https://puma.ub.uni-stuttgart.de/group/simtech/learningPUMA RSS feed for /group/simtech/learning2026-04-23T01:54:32+02:00https://puma.ub.uni-stuttgart.de/bibtex/21ae3450942b5d9c5e60bcc988f964384/mariawirzbergermariawirzberger2025-09-14T12:22:58+02:00competence gamification myown instruction learning video digital <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Melanie Schäfer" itemprop="url" href="/person/147ce6401b6840b80226d295c5edcacf0/author/0"><span itemprop="name">M. Schäfer</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Steffen Becker" itemprop="url" href="/person/147ce6401b6840b80226d295c5edcacf0/author/1"><span itemprop="name">S. Becker</span></a></span>, </span> und <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Maria Wirzberger" itemprop="url" href="/person/147ce6401b6840b80226d295c5edcacf0/author/2"><span itemprop="name">M. Wirzberger</span></a></span></span>. </span><span class="additional-entrytype-information">(<em><span>2024<meta content="2024" itemprop="datePublished"/></span></em>)</span>Sun Sep 14 12:22:58 CEST 2025TURN Conference 2024Digital fit ins Studium starten2024competence gamification myown instruction learning video digital https://puma.ub.uni-stuttgart.de/bibtex/27c42de936daf2942faf1e7eed65da74c/mariawirzbergermariawirzberger2025-09-14T12:16:37+02:00myown cognition AI learning technology tutoring chatbots ethics analytics llis <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Maria Wirzberger" itemprop="url" href="/person/1ab3f8dbd7a6c539b400c90f9ec69d0c6/author/0"><span itemprop="name">M. Wirzberger</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">Lehren und lernen mit digitalen Medien: Theorien und Design</span>, </em><em><span itemprop="publisher">Hogrefe</span>, </em></span>(<em><span>2024<meta content="2024" itemprop="datePublished"/></span></em>)</span>Sun Sep 14 12:16:37 CEST 2025Lehren und lernen mit digitalen Medien: Theorien und Design155–182Intelligente Systeme für das Lehren und Lernen2024myown cognition AI learning technology tutoring chatbots ethics analytics llis https://puma.ub.uni-stuttgart.de/bibtex/263bded38df79dcc836fa088d7220e15c/mariawirzbergermariawirzberger2025-09-12T20:31:50+02:00myown cognition neurodiversity learning llis society workplace <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Maria Wirzberger" itemprop="url" href="/person/1a89ab9683192756b8959addde18aa95c/author/0"><span itemprop="name">M. Wirzberger</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Laura Bareiß" itemprop="url" href="/person/1a89ab9683192756b8959addde18aa95c/author/1"><span itemprop="name">L. Bareiß</span></a></span>, </span> und <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Leyla Baybüyük" itemprop="url" href="/person/1a89ab9683192756b8959addde18aa95c/author/2"><span itemprop="name">L. Baybüyük</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">Neue Akzente</span>, </em> </span>(<em><span>2025<meta content="2025" itemprop="datePublished"/></span></em>)</span>Fri Sep 12 20:31:50 CEST 2025Neue Akzente5-7Starke Vielfalt im Kopf: Wie Neurodiversität unser Zusammenleben bereichern kann und wie wir damit in Arbeit und Bildung umgehen können1302025myown cognition neurodiversity learning llis society workplace https://puma.ub.uni-stuttgart.de/bibtex/210e791a85e2b9de0d19f27ca7c09b69d/mariawirzbergermariawirzberger2025-09-12T20:29:24+02:00myown learning technology performance effort digital feedback UTAUT acceptance academic self-regulation working expectancy <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Maria Wirzberger" itemprop="url" href="/person/1aa0c7aa833c1f78085582a4ea6384eda/author/0"><span itemprop="name">M. Wirzberger</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Laura Bareiß" itemprop="url" href="/person/1aa0c7aa833c1f78085582a4ea6384eda/author/1"><span itemprop="name">L. Bareiß</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Veronika Herbst" itemprop="url" href="/person/1aa0c7aa833c1f78085582a4ea6384eda/author/2"><span itemprop="name">V. Herbst</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Adrian Stock" itemprop="url" href="/person/1aa0c7aa833c1f78085582a4ea6384eda/author/3"><span itemprop="name">A. Stock</span></a></span>, </span> und <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Jule Kembitzky" itemprop="url" href="/person/1aa0c7aa833c1f78085582a4ea6384eda/author/4"><span itemprop="name">J. Kembitzky</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">Acta Psychologica</span>, </em> </span>(<em><span>2025<meta content="2025" itemprop="datePublished"/></span></em>)</span>Fri Sep 12 20:29:24 CEST 2025Acta Psychologica105273Performance expectancy benefits acceptance towards digital support for self-regulation2582025myown learning technology performance effort digital feedback UTAUT acceptance academic self-regulation working expectancy Introduction The persistent prevalence of distractions challenges people's capacities to study and work productively. Digital tools can support focusing on meaningful tasks with features like time tracking, feedback, or rewards. Evidence exists for benefits regarding behavioral focus, distraction management, and motivation, but also for hesitation to use digital support at all. Building on the Unified Theory of Acceptance and Use of Technology (UTAUT), this research explores which factors can foster or hinder the intention to use an exemplary software to support self-regulation. Methods A sample of 96 adult volunteers watched a short introductory video explaining how the software focUS fosters self-regulated studying and