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Learning with hands-on experiments can be supported by providing essential information virtually during lab work. Augmented reality (AR) appears especially suitable for presenting information during experimentation, as it can be used to integrate both physical and virtual lab work. Virtual information can be displayed in close spatial proximity to the correspondent components in the experimentation environment, thereby ensuring a basic design principle for multimedia instruction: the spatial contiguity principle. The latter is assumed to reduce learners' extraneous cognitive load and foster generative processing, which supports conceptual knowledge acquisition. For the present study, a tablet-based AR application has been developed to support learning from hands-on experiments in physics education. Real-time measurement data were displayed directly above the components of electric circuits, which were constructed by the learners during lab work. In a two group pretest?posttest design, we compared university students' (N = 50) perceived cognitive load and conceptual knowledge gain for both the AR-supported and a matching non-AR learning environment. Whereas participants in both conditions gave comparable ratings for cognitive load, learning gains in conceptual knowledge were only detectable for the AR-supported lab work.

Cognitive load theory is considered universally applicable to all kinds of learning scenarios. However, instead of a universal method for measuring cognitive load that suits different learning contexts or target groups, there is a great variety of assessment approaches. Particularly common are subjective rating scales, which even allow for measuring the three assumed types of cognitive load in a differentiated way. Although these scales have been proven to be effective for various learning tasks, they might not be an optimal fit for the learning demands of specific complex environments such as technology-enhanced STEM laboratory courses. The aim of this research was therefore to examine and compare the existing rating scales in terms of validity for this learning context and to identify options for adaptation, if necessary. For the present study, the two most common subjective rating scales that are known to differentiate between load types (the cognitive load scale by Leppink et al. and the naïve rating scale by Klepsch et al.) were slightly adapted to the context of learning through structured hands-on experimentation where elements such as measurement data, experimental setups, and experimental tasks affect knowledge acquisition. N = 95 engineering students performed six experiments examining basic electric circuits where they had to explore fundamental relationships between physical quantities based on the observed data. Immediately after the experimentation, the students answered both adapted scales. Various indicators of validity, which considered the scales’ internal structure and their relation to variables such as group allocation as participants were randomly assigned to two conditions with a contrasting spatial arrangement of the measurement data, were analyzed. For the given dataset, the intended three-factorial structure could not be confirmed, and most of the a priori-defined subscales showed insufficient internal consistency. A multitrait–multimethod analysis suggests convergent and discriminant evidence between the scales which could not be confirmed sufficiently. The two contrasted experimental conditions were expected to result in different ratings for the extraneous load, which was solely detected by one adapted scale. As a further step, two new scales were assembled based on the overall item pool and the given dataset. They revealed a three-factorial structure in accordance with the three types of load and seemed to be promising new tools, although their subscales for extraneous load still suffer from low reliability scores.

Recent studies emphasize a positive impact of learning with augmented reality (AR) systems in various instructional scenarios. Especially combining real and virtual learning components according to spatial and temporal contiguity principles is claimed to foster learning and to reduce extraneous cognitive processing. We applied these principles to a physics laboratory experiment examining heat conduction where students measure the temperature along heated metal rods via a thermal imaging camera. However, the traditional setup leads to a time delay between measuring and receiving data, and spatially separates relevant visualizations causing resource-consuming search processes. Using see-through smartglasses, traditional displays were transformed into virtual representations which were anchored to corresponding objects of the experimental setup, resulting in an integrated AR view of real-time data. Both traditional and AR-assisted workflows of data collection were investigated in a field study with undergraduate students ( N = 74 ) during a graded laboratory course. Performance and cognitive load were assessed as dependent variables. Although the AR condition did not show a learning gain in a conceptual knowledge test, they nonetheless reported a significant lower extraneous cognitive load than the traditional condition. These results contrast with recent findings on AR and integrated formats but reveal a significant impact on cognitive load research.

Fundamental concepts of thermodynamics rely on abstract physical quantities such as energy, heat and entropy, which play an important role in the process of interpreting thermal phenomena and statistical mechanics. However, these quantities are not covered by human visual perception, and since heat sensation is purely qualitative and easy to deceive, an intuitive understanding often is lacking. Today immersive technologies like head-mounted displays of the newest generation, especially HoloLens, allow for high-quality augmented reality learning experiences, which can overcome this gap in human perception by presenting different representations of otherwise invisible quantities directly in the field of view of the user on the experimental apparatus, which simultaneously avoids a split-attention effect. In a mixed reality (MR) scenario as presented in this paper—which we call a holo.lab—human perception can be extended to the thermal regime by presenting false-color representations of the temperature of objects as a virtual augmentation directly on the real object itself in real-time. Direct feedback to experimental actions of the users in the form of different representations allows for immediate comparison to theoretical principles and predictions and therefore is supposed to intensify the theory–experiment interactions and to increase students' conceptual understanding. We tested this technology for an experiment on thermal conduction of metals in the framework of undergraduate laboratories. A pilot study with treatment and control groups (N = 59) showed a small positive effect of MR on students' performance measured with a standardized concept test for thermodynamics, pointing to an improvement of the understanding of the underlying physical concepts. These findings indicate that complex experiments could benefit even more from augmentation. This motivates us to enrich further experiments with MR.

