TY - JOUR A1 - Palmisano, Chiara A1 - Kullmann, Peter A1 - Hanafi, Ibrahem A1 - Verrecchia, Marta A1 - Latoschik, Marc Erich A1 - Canessa, Andrea A1 - Fischbach, Martin A1 - Isaias, Ioannis Ugo T1 - A fully-immersive virtual reality setup to study gait modulation JF - Frontiers in Human Neuroscience N2 - Objective: Gait adaptation to environmental challenges is fundamental for independent and safe community ambulation. The possibility of precisely studying gait modulation using standardized protocols of gait analysis closely resembling everyday life scenarios is still an unmet need. Methods: We have developed a fully-immersive virtual reality (VR) environment where subjects have to adjust their walking pattern to avoid collision with a virtual agent (VA) crossing their gait trajectory. We collected kinematic data of 12 healthy young subjects walking in real world (RW) and in the VR environment, both with (VR/A+) and without (VR/A-) the VA perturbation. The VR environment closely resembled the RW scenario of the gait laboratory. To ensure standardization of the obstacle presentation the starting time speed and trajectory of the VA were defined using the kinematics of the participant as detected online during each walking trial. Results: We did not observe kinematic differences between walking in RW and VR/A-, suggesting that our VR environment per se might not induce significant changes in the locomotor pattern. When facing the VA all subjects consistently reduced stride length and velocity while increasing stride duration. Trunk inclination and mediolateral trajectory deviation also facilitated avoidance of the obstacle. Conclusions: This proof-of-concept study shows that our VR/A+ paradigm effectively induced a timely gait modulation in a standardized immersive and realistic scenario. This protocol could be a powerful research tool to study gait modulation and its derangements in relation to aging and clinical conditions. KW - gait modulation KW - virtual reality KW - obstacle avoidance KW - gait analysis KW - kinematics Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-267099 SN - 1662-5161 VL - 16 ER - TY - JOUR A1 - Brill, Michael A1 - Schwab, Frank T1 - A mixed-methods approach using self-report, observational time series data, and content analysis for process analysis of a media reception phenomenon JF - Frontiers in Psychology N2 - Due to the complexityof research objects, theoretical concepts, and stimuli in media research, researchers in psychology and communications presumably need sophisticated measures beyond self-report scales to answer research questions on media use processes. The present study evaluates stimulus-dependent structure in spontaneous eye-blink behavior as an objective, corroborative measure for the media use phenomenon of spatial presence. To this end, a mixed methods approach is used in an experimental setting to collect, combine, analyze, and interpret data from standardized participant self-report, observation of participant behavior, and content analysis of the media stimulus. T-pattern detection is used to analyze stimulus-dependent blinking behavior, and this structural data is then contrasted with self-report data. The combined results show that behavioral indicators yield the predicted results, while self-report data shows unpredicted results that are not predicted by the underlying theory. The use of a mixed methods approach offered insights that support further theory development and theory testing beyond a traditional, mono-method experimental approach. KW - presence KW - measurement KW - blinking KW - structure KW - mixed methods Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-201380 VL - 10 ER - TY - JOUR A1 - Hein, Rebecca M. A1 - Wienrich, Carolin A1 - Latoschik, Marc E. T1 - A systematic review of foreign language learning with immersive technologies (2001-2020) JF - AIMS Electronics and Electrical Engineering N2 - This study provides a systematic literature review of research (2001–2020) in the field of teaching and learning a foreign language and intercultural learning using immersive technologies. Based on 2507 sources, 54 articles were selected according to a predefined selection criteria. The review is aimed at providing information about which immersive interventions are being used for foreign language learning and teaching and where potential research gaps exist. The papers were analyzed and coded according to the following categories: (1) investigation form and education