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Abstract In contrast to traditional views of instructional design that are often focused on content development, researchers are increasingly exploring learning experience design (LXD) perspectives as a way to espouse a broader and more holistic view of learning. In addition to cognitive and affective perspectives, LXD includes perspectives on human–computer interaction that consist of usability and other interactions (ie—goal-directed user behavior). However, there is very little consensus about the quantitative instruments and surveys used by individuals to assess how learners interact with technology. This systematic review explored 627 usability studies in learning technology over the last decade in terms of the instruments (RQ1), domains (RQ2), and number of users (RQ3). Findings suggest that many usability studies rely on self-created instruments, which leads to questions about reliability and validity. Moreover, additional research suggests usability studies are largely focused within the medical and STEM domains, with very little focus on educators' perspectives (pre-service, in-service teachers). Implications for theory and practice are discussed. 

Research indicates that peer mentoring is an effective solution for building ethnic and racial minority women’s self-efficacy to persist in STEM degrees and careers. What is not known, however, is how to design a training program grounded in learning theory to build mentoring knowledge, skills, and self-efficacy in underrepresented populations in Historically Black Colleges and Universities (HBCU). This instructional design case fulfills that gap by presenting details of design challenges and decisions made while developing an eight-week online training program for both mentors and mentees participating in a STEM peer mentoring program at two HBCUs. This design case is a second iteration of the training program following an initial pilot study. Stakeholder feedback, along with a conceptual framework, including Tinto’s Institutional Departure Model and Bandura’s Theory of Self-Efficacy, guided the design work. 

Learners often have metacognitive deficits that limit their ability to select material at appropriate levels in independent studying situations. The increasing prevalence of intelligent recommender systems can assume this role, while also fostering a kind of experiential meta-instruction. The creation of hybrid tutors (federated systems of both adaptive and static learning resources with a single interface and learning record store) provides an opportunity to test this experiential instruction of metacognitive strategies. As a test case, we examine the hybrid tutor ElectronixTutor, which has two distinct intelligent recommender engines corresponding to distinct use cases. Each of these constitutes a method of providing scaffolding to learners so that they can internalize the principled, theoretically informed reasons for the order of their progression through learning content. However, the learning described is speculative and requires evaluation. By examining expected efficacy, perceived efficacy, actual efficacy, and especially the relationships among these three concepts, actionable insights should arise pertaining to adaptive instructional system design, learning science generally, and other areas