Evidence map›Paper›PMID 41266454›Full record

ArticleScientific reports2025

The MIND model a microlearning AI-integrated instructional design for enhanced learning outcomes.

Wali Khan Monib, Atika Qazi, Rosyzie Anna Apong, Jose Hernandez Santos, Malissa Maria Mahmud

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Wali Khan MonibCentre for Lifelong Learning, Universiti Brunei Darussalam, Gadong, BE1410, Brunei Darussalam. walikhan.szu@gmail.com.
Atika QaziCentre for Lifelong Learning, Universiti Brunei Darussalam, Gadong, BE1410, Brunei Darussalam. atika.qazi@ubd.edu.bn.ORCID http://orcid.org/0000-0002-3565-6355
Rosyzie Anna ApongSchool of Digital Science, Universiti Brunei Darussalam, Gadong, BE1410, Brunei Darussalam.
Jose Hernandez SantosCentre for Lifelong Learning, Universiti Brunei Darussalam, Gadong, BE1410, Brunei Darussalam.
Malissa Maria MahmudSchool of Education, Sunway University, 47500, Selangor, Malaysia.

Funding

Universiti Brunei Darussalam UBD/RSCH/URG/2024/012
6 · The paper itself

Abstract

In recent years, microlearning has gained significant attention due to technological advancements such as generative AI (GenAI), diverse learner needs, and a growing emphasis on improving learning outcomes. However, designing effective microlearning content remains challenging, as existing instructional design frameworks are inadequate for optimising learning outcomes. Therefore, this study developed a novel Microlearning AI-Integrated Instructional Design (MIND) Model to support effective instructional design to enhance learning outcomes. The model is grounded in multiple theoretical foundations, primarily the Technological Pedagogical Content Knowledge (TPACK) framework and the Factors Influencing Learning Outcomes (FIL) framework. To validate the MIND model, a mixed-methods approach was used with an intervention consisting of microlearning modules, comparing the MIND model (experimental group) with the ADDIE model (control group). Quantitative analysis using ANCOVA revealed that the MIND model significantly outperforms the ADDIE model in supporting effective instructional design to enhance learning outcomes, such as increased knowledge acquisition, understanding of module content, and improved knowledge application. Furthermore, t-test results indicated that learning outcomes within the MIND model group were consistent across gender, employment status, and locality, demonstrating inclusivity and accessibility. Kruskal-Wallis test showed a difference in learning outcomes across age groups, with younger learners achieving higher outcomes. Thematic analysis of qualitative data revealed that the modules developed using the MIND model featured media richness, interaction, engagement, self-concept, motivation, and satisfaction, contributing to learning outcomes. The MIND model serves as an innovative instructional design model that guides stakeholders in designing micro modules while remaining adaptable to conventional approaches, supporting flexible integration of cutting-edge technologies across formal, non-formal, and informal learning.

Indexed as

Artificial IntelligenceLearningModels, EducationalAdultFemaleHumansMaleYoung AdultAIInstruction design frameworkKnowledge and skills improvementLearning outcomesLifelong learningMicrolearning

Identifiers

PMID41266454
PMCPMC12635307

What OpenQuestion holds

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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.