">Diff since v0.8.3</a></p>
<p><strong>Merged pull requests:</strong></p>
<ul>
<li>Adapt to GPUArrays@10 (#580) (@pxl-th)</li>
</ul>
JuliaGPU/AMDGPU.jl: v0.7.3
<h2>AMDGPU v0.7.3</h2>
<p><a href="https://github.com/JuliaGPU/AMDGPU.jl/compare/v0.7.2...v0.7.3">Diff since v0.7.2</a></p>
<p><strong>Merged pull requests:</strong></p>
<ul>
<li>Fix ISA parsing (#531) (@pxl-th)</li>
</ul>
<p><strong>Closed issues:</strong></p>
<ul>
<li>AMDGPU 0.7.x target error on Frontier (#530)</li>
</ul>
JuliaGPU/AMDGPU.jl: v0.7.2
<h2>AMDGPU v0.7.2</h2>
<p><a href="https://github.com/JuliaGPU/AMDGPU.jl/compare/v0.7.1...v0.7.2">Diff since v0.7.1</a></p>
<p><strong>Merged pull requests:</strong></p>
<ul>
<li>Revert devlib linking opt (#529) (@pxl-th)</li>
</ul>
JuliaGPU/AMDGPU.jl: v0.7.1
<h2>AMDGPU v0.7.1</h2>
<p><a href="https://github.com/JuliaGPU/AMDGPU.jl/compare/v0.7.0...v0.7.1">Diff since v0.7.0</a></p>
<p><strong>Merged pull requests:</strong></p>
<ul>
<li>Fix intial device fetching (#528) (@pxl-th)</li>
</ul>
<p><strong>Closed issues:</strong></p>
<ul>
<li>Support for multi-GPU nodes broken in 0.7 (#527)</li>
</ul>
JuliaGPU/AMDGPU.jl: v0.8.2
<h2>AMDGPU v0.8.2</h2>
<p><a href="https://github.com/JuliaGPU/AMDGPU.jl/compare/v0.8.1...v0.8.2">Diff since v0.8.1</a></p>
<p><strong>Merged pull requests:</strong></p>
<ul>
<li>[rocSPARSE] Add a structure MatInfo for IC(0) and ILU(0) preconditioners (#558) (@amontoison)</li>
<li>Define comparison method for HIPContext (#561) (@pxl-th)</li>
<li>Improve type inference (#562) (@pxl-th)</li>
<li>Refactor alloc/retry (#563) (@pxl-th)</li>
<li>Fix functional (#565) (@pxl-th)</li>
<li>Use regular malloc/free (#566) (@pxl-th)</li>
</ul>
<p><strong>Closed issues:</strong></p>
<ul>
<li>has_rocm_gpu() fails (#564)</li>
</ul>