Analyzing and Selecting Instructional Strategies and Tactics Originally published in 1991, PIQ 4.2

“Formulation of instructional strategy to match subject matter and learner requirements” is an integral part of most instructional design models (Andrews & Goodson, 1980, p.5). Yet the meaning and purpose of instructional strategies in these design models vary considerably. An instructional strategy in traditional design models usually refers to the selection of instructional delivery vehicles (e.g., lecture, demonstration, computer-assisted instruction) and support activities (e.g., practice exercises, tutoring) (cf. Tracey, Flynn, & Legere, 1970). Contrast those conceptions with the many instructional strategies described in elaboration theory (Reigeluth & Stein, 1983), such as subsumptive sequencing, internally consistent orienting structures, synthesizers, summarizers, and cognitive strategy activators. What is obvious from these disparate conceptions is that instructional designers do not share a consistent definition of instructional strategies. Many of the activities that are referred to as instructional strategies are not in fact strategies, but rather are presentation vehicles. In this article, we first define instructional strategies and tactics in the context of an iterative design model. Instructional strategies are then distinguished from instructional tactics, which are the implementation of strategies. We then list the range of instructional strategies and tactics that implement them. Finally, we provide a decision tree for assisting designers to select appropriate instructional tactics.     

Analyzing and Selecting Instructional Strategies and Tactics

“Formulation of instructional strategy to match subject matter and learner requirements” is an integral part of most instructional design models (Andrews & Goodson, 1980, p.5). Yet the meaning and purpose of instructional strategies in these design model vary considerably. An instructional strategy in traditional design models usually refers to the selection of instructional delivery vehicles (e.g., lecture, demonstration, computer–assisted instruction) and support activities (e.g., practice exercises, tutoring) (cf. Tracey, Flynn, & Legere, 1970). Contrast those conceptions with the many instructional strategies described in elaboration theory (Reigeluth & Stein, 1983), such as subsumptive sequencing, internally consistent orienting structures, synthesizers, summarizers, and cognitive strategy activators. What is obvious from these disparate conceptions is that instructional designers do not share a consistent definition of instructional strategies. Many of the activities that are referred to as instructional strategies are not in fact strategies, but rather are presentation vehicles. In this article, we first define instructional strategies and tactics in the context of an iterative design model. Instructional strategies are then distinguished from instructional tactics, which are the implementation of strategies. We then list the range of instructional strategies and tactics that implement them. Finally, we provide a decision tree for assisting designers to select appropriate instructional tactics.     

Engaging by design: How engagement strategies in popular computer and video games can inform instructional design

Computer and video games are a prevalent form of entertainment in which the purpose of the design is to engage players. Game designers incorporate a number of strategies and tactics for engaging players in “gameplay.” These strategies and tactics may provide instructional designers with new methods for engaging learners. This investigation presents a review of game design strategies and the implications of appropriating these strategies for instructional design. Specifically, this study presents an overview of the trajectory of player positioning or point of view, the role of narrative, and methods of interactive design. A comparison of engagement strategies in popular games and characteristics of engaged learning is also presented to examine how strategies of game design might be integrated into the existing framework of engaged learning. The preparation of this article was supported in part by the Proctor & Gamble Interactive Media Fellows grant. The ideas expressed in this paper do not necessarily reflect the position of the grant agency. R Thanks to the ETR&D Development Editor, J. Michael Spector, and the reviewers for their insightful comments and suggestions. Thanks, too, to John C. Belland and Keith A. Hall for their advice and mentoring.     

Examining Instructional Design Principles Applied by Experienced Designers in Practice

There has been ongoing debate regarding the efficacy of teaching instructional design models to novice designers given that experienced instructional designers often use principles and adapted models when they engage in the instructional design problem‐solving process. This study utilized the Delphi technique to identify a core set of guiding principles used by designers in their practice. The purpose of this study was (1) to examine and describe the principles that guided instructional designers’ practice and (2) to identify the extent to which participants’ frames of reference included components of the ADDIE instructional design model. Sixty‐one principles were ultimately identified (reached consensus among the Delphi panel members). Thirty‐two of the principles aligned with the primary components of the design process (e.g., analysis, design, development, and evaluation). Additional principles (n = 29) related to other characteristics of design such as communication, project management, and design characteristics.     

