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Annotation in 3D user interfaces such as Augmented Reality (AR) and Virtual Reality (VR) is a challenging and promising area; however, there are not currently surveys reviewing these contributions. In order to provide a survey of annotations for Extended Reality (XR) environments, we conducted a structured literature review of papers that used annotation in their AR/VR systems from the period between 2001 and 2021. Our literature review process consists of several filtering steps which resulted in 103 XR publications with a focus on annotation. We classified these papers based on the display technologies, input devices, annotation types, target object under annotation, collaboration type, modalities, and collaborative technologies. A survey of annotation in XR is an invaluable resource for researchers and newcomers. Finally, we provide a database of the collected information for each reviewed paper. This information includes applications, the display technologies and its annotator, input devices, modalities, annotation types, interaction techniques, collaboration types, and tasks for each paper. This database provides a rapid access to collected data and gives users the ability to search or filter the required information. This survey provides a starting point for anyone interested in researching annotation in XR environments. 

Elicitation studies have become a popular method of participatory design. While traditionally used to examine unimodal gesture interactions, elicitation has started being used with other novel interaction modalities. Unfortunately, there has been no work that examines the impact of referent display on elicited interaction proposals. To address that concern this work provides a detailed comparison between two elicitation studies that were similar in design apart from the way that participants were prompted for interaction proposals (i.e., the referents). Based on this comparison the impact of referent display on speech and gesture interaction proposals are each discussed. The interaction proposals between these elicitation studies were not identical. Gesture proposals were the least impacted by referent display, showing high proposal similarity between the two works. Speech proposals were highly biased by text referents with proposals directly mirroring text-based referents an average of 69.36% of the time. In short, the way that referents are presented during elicitation studies can impact the resulting interaction proposals; however, the level of impact found is dependent on the modality of input elicited. 

More than two hundred papers on elicitation studies have been published in the last ten years. These works are mainly focused on generating user-defined gesture sets and discovering natural feeling multimodal interaction techniques with virtual objects. Few papers have discussed binning the elicited interaction proposals after data collection. Binning is a process of grouping the entire set of user-generated interaction proposals based on similarity criteria. The binned set of proposals is then analyzed to produce a consensus set, which results in the user-defined interaction set. This paper presents a formula to use when deciding how to bin interaction proposals, thus helping to establish a more consistent binning procedure. This work can provide human-computer interaction (HCI) researchers with the guidance they need for interaction elicitation data processing, which is largely missing from current elicitation study literature. Using this approach will improve the efficiency and effectiveness of the binning process, increase the reliability of us er-defined interaction sets, and most importantly, improve the replicability of elicitation studies. 

Interacting in stereoscopic head mounted displays can be difficult. There are not yet clear standards for how interactions in these environments should be performed. In virtual reality there are a number of well designed interaction techniques; however, augmented reality interaction techniques still need to be improved before they can be easily used. This dissertation covers work done towards understanding how users navigate and interact with virtual environments that are displayed in stereoscopic head-mounted displays. With this understanding, existing techniques from virtual reality devices ... (For more, see "View full record.") 

Although the use of technologies like multimedia and virtual reality (VR) in training offer the promise of improved learning, these richer and potentially more engaging materials do not consistently produce superior learning outcomes. Default approaches to such training may inadvertently mimic concepts like naïve realism in display design, and desirable difficulties in the science of learning – fostering an impression of greater learning dissociated from actual gains in memory. This research examined the influence of format of instructions in learning to assemble items from components. Participants in two experiments were trained on the steps to assemble a series of bars, that resembled Meccano pieces, into eight different shapes. After training on pairs of shapes, participants rated the likelihood they would remember the shapes and then were administered a recognition test. Relative to viewing a static diagram, viewing videos of shapes being constructed in a VR environment (Experiment 1) or viewing within an immersive VR system (Experiment 2) elevated participants’ assessments of their learning but without enhancing learning outcomes. Overall, these findings illustrate how future workers might mistakenly come to believe that technologically advanced support improves learning and prefer instructional designs that integrate similarly complex cues into training.