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Record W3033195982 · doi:10.5539/jel.v9n3p174

Bridging Knowledge and Action in the Workplace: An Evaluation on Internship Learning Outcomes of Child Development Associate Degree Program Students

2020· article· en· W3033195982 on OpenAlex
Yasemin Acar-Ciftci

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Education and Learning · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education and Employability
Canadian institutionsnot available
Fundersnot available
KeywordsInternshipMathematics educationPsychologyConceptualizationQualitative researchAction researchContext (archaeology)PedagogyMedical educationComputer scienceSociology

Abstract

fetched live from OpenAlex

The efficiency of the education systems fundamentally depends on the quality of teaching and learning in classrooms, workshops, laboratories, and other educational spaces. Perfect teachers, well-designed courses, and proper facilities, provision of necessary resources are required for an excellent education, but not enough. This study aims to evaluate child development associate degree program students in their learning during their summer internships the scope of Raelin’s Work-Based Learning Model. The individual level of this model takes place two types of learning (theory and practice) and four types of individual learning (conceptualization, experimentation, experience, and reflection) that arise from a matrix of two forms of knowledge (explicit and implicit). This research was designed as a case study, one of the qualitative research methods. Depending on the tradition of qualitative research, observation, semi-structured interview, and document review strategies were used to increase the reliability of this study. In the analysis of the qualitative data, the descriptive analysis technique was used to define and interpret the data in line with the predetermined themes. The findings obtained in this study revealed that although the students made various observations and practices during their internships, it has been identified that these studies did not include the learning types in the context of the model.

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.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.336
Threshold uncertainty score0.299

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.146
GPT teacher head0.475
Teacher spread0.329 · 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