Evidence map›Paper›PMID 41312182›Full record

ReviewSAGE open nursing

Structuring Continual Learning Through a Hierarchy of Objectives: A Conceptual Framework.

Alette H Svellingen, Kari Røykenes, Guttorm Brattebø

Abstract readReview
In one paragraph

Review in SAGE open nursing. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Alette H SvellingenFaculty of Health Sciences, VID Specialized University, Bergen, Norway.ORCID https://orcid.org/0000-0002-0623-9966
Kari RøykenesFaculty of Health Sciences, VID Specialized University, Bergen, Norway.
Guttorm BrattebøDepartment of Clinical Medicine, University of Bergen, Haukeland University Hospital, Bergen, Norway.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Continual learning is fundamental for developing critical thinking and problem-solving skills. Although learning activities are well established in education, the connection between objectives, activities, and learning outcomes is often underemphasized. This article proposes a conceptual model that clarifies how learning processes can be better aligned through a hierarchy of objectives, using nursing education as an illustrative context. Methods: A conceptual analysis was conducted, drawing on established theories, including Kolb's Experiential Learning Theory, the Sociocultural Learning Perspective, and the NLN Jeffries Simulation Theory, to synthesize five core components: hierarchy of objectives, participant, learning activity, learning cycle, and multiple learning activities. Results: The model presents a structured approach to continual learning by clarifying how each component interacts to foster competence development. The model is presented from a general perspective while also specifically providing examples for the healthcare context. Simulation is used to exemplify how learning activities can support long-term learning goals. Conclusions: Understanding the importance of each level of the model and how these levels interact, can assist organizations in pursuing excellence. Accordingly, knowing and defining learning outputs and outcomes is the basis for attain the overarching goals. Facilitating learners to conceptualize reflections into active experimentation requires multiple learning activities, towards a spiral of continual learning.

Indexed as

a hierarchy of objectivesconceptual modelcontinual learninghealthcaremultiple learning activitiessimulation-based education

Identifiers

PMID41312182
PMCPMC12647548

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.