level, (2) degree of immersion, and technology used, (3) predictors, and (4) criterions. The review identified key research findings relating the use of immersive technologies for learning and teaching a foreign language and intercultural learning at cognitive, affective, and conative levels. The findings revealed research gaps in the area of teachers as a target group, and virtual reality (VR) as a fully immersive intervention form. Furthermore, the studies reviewed rarely examined behavior, and implicit measurements related to inter- and trans-cultural learning and teaching. Inter- and transcultural learning and teaching especially is an underrepresented investigation subject. Finally, concrete suggestions for future research are given. The systematic review contributes to the challenge of interdisciplinary cooperation between pedagogy, foreign language didactics, and Human-Computer Interaction to achieve innovative teaching-learning formats and a successful digital transformation. KW - foreign language learning and teaching KW - intercultural learning and teaching KW - immersive technologies KW - education KW - human-computer interaction KW - systematic literature review Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-268811 VL - 5 IS - 2 ER - TY - JOUR A1 - Knoll, Johannes A1 - Schramm, Holger T1 - Advertising in social network sites – Investigating the social influence of user-generated content on online advertising effects JF - Communications N2 - In today’s social online world there is a variety of interaction and participatory possibilities which enable web users to actively produce content themselves. This user-generated content is omnipresent in the web and there is growing evidence that it is used to select or evaluate professionally created online information. The present study investigated how this surrounding content affects online advertising by drawing from social influence theory. Specifically, it was assumed that web users sharing an interpersonal relationship (interpersonal influence) and/or a group membership (collective influence) with authors of user-generated content which appears next to advertising on the web page are more strongly influenced in their response to the advertising than unrelated users. These assumptions were tested in a 2 × 2 between-subject experiment with 118 students who were exposed to four different Facebook profiles that differed in terms of interpersonal connection to the source (existent/non-existent) and collective connection to the source (existent/non-existent). The results show a significant impact in the case of collective influence, but not in the case of interpersonal influence. The underlying mechanisms of this effect and implications of the results for online advertising are discussed. KW - online advertising KW - social network sites KW - social influence KW - user-generated content KW - advertising effects Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-194192 SN - 1613-4087 SN - 0341-2059 N1 - This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively. VL - 40 IS - 3 ER - TY - THES A1 - Sonnenberg, Christoph T1 - Analyzing Technology-Enhanced Learning Processes: What Can Process Mining Techniques Contribute to the Evaluation of Instructional Support? T1 - Eine Analyse technologieunterstützter Lernprozesse: Welchen Beitrag kann Process Mining für die Bewertung instruktionaler Hilfe leisten? N2 - The current dissertation addresses the analysis of technology-enhanced learning processes by using Process Mining techniques. For this purpose, students’ coded think-aloud data served as the measurement of the learning process, in order to assess the potential of this analysis method for evaluating the impact of instructional support. The increasing use of digital media in higher education and further educational sectors enables new potentials. However, it also poses new challenges to students, especially regarding the self-regulation of their learning process. To help students with optimally making progress towards their learning goals, instructional support is provided during learning. Besides the use of questionnaires and tests for the assessment of learning, researchers make use increasingly of process data to evaluate the effects of provided support. The analysis of observed behavioral traces while learning (e.g., log files, eye movements, verbal reports) allows detailed insights into the student’s activities as well as the impact of interventions on the learning process. However, new