How Expert Designers Design

Two studies were carried out with expert educational designers at Arthur Andersen and the Open University of the Netherlands to determine the priorities they employed when designing competence‐based learning environments. Designers in a university context and in a business context agree almost completely on what principles are important, the most important being that one should start a design enterprise from the needs of the learners, instead of the content structure of the learning do main. The main difference between the two groups is that university designers find it extremely important to consider alternative solutions during the whole design process; something that is considerably less important by business designers. University designers also tend to focus on the project plan and the desired characteristics of the instructional blueprint whereas business designers were much more client‐oriented and stressed the importance of “buying in” the client early in the process.     

The cognitive approach to training development: A practitioner's assessment

This article begins this special issue of ETR&D-Development by discussing what the cognitive approach to instructional design (ID) is and how ID practitioners can design training differently using the approach. Following some introductory comments about purpose, scope and perspective, the article is in two parts. The first part describes why the cognitive approach to ID is important and how the current approach to instructional design and training development is different from the cognitive approach. It then explains how learning occurs according to the cognitive point of view, and the different categories of learning according to one type of cognitive psychology. The second part describes a model that synthesizes and summarizes the components of a well-designed lesson, and describes what is different about this model from the current approach to ID. This model relates what learners have to do to learn to what instructional designers have to do to help them do so. It presents and briefly explains and exemplifies a general framework for instructional design based on cognitive psychology. Finally, it presents a table that can be used as a job aid to design training.     

Ask the instructional designers: A cursory glance at practice in the workplace

The purpose of this exploratory study was to make better connections between what is professed in instructional design degree programs and what happens in the workplace. Findings from the study of how three corporate instructional designers navigated and made sense of their daily practice included the factors that mostly influence their instructional design (ID) decisions, their perspectives on ID theories and models, how they compensated for any deficits in their knowledge or skills, and their hiring preferences.     

Designing for learning in the Yellow House: a comparison of instructional and learning design origins and practices

ABSTRACT

For the past two decades, there has been persistent debate around whether there is a difference between the fields of instructional design (ID) and learning design (LD). While differences in the two approaches are certainly apparent, there are cross-over points that can provide ID and LD researchers and practitioners with opportunities for dialogue about the purposes and remit of research-based practices for optimal design. Though potentially disruptive, initiating dialogues among learning and instructional designers could lead to more thorough and critical analyses of both ID and LD repertoires. Should boundary crossings occur, there is a potential for a third space for the contemplation, research, and practice of design. A goal of this article is to use the notion of Van Gogh’s Yellow House as an anchoring metaphor for the third space – a location for shared discourse, inspiration, collaboration, and challenge for a community of designers of/for learning. Using the impressionist and expressionist terminology to help elucidate the ways of thinking of designers of both traditions, this article examines the history, underlying philosophical approaches, methodologies, and design goals of ID and LD. We conclude that the emergence of a third space for design can help us move beyond the LD and ID dichotomies. We suggest that a socio-materialist perspective alleviates issues of incommensurability by acknowledging ontological multiplicity.     

A comparison of teacher referral and pupil self-referral measures relative to perceived school adjustment

This study investigated the relationship between teacher referral and pupil self-referral relative to perceived school adjustment of 417 4th grade pupils. Two major questions were focused upon: (a) To what extent do teachers and pupils agree relative to perceived learning and/or adjustment problems within the classroom? and (b) What are the relationships between teacher referral and pupil self-referral relative to sex of the child and type of problem indicated? The results suggest that a significant relationship exists between teacher referral and pupil self-referral (p <,001). Further, a disproportionate number of males in the sample were referred by their teachers as compared to female students (38% to 12%). However, relative to pupil self-referral, a much higher percentage of females (33%) “referred themselves.” It is suggested that greater consideration should be given by local school districts to including a pupil self-referral component within their overall screening mechanism for the identification of children in need of special education services. Further, school personnel should consider the possibility that their screening results may reflect teacher bias relative to “pupil sex stereotyping” in that males may be over-referred and famales under-referred.     