working. Subsequently, participants completed an online survey to capture their willingness to use focUS, expected gains and challenges, and individual characteristics. Results Participants expressed stronger intentions to use focUS when they expected increased benefits in performance. By trend, lower levels of expected effort also hinted on stronger intentions to use focUS. Contrary to expectations, participants lacking previous experience with software in the scope described, who anticipated higher effort when using focUS, tended to express stronger intentions to use it. Discussion Taken together, our evidence suggests that highlighting specific performance improvements may encourage the use of digital support for tasks that require self-regulation. Ensuring the use of digital support to be as effortless as possible could provide yet another compelling argument to use it. Particularly for inexperienced users, sparking curiosity for the challenges of the unknown might be a worthwhile strategy to reduce hesitation towards emerging technologies.https://puma.ub.uni-stuttgart.de/bibtex/2b8e91288f1f78f9aad0477bca97182c1/mariawirzbergermariawirzberger2025-09-12T12:21:06+02:00feedback myown focUS cognition learning training eduScrum <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Alina Schmitz-Hübsch" itemprop="url" href="/person/1c080bec330ea1993d3d8ed7a320e6431/author/0"><span itemprop="name">A. Schmitz-Hübsch</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Laura Bareiß" itemprop="url" href="/person/1c080bec330ea1993d3d8ed7a320e6431/author/1"><span itemprop="name">L. Bareiß</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Eva Jahn" itemprop="url" href="/person/1c080bec330ea1993d3d8ed7a320e6431/author/2"><span itemprop="name">E. Jahn</span></a></span>, </span> und <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Maria Wirzberger" itemprop="url" href="/person/1c080bec330ea1993d3d8ed7a320e6431/author/3"><span itemprop="name">M. Wirzberger</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">Frontiers in Computer Science</span>, </em> </span>(<em><span>2025<meta content="2025" itemprop="datePublished"/></span></em>)</span>Fri Sep 12 12:21:06 CEST 2025Frontiers in Computer Science1593889eduScrum meets focUS: A computer-assisted training to promote selfregulation skills in Higher Education72025feedback myown focUS cognition learning training eduScrum Given the ever-evolving demands of the professional world, higher education plays a vital role in equipping students with strategies for self-organized and sustainable skill development. This enables students to quickly and independently adapt to new knowledge and skills throughout their careers. Therefore, it is of the essence to integrate methods that enhance self-regulation skills into our study programs, alongside the instruction of specific subject-matter expertise. Addressing these demands, we introduce a focused training that embeds the assistive software tool focUS into a structured seminar concept, leveraging eduScrum elements and accompanying learning communities. After introducing the results of a pilot evaluation with a small group of interdisciplinary doctoral students, we discuss possibilities of technical and conceptual integration in course curricula and learning counseling in higher education. Taken together, our approach indicates value for empowering future professionals across various domains to unleash their full potential.https://puma.ub.uni-stuttgart.de/bibtex/2f1192f6e4c03016955aa049a78516ee2/mariawirzbergermariawirzberger2025-09-12T12:10:06+02:00fNIRS imported myOwn haptics cognition neurodiversity learning training VR <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Anna Vorreuther" itemprop="url" href="/person/19289c530e18b62601bf4d6060e049555/author/0"><span itemprop="name">A. Vorreuther</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Nektaria Tagalidou" itemprop="url" href="/person/19289c530e18b62601bf4d6060e049555/author/1"><span itemprop="name">N. Tagalidou</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Katharina Lingelbach" itemprop="url" href="/person/19289c530e18b62601bf4d6060e049555/author/2"><span itemprop="name">K. Lingelbach</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Laura Bareiß" itemprop="url" href="/person/19289c530e18b62601bf4d6060e049555/author/3"><span itemprop="name">L. Bareiß</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Maria Wirzberger" itemprop="url" href="/person/19289c530e18b62601bf4d6060e049555/author/4"><span itemprop="name">M. Wirzberger</span></a></span>, </span> und <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Mathias Vukelić" itemprop="url" href="/person/19289c530e18b62601bf4d6060e049555/author/5"><span itemprop="name">M. Vukelić</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">MuC &#039;25: Proceedings of the Mensch und Computer 2025</span>, </em></span><em>Seite <span itemprop="pagination">571-577</span>. </em>(<em><span>31.08.2025<meta content="31.08.2025" itemprop="datePublished"/></span></em>)</span>Fri Sep 12 12:10:06 CEST 2025MuC '25: Proceedings of the Mensch und Computer 2025 08571-577Exploring Neuroadaptivity for Virtual-Reality-Based Cognitive Skill Training in Autistic Adults2025fNIRS imported myOwn haptics cognition neurodiversity learning training VR 31This paper presents a novel adaptive training system that integrates a Virtual Reality (VR) environement, real-time neurofeedback (NF) via functional near-infrared spectroscopy (fNIRS), and tactile stimulation, specifically designed to enhance cognitive skills in autistic