Instructional designers are tasked with making countless decisions in every project they complete. Questions ranging from “Who is my learning audience?” to “How will this project be evaluated for effectiveness upon implementation?” all require the instructional designer to make a variety of decisions to ensure that their instructional design efforts are contributing to efficiency, effectiveness, and ease of learning (Morrison, Ross, Kalman, & Kemp, 2013). As the utility of instructional design continues to be recognized across industries, the complexities of design will continue to grow. With more options available in terms of how instructional solutions are to be designed and disseminated to a range of different learning audiences, the complexities of design decisions facing instructional designers are insurmountable.
There is a large body of literature in other design disciplines that outline strategies for engaging in decision-making and documenting design decisions. Many of these strategies lend themselves to the ID field, particularly with working on complex, ill-structured design problems. Marston and Mistree (1997) argue the importance of decision-making in design practices stating that decisions serve as markers to identify the progress that is made on designing a solution.
The purpose of this chapter is to help instructional designers differentiate between the different types of decisions they may be responsible for during a project. Various approaches for engaging in decision-making will be discussed and tools will be provided to assist the instructional designer with documenting their design decisions.
Instructional design problems can be classified as well-structured (Jonassen, 2000). Well-structured problems typically have one possible solution, whereas ill-structured problems may have multiple solutions. Instructional designers will often find themselves tasked with designing instructional solutions for problems of an ill-structured nature. While some problems may require a quick decision by the designer, other problems may be more complex; thus, requiring several interrelated decisions (Jonassen, 2011).
Decisions can be categorized according to types such as choices, acceptances/rejections, evaluation, and constructions (Yates & Tschirhart, 2006). Choices consist of selecting an option from a large set of options. Acceptance/rejection decisions consist of a binary decision where the option (or solution) is accepted or not. Evaluative decisions involve an individual assigning worth to a possible option and determining their level of commitment if they were to proceed with that option (Fitzpatrick, Sanders, & Worthen, 2011; Guerra-Lopez, 2008). Decisions of a more constructive nature involve trying to “identify ideal solutions given available resources (Jonassen, 2012, p. 343).
Table 1 provides an overview of their typology along with the types of decisions an instructional designer may encounter during a project.
Jonassen (2012) suggests that decisions fall under two models of decision-making: normative and naturalistic. Normative models involve an individual evaluating the situation and considering several options before deciding on a solution that yields the optimal solution given any constraints or resources related to the situation. He further categorizes normative models of decision-making as falling into three categories (rational choice, cost-benefit, and risk assessment).
Rational choice models involve the instructional designer evaluating alternative options for addressing a problem and weighing the option to determine what is the most viable of the solutions. Oftentimes, the instructional designer will evaluate the strengths and weaknesses of each solution using decision-making tools such as SWOT or force field analyses. A cost-benefit analysis seeks to select solutions based on the potential for their return-on-investment. There may be instances where it is worth foregoing training if an organization cannot justify incurring the costs associated with training. A risk assessment model is when an instructional designer will evaluate the risks associated with not proceeding with a particular solution.
Naturalistic models are suggested to assist in the decision-making process when decisions are more contextually-embedded. These models “stress the role of identity and unconscious emotions in decision-making” (Jonassen, 2012, p. 348). Narrative-based models place value on the explanations that accompany the various decision options. More emphasis is placed on the explanation rather than the cost-benefit analysis associated with a particular solution. Identify-based decisions are centered around how any individual relates to solutions on a personal level. Table 2 provides examples of instructional design decisions that may fall under normative or naturalistic decision-making models.
Mike is an instructional designer who works in the Department of Employee Development for an automotive aftermarket manufacturer. Over the weekend, an employee had a fatal accident operating a piece of machinery during the night shift. Mike and his supervisor have been included in meetings to explore whether modifications are needed to the company’s existing health and safety modules.