analytical challenges emerge, especially when going beyond the analysis of pure frequencies of observed events. For example, the question how to deal with temporal dynamics and sequences of learning activities arises. Against this background, the current dissertation concentrates on the application of Process Mining techniques for the detailed analysis of learning processes. In particular, the focus is on the additional value of this approach in comparison to a frequency-based analysis, and therefore on the potential of Process Mining for the evaluation of instructional support. An extensive laboratory study with 70 university students, which was conducted to investigate the impact of a support measure, served as the basis for pursuing the research agenda of this dissertation. Metacognitive prompts supported students in the experimental group (n = 35) during a 40-minute hypermedia learning session; whereas the control group (n = 35) received no support. Approximately three weeks later, all students participated in another learning session; however, this time all students learned without any help. The participants were instructed to verbalize their learning activities concurrently while learning. In the three analyses of this dissertation, the coded think aloud data were examined in detail by using frequency-based methods as well as Process Mining techniques. The first analysis addressed the comparison of the learning activities between the experimental and control groups during the first learning session. This study concentrated on the research questions whether metacognitive prompting increases the number of metacognitive learning activities, whether a higher number of these learning activities corresponds with learning outcome (mediation), and which differences regarding the sequential structure of learning activities can be revealed. The second analysis investigated the impact of the individual prompts as well as the conditions of their effectiveness on the micro level. In addition to Process Mining, we used a data mining approach to compare the findings of both analysis methods. More specifically, we classified the prompts by their effectiveness, and we examined the learning activities preceding and following the presentation of instructional support. Finally, the third analysis considered the long-term effects of metacognitive prompting on the learning process during another learning session without support. It was the key objective of this study to examine which fostered learning activities and process patterns remained stable during the second learning session. Overall, all three analyses indicated the additional value of Process Mining in comparison to a frequency-based analysis. Especially when conceptualizing the learning process as a dynamic sequence of multiple activities, Process Mining allows identifying regulatory loops and crucial routing points of the process. These findings might contribute to optimizing intervention strategies. However, before drawing conclusions for the design of instructional support based on the revealed process patterns, additional analyses need to investigate the generalizability of results. Moreover, the application of Process Mining remains challenging because guidelines for analytical decisions and parameter settings in technology-enhanced learning context are currently missing. Therefore, future studies need to examine further the potential of Process Mining as well as related analysis methods to provide researchers with concrete recommendations for use. Nevertheless, the application of Process Mining techniques can already contribute to advance the understanding of the impact of instructional support through the use of fine-grained process data. N2 - Die vorliegende Dissertation beschäftigt sich mit der Analyse technologieunterstützter Lernprozesse unter Verwendung von Process Mining Methoden. Dabei werden kodierte Protokolle des lauten Denkens als Prozessmaß genutzt, um eine Bewertung des Potentials dieses Analyseansatzes für die Evaluation der Effekte instruktionaler Hilfe vornehmen zu können. Die zunehmende Verbreitung digitaler Medien in der Hochschulbildung und weiteren Ausbildungssektoren schafft neue Potentiale, allerdings auch neue Anforderungen an den Lerner, insbesondere an die Regulation seines Lernprozesses. Um ihn dabei zu unterstützen seinen Lernfortschritt optimal zu gestalten, wird ihm während des Lernens instruktionale Hilfe angeboten. Neben der Evaluation mittels