adults. Central to this system is an integration platform that enables real-time, synchronised interplay between user behaviours and neurophysiological data. The presented neuroadaptivity loop employs a feedback mechanism that continuously assesses users’ cognitive states through fNIRS, allowing the system to dynamically adjust environmental complexity and send tactile cues based on real-time mental state indicators. This multimodal approach fosters cognitive executive functions relevant for managing everyday situations. By prioritising user-centred design through iterative feedback from autistic individuals, the platform ensures usability and safety while promoting skill transfer from structured training to real-world applications. The implications of this system extend to personalised, adaptive technologies in workplace training, highlighting important considerations regarding user empowerment.https://puma.ub.uni-stuttgart.de/bibtex/2152183f0edd23d3a6b697219f2c6ca41/inspo5inspo52025-01-31T11:03:06+01:00imaging deep sports learning medicine body resonance system composition machine musculoskeletal magnetic <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Saied Ramedani" itemprop="url" href="/person/13afe397a451bce869962d016312aff6a/author/0"><span itemprop="name">S. Ramedani</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Ebru Kelesoglu" itemprop="url" href="/person/13afe397a451bce869962d016312aff6a/author/1"><span itemprop="name">E. Kelesoglu</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Norman Stutzig" itemprop="url" href="/person/13afe397a451bce869962d016312aff6a/author/2"><span itemprop="name">N. Stutzig</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Hendrik Von Tengg‐Kobligk" itemprop="url" href="/person/13afe397a451bce869962d016312aff6a/author/3"><span itemprop="name">H. Von Tengg‐Kobligk</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Keivan Daneshvar Ghorbani" itemprop="url" href="/person/13afe397a451bce869962d016312aff6a/author/4"><span itemprop="name">K. Daneshvar Ghorbani</span></a></span>, </span> und <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Tobias Siebert" itemprop="url" href="/person/13afe397a451bce869962d016312aff6a/author/5"><span itemprop="name">T. Siebert</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">Physiological Reports</span>, </em> </span>(<em><span>Januar 2025<meta content="Januar 2025" itemprop="datePublished"/></span></em>)</span>Fri Jan 31 11:03:06 CET 2025Physiological Reports013Quantification of training‐induced alterations in body composition via automated machine learning analysis of MRI images in the thigh region: A pilot study in young females132025imaging deep sports learning medicine body resonance system composition machine musculoskeletal magnetic AbstractThe maintenance of an appropriate ratio of body fat to muscle mass is essentialfor the preservation of health and performance, as excessive body fat is associatedwith an increased risk of various diseases. Accurate body composition assessmentrequires precise segmentation of structures. In this study we developed a novelautomatic machine learning approach for volumetric segmentation and quantita-tive assessment of MRI volumes and investigated the efficacy of using a machinelearning algorithm to assess muscle, subcutaneous adipose tissue (SAT), and bonevolume of the thigh before and after a strength training. Eighteen healthy, young,female volunteers were randomly allocated to two groups: intervention group(IG) and control group (CG). The IG group followed an 8-week strength endur-ance training plan that was conducted two times per week. Before and after thetraining, the subjects of both groups underwent MRI scanning. The evaluation ofthe image data was performed by a machine learning system which is based ona 3D U-Net- based Convolutional Neural Network. The volumes of muscle, bone,and SAT were each examined using a 2 (GROUP [IG vs. CG]) × 2 (TIME [pre-intervention vs. post-intervention]) analysis of variance (ANOVA) with repeatedmeasures for the factor TIME. The results of the ANOVA demonstrate significantTIME × GROUP interaction effects for the muscle volume (F1,16 = 12.80, p = 0.003,ηP2 = 0.44) with an increase of 2.93% in the IG group and no change in the CG(−0.62%, p = 0.893). There were no significant changes in bone or SAT volumebetween the groups. This study supports the use of artificial intelligence systemsto analyze MRI images as a reliable tool for monitoring training responses onbody composition.https://puma.ub.uni-stuttgart.de/bibtex/2b8f62b41f47a893b42323cc2d2b060da/mariawirzbergermariawirzberger2024-08-25T16:59:26+02:00myown smartphone environment awareness learning llis mobile <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Oliver Stock" itemprop="url" href="/person/162c8d3e404787670b7271c7e0b324269/author/0"><span itemprop="name">O. Stock</span></a></span>, </span> und <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Maria Wirzberger" itemprop="url" href="/person/162c8d3e404787670b7271c7e0b324269/author/1"><span itemprop="name">M. Wirzberger</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">NaturschutzDigital 2023 – Innovative Digitalformate in der Naturschutzbildung</span>, </em></span><em><span itemprop="publisher">Bundesamt für Naturschutz</span>, </em>(<em><span>2024<meta content="2024" itemprop="datePublished"/></span></em>)</span>Sun Aug 25 16:59:26 CEST 2024NaturschutzDigital 2023 – Innovative Digitalformate in der NaturschutzbildungBeeLife – Wildbienen auf dem Weg ins Klassenzimmer2024myown smartphone environment