It is most likely that Mike and his supervisor will employ a normative approach to decision-making by conducting a risk assessment to determine the need for updating existing modules or developing new courses. The following are examples of some questions that Mike may ask during his meeting with the organizational leadership:
Angela has recently been hired as an instructional designer and trainer in support of employee development initiatives for a local hospital. In a recent meeting that was held with managers in human resources, there was a discussion about whether mandatory training courses should be offered in an online format. At her previous organization, Angela remembers that there were a lot of issues with transferring courses to an online format and she wonders if the employee development team has the necessary manpower and resources to support these modules.
Several studies have been conducted exploring the development of instructional designers' design judgment (Demiral-Uzan, 2015; Gray et al., 2015; Honebein, 2017; Korkmaz & Boling, 2014). These studies have explored how instructional designers engage in making decisions based on resources available in real-world settings. The results of these studies have supported the idea that instructional design is not limited to a linear approach for designing and developing instructional solutions; it is complex, and heavily influenced by contextual factors that are uniquely situated in relation to the project goals.
Other studies have sought to explore the role of experience and instructional designers’ abilities to make decisions. There are several differences inherent in terms of how novice instructional designers engage in decision-making compared to experts (Ertmer et al., 2008, 2009; Hoard, Stefaniak, Baaki, & Draper, 2019; Perez & Emery, 1995; Stefaniak, Baaki, Hoard, & Stapleton, 2018). Novice instructional designers are more apt to rely on instructional design models to guide their design process in a linear fashion whereas expert designers design in a more recursive manner. Several of the abovementioned studies also reported that novices tend to revert back to instructional design solutions they have used in previous projects; experts are more prone to customize solutions to meet the unique needs of their learning audience.
Several researchers in the instructional design field have suggested that an apprentice model can be beneficial to novice instructional design students as they are acquiring and developing design skills. The use of a cognitive apprenticeship provides a framework for instructors and expert instructional designers to model behavior and design practices in addition to providing the necessary instructional scaffolding to support instructional designers as they engage in design decision-making (Bannan-Ritland, 2001; Ertmer & Cennamo, 1995, Moallem, 1998; Shambaugh & Magliaro, 2001; Stefaniak, 2017)
Instructional design is an iterative and recursive process that requires the instructional designer to continuously monitor and revisit their designs to ensure alignment between instructional components from conception to implementation. Table 3 provides an overview of various tools that an instructional designer can utilize throughout their design process to log and reflect upon their instructional design decisions. Also, examples of studies and resources that discuss the use of these tools in detail are included in the table.
While decision-making is recognized as a common form of problem-solving in instructional design practices, Jonassen (2012) contends that there is a need for empirical research to assess decision-making in our field. To date, there is a growing body of literature exploring the decision-making practices of instructional designers; however, we, as a field, have just begun to skim the surface. More studies are needed to explore the types and quality of decisions made by instructional designers of all levels in a variety of contexts. We know that contextual factors contribute to or hinder the effectiveness of instructional designers’ final designs (Morrison et al., 2013; Smith & Ragan, 2005). Researchers have criticized that the role of context continues to be an aspect of design that still warrants further explanation and understanding (Tessmer, 1990; Tessmer & Wedman, 1995). This continues to be an issue facing our field. Additional studies on factors influencing instructional designers’ abilities to engage in decision-making will better equip our field to prepare the future of instructional design (Ertmer et al., 2009; Jonassen, 2008; Stefaniak et al., 2018; Tracey & Boling, 2014).
In the meantime, instructional designers can continue to focus on cultivating their designer identity (Tracey & Hutchinson, 2016, 2018) by documenting their thoughts and making use of the tools mentioned in this chapter to track their design decisions during projects. Over time, the aspiring instructional designer will begin to identify patterns in terms of how they approach various types of design problems, identify and utilize design resources and space, and articulate their rationale to fellow designers and clients. This continual practice of design documentation will serve the field well by informing both theory and practice.
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