Effect of instruction using students' prior knowledge and conceptual change strategies on science learning

One of the factors affecting students' learning in science is their existing knowledge prior to instruction. The students' prior knowledge provides an indication of the alternative conceptions as well as the scientific conceptions possessed by the students. This study is concerned primarily with students' alternative conceptions and with instructional strategies to effect the learning of scientific conceptions; i.e., to effect conceptual change from alternative to scientific conceptions. The conceptual change model used here suggests conditions under which alternative conceptions can be replaced by or differentiated into scientific conceptions and new conceptions can be integrated with existing conceptions. The instructional strategy and materials were developed for a particular student population, namely, black high school students in South Africa, using their previously identified prior knowledge (conceptions and alternative conceptions) and incorporate the principles for conceptual change. The conceptions involved were mass, volume, and density. An experimental group of students was taught these concepts using the special instructional strategy and materials. A control group was taught the same concepts using a traditional strategy and materials. Pre- and posttests were used to assess the conceptual change that occurred in the experimental and control groups. The results showed a significantly larger improvement in the acquisition of scientific conceptions as a result of the instructional strategy and materials which explicitly dealt with student alternative conceptions.     

A meta-analysis of single-subject-design intervention research for students with LD

This article summarizes single-subject-design intervention studies that include students with learning disabilities. Effect sizes of 85 studies were analyzed across instructional domains (e.g., reading, mathematics); sample characteristics (e.g., age, intelligence); intervention parameters (e.g., number of instructional sessions, instructional components); and methodological procedures (e.g., internal validity, treatment integrity, sample representation). The major findings were as follows: (a) All domain areas except handwriting yielded effect sizes at or above Cohen's .80 threshold for a substantial finding; (b) instructional components related to drill-repetition-practice-review, segmentation, small interactive groups, and the implementation of cues to use strategies contributed significant variance (15%) to estimates of effect size; (c) strategy instruction (SI) models better predicted effect size estimates than direct instruction (DI) models when the results were qualified by the reported intellectual and reading levels of the participants; (d) high-IQ discrepancy groups yielded lower effect sizes compared to low-IQ discrepancy groups in the domain of reading, whereas the reverse effect occurred when treatment outcomes were not reading measures; and (e) the low-IQ discrepancy groups yielded higher effect sizes for a Combined DI and SI Model when compared to competing models. The results are supportive of the pervasive influence of cognitive strategy and direct instruction models across treatment domains and of the notion that variations in sample definition moderate treatment outcomes.     

Behaviorism,Cognitivism, Constructivism: Comparing Critical Features from an Instructional Design Perspective

The way we define learning and what we believe about the way learning occurs has important implications for situations in which we want to facilitate changes in what people know and/ or do. Learning theories provide instructional designers with verified instructional strategies and techniques for facilitating learning as well as a foundation for intelligent strategy selection. Yet many designers are operating under the constraints of a limited theoretical background. This paper is an attempt to familiarize designers with three relevant positions on learning (behavioral, cognitive, and constructivist) which provide structured foundations for planning and conducting instructional design activities. Each learning perspective is discussed in terms of its specific interpretation of the learning process and the resulting implications for instructional designers and educational practitioners. The information presented here provides the reader with a comparison of these three different viewpoints and illustrates how these differences might be translated into practical applications in instructional situations.     

How Do Instructional‐Design Practitioners Make Instructional‐Strategy Decisions?

Many theories have been proposed to help instructional designers make instructional‐strategy decisions, yet it is not clear if these theories are actually used by ID practitioners. This study used a web‐survey to examine the design strategies of 113 ID practitioners. The survey asked respondents to rate how frequently they used learning or ID theories as well as 10 other design strategies, to help make instructional‐strategy decisions. Respondents were also asked how often they used different information sources to learn about new theories, trends, and strategies, and to respond to a set of contrasting statements depicting objectivist vs. construc‐tivist assumptions. The results indicate that ID practitioners most often rely on interaction with others both as a means of making instructional‐strategy decisions and of learning about new theories, trends, and strategies. Only fifty percent of the respondents said they regularly use theories when making instructional‐strategy decisions, using other design strategies more frequently instead; and most practitioners are eclectic in their underlying philosophical assumptions. Based on these results, we discuss implications for training and ongoing support of instructional designers.     