awareness learning llis mobile https://puma.ub.uni-stuttgart.de/bibtex/2b3f90b8922236ccac248f783843a3c1b/mariawirzbergermariawirzberger2023-09-23T10:00:44+02:00myown simtech cognition learning performance imported emotion instruction personality llis <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Alina Schmitz-Hübsch" itemprop="url" href="/person/124d07f98bb72c6d80a0bd07110ff47c6/author/0"><span itemprop="name">A. Schmitz-Hübsch</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Ron Becker" itemprop="url" href="/person/124d07f98bb72c6d80a0bd07110ff47c6/author/1"><span itemprop="name">R. Becker</span></a></span>, </span> und <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Maria Wirzberger" itemprop="url" href="/person/124d07f98bb72c6d80a0bd07110ff47c6/author/2"><span itemprop="name">M. Wirzberger</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">Adaptive Instructional Systems. HCII 2023. Lecture Notes in Computer Science</span>, </em><em><span itemprop="publisher">Springer</span>, </em></span>(<em><span>2023<meta content="2023" itemprop="datePublished"/></span></em>)</span>Sat Sep 23 10:00:44 CEST 2023Adaptive Instructional Systems. HCII 2023. Lecture Notes in Computer Science60–75Personality Traits in the Emotion-Performance-Relationship in Intelligent Tutoring Systems2023myown simtech cognition learning performance imported emotion instruction personality llis Affective Tutoring Systems (ATS) detect and mitigate critical emotional learner states with the aim of providing individualized support. In tutoring systems for safety-critical work environments, students are trained to achieve and maintain high performance, therefore an ATS should be capable of identifying critical emotional states hindering performance. Interindividual differences in the emotion-performance-relationship can be considered by using the ARC categorization system. The present contribution aims at developing a questionnaire-based method of classifying new learners to the categories. To that end, we investigated differences in personality traits between the different categories. In an airspace surveillance task, we measured performance, emotional valence, emotional arousal, and personality traits in N = 50 subjects. Results showed that a positive valence-performance-relationship, compared to a negative valence-performance-relationship, is associated with higher Neuroticism, lower Conscientiousness, and lower Openness to experience. There were no significant differences in the traits Agreeableness and Extraversion. Based on these results, a future ATS for safety-critical work environments could classify new learners in the ARCs using self-report data and thus dispense with physiological sensors. Thereby, user state diagnosis and evaluation for high performance is possible, setting the ground for an ATS adapting to critical emotional learner states.https://puma.ub.uni-stuttgart.de/bibtex/29e4c486ece9d04659e8d9fbcc722ec5c/mariawirzbergermariawirzberger2022-10-20T10:52:15+02:00myown reflection instruction AI learning teaching <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Tabea Berberena" itemprop="url" href="/person/14212f20e345f76e406a0504889efee7c/author/0"><span itemprop="name">T. Berberena</span></a></span>, </span> und <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Maria Wirzberger" itemprop="url" href="/person/14212f20e345f76e406a0504889efee7c/author/1"><span itemprop="name">M. Wirzberger</span></a></span></span>. </span><span class="additional-entrytype-information">(<em><span>2022<meta content="2022" itemprop="datePublished"/></span></em>)</span>Thu Oct 20 10:52:15 CEST 2022Reflection on intelligent systems: Towards a cross-disciplinary definitionEmbedding reflective learning opportunities in teaching about intelligent systems2022myown reflection instruction AI learning teaching https://puma.ub.uni-stuttgart.de/bibtex/2ddb88e415cf97c13a1b0b3116bac9e0a/mariawirzbergermariawirzberger2022-08-03T08:22:39+02:00myown environment learning llis classroom education technology sustainability <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Julia Mönch" itemprop="url" href="/person/1028dec02daeefc3ec58085def5724008/author/0"><span itemprop="name">J. Mönch</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Adrian Stock" itemprop="url" href="/person/1028dec02daeefc3ec58085def5724008/author/1"><span itemprop="name">A. Stock</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Judith Baatz" itemprop="url" href="/person/1028dec02daeefc3ec58085def5724008/author/2"><span itemprop="name">J. Baatz</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Felix Krieglstein" itemprop="url" href="/person/1028dec02daeefc3ec58085def5724008/author/3"><span itemprop="name">F. Krieglstein</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Oliver Stock" itemprop="url" href="/person/1028dec02daeefc3ec58085def5724008/author/4"><span itemprop="name">O. Stock</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Markus Suren" itemprop="url" href="/person/1028dec02daeefc3ec58085def5724008/author/5"><span itemprop="name">M. Suren</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Günter Daniel Rey" itemprop="url" href="/person/1028dec02daeefc3ec58085def5724008/author/6"><span itemprop="name">G. Rey</span></a></span>, </span> und <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Maria Wirzberger" itemprop="url" href="/person/1028dec02daeefc3ec58085def5724008/author/7"><span itemprop="name">M. Wirzberger</span></a></span></span>. </span><span class="additional-entrytype-information">(<em><span>2022<meta