Fragebögen und Testverfahren wird die Wirksamkeit der angebotenen Unterstützung zunehmend durch Prozessdaten bewertet. Die Analyse von beobachteten Verhaltensspuren während des Lernens (z.B. Logfiles, Blickbewegungen, Verbalprotokolle) ermöglicht einen detaillierten Einblick in die Lernhandlungen und die Folgen von Unterstützungsmaßnahmen. Allerdings stellen sich auch eine Reihe von neuen analytischen Herausforderungen, wie der Umgang mit zeitlichen Dynamiken und Sequenzen von Lernhandlungen, insbesondere wenn man über Häufigkeitsanalysen der beobachteten Ereignisse hinausgehen möchte. Vor diesem Hintergrund beschäftigt sich die vorliegende Arbeit mit der Anwendung von Process Mining Methoden zur detaillierten Betrachtung von Lernprozessen. Insbesondere der Mehrwert dieses Ansatzes gegenüber einer reinen Häufigkeitsanalyse und somit die Potentiale von Process Mining für die Evaluation von Fördermaßen sollen herausgestellt werden. Als Grundlage für die Bearbeitung der Fragestellung diente eine umfangreiche Laborstudie mit 70 Universitätsstudierenden, die durchgeführt wurde um die Effekte einer instruktionalen Fördermaßnahme zu prüfen. Die Probanden der Experimentalgruppe (n = 35) erhielten in einer 40-minütigen Hypermedia-Lernsitzung eine Förderung durch metakognitive Prompts, während die Kontrollgruppe (n = 35) ohne Hilfe lernte. In einer weiteren Lernsitzung drei Wochen später bearbeiteten alle Teilnehmer eine weitere Lerneinheit, diesmal ohne Unterstützung für alle Probanden. Während des Lernens wurden alle Teilnehmer instruiert, ihre Lernhandlungen kontinuierlich zu verbalisieren. Die kodierten Verbalprotokolle wurden in den drei Analysen dieser Dissertation detailliert mit Häufigkeits- und Process Mining Analysen untersucht. Die erste Analyse konzentrierte sich auf den Vergleich der Lernhandlungen der Experimental- und Kontrollgruppe während der ersten Sitzung. Es wurde den Fragen nachgegangen, ob metakognitive Prompts die Lerner dazu anregen mehr metakognitive Lernhandlungen auszuführen, ob eine höhere Anzahl dieser Lernhandlungen mit dem Lernerfolg zusammenhängt (Mediation) und welche Unterschiede sich in den Abfolgen der Lernhandlungen finden lassen. In der zweiten Analyse wurden die Effekte der einzelnen Prompts sowie die Bedingungen für ihre Wirksamkeit auf einer sehr detaillierten Ebene betrachtet. Zusätzlich zu Process Mining wurde auch eine Data Mining Methode eingesetzt, um deren Befunde zu vergleichen. Im Detail fanden eine Klassifikation der Prompts anhand ihrer Effektivität und eine Untersuchung der kodierten Lernaktivitäten vor und nach der Präsentation instruktionaler Hilfe statt. Schließlich untersuchte die dritte Analyse die langfristigen Effekte metakognitiver Prompts auf den Lernprozess in einer weiteren Lernsitzung ohne Unterstützung. Hier stand die Frage im Mittelpunkt, welche geförderten Lernaktivitäten und Prozessmuster während der zweiten Lernsitzung stabil blieben. Insgesamt belegen die Ergebnisse aller drei durchgeführten Analysen den Mehrwert von Process Mining im Vergleich zu reinen häufigkeitsbasierten Analysemethoden. Insbesondere unter Betrachtung des Lernprozesses als dynamische Abfolge von mehreren Lernhandlungen, ermöglicht Process Mining die Identifikation von Regulationsschleifen und zentralen Verzweigungen des Prozesses. Diese Befunde könnten zur Optimierung von Interventionen verwendet werden. Bevor aus den aufgedeckten Prozessmustern Schlussfolgerungen für die Gestaltung instruktionaler Hilfe gezogen werden können, müssen allerdings weitere Analysen erst noch die Generalisierbarkeit der Befunde belegen. Darüber hinaus bleibt die Anwendung von Process Mining herausfordernd, da derzeit keine Richtlinien für analytische Entscheidungen und Parametereinstellungen für technologieunterstützte Lernkontexte vorhanden sind. Darum müssen in Zukunft weitere Studien das Potential von Process Mining und verwandten Analysemethoden betrachten, um Forschern konkrete Anwendungsempfehlungen zur Verfügung stellen zu können. Generell kann Process Mining aber bereits jetzt dazu beitragen, das Verständnis der Auswirkungen instruktionaler Hilfe auf der Prozessebene voran zu treiben. KW - Selbstgesteuertes Lernen KW - Prozessanalyse KW - Process Mining KW - Metacognitive Prompting KW - Instructional Support KW - Technology-Enhanced Learning KW - Self-Regulated Learning KW - Metakognition KW - Lautes Denken Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-152354 ER - TY - JOUR A1 - Hutmacher, Fabian A1 - Schläger, Linus A1 - Meerson, Rinat T1 - Autobiographical memory in the digital age: Insights based on the subjective reports of users of smart journaling apps JF - Applied Cognitive Psychology N2 - Humans have long used external memory aids to support remembering. However, modern digital technologies could facilitate recording and remembering personal information in an unprecedented manner. The present research sought to understand the potential impact of these technologies on autobiographical memory based on interviews with users of smart journaling apps. In Study 1 (N = 12), participants who had no prior experience with smart journaling apps tested the app Day One for 2 weeks and were interviewed about their subjective perceptions afterwards. In order to cross-validate the obtained findings, Study 2 (N = 4) was based on in-depth interviews with long-time users of different smart journaling apps. Taken together, the two studies provide insights into the way autobiographical remembering may change in the digital age – but also into the opportunities and risks potentially associated with the use of technologies that allow creating a detailed and multimedia-based record of one's life. KW - autobiographical memory KW - total recall KW - smart journaling KW - digital age KW - new media Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-318620 SN - 0888-4080 VL - 37 IS - 4 SP - 686 EP - 698 ER - TY - JOUR A1 - Wienrich, Carolin A1 - Döllinger, Nina A1 - Hein, Rebecca T1 - Behavioral Framework of Immersive Technologies (BehaveFIT): How and why virtual reality can support behavioral change processes JF - Frontiers in Virtual Reality N2 - The design and evaluation of assisting technologies to support behavior change processes have become an essential topic within the field of human-computer interaction research in general and the field of immersive intervention technologies in particular. The mechanisms and success of behavior change techniques and interventions are broadly investigated in the field of psychology. However, it is not always easy to adapt these psychological findings to the context of immersive technologies. The lack of theoretical foundation also leads to a lack of explanation as to why and how immersive interventions support behavior change processes. The Behavioral Framework for immersive Technologies (BehaveFIT) addresses this lack by 1) presenting an intelligible categorization and condensation of psychological barriers and immersive features, by 2) suggesting a mapping that shows why and how immersive technologies can help to overcome barriers and finally by 3) proposing a generic prediction path that enables a structured, theory-based approach to the development and evaluation of immersive interventions. These three steps explain how BehaveFIT can be used, and include guiding questions for each step. Further, two use cases illustrate the usage of BehaveFIT. Thus, the present paper contributes to guidance for immersive intervention design and evaluation, showing that immersive interventions support behavior change processes and explain and predict 'why' and 'how' immersive interventions can bridge the intention-behavior-gap. KW - immersive technologies KW - behavior change KW - intervention design KW - intervention evaluation KW - framework KW - virtual reality KW - intention-behavior-gap KW - human-computer interaction Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-258796 VL - 2 ER - TY - JOUR A1 - Rudloff, Jan Philipp A1 - Hutmacher, Fabian A1 - Appel, Markus T1 - Beliefs about the nature of knowledge shape responses to the pandemic: Epistemic beliefs, the Dark Factor of Personality, and COVID‐19–related conspiracy ideation and behavior JF - Journal of Personality N2 - Objective Global challenges such as climate change or the COVID‐19 pandemic have drawn public attention to conspiracy theories and citizens' non‐compliance to science‐based behavioral guidelines. We focus on individuals' worldviews about how one can and should construct reality (epistemic beliefs) to explain the endorsement of conspiracy theories and behavior during the COVID‐19 pandemic and propose the Dark Factor of Personality (D) as an antecedent of post‐truth epistemic beliefs. Method and Results This model is tested in four pre‐registered studies. In Study 1 (N = 321), we found first evidence for a positive association between D and post‐truth epistemic beliefs (Faith in Intuition for Facts, Need for Evidence, Truth is Political). In Study 2 (N = 453), we tested