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Purposeful Use of Technology to Support Critical Thinking

2017· article· en· W2776722099 on OpenAlexaff
Ruth Swart

Bibliographic record

VenueJOJ Nursing & Health Care · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Critical Thinking Development
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCritical thinkingPsychologyEngineering ethicsMathematics educationEngineering

Abstract

fetched live from OpenAlex

A mixed methods research study was undertaken to examine undergraduate nursing students 'perspectives one course redesigned to include purposeful integration of technology to support an inquiry-based approach to critical thinking instruction. The face-to-face and online technology-enhanced environments of learning were developed as settings to generate inquiry to achieve the desired student outcome of critical thinking. Critical thinking is necessary for graduates from higher education programs. With technology's growth in use, diversity, and prevalence, technology has become a significant component in work and educational contexts. A course was planned to include inquiry to facilitate the development of critical thinking plat formed within two technology-enhanced environments. The findings of the study revealed student perspective of the use of technology with the instructional approach of inquiry, and their demonstration of the desired learning outcome of critical thinking. Thus, identifying factors important to the designing of a course to appropriately use technology to support student learning.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.845
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.076
GPT teacher head0.479
Teacher spread0.403 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations13
Published2017
Admission routes1
Has abstractyes

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