content="2022" itemprop="datePublished"/></span></em>)</span>Wed Aug 03 08:22:39 CEST 2022“Wild sisters” meet app: Connecting virtual and real worlds to foster environmental awareness in classroom settings2022myown environment learning llis classroom education technology sustainability Bees are significant contributors to our diverse flora, as they pollinate plants and trees. In addition to honeybees, their “wild sisters” provide further support with this task. There are more than 560 different species of wild bees known in Germany alone. Unlike honeybees, they lack protective beehives and the care of beekeepers. More than half of them is endangered or already became extinct. Potential consequences of this development are far reaching and devastating for the diversity of our ecosystem. As wild bees play such a crucial role, the question emerges why we do not protect them adequately. The answer is rather simple: Most people lack knowledge about these species, their living conditions, and the tremendous impact on our lives. In this talk, we introduce a project that has the goal to change this situation and build a sense of responsibility already at an early stage in life. A mobile application for classroom settings is developed and integrated into project workshops, inviting students on an insightful journey into the world of wild bees. By combining hands-on environmental actions with virtual game elements, this approach strives to sensitize students at a young age to the dramatic consequences if wild bees were to become extinct. The project follows a child-centered design process and builds on findings from multimedia learning research, for example, on intelligent agents that accompany learning and provide feedback and support. The talk will present results from an evaluation of the combined concept in school contexts and discuss potential future directions.https://puma.ub.uni-stuttgart.de/bibtex/24d70cb60b62d206c9162e8167351306e/mariawirzbergermariawirzberger2022-08-03T08:19:57+02:00feedback myown cognition AI self-regulation learning llis <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Maria Wirzberger" itemprop="url" href="/person/1271134d8d8c4d3674c3166addc1b99e7/author/0"><span itemprop="name">M. Wirzberger</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Anastasia Lado" itemprop="url" href="/person/1271134d8d8c4d3674c3166addc1b99e7/author/1"><span itemprop="name">A. Lado</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Caroline Scheiger" itemprop="url" href="/person/1271134d8d8c4d3674c3166addc1b99e7/author/2"><span itemprop="name">C. Scheiger</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Adrian Stock" itemprop="url" href="/person/1271134d8d8c4d3674c3166addc1b99e7/author/3"><span itemprop="name">A. Stock</span></a></span>, </span> und <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Francesca Zermiani" itemprop="url" href="/person/1271134d8d8c4d3674c3166addc1b99e7/author/4"><span itemprop="name">F. Zermiani</span></a></span></span>. </span><span class="additional-entrytype-information">(<em><span>2022<meta content="2022" itemprop="datePublished"/></span></em>)</span>Wed Aug 03 08:19:57 CEST 2022Augmented learning contexts: Leveraging augmented technologies to foster self-regulation in everyday life2022feedback myown cognition AI self-regulation learning llis The omnipresence of distracting information constantly challenges our limited attentional resources. Consequently, approaching educational goals effectively and concentrating on them often becomes difficult for learners. Looking at existing training tools to strengthen executive functions, we often notice the use of artificial tasks and settings that limit the transferability of the acquired skills to everyday life situations. Addressing this gap, the talk introduces an example of how people can be supported to set goals, implement periods of focused work, and integrate a meaningful break management by using an attention training software during regular study and work activities. The computer-based intervention influences the entire lifecycle of self-regulated learning and can easily become part of daily computer use. It enables users to redefine their existing goals into training tasks and thus motivates them to achieve sustainable training results. As its core, the software has an intelligent feedback mechanism that visually discloses the value of staying focused against getting distracted, building on a model of the expected value of cognitive control. Results from field experiments already indicate the benefit of this approach over a control condition, in particular related to task-specific learning. The talk will take a more fine-grained look at patterns of distractibility across different task settings and discuss related benefits of embedding this novel approach to executive functions training across formal and informal learning contexts and workplace scenarios.https://puma.ub.uni-stuttgart.de/bibtex/200a69b89255cfb3b24a69d6a18430d9c/mariawirzbergermariawirzberger2022-08-03T08:17:26+02:00myown augmented instruction cognition learning llis <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Maria Wirzberger" itemprop="url" href="/person/19b8b3bf26dafe977876590c764bc512c/author/0"><span itemprop="name">M. Wirzberger</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Christian Scharinger" itemprop="url" href="/person/19b8b3bf26dafe977876590c764bc512c/author/1"><span itemprop="name">C. Scharinger</span></a></span>, </span> und <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Manuel Ninaus" itemprop="url" href="/person/19b8b3bf26dafe977876590c764bc512c/author/2"><span itemprop="name">M. Ninaus</span></a></span></span>. </span><span class="additional-entrytype-information">(<em><span>2022<meta content="2022" itemprop="datePublished"/></span></em>)</span>Wed Aug 03 08:17:26 CEST 2022Augmented learning – An emerging field in instructional research? 