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Detecting mistakes in CPR training with multimodal data and neural networks
Di Mitri, Daniele; Schneider, Jan; Specht, Marcus; Drachsler, Hendrik
Journal Article
| In: Sensors | 2019
39363 Endnote
Author(s):
Di Mitri, Daniele; Schneider, Jan; Specht, Marcus; Drachsler, Hendrik
Title:
Detecting mistakes in CPR training with multimodal data and neural networks
In:
Sensors, 19 (2019) 14, S. 3099
DOI:
10.3390/s19143099
URL:
https://www.mdpi.com/1424-8220/19/14/3099
Publication Type:
3a. Beiträge in begutachteten Zeitschriften; Beitrag in Sonderheft
Language:
Englisch
Keywords:
Neuropsychologie; Psychomotorik; Praktisches Lernen; Student; Medizin; Lernprozess; Datenanalyse; Computerprogramm; Messung; Fehler; Feedback; Automatisierung; Tutorensystem; Validität; Indikator
Abstract:
This study investigated to what extent multimodal data can be used to detect mistakes during Cardiopulmonary Resuscitation (CPR) training. We complemented the Laerdal QCPR ResusciAnne manikin with the Multimodal Tutor for CPR, a multi-sensor system consisting of a Microsoft Kinect for tracking body position and a Myo armband for collecting electromyogram information. We collected multimodal data from 11 medical students, each of them performing two sessions of two-minute chest compressions (CCs). We gathered in total 5254 CCs that were all labelled according to five performance indicators, corresponding to common CPR training mistakes. Three out of five indicators, CC rate, CC depth and CC release, were assessed automatically by the ReusciAnne manikin. The remaining two, related to arms and body position, were annotated manually by the research team. We trained five neural networks for classifying each of the five indicators. The results of the experiment show that multimodal data can provide accurate mistake detection as compared to the ResusciAnne manikin baseline. We also show that the Multimodal Tutor for CPR can detect additional CPR training mistakes such as the correct use of arms and body weight. Thus far, these mistakes were identified only by human instructors. Finally, to investigate user feedback in the future implementations of the Multimodal Tutor for CPR, we conducted a questionnaire to collect valuable feedback aspects of CPR training. (DIPF/Orig.)
DIPF-Departments:
Informationszentrum Bildung
Formative assessment in mathematics. Mediated by feedback's perceived usefulness and students' […]
Rakoczy, Katrin; Pinger, Petra; Hochweber, Jan; Klieme, Eckhard; Schütze, Birgit; Besser, Michael
Journal Article
| In: Learning and Instruction | 2019
38172 Endnote
Author(s):
Rakoczy, Katrin; Pinger, Petra; Hochweber, Jan; Klieme, Eckhard; Schütze, Birgit; Besser, Michael
Title:
Formative assessment in mathematics. Mediated by feedback's perceived usefulness and students' self-efficacy
In:
Learning and Instruction, 60 (2019) , S. 154-165
DOI:
10.1016/j.learninstruc.2018.01.004
URL:
https://www.sciencedirect.com/science/article/pii/S0959475217302189?via%3Dihub
Publication Type:
3a. Beiträge in begutachteten Zeitschriften; Aufsatz (keine besondere Kategorie)
Language:
Englisch
Keywords:
Längsschnittuntersuchung; Hessen; Deutschland; Mathematikunterricht; Schülerleistung; Leistungsbeurteilung; Feedback; Wirkung; Interesse; Lernerfolg; Selbstwirksamkeit; Schüler; Wahrnehmung; Schuljahr 09; Realschule; Lernprozess; Lernziel; Lernstrategie; Leistungstest
Abstract (english):
Although formative assessment is regarded as a promising way to improve teaching and learning, there is considerable need for research on precisely how it influences student learning. In this study we developed and implemented a formative assessment intervention for mathematics instruction and investigated whether it had effects on students' interest and achievement directly and via students' perception of the usefulness of the feedback and their self-efficacy. We conducted a cluster randomized field trial with pretest and posttest. The 26 participating classes were randomly assigned to a control group or the intervention group. Results of path analyses indicate that feedback was perceived as more useful in the formative assessment condition, self-efficacy was greater, and interest tended to increase; learning progress did not differ between the groups. The assumed indirect effects were partly confirmed: formative assessment showed an indirect effect on interest via its perceived usefulness. (DIPF/Orig.)
