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Record W2963652187

Developing self efficacy in research skills: becoming research-minded

2010· book-chapter· en· W2963652187 on OpenAlexaboutno aff
Anne Quinney, Jonathan Parker

Bibliographic record

VenueBournemouth University Research Online (Bournemouth University) · 2010
Typebook-chapter
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsnot available
Fundersnot available
KeywordsCompetence (human resources)UnderpinningWork (physics)Capacity buildingSelf-efficacyPsychologyPedagogyMedical educationPolitical scienceEngineeringMedicineSocial psychology
DOInot available

Abstract

fetched live from OpenAlex

The OSWE project’s aims to promote research capacity and develop outcome measures in social work education mirror the capacity and capability building ambitions articulated in the JUCSWEC research strategy (2006) and resonate with concerns about the limited research mindedness and competence of practitioners and social work students. This situation is not unique to the UK. A study from Canada (Unrau and Beck, 2004, p. 188) captures these concerns: \n \nWhile professional and academic expectations are that students integrate research into their practice frameworks…it is not at all clear to what degree students….are learning research skills. Furthermore, studies consistently show that social work students do not exercise research knowledge and skills in their early years of entering the profession. \n \nFurther synergies between the project discussed within this chapter and the intent to build research capacity in social work were created by focusing on the development of self-efficacy in research skills of social work students at Bournemouth University. This concern for research capacity and capability enhancement, or ‘collaborative capacity building’ (Burgess and Carpenter, 2008, p. 909), was reflected in the local project through the active collaboration between an established and an emerging researcher. This chapter describes the use of research self-efficacy as a tool to evaluate and promote student learning, through self-assessment and lecturer-assessment. We suggest ways in which the approach can be used to plan, predict and assist future learning. \n \nThe project rationale arose from the desire to increase and enhance research capacity and awareness in social work students. The underpinning premise is summarised by Holden: “when a social worker…has greater confidence regarding his or her research abilities he/she will feel more empowered as a social worker” (Holden et al., 1999, p. 465). This is because high self-efficacy ratings in research are consistently predictive of future confident and successful research behaviour in social workers in the USA (Holden et al., 1999). This confidence in being able to engage with research will enable practitioners to develop practice based on competent reading of research and contribute to the enhancement of the profession and its research base. \n

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.042
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.958
Threshold uncertainty score0.224

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0420.029
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.005
Scholarly communication0.0060.004
Open science0.0010.006
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.329
GPT teacher head0.479
Teacher spread0.150 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designTheoretical or conceptual
DomainMethods
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations16
Published2010
Admission routes1
Has abstractyes

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