2022myown augmented instruction cognition learning llis Twenty-first century learning is characterized by an increasing number of augmented learning environments (e.g., multimedia, educational games, virtual reality, intelligent companions). The general idea is to support learning by integrating elements or mechanisms to optimize learning outcomes and experiences. While these augmented learning scenarios seem promising, effects on learning appear heterogeneous. Therefore, a better understanding of underlying mechanisms is crucial. For instance, new interactive features and technologies might increase learners’ motivation and interest in the topic but at the same time they are prone to overstrain their cognitive resources. Importantly, we can investigate these learning situations by augmenting them with process measures (e.g., EEG, eye tracking, fMRI, log files) or leverage data mining techniques to analyze large educational datasets, allowing a more fine-grained analysis of the learning process. Modern technologies such as virtual reality devices or game engines advance how learning content can be presented. Computer-based technology enables us to augment learning contexts and bring intelligent companions into individual learners’ daily lives. In the current symposium, we address important factors of learning, i.e., working memory, attention, emotions, and self-regulation, with augmented measures, materials, and contexts. In particular, studies on multimedia, educational games, virtual reality, and intelligent companions will be presented. Consequently, our symposium provides insights into late-breaking research innovations in the field of augmented learning. It also critically discusses potential limitations and downsides of this field of research to pave the way for a future research agenda.https://puma.ub.uni-stuttgart.de/bibtex/2e36b4e8e15fde2a2cd5880a2c346dc45/mariawirzbergermariawirzberger2022-04-14T07:10:54+02:00mind-wandering myown instruction cognition learning attention video <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Francesca Zermiani" itemprop="url" href="/person/1f68fd5dc59da2486b709bbe6c5a434d8/author/0"><span itemprop="name">F. Zermiani</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Andreas Bulling" itemprop="url" href="/person/1f68fd5dc59da2486b709bbe6c5a434d8/author/1"><span itemprop="name">A. Bulling</span></a></span>, </span> und <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Maria Wirzberger" itemprop="url" href="/person/1f68fd5dc59da2486b709bbe6c5a434d8/author/2"><span itemprop="name">M. Wirzberger</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">2022 Symposium on Eye Tracking Research and Applications (ETRA &#039;22), June 8–11, 2022, Seattle, WA, USA</span>, </em></span><em>New York, NY, USA, </em><em><span itemprop="publisher">ACM</span>, </em>(<em><span>2022<meta content="2022" itemprop="datePublished"/></span></em>)</span>Thu Apr 14 07:10:54 CEST 2022New York, NY, USA2022 Symposium on Eye Tracking Research and Applications (ETRA '22), June 8–11, 2022, Seattle, WA, USAMind wandering trait-level tendencies during lecture viewing: A pilot study2022mind-wandering myown instruction cognition learning attention video Mind wandering (MW) is defined as a shift of attention to task-unrelated internal thoughts that is pervasive and disruptive for learning performance. Current state-of-the-art gaze-based attention-aware intelligent systems are capable of detecting MW from eye movements and delivering interventions to mitigate its negative effects. However, the beneficial functions of MW and its trait-level tendency, defined as the content of MW experience, are still largely neglected by these systems. In this pilot study, we address the questions of whether different MW trait-level tendencies can be detected through off-screen fixations’ frequency and duration and blink rate during a lecture viewing task. We focus on prospective planning and creative problem-solving as two of the main MW trait-level tendencies. Despite the non-significance, the descriptive values show a higher frequency and duration of off-screen fixations, but lower blink rate, in the creative problem-solving MW condition. Interestingly, we do find a highly significant correlation between MW level and engagement scores in the prospective planning MW group. Potential explanations for the observed results are discussed. Overall, these findings represent a preliminary step towards the development of more accurate and adaptive learning technologies, and call for further studies on MW trait-level tendency detection.https://puma.ub.uni-stuttgart.de/bibtex/24c4e8721f29b1ea5976a6d62d1fd7c1e/mariawirzbergermariawirzberger2021-11-25T21:00:30+01:00myown schools survival learning analysis COVID-19 <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Markus Wolfgang Hermann Spitzer" itemprop="url" href="/person/137155827da23b554fdcc78e1a52f3cc2/author/0"><span itemprop="name">M. Spitzer</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Raphael Gutsfeld" itemprop="url" href="/person/137155827da23b554fdcc78e1a52f3cc2/author/1"><span itemprop="name">R. Gutsfeld</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Maria