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Review
. 2023 Mar 30;13(4):715-735.
doi: 10.3390/ejihpe13040054.

Instructional Design Made Easy! Instructional Design Models, Categories, Frameworks, Educational Context, and Recommendations for Future Work

Affiliations
Review

Instructional Design Made Easy! Instructional Design Models, Categories, Frameworks, Educational Context, and Recommendations for Future Work

Hassan Abuhassna et al. Eur J Investig Health Psychol Educ. .

Abstract

Educators and course designers may face great hurdles when designing courses if they include an online setting. Instructional design (ID) has played a vital role as a change agent in facilitating the pedagogical and technological transformation of educators and students. However, some instructors still find ID challenging and there are information gaps regarding instructional design models, categories, educational context, and recommendations for future work. This systematic literature review (SLR) analyzed 31 publications using PRISMA to address this gap. The results of this review suggest combining ID models with broader theoretical frameworks. Investigations and research on ID should include a bigger number of ID types. It is highly recommended that extra frameworks be added to the ID procedure. To explore and grasp all parties engaged in ID, including the role of the instructor, the ID designer, and the student, it is important for additional educational contexts to be amalgamated. For novices in the field, such as graduate students, it is crucial to pay close attention to the several phases and techniques of ID. This review sheds light on the trends, future agenda, and research requirements associated with ID in educational settings. It might serve as a basis for future research on ID in educational contexts.

Keywords: course design; designing instruction; instructional design; instructional technology.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
The PRISMA framework.
Figure 2
Figure 2
ID models and educational settings.
Figure 3
Figure 3
ID sample distributions.
Figure 4
Figure 4
Geographical distribution.

References

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