the model proper by further showing that post‐truth epistemic beliefs predict the endorsement of COVID‐19 conspiracies and disregarding COVID‐19 behavioral guidelines. Study 3 (N = 923) largely replicated these results at a later stage of the pandemic. Finally, in Study 4 (N = 513), we replicated the results in a German sample, corroborating their cross‐cultural validity. Interactions with political orientation were observed. Conclusion Our research highlights that epistemic beliefs need to be taken into account when addressing major challenges to humankind. KW - conspiracy theories KW - COVID‐19 KW - Dark Factor of Personality KW - epistemic beliefs KW - post‐truth Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-293793 VL - 90 IS - 6 SP - 937 EP - 955 ER - TY - THES A1 - Oberdörfer, Sebastian T1 - Better Learning with Gaming: Knowledge Encoding and Knowledge Learning Using Gamification T1 - Besser Lernen durch Spielen: Wissensencodierung und Lernen von Wissen mit Gamification N2 - Computer games are highly immersive, engaging, and motivating learning environments. By providing a tutorial at the start of a new game, players learn the basics of the game's underlying principles as well as practice how to successfully play the game. During the actual gameplay, players repetitively apply this knowledge, thus improving it due to repetition. Computer games also challenge players with a constant stream of new challenges which increase in difficulty over time. As a result, computer games even require players to transfer their knowledge to master these new challenges. A computer game consists of several game mechanics. Game mechanics are the rules of a computer game and encode the game's underlying principles. They create the virtual environments, generate a game's challenges and allow players to interact with the game. Game mechanics also can encode real world knowledge. This knowledge may be acquired by players via gameplay. However, the actual process of knowledge encoding and knowledge learning using game mechanics has not been thoroughly defined, yet. This thesis therefore proposes a theoretical model to define the knowledge learning using game mechanics: the Gamified Knowledge Encoding. The model is applied to design a serious game for affine transformations, i.e., GEtiT, and to predict the learning outcome of playing a computer game that encodes orbital mechanics in its game mechanics, i.e., Kerbal Space Program. To assess the effects of different visualization technologies on the overall learning outcome, GEtiT visualizes the gameplay in desktop-3D and immersive virtual reality. The model's applicability for effective game design as well as GEtiT's overall design are evaluated in a usability study. The learning outcome of playing GEtiT and Kerbal Space Program is assessed in four additional user studies. The studies' results validate the use of the Gamified Knowledge Encoding for the purpose of developing effective serious games and to predict the learning outcome of existing serious games. GEtiT and Kerbal Space Program yield a similar training effect but a higher motivation to tackle the assignments in comparison to a traditional learning method. In conclusion, this thesis expands the understanding of using game mechanics for an effective learning of knowledge. The presented results are of high importance for researches, educators, and developers as they also provide guidelines for the development of effective serious games. N2 - Computerspiele stellen attraktive, spannende und motivierende Lernumgebungen dar. Spieler erlernen zu Spielbeginn die grundlegenden Spielregeln und wenden dieses Wissen während des Spielablaufs an. Dadurch wird das dem Spiel zu Grunde liegende Wissen durch Wiederholung geübt und verinnerlicht. Durch einen konstanten Fluss an neuen Herausforderungen, die in ihrer Schwierigkeit ansteigen, müssen Spieler das Wissen auf neue Szenarien übertragen. Innerhalb eines Computerspiels sind Spielmechaniken für eine Anwendung als auch Demonstration des Spielwissens verantwortlich. Die Spielmechaniken regeln den Spielablauf, in dem sie die Spieleraktionen definieren, die virtuelle Umgebung generieren und die Herausforderungen des Spiels festlegen. Das in den Spielmechaniken kodierte Wissen kann jedoch auch der realen Welt entstammen. In diesem Fall entwickeln Spieler Kompetenzen, die später auch in der Realität Anwendung finden können. Das Kodieren von Wissen in Spielmechaniken und der damit einhergehende Lernprozess wurde