Wirzberger" itemprop="url" href="/person/137155827da23b554fdcc78e1a52f3cc2/author/2"><span itemprop="name">M. Wirzberger</span></a></span>, </span> und <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Korbinian Moeller" itemprop="url" href="/person/137155827da23b554fdcc78e1a52f3cc2/author/3"><span itemprop="name">K. Moeller</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">Trends in Neuroscience and Education</span>, </em> </span>(<em><span>Dezember 2021<meta content="Dezember 2021" itemprop="datePublished"/></span></em>)</span>Thu Nov 25 21:00:30 CET 2021Trends in Neuroscience and Education12100168Evaluating students' engagement with an online learning environment during and after {COVID}-19 related school closures: A survival analysis approach252021myown schools survival learning analysis COVID-19 Evaluating students’ engagement with an online learning environment during and after COVID-19 related school closures: A survival analysis approach - ScienceDirecthttps://puma.ub.uni-stuttgart.de/bibtex/21cb8221179fc2538bce7d72f3dfb7759/mariawirzbergermariawirzberger2021-06-06T17:23:54+02:00myown reflection bias stereotype learning education higher <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Tabea Berberena" itemprop="url" href="/person/142aecd5871697470ff4ade19584d946d/author/0"><span itemprop="name">T. Berberena</span></a></span>, </span> und <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Maria Wirzberger" itemprop="url" href="/person/142aecd5871697470ff4ade19584d946d/author/1"><span itemprop="name">M. Wirzberger</span></a></span></span>. </span><span class="additional-entrytype-information">(<em><span>2021<meta content="2021" itemprop="datePublished"/></span></em>)</span>Sun Jun 06 17:23:54 CEST 2021Unveiling unconscious biases and stereotypes in students: The necessity of self-reflection in Higher Education2021myown reflection bias stereotype learning education higher Preparing the next generation for an ever-changing environment is of utmost importance in Higher Education. Though cultural diversity is highly prevalent in modern societies, (implicit) biases, stereotypes and racism maintain a persistent yet mostly overlooked part of everyday life. Many students are not aware of their biases. Hence, it is imperative for them to undergo a critical self-reflection process about their beliefs and (unconscious) biases. To induce this process, raise awareness and confront them with potential (unconscious) biases and stereotypes, 404 university students in teacher training and vocational education completed an Implicit Association Test (IAT) on skin color before watching a lecture discussing biases and stereotypes. The preliminary results show a variety of reactions after taking the test, ranging from denial and anger to discomfort and surprise. We will discuss possibilities to support students in leveraging the resulting cognitive dissonance as an opportunity to begin their individual self-reflection process.https://puma.ub.uni-stuttgart.de/bibtex/24b1265f226d59f31e7fa5f7777403abe/mariawirzbergermariawirzberger2021-04-07T12:39:48+02:00myown diversity reflection culture bias stereotype learning classroom <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Tabea Berberena" itemprop="url" href="/person/1205f5cc41f48435cc8b510bb4a5b35fb/author/0"><span itemprop="name">T. Berberena</span></a></span>, </span> und <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Maria Wirzberger" itemprop="url" href="/person/1205f5cc41f48435cc8b510bb4a5b35fb/author/1"><span itemprop="name">M. Wirzberger</span></a></span></span>. </span><span class="additional-entrytype-information">(<em><span>2021<meta content="2021" itemprop="datePublished"/></span></em>)</span>Wed Apr 07 12:39:48 CEST 2021EARLI 2021 - OnlineBringing Thiagi to the classroom: Reducing stereotype-threat by promoting reflection in CRT2021myown diversity reflection culture bias stereotype learning classroom Culture and ethnicity influence how a person learns and views the world. Experiences at home influence students’ learning fundamentally. However, cultural diversity in classrooms as well as issues such as stereotypes and biases have yet to be addressed in the German education system. School materials i.e., do many times not reflect the cultural diversity in modern classrooms, portraying and promoting stereotypes and biases. These (unconscious) biases are at the center of the problem and have yet to gain the attention and importance they deserve. Since stereotypes and biases are learned constructs, it is of utmost importance to provide tools to unlearn/relearn incorrect constructs and form new synapsis. The existing challenges have thus far failed to be addressed by generic teaching techniques and pedagogy. A new strategy and teaching approach in education is needed to address these issues in an attempt to reduce the current achievement gaps across students of different cultural backgrounds and to incorporate experiences of all students in classroom interactions. In this workshop, we will introduce an interactive teaching and learning approach to promote reflection in culturally responsive teaching (CRT). The instructional design method of Thiagi will serve as an innovative tool to successfully implement CRT, raise awareness of existing stereotypes/ (unconscious) biases, and thus model a way to reduce stereotype-threat. By integrating diversity in form of CRT in the curriculum, we can fundamentally change existing patterns and enable every student to understand and connect to academic