Everyone already has their community beyond the screen: reconceptualizing online learning and expanding boundaries

A constructivist learning paradigm emphasises authenticity as a required condition for learning. However, the design of an online learning environment is ultimately separate from learners’ real-life environments, it is inevitably challenging to make online learning authentic. In this article, the author aims to propose an alternative way of conceptualizing online learning and its boundaries, based on a double-layered Community of Practice model as a means to facilitate authentically constructivist online learning. The model conceptualizes online learning as interlinked processes of participation and socialization in multiple communities across online- and offline-“layers” of learners’ lives. The model guides online course designers in expanding the perceived boundaries of the course environments they design to include learners’ offline learning contexts. Instead of having an exclusive focus on providing learners with constructivist learning opportunities within a non-authentic course environment, the model suggests helping learners to engage in more personalized social learning activities situated in their everyday lives. The paper presents data from a series of case studies drawn from the author’s work that has examined students’ learning experiences in different kinds of online courses, unpacking and answering the central question of what authentically constructivist online learning looks like in each case. With a more holistic conceptualization of online learning, which recognizes and supports online learners’ simultaneous presence across internal and external communities, instructional designers may be able to facilitate learners’ more authentically constructivist learning experiences.     

Student Models of Instructional Design

Mental models are one way that humans represent knowledge (Markman, 1999). Instructional design (ID) is a conceptual model for developing instruction and typically includes analysis, design, development, implementation, and evaluation (i.e., ADDIE model). ID, however, has been viewed differently by practicing teachers and instructional designers (Kennedy, 1994). In a graduate ID course students constructed their own ID models. This study analyzed student models for (a) what ADDIE components were included (by teacher, nonteacher), and (b) model structural characteristics (by teacher, nonteacher). Participants included 178 students in 12 deliveries of a master's level ID course (115 teachers, 63 nonteachers). Our conceptual ID model is presented, and the ID model task is described. Students most frequently represented design, followed by program evaluation, needs assessment, development, and implementation. In terms of structural characteristics, 76 models were characterized as metaphoric, 61 dynamic, and 35 sequential. Three interrelated conclusions and implications for ID learning are offered. Susan G. Magliaro [sumags@vt.edu] is Director of the School of Education and the Center for Teacher Education at Virginia Tech. Neal Shambaugh is Assistant Professor of Instructional Design & Technology in the College of Human Resources & Education at West Virginia University. An erratum to this article is available at .     

Learning and using science ideas when doing investigate‐and‐redesign tasks: A study of naive,novice, and expert designers doing constrained and scaffolded design work

This study reports on what naive, novice, and expert designers do and learn when investigating simple mechanical devices and then planning their redesign. Participating in the study were 32 high school and adult subjects who did two investigate‐and‐redesign (I&R) tasks. Same gender pairs of subjects with similar design experiences explored, analyzed, and evaluated different brands of a device, designed experiments to compare them, and then proposed their redesign. Each two‐hour session was videotaped, and portions were analyzed using methods adapted from protocol analysis techniques. Results suggest that when naive designers do I&R tasks, their learning is highly contextualized and device‐specific. Naive designers made few connections from their work to key science ideas, and instead used mechanical advantage preconceptions that they did not spontaneously redress during the I&R sequence. Experts made connections to concepts and cases, inferred key design decisions, and sought “critical design problems” for the devices studied. All groups used strategies involving analysis more than those involving synthesis or evaluation. Notably, during conceptual design, opportunities for using science, present especially when subjects analyze design ideas, went underutilized by nonexpert designers. Scaffolded questions are needed to focus the learning of science embedded in design‐oriented activities. All findings reported are tentative, given the limited number of cases included in this study. © 2001 John Wiley & Sons, Inc. J Res Sci Teach 38: 791–820, 2001     

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.     

Adjusting claims as new evidence emerges: Do students incorporate new evidence into their scientific explanations?

Constructing explanations of complex phenomena is an important part of doing science and it is also an important component of learning science. Students need opportunities to make claims based on available evidence and then use science concepts to justify why evidence supports the claim. But what happens when new evidence emerges for the same phenomenon? The “claim” portion of the claim, evidence, and reasoning explanation framework is viewed as the most accessible to students. When new evidence suggests that students adjust their current thinking however, do students incorporate this new information and modify their claims? This research utilized a time series research design to explore how students modify their claim over four iterations of one explanation, termed an evolving explanation. As new data were collected and analyzed to provide additional evidence, students needed to evaluate their current claim to see if it took into account all available evidence. This research explores that process including the supports that the teacher provided and the challenges that students faced in developing one claim, over time. The findings indicate that many students face challenges adjusting their claims when new, conflicting evidence emerges, even with class discussion, teacher feedback, and written scaffolds. Several possible reasons exist to account for this challenge. Students may (1) ignore new evidence, (2) find “undoing” their initial idea too cognitively demanding, or (3) simply not have any similar experience from which to build. Providing students with experiences of writing evolving explanations reflects what scientists do, while simultaneously preparing students to become more scientifically proficient.     

