In this chapter, Wagner discusses the challenge of how to define the field.

This chapter describes the basic functions of memory and three stages of memory storage. It provides an overview of procedural and declarative memory and semantic and episodic memory, and provides implications for designers.

Modern sociocultural learning theories stem from the work of Russian psychologist Lev Vygotsky. When examining learning theories, LIDT professionals should consider the role culture, interaction, and collaboration have on quality learning. We propose a set of principles to guide the design of learning experiences. We provide examples of applications and environments that promote deep and meaningful learning.

Like motivation itself, theories of it are full of diversity. For convenience in navigating through the diversity, we have organized the chapter around six major theories or perspectives about motives and their sources. We call the topics (1) motives as behavior change, (2) motives as goals, (3) motives as interests, (4) motives as attributions about success, (5) motives as beliefs about self-efficacy, and (6) motives as self-determination. We end with a perspective called expectancy-value theory, which integrates ideas from some of the other six theories and partly as a result implies some additional suggestions for influencing students’ motivations to learn in positive ways.

Connectivism is a theory that attempts to explain the link between individual and organizational learning. This paper was originally published on Siemens’s personal website in 2004 before being published in the International Journal of Instructional Technology and Distance Learning. It has been cited thousands of times and is considered a landmark theory for the Internet age.

Benjamin Bloom and his associates developed a taxonomy of different kinds of thinking and learning. The taxonomy is divided into three parts: the cognitive, affective, and the psychomotor domains. In this chapter, we will address how the taxonomy was developed, how it evolved, and how educators use it for teaching purposes.

Phases of rapid development in the field of learning and instructional design technology have given way to dozens of instructional design models. These models often form the foundation of instructional design courses, introducing students to the field. However, broad and specific misconceptions often drive new designers to overly rely on models to guide them through an applied instructional design process. In this chapter, we explore a brief history of instructional design models, common components of models, commonly referenced models, and resources and advice for instructional designers as they engage in the instructional development process.

This chapter begins by discussing the need for paradigm change in education and for a critical systems approach to paradigm change. It then examines current progress toward paradigm change. Next, the chapter explores what a learner-centered, Information-Age educational system should be like, including the APA learner-centered psychological principles, the National Research Council’s findings on how people learn, the work of McCombs and colleagues on learner-centered schools and classrooms, personalized learning, differentiated instruction, and brain-based instruction. Finally, one possible vision of a learner-centered school is described.

While most instructional design courses and much of the instructional design industry focus on ADDIE (Analysis, Design, Development, Implementation, Evaluation), approaches such as design thinking, human-centered design, and agile methods like SAM (Successive Approximation Model), have drawn attention. This chapter unpacks what we know about design thinking and presents a concise history of design thinking to situate it within the broader design research field. It then traces its emergence in other fields. The chapter considers lessons for instructional designers and concludes by setting an agenda to address issues for scholarship, teaching, and practice.

The overarching goal for instructional designers is to enhance learning and performance outcomes, often achieved through needs assessments, learner analyses, and the development of targeted instructional materials. This chapter delves into the foundational principles of HP and differentiates between HPT and instructional design. The role of performance analysis is explored, focusing on organizational, environmental, and cause analyses to identify performance gaps and root causes. The role of non-instructional interventions, such as organizational design, job analysis, and feedback systems to support infrastructure are discussed. Recommendations for integrating HPT principles into instructional design through a systems approach are also provided.

This chapter presents an engaging discussion of the way that gamification and learning technology have developed over recent years, as well as examining some of the theoretical contestations in the field, mapping out avenues for future research and development, and providing clear advice for designers considering adopting gamified approaches. The chapter begins by defining the game and recognizing that gaming and gamification both have a long history. It notes that gamification is distinct from games, and uses Kapp’s (2012) discussion of the elements of gamification to discuss this. From that point, a conversation is developed about the need to design gamification in such a way so that is fit for its intended purpose. This leads into a discussion about how various learning theories, including behaviourism, and motivation theories, relate to gamification design. It notes the distinct advantages that have been lent to the development and adoption of gamification via mobile technology, and especially internet enabled devices. It will also recognize that some of the promises of gamification, especially as it relates to learning and instructional design, have failed to materialize. The chapter concludes with advice for designers to consider as they design their own gamification, including how they might leverage the most value on gamified resources. The chapter makes significant use of authentic examples and case studies drawn from a range of different industries and areas, thus ensuring that students of all backgrounds are able to access the material and apply it to their own experience.