DIPF-Departments:
Bildungsqualität und Evaluation
Dancing salsa with machines - filling the gap of dancing learning solutions
Romano, Gianluca; Schneider, Jan; Drachsler, Hendrik
Journal Article
| In: Sensors | 2019
39401 Endnote
Author(s):
Romano, Gianluca; Schneider, Jan; Drachsler, Hendrik
Title:
Dancing salsa with machines - filling the gap of dancing learning solutions
In:
Sensors, 19 (2019) 17, S. 3661
DOI:
10.3390/s19173661
URN:
urn:nbn:de:0111-pedocs-189614
URL:
https://nbn-resolving.org/urn:nbn:de:0111-pedocs-189614
Publication Type:
3a. Beiträge in begutachteten Zeitschriften; Beitrag in Sonderheft
Language:
Englisch
Keywords:
Tanz; Musik; Lernprozess; Analyse; Feedback; Online; Rhythmus; Verstehen; Coaching; Computerunterstütztes Lernen; Emotionaler Zustand; Gestik; Mimik; Tool; Evaluation
Abstract (english):
Dancing is an activity that positively enhances the mood of people that consists of feeling the music and expressing it in rhythmic movements with the body. Learning how to dance can be challenging because it requires proper coordination and understanding of rhythm and beat. In this paper, we present the first implementation of the Dancing Coach (DC), a generic system designed to support the practice of dancing steps, which in its current state supports the practice of basic salsa dancing steps. However, the DC has been designed to allow the addition of more dance styles. We also present the first user evaluation of the DC, which consists of user tests with 25 participants. Results from the user test show that participants stated they had learned the basic salsa dancing steps, to move to the beat and body coordination in a fun way. Results also point out some direction on how to improve the future versions of the DC. (DIPF/Orig.)
DIPF-Departments:
Informationszentrum Bildung
Beyond reality - extending a presentation trainer with an immersive VR module
Schneider, Jan; Romano, Gianluca; Drachsler, Hendrik
Journal Article
| In: Sensors | 2019
39390 Endnote
Author(s):
Schneider, Jan; Romano, Gianluca; Drachsler, Hendrik
Title:
Beyond reality - extending a presentation trainer with an immersive VR module
In:
Sensors, 19 (2019) 16, S. 3457
DOI:
10.3390/s19163457
URN:
urn:nbn:de:0111-pedocs-188758
URL:
https://nbn-resolving.org/urn:nbn:de:0111-pedocs-188758
Publication Type:
3a. Beiträge in begutachteten Zeitschriften; Beitrag in Sonderheft
Language:
Englisch
Keywords:
Computerunterstütztes Lernen; Vortrag; Präsentation; Fertigkeit; Training; Lernprozess; Lernumgebung; Feedback; Virtuelle Realität; Tool; Evaluation; Test; Fragebogen
Abstract (english):
The development of multimodal sensor-based applications designed to support learners with the improvement of their skills is expensive since most of these applications are tailor-made and built from scratch. In this paper, we show how the Presentation Trainer (PT), a multimodal sensor-based application designed to support the development of public speaking skills, can be modularly extended with a Virtual Reality real-time feedback module (VR module), which makes usage of the PT more immersive and comprehensive. The described study consists of a formative evaluation and has two main objectives. Firstly, a technical objective is concerned with the feasibility of extending the PT with an immersive VR Module. Secondly, a user experience objective focuses on the level of satisfaction of interacting with the VR extended PT. To study these objectives, we conducted user tests with 20 participants. Results from our test show the feasibility of modularly extending existing multimodal sensor-based applications, and in terms of learning and user experience, results indicate a positive attitude of the participants towards using the application (PT+VR module). (DIPF/Orig.)