allerdings noch nicht genau theoretisch erfasst. Diese Dissertation versucht diese Forschungslücke zu schließen, indem ein theoretisches Model der Wissenskodierung in Spielmechaniken entworfen wird: das Gamified Knowledge Encoding. Dieses Model wird sowohl für das Design einer Lernanwendung für das Wissen der Affinen Transformationen, GEtiT, als auch zur Vorhersage von Lerneffekten eines Computerspiels, Kerbal Space Program, herangezogen. In einer Usability-Studie wird sowohl die Anwendbarkeit des Modells für ein effektives Spieldesign als auch das Gesamtdesign von GEtiT bewertet. Das Lernergebnis, das beim Spielen von GEtiT und Kerbal Space Program erzielt wird, wird in vier weiteren Nutzerstudien überprüft. Die Studien validieren den Einsatz des Gamified Knowledge Encoding Models zur Entwicklung von computerspielbasierten Lernumgebungen und die Vorhersage von Lerneffekten. GEtiT und Kerbal Space Program erzielen ein ähnliches Lernergebnis bei einer höheren Motivation im Vergleich zu einer traditionellen Lernmethode. Als Endergebnis erweitert das präsentierte Forschungsprojekt das generelle Verständnis über die Verwendung von Spielmechaniken für ein effektives Lernen. Die präsentierten Ergebnisse sind von großer Bedeutung für Forscher, Pädagogen und Entwickler, da sie auch Richtlinien für die Entwicklung effektiver Serious Games hervorbringen. KW - Serious game KW - Gamification KW - Lernen KW - Game mechanic KW - Spielmechanik KW - Knowledge encoding KW - Wissensencodierung KW - Virtuelle Realität Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-219707 ER - TY - JOUR A1 - Döllinger, Nina A1 - Wienrich, Carolin A1 - Latoschik, Marc Erich T1 - Challenges and opportunities of immersive technologies for mindfulness meditation: a systematic review JF - Frontiers in Virtual Reality N2 - Mindfulness is considered an important factor of an individual's subjective well-being. Consequently, Human-Computer Interaction (HCI) has investigated approaches that strengthen mindfulness, i.e., by inventing multimedia technologies to support mindfulness meditation. These approaches often use smartphones, tablets, or consumer-grade desktop systems to allow everyday usage in users' private lives or in the scope of organized therapies. Virtual, Augmented, and Mixed Reality (VR, AR, MR; in short: XR) significantly extend the design space for such approaches. XR covers a wide range of potential sensory stimulation, perceptive and cognitive manipulations, content presentation, interaction, and agency. These facilities are linked to typical XR-specific perceptions that are conceptually closely related to mindfulness research, such as (virtual) presence and (virtual) embodiment. However, a successful exploitation of XR that strengthens mindfulness requires a systematic analysis of the potential interrelation and influencing mechanisms between XR technology, its properties, factors, and phenomena and existing models and theories of the construct of mindfulness. This article reports such a systematic analysis of XR-related research from HCI and life sciences to determine the extent to which existing research frameworks on HCI and mindfulness can be applied to XR technologies, the potential of XR technologies to support mindfulness, and open research gaps. Fifty papers of ACM Digital Library and National Institutes of Health's National Library of Medicine (PubMed) with and without empirical efficacy evaluation were included in our analysis. The results reveal that at the current time, empirical research on XR-based mindfulness support mainly focuses on therapy and therapeutic outcomes. Furthermore, most of the currently investigated XR-supported mindfulness interactions are limited to vocally guided meditations within nature-inspired virtual environments. While an analysis of empirical research on those systems did not reveal differences in mindfulness compared to non-mediated mindfulness practices, various design proposals illustrate that XR has the potential to provide interactive and body-based innovations for mindfulness practice. We propose a structured approach for future work to specify and further explore the potential of XR as mindfulness-support. The resulting framework provides design guidelines for XR-based mindfulness support based on the elements and psychological mechanisms of XR interactions. KW - virtual reality KW - augmented reality KW - mindfulness KW - XR KW - meditation Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-259047 VL - 2 ER -