A strong core of qualities—a model of the professional educator that moves beyond reflection

This paper seeks to move beyond reflective practice as an approach to continuing professional development in teaching and related professions. Drawing on experience of working with teachers in a Scottish Higher Education context, consideration is given to what makes a “good” teacher, leading to a new model proposal that emphasises the importance to continuing professional development of sense making. A strong core of qualities is identified as an important characteristic of teachers able to grow and develop practice. The composition, characteristics and action of this strong core are identified.     

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.     

Looking for Ways to Increase Student Motivation: Internationalisation and Value Innovation

Understanding what constitutes the perceived value of foreign education to international business students is critical for business schools in order to achieve their recruitment targets. One established method relies on a financial interpretation of the costs and benefits of business education. By contrast, this study advocates a holistic approach by employing the concept of “internal” and “external” career success as its theoretical underpinning. A survey of undergraduate Chinese students in two British business schools based on such approach provides confirmation of the importance of an individual's judgement of own success as the foundation of value‐related expectations and suggests that academic practice should be concerned with a wider range of competencies and responses to individual attitudes, shifting emphasis towards a greater spectrum of social values.     

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 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 sub-sumptive 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.     

The role of design ethics in maintaining students' privacy: A call to action to learning designers in higher education

Maintaining students' privacy in higher education, an integral aspect of learning design and technology integration, is not only a matter of policy and law but also a matter of design ethics. Similar to faculty educators, learning designers in higher education play a vital role in maintaining students' privacy by designing learning experiences that rely on online technology integration. Like other professional designers, they need to care for the humans they design for by not producing designs that infringe on their privacy, thus, not causing harm. Recognizing that widely used instructional design models are silent on the topic and do not address ethical considerations such as privacy, we focus this paper on how design ethics can be leveraged by learning designers in higher education in a practical manner, illustrated through authentic examples. We highlight where the ethical responsibility of learning designers comes into the foreground when maintaining students' privacy and well-being, especially in online settings. We outline an existing ethical decision-making framework and show how learning designers can use it as a call to action to protect the students they design for, strengthening their ethical design capacity.

Practitioner notes

What is already known about this topic

• Existing codes of ethical standards from well-known learning design organizations call upon learning designers to protect students' privacy without clear guidance on how to do so.
• Design ethics within learning design is often discussed in abstract ways with principles that are difficult to apply.
• Most, if not all, design models that learning design professionals have learned are either silent on design ethics and/or do not consider ethics as a valid dimension, thus, making design ethics mostly excluded from learning design graduate programs.
• Practical means for engaging in ethical design practice are scarce in the field.

What this paper adds

• A call for learning designers in higher education to maintain and protect students' privacy and well-being, strengthening their ethical design capacity.
• A demonstration of how to use a practical ethical decision-making framework as a designerly tool in designing for learning to maintain and protect students' privacy and well-being.
• Authentic examples—in the form of vignettes—of ethical dilemmas/issues that learning designers in higher education could face, focused on students' privacy.
• Methods—using a practical ethical decision-making framework—for learning design professionals in higher education, grounded in the philosophy of designers as the guarantors of designs, to be employed to detect situations where students' privacy and best interests are at risk.
• A demonstration of how learning designers could make stellar design decisions in service to the students they design for and not to the priorities of other design stakeholders.

Implications for practice and/or policy

• Higher education programs/institutions that prepare/employ learning designers ought to treat the topics of the designer's responsibility and design ethics more explicitly and practically as one of the means to maintain and protect students' privacy, in addition to law and policies.
• Learning designers in higher education ought to hold a powerful position in their professional practice to maintain and protect students' privacy and well-being, as an important aspect of their ethical design responsibilities.
• Learning designers in higher education ought to adopt a design thinking mindset in order to protect students' privacy by (1) challenging ideas and assumptions regarding technology integration in general and (2) detecting what is known in User Experience (UX) design as “dark patterns” in online course design.