DIPF-Departments:
Informationszentrum Bildung
Künstliche Intelligenz in der Bildung. Ihr Potenzial und der Mythos des Lehrkraftroboters
Zehner, Fabian
Journal Article
| In: Schulmanagement | 2019
39117 Endnote
Author(s):
Zehner, Fabian
Title:
Künstliche Intelligenz in der Bildung. Ihr Potenzial und der Mythos des Lehrkraftroboters
In:
Schulmanagement, 50 (2019) 2, S. 8-12
URN:
urn:nbn:de:0111-pedocs-175625
URL:
http://nbn-resolving.org/urn:nbn:de:0111-pedocs-175625
Publication Type:
3b. Beiträge in weiteren Zeitschriften; praxisorientiert
Language:
Deutsch
Keywords:
Datenanalyse; Anwendungsbeispiel; Künstliche Intelligenz; Bildung; Begriff; Definition; Computer; Daten; Roboter; Computerunterstütztes Lernen; Lernumgebung; Anpassung; Computerprogramm; Medieneinsatz; Einflussfaktor; Lernprozess; Fernunterricht; Kooperatives Lernen; Leistungsbeurteilung; Automatisierung
Abstract:
Was kann künstliche Intelligenz wirklich? Und wie können wir sie als gewinnbringend im Bildungssektor einsetzen? Sollten wir Angst davor haben, dass der Klassenlehrer unserer Enkelkinder in wenigen Jahrzehnten eduBot heißen könnte? dieser Beitrag beleuchtet anhand verschiedener Anwendungsbeispiele, welches Potenzial tatsächlich hinter künstlicher Intelligenz streckt. (DIPF/Orig.)
DIPF-Departments:
Bildungsqualität und Evaluation
Information literacy and its interplay with AI
Heck, Tamara; Weisel, Luzian; Kullmann, Sylvia
Book Chapter
| Aus: DIPF | Leibniz-Institut für Bildungsforschung und Bildungsinformation (Hrsg.): Proceedings of Conference on Learning Information Literacy across the Globe, Frankfurt am Main, Germany, 10th of May 2019 | Frankfurt am Main: DIPF | Leibniz‐Institut für Bildungsforschung und Bildungsinformation | 2019
39306 Endnote
Author(s):
Heck, Tamara; Weisel, Luzian; Kullmann, Sylvia
Title:
Information literacy and its interplay with AI
In:
DIPF | Leibniz-Institut für Bildungsforschung und Bildungsinformation (Hrsg.): Proceedings of Conference on Learning Information Literacy across the Globe, Frankfurt am Main, Germany, 10th of May 2019, Frankfurt am Main: DIPF | Leibniz‐Institut für Bildungsforschung und Bildungsinformation, 2019 , S. 2
URL:
https://informationliteracy.eu/conference/assets/papers/LILG-2019_Weisel-Heck_IL-interplay-AI.pdf
Publication Type:
4. Beiträge in Sammelbänden; Tagungsband/Konferenzbeitrag/Proceedings
Language:
Englisch
Keywords:
Informationskompetenz; Technologie; Digitalisierung; Literalität; Künstliche Intelligenz; Lernprozess; Unterstützung
Abstract:
Information literacy (IL) [1] - and similarly digital literacy [2, 3] - want to convey skills to handle information and data, its use and the creation of new information and services. It emphasizes to teach competencies that enable learners to adapt to new environments and thus foster life-long learning. Artificial intelligence systems (AI) enter all kinds of areas, specifically the educational sector on all levels. For example, learning analytics and learning supportive services are established. Learners might see the opportunities of those services that promise to foster individual learning and skill development. At the same time, they need to develop novel kinds of literacy to understand and to apply AI. Thus, IL teaching and literacy frameworks need to consider an adaptation to recent changes that come with AI. Our contribution wants to start a discussion within the IL expert field on how IL teaching needs to prepare learners for the new era of AI. We will discuss if IL teaching frameworks need to be adapted to foster AI literacy and moreover, how IL teaching concept can benefit from developments in AI. Based on a scoping review in AI in education, we will introduce current ideas of AI technology and applications and discuss them in relation to IL teaching schemes [2]. Following up the dialog of our IL working group [4], we want to contribute to current discussions on AI in education and the potential influence it might have on IL teaching, and reversely. (DIPF/Orig.)
