Augmenting reality via head-mounted displays (HMD-AR) is an emerging technology in education. The interactivity provided by HMD-AR devices is particularly promising for learning, but presents a challenge to human activity recognition, especially with children. Recent technological advances regarding speech and gesture recognition concerning Microsoft’s HoloLens 2 may address this prevailing issue. In a within-subjects study with 47 elementary school children (2nd to 6th grade), we examined the usability of the HoloLens 2 using a standardized tutorial on multimodal interaction in AR. The overall system usability was rated “good”. However, several behavioral metrics indicated that specific interaction modes differed in their efficiency. The results are of major importance for the development of learning applications in HMD-AR as they partially deviate from previous findings. In particular, the well-functioning recognition of children’s voice commands that we observed represents a novelty. Furthermore, we found different interaction preferences in HMD-AR among the children. We also found the use of HMD-AR to have a positive effect on children’s activity-related achievement emotions. Overall, our findings can serve as a basis for determining general requirements, possibilities, and limitations of the implementation of educational HMD-AR environments in elementary school classrooms.

Multiple external representations (MERs) play an important role in the learning field of mathematics. Whereas the cognitive theory of multimedia learning and the integrative text and picture comprehension model assume that the heterogeneous combination of symbolic and analogous representations fosters learning; the design, functions, and tasks framework holds that learning benefits depend on the specific functions of MERs. The current paper describes a conceptual replication study of one of the few studies comparing single representations, heterogeneous, and homogeneous MERs in the context of mathematics learning. In a balanced incomplete block design, the participants were provided single representations (a graphic, text, or formula) or a heterogeneous (e.g., text + graphic) or homogeneous (text + formula) combination of these to solve linear system of equations problems. In accordance with previous research, performance was superior in conditions providing MERs compared to single‐representation conditions. Moreover, heterogeneous MERs led to time savings over homogeneous MERs which triggered an increase in cognitive load. Contrary to previous research, text was the least fixated representation whereas the graphical representation proved to be most beneficial. With regard to practical implications, experts should be fostered through more challenging homogeneous MERs whereas novices should be supported through the accessible graphic contained in heterogeneous MERs.

Augmented Reality (AR) can enhance student-centered lab work by bridging the spatial and temporal split between virtual information and observed real-world phenomena. While the Cognitive Theory of Multimedia Learning and the Cognitive Load Theory suggest that AR can reduce extraneous cognitive load (ECL) and foster learning, the empirical results remain inconsistent. This re-analysis of three related studies with different target groups and AR devices explores whether learners’ spatial abilities and verbal working memory capacity moderate the effect of AR support in lab work settings on ECL and conceptual knowledge gains. Although these moderators could not be confirmed consistently, the results indicate that tablet-based AR holds the potential to support learners with low spatial abilities. Moreover, low verbal working memory learners were demonstrated to be particularly vulnerable to the spatial contiguity failure that can be caused by smartglasses AR. Moderation effects were only observed for ECL but not for conceptual knowledge gains. The findings highlight that the benefit of AR support can depend on learners’ cognitive prerequisites and additional contextual factors, such as the AR device used and the age of the target group. The design and implementation of AR-supported lab work environments should account for these factors to optimize the learning outcomes.

Background: New methods are constantly being developed to adapt cognitive load measurement to different contexts. However, research on middle childhood students' cognitive load measurement is rare. Research indicates that the three cognitive load dimensions (intrinsic, extraneous, and germane) can be measured well in adults and teenagers using differentiated subjective rating instruments. Moreover, digital ink recorded by smartpens could serve as an indicator for cognitive load in adults. Aims: With the present research, we aimed at investigating the relation between subjective cognitive load ratings, velocity and pressure measures recorded with a smartpen, and performance in standardized sketching tasks in middle childhood students. Sample: Thirty‐six children (age 7–12) participated at the university's laboratory. Methods: The children performed two standardized sketching tasks, each in two versions. The induced intrinsic cognitive load or the extraneous cognitive load was varied between the versions. Digital ink was recorded while the children drew with a smartpen on real paper and after each task, they were asked to report their perceived intrinsic and extraneous cognitive load using a newly developed 5‐item scale. Results: Results indicated that cognitive load ratings as well as velocity and pressure measures were substantially related to the induced cognitive load and to performance in both sketching tasks. However, cognitive load ratings and smartpen measures were not substantially related. Conclusions: Both subjective rating and digital ink hold potential for cognitive load and performance measurement. However, it is questionable whether they measure the exact same constructs.

Mobile eye tracking is an important tool in psychology and human-centered interaction design for understanding how people process visual scenes and user interfaces. However, analyzing recordings from head-mounted eye trackers, which typically include an egocentric video of the scene and a gaze signal, is a time-consuming and largely manual process. To address this challenge, we develop eyeNotate, a web-based annotation tool that enables semi-automatic data annotation and learns to improve from corrective user feedback. Users can manually map fixation events to areas of interest (AOIs) in a video-editing-style interface (baseline version). Further, our tool can generate fixation-to-AOI mapping suggestions based on a few-shot image classification model (IML-support version). We conduct an expert study with trained annotators (n = 3) to compare the baseline and IML-support versions. We measure the perceived usability, annotations’ validity and reliability, and efficiency during a data annotation task. We asked our participants to re-annotate data from a single individual using an existing dataset (n = 48). Further, we conducted a semi-structured interview to understand how participants used the provided IML features and assessed our design decisions. In a post hoc experiment, we investigate the performance of three image classification models in annotating data of the remaining 47 individuals.

This paper investigates the use of augmented reality (AR) technology to deliver augmented lectures to support students in acquiring the curricular competency of using spatial imagination in mathematics education. As a very important stage in education to develop spatial abilities this paper focuses on elementary school children. Due to the challenges of working with children in experimental studies, this education level has received comparatively little attention in terms of support through ubiquitous technology. A theory-driven design approach was adopted in the development of an AR-based learning environment to visualize various virtual 3D cube buildings aligned with real blueprints. The designed environment was evaluated by a group of 1st and 2nd grade students in terms of system usability. The results showed that the theory-driven design was successful with a score of 86.56 on the System Usability test. In our future work, we aimed to assess the effectiveness of the proposed AR environment in terms of learning gains by performing more task-focused studies before and after experiment and comparing the results with the traditional teaching methods.