ADDIE vs. Agile: Instructional Design Models to Customize Online Learning Environments

Moore (2016) says models provide novice designers with a new approach and give experienced designers a starting point to expand their repertoire.

By Ashley Breton Posted on: November 2021 Updated on: July 2022

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Image taken from Wix.com

Since the internet revolution, increasing numbers of instructors and learners are moving to online education (Irlbeck et al. 2006 as cited in Moore, 2016). However, whether designing an online module or a face-to-face course, it is favourable to have a solid understanding of instructional design (ID) models to help reach the desired goal (Moore, 2016). Models provide novice designers with a new approach and give experienced designers a starting point to expand their repertoire (Moore, 2016). But, with a multitude of ID models out there, either in theory or in practice, choosing the right model can be an arduous task (Dousay, 2017).

This paper will explore two proven and widely used ID models for building successful online learning experiences: ADDIE and Agile. The aim is to provide an overview of each methodology by first looking at the origins of each framework; what makes each approach unique; and will conclude with a discussion on the strengths and limitations of each model.

In the field of ID, a model dictates decisions about tool selection, methods of assessment, the types of activities learners participate in, and the degree of various kinds of interaction (Bates, 2015b). For many years, educators, IDs, and training developers have used ADDIE as a framework in designing and developing educational and training programs (Bates, 2015a). The origin of the ADDIE model is unknown (Molenda, 2003), although some speculate it was developed in the 1970s at the Center for Educational Technology at Florida State University (Molenda, 2003). However, it is also thought to date back much earlier to the Second World War as a framework for training the US military (Bates, 2015a). Whichever is true, ADDIE remains one of the most widely accepted ID models within educational environments — with a solid reputation for developing high-quality design projects — and has been the foundation of numerous variations (Göksu et al., 2017; Bates, 2015a).

ADDIE is an acronym for Analyze, Design, Develop, Implement and Evaluate (Bates, 2015a). It is a holistic, systematic approach to ID to organize problem-solving activity into a sequential but iterative process, complete with five phases, to develop improved learning experiences, either online or face-to-face (Molenda, 2003; Bates, 2015a; Dousay, 2017).

In its unadulterated form, each of the five phases is completed and refined in sequential order, and the cycle can continue until the desired outcome is reached (Molenda, 2003). This systematic design process provides clear learning objectives, structured content, workload management, and performance assessment firmly linked to measurable outcomes for evaluating the overall effectiveness of a course (Bates, 2015a; Branch, 2009). Employing these rules and procedures can assist designers in planning content that focuses on guiding the learner as they construct knowledge in a learning space (Branch, 2009). According to Branch (2009), this sets in motion a learner-centered approach rather than a teacher-centered approach, making course content more relevant and meaningful for learners.

However, ADDIE’S process-heavy system and rigid procedures could make it challenging for practitioners to iterate phases when mistakes are made, which might slow down the overall design process (Moore, 2016). In consequence, ADDIE can become costly to implement (Bates, 2015a). Another criticism Bates (2015a) points out is that ADDIE focuses more on content design and development than human interaction. This is a mistake, because ID is as much a human endeavor as face-to-face teaching, and therefore should create opportunities for meaningful exchanges (Osguthorpe et al., 2003). Finally, the model is frequently criticized for “its excessive linearity and lack of flexibility” and being too rigid for the information age (Gawlik-Kobylinska, 2018, p. 16; Bates, 2015a). Considering this, ADDIE might be best applied to large, complex design projects with soft or open timelines involving online learning environments with sequential modules, as practitioners would be able to focus on content and learner performance (Bates, 2015a; Asucion, 2016 as cited in Battle, 2019). A good example might be traditional engineering projects, like online civil or mechanical engineering courses, which contain content and activities that rarely change over time.

With continuous technological developments and ever-changing demands, some IDs are turning away from ADDIE to more contemporary models, like Agile, to help develop more versatile online environments that provide learners with the knowledge and skills for a digital age (Bates, 2015b).

The Agile framework is relatively new, but its principles and ideas have been around for decades (Abbas et al., 2008). Initially developed for the software industry in 2001 (Abbas et al., 2008), the basis of this model has become increasingly popular in the ID world and has been steadily emerging into its process (Gawlik-Kobylinska, 2018; Bates, 2015b). Within ID environments, Agile is a dynamic approach to design for learning that comprises of five non-linear stages: Align, Get-set, Iterate and Implement, Leverage, and Evaluate (Bates, 2015b). This design process reduces the planning stage and jumps straight into content development via short creation periods or “sprints,” meeting regularly to reflect on how to become more effective, while engaging in rapid feedback and evaluation to quickly adapt to changes in the environment (Gawlik-Kobylinska, 2018, p.19; Abbas et al., 2008). Agile’s high levels of flexibility (or willingness to change) and emphasis on fast-paced course development equates to more cost savings and allows IDs to fully exploit the educational potential of new tools or software (Gawlik-Kobylinska, 2018; Bates, 2015b).

