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Record W4387721431 · doi:10.1016/j.nedt.2023.105986

Undergraduate nursing students' perceptions of active learning strategies: A focus group study

2023· article· en· W4387721431 on OpenAlexfundno aff
Frances Kalu, Carolyn Wolsey, Parivash Enghiad

Bibliographic record

VenueNurse Education Today · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicInnovative Teaching Methods
Canadian institutionsnot available
FundersUniversity of Calgary
KeywordsActive learning (machine learning)Focus groupNonprobability samplingSnowball samplingCritical thinkingCooperative learningPsychologyExperiential learningProblem-based learningQualitative researchMedical educationNursingTeaching methodMedicinePedagogyPopulationComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Active learning strategies have been identified as promoting critical thinking, strengthening clinical reasoning, and supporting the transfer of theoretical knowledge to practice amongst nursing students. AIM: This study aimed to understand the undergraduate nursing students' perceptions of the active learning strategies being used in the classroom and to identify critical elements within their learning spaces which contribute to their learning. DESIGN: Qualitative, focus group study. SETTING: A four-year undergraduate baccalaureate nursing program in the Middle East. PARTICIPANTS: 50 undergraduate nursing students selected through purposive and snowball sampling participated in the study. METHODS: Five focus group sessions were conducted with 10 participants in each session. Data collected from the discussions were transcribed and thematically analyzed and aligned with the Taxonomy of Significant Learning. RESULTS: Study results show that undergraduate nursing students affirm that the use of active learning strategies supports the acquisition of foundational understanding, application and integration of knowledge, caring about the learning process, learning to learn, and the human dimension of learning. Participants also identified how best active learning strategies should be utilized and aspects of learning spaces that promote learning. CONCLUSIONS: Although the use of active learning strategies positively enhances the learning process, it is important to ensure that strategies are intentionally integrated into the classroom and aligned with the expected learning outcomes. Considerations of the learning space used are also of importance.

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)0.007
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0030.002
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.037
GPT teacher head0.463
Teacher spread0.426 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
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

Citations32
Published2023
Admission routes1
Has abstractyes

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