We demonstrate how information derived from pervasive sensors can quantify cognitive states of learners while they are reading a textbook. Eye tracking is one of the most effective approaches to measuring reading behavior. For example, high fixation duration represents a reader's attention on a document. However, it is still a challenging task to predict the reason for the attention (i.e., is it because of his/her interest or trouble of understanding?). In this paper, we utilize additional sensing modality to solve the problem. On the dataset of 12 high school students' reading behaviors, we have found that the changing of pupil diameter and nose temperature are highly correlated with their cognitive states including their interests and efforts for reading/solving tasks on learning materials in Physics.

During the last decade the development of modern digital media such as smartphones and tablet computers has enabled new experimental possibilities in STEM education. Besides these now nearly ubiquitous devices, the fields of virtual reality (VR) and augmented reality (AR) also made huge progress and reached education. In this paper we introduce an AR experiment alongside the basic idea of this column and following prior work. In the experiment high school students use smartglasses and real-time measurement data to study Kirchhoff’s circuit laws in electrical DC circuits.

Amagnetic linear accelerator (or Gauss accelerator) is a device that uses the conversion of magnetic energy into kinetic energy to launch an object with high velocity. A simple experimental implementation consists of a line of steel spheres in which the first one is a permanent magnetic sphere. If another steel ball collides with the magnetic sphere from the left, the rightmost steel sphere is ejected at a much larger velocity than the impacting steel sphere. Several approaches have been published to determine the velocity of the ejected sphere, for example by using photogates or by measuring the impact position of the ejected sphere after falling from a table. All of these approaches have in common that the measurement of the velocity is a static process. This article describes an approach in which video motion analysis on tablet computers is used to measure simultaneously the time course of the velocity of the impacting steel sphere as well as the ejected steel sphere, thus giving students insight into the dynamics of the processes that lead to a higher kinetic energy of the ejected sphere.Amagnetic linear accelerator (or Gauss accelerator) is a device that uses the conversion of magnetic energy into kinetic energy to launch an object with high velocity. A simple experimental implementation consists of a line of steel spheres in which the first one is a permanent magnetic sphere. If another steel ball collides with the magnetic sphere from the left, the rightmost steel sphere is ejected at a much larger velocity than the impacting steel sphere. Several approaches have been published to determine the velocity of the ejected sphere, for example by using photogates or by measuring the impact position of the ejected sphere after falling from a table. All of these approaches have in common that the measurement of the velocity is a static process. This article describes an approach in which video mot...

The importance of coupled oscillations for natural and engineering sciences is undisputed. But due to the complex processes behind the phenomena, its educational arrangement remains challenging.

The importance of Scanning Tunneling Microscopy (STM) in today’s research and industry leads to the question of how to include such a key technology in physics education. Manfred Euler has developed an acoustic model experiment to illustrate the fundamental measuring principles based on an analogy between quantum mechanics and acoustics. Based on earlier work we applied mobile devices such as smartphones and tablets instead of using a computer to record and display the experimental data and thus converted Euler’s experimental setup into a low-cost experiment that is easy to build and handle by students themselves.

In the field of Virtual Reality (VR) and Augmented Reality (AR) technologies have made huge progress during the last years and also reached the field of education. The virtuality continuum, ranging from pure virtuality on one side to the real world on the other has been successfully covered by the use of immersive technologies like head-mounted displays, which allow to embed virtual objects into the real surroundings, leading to a Mixed Reality (MR) experience. In such an environment digital and real objects do not only co-exist, but moreover are also able to interact with each other in real-time. These concepts can be used to merge human perception of reality with digitally visualized sensor data and thereby making the invisible visible. As a first example, in this paper we introduce alongside the basic idea of this column an MR-experiment in thermodynamics for a laboratory course for freshman students in physics or other science and engineering subjects which uses physical data from mobile devices for analyzing and displaying physical phenomena to students., This article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing. The following article appeared in The Physics Teacher 55, 376 (2017) and may be found at doi: http://dx.doi.org/10.1119/1.4999739