However, while this operation may help customize e-learning experiences faster at a lower initial cost (Bates, 2015b), it deduces problem-solving activity to an algorithmic procedure by assuming designers always have the right information under invariant conditions (Foshay, 2016, 4:54). Another criticism is that Agile unfairly focuses on the ID team and goals throughout the development process, rather than on the learners’ experience ( Battle, 2019). For instance, the emphasis on speed may hinder the development of quality course content (Bates, 2015b). Critics of Agile also warn that the full scope of a project is unclear at the beginning (Moore, 2016). As a result, some stakeholders can be unsupportive due to a perceived lack of planning (Moore, 2016).

Finally, the Agile approach often involves numerous small self-organizing teams developing alongside one another, which requires a great deal of skill and experience (Gawlik-Kobylinska, 2018). Given this, Agile design approaches need confident instructors with a solid background in teaching best practices (Bates, 2015b) and innovative and creative IDs in teams with good communication and interpersonal skills (Gawlik-Kobylinska, 2018). All things considered, a lightweight Agile process might be best applied to small design projects with transient deadlines and where the components for the learning environment are constantly changing (Abbas et al., 2008). A good example might be online military field training courses (Gawlik-Kobylinska, 2018) involving fast-paced environments where emerging technologies persistently influence the industry.

Ultimately, ID can be a complex process, as every project is unique (Dousay, 2017) with multiple potential pathways to success (Moore, 2016). So, when IDs select a model to facilitate a design project, whether it be a traditional model like ADDIE or a relatively new, more tech-forward model like Agile, it is up to them to decide which works best for their specific context and design plans (Moore, 2016). And, due to the seemingly ambiguous nature of ID, only when expectations have been exceeded or the highest goals of education have been reached, an ID will know they are on the right path (Osguthorpe et al., 2003). References

Abbas, N., Gravell, A., & Wills, G. (2008). Historical roots of Agile methods: Where did “Agile thinking” come from?. International Conference on Agile Processes and Extreme Programming in Software Engineering. DOI: 10.1007/978-3-540-68255-4_10.

Bates, T. (2015a). Chapter 4.3 The ADDIE model. OpenBCcampus

Bates, T. (2015b). Chapter 4.7 ‘Agile’ design: Flexible designs for learning. OpenBCcampus.

Battle, E. (2019). Agile learning versus ADDIE: The choice for instructional designers in online learning development in higher education. ProQuest. Retrieved on November 24, 2021 https://www.proquest.com/openview/1e8d0c920464fa177aa2ef922e4aba18/1?pq-origsite=gscholar&cbl=18750&diss=y

Branch, R. (2009). Instructional design: The ADDIE approach. Springer. https://www.academia.edu/24109729/ADDIE_Robert_Maribe_Branch_auth_Instructional_Desi_BookZZ_org_?auto=download&email_work_card=download-paper

Dousay. T. (2017). Chapter 22. Instructional design models. In R. West (Ed.), Foundations of Learning and Instructional Design Technology (1st ed.).

Foshay, R. (2016, June 30). ADDIE or Agile Design and Development [Video]. YouTube. Retrieved from https://www.youtube.com/watch?v=HUTad6P8gcA&t=655s

Gawlik-Kobylinska, M. (2018). Reconciling ADDIE and Agile instructional design models - Case study. New Trends and Issues Proceedings on Humanities and Social Sciences, 5(3), 14–21. https://doi.org/10.18844/prosoc.v5i3.3906

Göksu, I., Özcan, K., Çakir, R., & Göktas, Y. (2017). Content analysis of research trends in instructional design models: 1999-2014. Journal of Learning Design, 10(2), 85-109.

Molenda, M. (2003). In search of the elusive ADDIE model. Retrieved on November 22, 2021 from http://www.damiantgordon.com/Courses/DT580/In-Search-of-Elusive-ADDIE.pdf

Osguthorpe, R. T., Osguthorpe, R.D., Jacob, W., & Davies, R. (2003). The moral dimensions of instructional design. Educational Technology, 43(2), 19–23.