The purpose of this chapter is to define and describe the roles and competencies of instructional designers working in the context of higher education. Inspired by existing research, this chapter summarizes these roles and competencies of instructional designers in higher education. We first review the context and settings in which these professionals work, delineate their common roles and responsibilities within these settings, and highlight the academic backgrounds and professional experiences that align with this career role. Next, we outline the core competencies for instructional designers in higher education by describing their typical work expectations and the necessary knowledge and skills needed to perform effectively and efficiently in this environment. Finally, we discuss how to gain the necessary competencies and experiences to serve in this capacity along with some closing remarks.

The purpose of this chapter is to provide tools and resources for structuring effective communications between instructional designers and faculty members in different settings where faculty engage in educational development. The chapter offers scripts for suggested communications, application exercises, and links to sample tools across stages of the ADDIE (Analyze, Develop, Design, Implement, Evaluate) instructional design (ID) process. The aim is to promote constructive and creative instructional design communications with faculty members in a variety of interactions.

The purpose of a needs assessment is to determine the current state of performance and the desired state of performance. When conducting a needs assessment, it is important to gather sufficient data to understand the situation warranting instructional solutions. The purpose of this chapter is to provide guidance for instructional designers interested in conducting needs assessment practices on a variety of scales.

This chapter provides newly minted and experienced instructional designers alike with the knowledge to manage Instructional Design (ID) projects in higher education contexts. As instructional designers and instructional design technology scholars, our goal is to help other instructional designers collaborate more effectively with academic and non-academic stakeholders. We provide best practices and templates for managing projects and communicating results. We conclude by suggesting professional development venues aligned with the priorities of the field and institutions of higher education.

This chapter provides instructional designers working in institutions of higher education (IHEs) with an introduction to the complexities of supporting instructional continuity amid the numerous and varied realities that make it challenging for students or faculty to complete a course as designed. From pandemics to hurricanes and unexpected illnesses to terrorism, there are many events that can interrupt instruction. Instructional designers can help minimize the impacts of such disruptions by employing a variety of tactics. In this chapter we define instructional continuity, explore the role of instructional designers in cultivating it, highlight some best practices, outline major implications for instructional designers, and share several resources to prepare for if/when there are events that interrupt the teaching-learning process.

Message design is an interdisciplinary area of knowledge. Message design contains words, visuals, and forms used to design, produce, and transmit messages. In this chapter, we will review message design outside the realm of training. Although an instructional designer or technologist’s primary function is training, there are many other duties an instructional designer has to perform, such as writing reports, leading instructional teams, or serving as a change agent, among many other functions.

The body of research supporting the inclusion of extended reality (XR) into higher education is substantial. However, due to the pandemic and the need to increase virtual presence with remote students and workers, the incorporation of diverse XR options into education is catching serious attention of university administrators. Instructional designers (IDs) are well trained in the analysis, design, implementation, and evaluation skills needed to select appropriate platforms and uses of XR. This chapter illustrates how IDs can assist in high-level design decisions regarding these resources. Familiar models and design approaches are recommended along with templates for working with leadership regarding research and funding and evaluating XR for best use for the higher education applications.

When teachers deliver instruction online, they require adequate training and support to do so successfully because an online instructor's role includes different responsibilities than traditional classroom instruction (Kim & Bonk, 2006). This chapter includes information on the practical application and adoption of an accessibility training program for online instructors, developed by instructional designers at a state college for two- to four-year degrees located in central Florida.

In this chapter, we introduce the Analytical Design Model, a strategy developed at Penn State’s World Campus for improving course quality and student outcomes through an evidence-based approach to instructional design. ADM utilizes data from a variety of sources and offers an efficient and flexible process to analysis that results in concrete improvement targets for courses. ADM is not an instructional design model in itself, but rather a method for making instructional design more strategic and aligned to academic program priorities.

In this book chapter, we provide guidelines and best practices to instructional designers working in higher education settings on how to use learning analytics to support and inform design decisions. We start by defining learning analytics and frame such a definition from a practitioner point of view. Then, we share best practices on how to use learning analytics to support and inform design decisions in designing courses in higher education. We share examples of learning analytics—through screenshots—gathered from our instructional design experience in higher education and comment on what implications such examples have on design decisions. We conclude by sharing a list of commonly available tools that support gathering learning analytics that instructional designers can put at their disposal throughout the design process, and in conducting needs analyses and formative/summative evaluations.

This chapter introduces the use of Q methodology to evaluate instruction in the context of higher education. As an important component of instructional design, evaluation is essential to ensure the quality of a program or curriculum. Different data collection methods and analysis tools are needed to evaluate educational interventions (Frechtling, 2010; Saunders, 2011). Instructional design practitioners are required to be familiar with a range of quantitative and qualitative analytic methods to perform a variety of evaluations in different contexts. Q methodology is a unique mixed method that utilizes both quantitative and qualitative techniques to examine people’s subjective viewpoints (Brown, 1993). We propose that Q methodology should be included in the evaluator’s toolbox. We attempt to provide instructional design practitioners with some practical guidelines to apply Q methodology to evaluation based on a systematic overview of evaluation and Q methodology. Suggestions and limitations of using Q methodology for higher education evaluation are also discussed.

Quality Assurance (QA) in higher education is a concept that owes its beginnings to quality assurance in the industrial sector. The purpose of this chapter is to describe strategies instructional designers can implement to promote quality assurance within their institutions.

As instructional designers helping subject matter experts design innovating learning experiences and leveraging educational technologies, they oftentimes find themselves conducting research to support the work they do. This research can take many forms, from reading research articles, investigating and testing educational tools, conducting research studies, participating in research communities, to serving in professional organizations. This chapter includes scenarios that illustrate how instructional designers can engage in research such as building a research network with professionals with different levels of research skills, creating partnerships with SMEs to conduct classroom-based research, and how to set up a research and evaluation agenda connected to professional development goals.

Instructional designers face a complex task of creating contextually relevant and meaningful professional development opportunities that meet campus-wide and departmental professional development needs for faculty who have multiple demands on their time. This chapter discusses principles of effective teaching with technology and provides a specific example of how proven instructional strategies and technology integration are embedded in a course supporting faculty in the use of a new learning management system.