Evidence map›Paper›PMID 42163225›Full record

ArticleBMC medical education2026

Ethical engagement with artificial intelligence in faculty research education: evaluation of the New Knowledge Help (NKH) approach.

Noor-I-Kiran Naeem, Zil-E-Fatima Naeem, Asfandyar Anwer

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Article in BMC medical education, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Noor-I-Kiran NaeemDecodingEdu, Gojra, Pakistan. noorikiran@yahoo.com.
Zil-E-Fatima NaeemGovernment City Hospital, Toba Tek Singh, Pakistan.
Asfandyar AnwerGovernment City Hospital, Toba Tek Singh, Pakistan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArtificial intelligence (AI) offers new opportunities in healthcare research; however, faculty often lack structured training on its effective and ethical use. Existing faculty development initiatives frequently emphasise tool awareness rather than supporting ethical, reflective, and process-oriented engagement with AI. The New Knowledge Help (NKH) approach was developed as a pedagogical framework to support ethical engagement with AI in faculty research education and was operationalised using instructional design principles. This study evaluated the NKH approach using Kirkpatrick's four-level framework.

methodsA blended programme of six face-to-face and two synchronous virtual workshops was conducted in three cities of Pakistan from November 2023 to March 2024. A total of 290 faculty members participated in NKH-guided workshops focused on ethical engagement with AI across the research process. The NKH approach was grounded in the Four-Component instructional design (4 C/ID) model and evaluated using the Kirkpatrick model across four levels: reaction, learning, behaviour, and results. Data were collected through post-workshop feedback, pre- and post-knowledge tests, and a three-month follow-up survey considering learning application and self-reported scholarly outputs.

resultsThe study revealed high levels of participants' satisfaction with workshop content and delivery (Level 1: mean satisfaction scores 4.4-4.95/5; Satisfaction Index = 87.2%). There was a 22% learning gain in post-test knowledge as compared to pre-test results (Level 2, p < 0.05). At Level 3, 30% of participants reported full implementation of NKH-aligned practices, 25% partial implementation, while 45% reported they had not yet applied the skills in the three-month follow-up. At Level 4, 6.2% of faculty completed full manuscript writing using AI tools, while 44% reported partial ethical integration of AI-supported practices in writing, with a significant association (p = 0.04).

conclusionThe study concludes that the NKH approach supports the ethical engagement of faculty with AI tools in research, as demonstrated by enhanced satisfaction, knowledge gain, and early scholarly activities. The varied practices of faculty at level 3 and 4 suggest the need for institutional support, peer networking, and explicit guidance. The NKH approach offers a structured and pedagogically informed framework for fostering ethical engagement with AI in faculty training.

Indexed as

Artificial IntelligenceFaculty, MedicalAcademiaFemaleHumansMalePakistanArtificial IntelligenceEthical EngagementFaculty DevelopmentInstructional Design

Identifiers

PMID42163225
PMCPMC13474874

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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.