Instructional designers (IDs) play a crucial role in higher education institutions’ teaching and learning endeavors. This review of literature on IDs in higher education between 2000 and 2020 found that their roles, responsibilities, and challenges are well-described, but little is known about what supports them. As ID roles evolve in response to new challenges while helping faculty and institutions adapt to changes during and after the COVID-19 pandemic, there is a rapidly emerging need to focus on additional areas of research, such as faculty perspectives, what it means to be an ID, and how IDs are--or can be--supported.

Using a multiple case study approach, we interviewed 14 instructional designers working at different universities to explore the approaches and strategies they utilized when experiencing conflict with faculty. While past practitioner-based research has identified strategies instructional designers employ to cultivate effective and productive collaborations with faculty, there are no similar publications examining how practitioners in the field handle conflict with faculty during these collaborations. Based on an analysis of the interview data, we uncovered conflict prevention and management strategies used by instructional designers that synchronizes with three phases of a typical faculty collaboration timelines: (1) at the outset of the collaboration (2) during the collaboration; and (3) post collaboration. Results suggest an interconnectedness across the approaches and strategies. This article concludes with a discussion of our findings including future research and implications.

Needs assessments are avoided due to perceptions of burden associated. While most research focuses on the facilitators, this research leverages the Perceived Burden in Needs Assessment Participant Scale (a= 0.86) to explore the participant perspective. Most participants reported low levels of burden (n = 244, M = 2.97, SD = 0.88), debunking the myth of severe levels of needs assessment burden. The results also yielded implications for NA practice, including that practitioners should: 1) make use of extant data, 2) ensure tasks and recommendations are reasonable, 3) minimize what participants must give up, 4) remain flexible, and 5) seek understanding.

Theoretically-informed design is a hallmark of the field of learning and instructional design and technology (LIDT). Designing digital environments for learning on the basis of theory can lead to theoretically pure and potentially effective learning interventions, yet theory alone is insufficient to consider the myriad of issues that emerge while a learner is engaged in digitally mediated learning. As the field of LIDT shifts towards more human-centered design practice, the phenomenon of learning experience design (LXD) has emerged as a novel, multidisciplinary focus area. LXD equips designers with a range of useful methods for explicitly considering the learner within the learning context. Two methods that we argue are particularly well-suited for this are personas and scenarios. The development of personas and scenarios can be informed by activity theory, which provides a lens for holistically considering the technology usage context and the learner’s role therein. The current article discusses the interplay of activity theory, personas, and scenarios, and illustrates how this can be potentially useful in learning experience design practice in two separate case examples. Implications are discussed.

Self-regulated learning (SRL) and higher-order thinking skills (HOTS) are associated with academic achievement, but fostering these skills is not easy. Scholars have suggested an alternative way to scaffold these important skills through learning analytics (LA). This paper presents a formative evaluation of a course-level LA implementation through the lens of self-regulated learning (SRL) and higher-order thinking skills (HOTS). We explored the changes in students’ SRL, HOTS, and perceptions at the end of the course term. Results indicate an increase in some elements of SRL and HOTS, and positive student perceptions. Discussion on implications and opportunities for informing future teaching strategies and course design reiteration are included.

Accelerated courses offer the same learning outcomes and credit hours as their semester-length counterparts but over a shorter duration of study. At many universities, accelerated online courses are gaining traction as a solution to students’ demand for more flexible scheduling. Many educators find it challenging to convert 16-week online courses to eight-week online courses. To help think through this conversion, we have been inspired by Marie Kondō’s system for decluttering and tidying living and work spaces, only keeping items that are needed and spark joy. In this article we share our Marie Kondō-inspired approach to designing accelerated online courses.

For maximally efficient and effective conversation-based intelligent tutoring systems, designers must understand the expectations carried by their intended learners. Strategies programmed into the agents may be interpreted differently by the learners. For example, conversational heuristics in these systems may be biased against false alarms in identifying wrong answers (potentially accepting more incorrect answers), or they may avoid directly answering learner-generated questions in an attempt to encourage more open-ended input. Regardless of pedagogical merit, the learner may view these agents’ dialogue moves as bugs rather than features and respond by disengaging or distrusting future interactions. We test this effect by orchestrating situations in agent-based instruction of electrical engineering topics (through an intelligent tutoring system called AutoTutor) where the pedagogical agent behaves in ways likely counter to learner expectations. To better understand the learning experience of the user, we then measure learner response via think-aloud protocol, eye-tracking, and direct interview. We find that, with few exceptions, learners do not reason that the actions are meant as instructional or technical strategies, but instead broadly understood as errors. This indicates a need for either alteration of agent dialogue strategies, or else additional (implicit or explicit) introduction of the strategies to productively shape learners’ interactions with the system.