content.https://puma.ub.uni-stuttgart.de/bibtex/2a890e58a66f50878855f0536ab5f019c/mariawirzbergermariawirzberger2021-04-07T12:37:01+02:00myown AI self-regulation learning attention classroom <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Maria Wirzberger" itemprop="url" href="/person/17b273695105a95d40f5ea507bdf31191/author/0"><span itemprop="name">M. Wirzberger</span></a></span></span>. </span><span class="additional-entrytype-information">(<em><span>2021<meta content="2021" itemprop="datePublished"/></span></em>)</span>Wed Apr 07 12:37:01 CEST 2021EARLI 2021 - OnlineACTrain@School: Can we bring AI to the classroom to foster self-regulated learning?2021myown AI self-regulation learning attention classroom Learning requires a multitude of metacognitive activities that support knowledge acquisition and direct the learning process. These include selecting and planning goals, applying, observing and evaluating learning strategies as well as regulatory efforts required for goal achievement. We introduce an example of how learners can be supported to set goals, implement periods of focused work and integrate a meaningful break management by using the AI-based training software ACTrain. Metacognitive feedback based on principles of machine learning conveys the value of staying focused on goal-related activities. Pilot results already indicate positive effects of the presented approach and suggest further investigation. We will explore potentials for integrating such approach in school settings and how this could affect the role of teachers.https://puma.ub.uni-stuttgart.de/bibtex/2e3939e795d8551782e3aa908fc5829ac/mariawirzbergermariawirzberger2021-04-07T12:35:02+02:00myown school AI self-regulation learning attention classroom <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Maria Wirzberger" itemprop="url" href="/person/1f1f9ed53ea63e8c932811ebbca0f9583/author/0"><span itemprop="name">M. Wirzberger</span></a></span>, </span> und <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Madeleine Schwarz" itemprop="url" href="/person/1f1f9ed53ea63e8c932811ebbca0f9583/author/1"><span itemprop="name">M. Schwarz</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">Bildung und Erziehung</span>, </em> </span>(<em><span>2021<meta content="2021" itemprop="datePublished"/></span></em>)</span>Wed Apr 07 12:35:02 CEST 2021Bildung und Erziehung280-295Förderung selbstregulierten Lernens durch ein KI-gestütztes Training742021myown school AI self-regulation learning attention classroom Lernen erfordert vielfältige metakognitive Aktivitäten, die den Wissensaufbau und die Steuerung des eigenen Lernprozesses unterstützen. Dazu zählen die Auswahl und Planung von Zielen, die Anwendung, Beobachtung und Bewertung von Lernstrategien sowie regulierende Eingriffe zum Erreichen gesetzter Ziele. Der Artikel zeigt beispielhaft auf, wie eine KI-gestützte Trainingssoftware Lernende dabei fördern kann, sich Ziele zu setzen, Phasen fokussierten Arbeitens umzusetzen und ein sinnvolles Pausenmanagement einzubinden. Metakognitives Feedback bildet aufbauend auf Prinzipien des maschinellen Lernens den Wert zielgerichteten Handelns ab. In Pilotbefunden zeigen sich bereits erste positive Effekte dieses Ansatzes, die eine weitere Exploration nahelegen. Basierend darauf wird eine mögliche curriculare Einbindung im Lernfeld Schule sowie Implikationen für die Rolle der Lehrkräfte diskutiert.https://puma.ub.uni-stuttgart.de/bibtex/237e3d17a5d1cb742a6d9f551a3c50d0d/mariawirzbergermariawirzberger2021-02-07T16:45:26+01:00myown multimedia instruction cognition load learning attention <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Maria Wirzberger" itemprop="url" href="/person/1985d50c4ff1c05215b5a485b3e874c9b/author/0"><span itemprop="name">M. Wirzberger</span></a></span></span>. </span><span class="additional-entrytype-information">(<em><span>2012<meta content="2012" itemprop="datePublished"/></span></em>)</span>Sun Feb 07 16:45:26 CET 2021Experimentelle Induktion beeinträchtigter Aufmerksamkeit im Kontext des seductive detail Effekts2012myown multimedia instruction cognition load learning attention Die vorliegende Arbeit untersucht ausgehend von der Cognitive Theory of Multimedia Learning (CTML) einen aufmerksamkeitsbezogenen Erklärungsansatz für den seductive detail Effekt. Dieser Effekt resultiert aus dem Einfügen interessanter, jedoch irrelevanter Informationen in einen Lerntext, die die Lernleistung beeinträchtigen. Im Besonderen steht hier die Hypothese im Fokus, dass sich seductive details stärker auswirken, wenn bereits eine Beeinträchtigung der Aufmerksamkeit vorliegt. Im Rahmen einer experimentellen Erhebung mit 53 Studierenden wurde anhand eines 2x2-faktoriellen, multivariaten Designs die Anwesenheit von seductive details (durch seduktive Textpassagen), sowie be- einträchtigter Aufmerksamkeit (durch die Einblendung ablenkender Systemmit- teilungen), gezielt manipuliert und deren Effekt auf die Behaltens- und Verstehensleistung, sowie die Lernzeit erfasst. In den Analysen zeigte sich eine signifikante Verlängerung der Lernzeit durch das Einfügen seduktiver Textpassagen, und darüber hinaus wurde auch ein moderierender Einfluss des bestehenden Aufmerksamkeitsniveaus deutlich. Weder die Behaltens- noch die Verstehensleistung verringerte sich jedoch signifikant durch das Hinzufügen von seductive details oder die Induktion beeinträchtigter Aufmerksamkeit, und auch eine signifikante Wechselwirkung zwischen beiden Aspekten wurde nicht deutlich. Daher wird abschließend die Relevanz komplexer statistischer Analyseverfahren zur weiteren Erhellung der zugrundeliegenden Wirkmechanismen diskutiert.