Relationships between motivational strategies and cognitive learning in distance education courses

This study examines the relationships between students’ academic levels, the use of motivational regulation strategies, and cognitive learning strategies. A total of 141 undergraduate and graduate students enrolled in online distance courses participated in the study. The findings show that students use different motivational regulation strategies and cognitive learning strategies depending on their academic levels. Additionally, hierarchical regression analyses using two dependent variables (i.e., surface level learning strategy and deep processing level learning strategy) indicate that a surface level learning strategy (i.e., rehearsal) and deep processing level strategies (i.e., elaboration, organization, and critical thinking) are predicted by different sets of motivational regulation strategies after controlling for academic level and age. The results provide distance educators and instructional designers with practical suggestions on how to support undergraduate and graduate students’ motivational needs and further promote their use of cognitive learning strategies in online distance education programs in higher education.     

Instructional strategies and tactics for the design of introductory computer programming courses in high school

This article offers an examination of instructional strategies and tactics for the design of introductory computer programming courses in high school. We distinguish the Expert, Spiral and Reading approach as groups of instructional strategies that mainly differ in their general design plan to control students' processing load. In order, they emphasize topdown program design, incremental learning, and program modification and amplification. In contrast, tactics are specific design plans that prescribe methods to reach desired learning outcomes under given circumstances. Based on ACT^* (Anderson, 1983) and relevant research, we distinguish between declarative and procedural instruction and present six tactics which can be used both to design courses and to evaluate strategies. Three tactics for declarative instruction involve concrete computer models, programming plans and design diagrams; three tactics for procedural instruction involve worked-out examples, practice of basic cognitive skills and task variation. In our evaluation of groups of instructional strategies, the Reading approach has been found to be superior to the Expert and Spiral approaches.The authors wish to express their gratitude to Sanne Dijkstra, Otto Jelsma and Georg Rakers for their helpful comments on a draft of this article. Correspondence concerning this article should be addressed to Jeroen J. G. van Merrienboer.Notes     

A profile of instructional designers in Australia

This paper reports on the findings of a questionnaire which elicited information from ninety‐nine instructional designers in Australia about their qualifications, the activities they undertake, and perceptions of their role. Over half of those surveyed have what they consider to be qualifications in instructional design. The range of activities undertaken is large. There are slight variations in the activities performed by instructional designers at universities compared with instructional designers at Technical and Further Education (TAFE) institutes. There was very little difference in the frequency of activities performed by those with instructional design qualifications and those without. The research shows that many people are confused about the role of instructional designers. There are many negative perceptions of the role held by people with whom instructional designers work and these perceptions can adversely affect the instructional designers' work.     

Design Principles for Augmented Reality Learning

Augmented reality is an emerging technology that utilizes mobile, context-aware devices (e.g., smartphones, tablets) that enable participants to interact with digital information embedded within the physical environment. This overview of design principles focuses on specific strategies that instructional designers can use to develop AR learning experiences. A review of the literature reveals the following three design principles as instructive: 1. Enable and then challenge (challenge): 2. Drive by gamified story (fantasy); and 3. See the unseen (curiosity). These design principles can also be viewed as an attempt to either leverage the unique affor- dances of AR or minimize the limitations of the medium as reported in the literature (Dunleavy & Dede, 2014). As the field matures and more research teams explore the potential of AR to enhance teaching and learning, it will be critical to determine the design techniques that optimize the unique affordances of AR, minimize the limitations of the medium, and ultimately enhance learning across the curriculum.     

Philosophical and methodological beliefs of instructional design faculty and professionals