In this chapter, we discuss fundamental principles that define a creative learning environment and how these can be integrated into pedagogical design. Utilizing research, a creative environment instrument, and diverse learning settings as a springboard, we emphasize the link between a learning environment’s design and how it nurtures creativity. We propose the use of the SCALE (Support for Creativity in a Learning Environment) instrument (Richardson & Mishra, 2018) as a frame for understanding and evaluating the characteristics of creative learning environments. Using the SCALE’s constructs—characteristics of the environment, learning climate, and learner engagement—as benchmarks, we consider how these offer criteria to build into the design of learning environments. We examine the theoretical underpinnings of creativity, creative environments, and learning, identifying gaps in classroom research that the SCALE instrument can bridge. This chapter discusses applications of these principles across various environments, including online and blended spaces, acknowledging that different environments present distinctive affordances, opportunities, constraints, and possibilities. Our implications take a future-oriented perspective on online creative learning environment design in both research and practice.

This chapter elucidates on learning experience design (LXD), a philosophical approach to instructional that draws from various perspectives including human-computer interaction and design thinking. LXD aims to guide the design and development of digital learning technologies, emphasizing on creating highly usable and satisfying digital learning experiences. The chapter outlines specific human-centered design techniques, their goals, and the ideal stage of application during the design and development of digital learning experiences.

This chapter addresses the methodological vacuum in evaluating LXD practices. It elucidates common evaluation methods for LXD, providing a structured approach amidst the existing challenges in terminology, theoretical foundation, and method-application from user experience design (UXD) in learning design contexts. This chapter aims to bridge the gap by offering methodological guidance, thus fostering a more robust framework for evaluating LXD initiatives.

Media and instructional methods have had a problematic history in the instructional design field. In the 1990s, the "media vs. methods" debate exploded across influential issues of journals, including Educational Technology Research and Development, led by thinkers such as Richard Clark and Robert Kozma. This chapter discusses this historical debate and its insights, and updates it for our time, providing examples of how many designers still struggle with focusing on the media of a design, over the instructional methods.

Technology can be a powerful tool to reimagine learning experiences. Technology-enabled learning allows learners to tap resources and expertise anywhere in the world. Because of this, promoting effective implementation of technology is a key focus of the U.S. and other governments. This chapter provides an abridgment of part of the U.S. National Educational Technology Plan, a guiding document for educational technology initiatives throughout the United States.

Online learning has continued to increase in the last decade across higher education and K-12 education. Covid-19 forced many instructors and teachers globally to teach and learn online. Research in online learning has been conducted at micro and macro levels. This chapter explores several research trends in distance learning in order to assess the state of distance learning and provide recommendations for designers.

Learning and instructional designers are increasingly required to make use of various forms of data and analytics in order to design, implement and evaluate interventions. This is largely due to the increase in data available to learning designers and learning analysts due the update of digital technologies as part of learning and training. This chapter examines the historical development of what has become known as learning analytics, defining the field and considering various models of learning analytics, including the process model with its focus on student learning. The chapter then explores the ways that learning analytics might be effectively connected to the field of learning design, and provides a number of examples of applications of this, including learning analytics dashboards, tailored messaging and feedback systems and writing analytics. Examples of these different applications are also presented and discussed. Finally, the chapter concludes with a consideration for he challenges and future directions for learning analytics.

Computer-Supported Collaborative Learning (CSCL) research has become pervasive in STEM (science, technology, engineering, and mathematics) education over the last several decades. Guided by sociocultural and social constructivist theories of learning, CSCL focuses on shared meaning making and is influenced by the three pillars of CSCL: enabling technologies, pedagogical designs, and modes of collaboration. This chapter identifies four different approaches or clusters to CSCL that involve different combinations of these pillars. Focusing on two of these clusters, this chapter (a) identifies robust themes in this field and (b) discusses the positive outcomes associated with these aspects of CSCL. Outcomes include learning gains, process improvements, and affective outcomes. Across clusters, results demonstrate that scaffolding and feedback in different combinations affect outcomes. Moreover, different combinations are used with learners at different ages and with different learning goals. Designing CSCL for different learning environments requires considering the complex system of learning environments that emerge from the interaction among contexts, learner characteristics, and learning activities.

The field of learning and instructional design and technology (LIDT) has an important contribution to offer towards what Beckwith (1988) called “the transformation of learners and . . . learning” (p. 18). However, in pursuit of this mission, we have become too fixated on being designers and applying the methods of design thinking. As valuable as design is, it’s ultimately too narrow an approach to help us have the impact we desire because it overemphasizes the importance of the products and services we create. To be more influential, we need other approaches that focus our efforts on nurturing people’s “intrinsic talents and capacities” that are ultimately outside of our ability to manage and control (Thomson, 2005, p. 158; see also Biesta, 2013). In this chapter I first describe how design’s focus on creating and making misleads our understanding and application of important dimensions of our field. I then describe how we can cultivate an LIDT identity that is better suited for the aims we are pursuing. An LIDT-specific identity may include some methods from design thinking, but it will also encompass additional ways of improving the human condition. I end by calling on readers to consider what this important evolution for our field means for their personal practice.