The purpose of this research was to probe the philosophical beliefs of instructional designers using sound philosophical constructs and quantitative data collection and analysis. We investigated the philosophical and methodological beliefs of instructional designers, including 152 instructional design faculty members and 118 non-faculty professionals. We used the Philosophy of Social Science Inventory, a 52-item questionnaire, to measure 20 beliefs within four categories. We probed four ontological beliefs (ontological realism, ontological relativism, physicalism, and idealism); five epistemological beliefs (epistemological relativism, fallibilism, epistemological objectivity, rationalism, and empiricism); three axiological beliefs (ethical realism, ethical relativism, and valueneutrality in research); and eight methodological beliefs (nomothetic, idiographic and critical methods, scientific naturalism, humanism, and quantitative, qualitative and mixed methods). Our research questions included (a) What are the predominant philosophical and methodological beliefs of instructional designers? (b) Do instructional design faculty and non-faculty instructional designers, identifying with different research methodologies, hold different sets of philosophical beliefs? and (c) What relationships exist between philosophical beliefs and age, gender, ethnicity, level of education, and/or years of service? Overall, the philosophical profile of instructional designers can reasonably be described as pragmatic. Belief characterizations of methodological subgroups (e.g., those identifying with qualitative, quantitative, or mixed methods research) generally supported our hypotheses. Although demographic variables (except gender) were not singularly important, our analyses suggest that a combination of ethnicity, gender, research preference, and level of education can be used to predict philosophical and methodological beliefs.     

E‐Learning Ain't Performance: Reviving HPT in an Era of Agile and Lean

Not all instructional design models are fully integrated into the HPT practice. Some of these processes such as the successive approximation model (SAM) and the lot like Agile methods approach (LLAMA) are the outgrowth of Agile processes for instructional design. The major design processes are often assumed to be competitive; that is, one model is better than the other. However, most Agile instructional design processes assume that the most ubiquitous performance solution is e‐learning, hence the direct integration of Agile processes. Therefore, instead of thinking about design models, we think about instructional methods and solutions over human performance technology (HPT). These methods are all equal until one understands the conditions or the context of the instructional or performance problem. We recommend designers reverse engineer the Agile instructional systems design process by using a rapid performance analysis method that quickly pinpoints and confirms the performance problem(s).     

The Use of Task Analysis Procedures by Instructional Designers

The purpose of this study was to learn about the use of task analysis procedures by instructional designers. Task analysis is regarded by many to be the most integral part of the instructional design process and the most technical aspect of the instructional designer's job. It is also thought to be the most ambiguous of the instructional design, processes. A questionnaire was developed that surveyed 164 members of the International Society for Performance Improvement (ISPI) and the Association for Educational Communications and Technology (AECT) with instructional design responsibilities. This research learned what instructional design activities designers associate with task analysis and the percentage of time instructional designers devote to task analysis. It also learned what task analysis methods are most and least often used by instructional designers and identified those task analysis methods not known by instructional designers. Finally, this study determined how instructional designers learn to conduct task analyses and the factors that impact task analysis practices.     

Assimilation in Online Course Design

As online education continues to grow, instructors from traditional classrooms are being asked to design online courses. In this study, data from interviews with thirty-three public four-year college and university instructors, who had experience designing online courses, were used to understand the instructor’s perspective on online course design. Using grounded theory, data were analyzed, sorted, and coded to uncover the strategies instructors use to design online courses. Results revealed instructors adapt to the online environment by using strategies to mimic elements of face-to-face courses: in essence, adaption comes through assimilation. Instructors expressed interest in helping students navigate online to encourage active participation in courses. They described using technology and learning management system (LMS) features (e.g., videos, discussion forums) to “hear” and “see” students, as a way to increase interaction and presence, familiar elements from face-to-face education. They spoke of creating authentic assignments to increase student engagement. The implications of this study include effective design and instructional strategies for online courses, as well as understanding the motivation of instructors who design online courses. The study results are relevant to a broad audience including online instructors, instructional designers, LMS organizations, and administrators.     

Middle school children's strategic behavior: Classification and relation to academic achievement and mathematical problem solving

Theories of problem solving (e.g., Verschaffelet al., 2000) hold strategic behavior centralto processing mathematical word problems. Thepresent study explores 80 sixth- andseventh-grade students' self-reported use of 14categories of strategies (Zimmerman &Martinez-Pons, 1986) and the relationship ofstrategy use to academic achievement,problem-solving behaviors, and problem-solvingsuccess. High and low achievement groupsdiffered in the number of different strategiesand categories of strategies reported but notin overall number of strategies, confidence inusing strategies, or frequency of strategy use.Students whose behaviors evidenced elaborationof the word problem's text reported moreself-evaluation; organizing and transforming;and goal setting and monitoring behavior.Implications for instructional practices thatsupport active stances toward problem solvingare discussed.