DIPF-Departments:
Informationszentrum Bildung
Motivation und Volition im Schulalter. Einführung und Überblick
Gaspard, Hanna; Hasselhorn, Marcus; Nagengast, Benjamin; Trautwein, Ulrich
Book Chapter
| Aus: Gaspard, Hanna; Trautwein, Ulrich; Hasselhorn, Marcus (Hrsg.): Diagnostik und Förderung von Motivation und Volition | Göttingen: Hogrefe | 2019
39083 Endnote
Author(s):
Gaspard, Hanna; Hasselhorn, Marcus; Nagengast, Benjamin; Trautwein, Ulrich
Title:
Motivation und Volition im Schulalter. Einführung und Überblick
In:
Gaspard, Hanna; Trautwein, Ulrich; Hasselhorn, Marcus (Hrsg.): Diagnostik und Förderung von Motivation und Volition, Göttingen: Hogrefe, 2019 (Tests und Trends in der pädagogisch-psychologischen Diagnostik, 17), S. 1-18
Publication Type:
4. Beiträge in Sammelwerken; Sammelband (keine besondere Kategorie)
Language:
Deutsch
Keywords:
Schüler; Motivation; Handlung; Wille; Theorie; Erwartung; Wert; Ziel; Selbstregulation; Lernprozess; Diagnostik; Förderung
Abstract:
Motivation und Volition spielen eine entscheidende Rolle für schulisches Lernen. Sie umfassen eine breite Palette an Konstrukten, die im Lernkontext relevant sind. Da motivationale wie auch volitionale Merkmale stark zwischen Situationen und Personen variieren, ist zwischen aktueller Motivation und Volition in der Lernsituation auf der einen Seite und motivationalen und volitionalen Dispositionen auf der anderen Seite zu unterscheiden. Anhand des Rubikon-Modells der Handlungsphasen werden die Begriffe Motivation und Volition voneinander abgegrenzt. Anschließend werden zentrale theoretische Ansätze zu beiden Konstrukten vorgestellt und Befunde zur Entwicklung im Schulalter und zur Bedeutung von Motivation und Volition im Schulkontext zusammengefasst. Schließlich werden Implikationen dieser theoretischen Ansätze sowie zentraler empirischer Befunde für die Diagnostik und Förderung von Motivation und Volition skizziert. (DIPF/Orig.)
DIPF-Departments:
Bildung und Entwicklung
From signals to knowledge. A conceptual model for multimodal learning analytics
Di Mitri, Daniele; Schneider, Jan; Specht, Marcus; Drachsler, Hendrik
Journal Article
| In: Journal of Computer Assisted Learning | 2018
38545 Endnote
Author(s):
Di Mitri, Daniele; Schneider, Jan; Specht, Marcus; Drachsler, Hendrik
Title:
From signals to knowledge. A conceptual model for multimodal learning analytics
In:
Journal of Computer Assisted Learning, 34 (2018) 4, S. 338-349
DOI:
10.1111/jcal.12288
URL:
https://onlinelibrary.wiley.com/doi/full/10.1111/jcal.12288
Publication Type:
3a. Beiträge in begutachteten Zeitschriften; Beitrag in Sonderheft
Language:
Englisch
Keywords:
Computerunterstütztes Lernen; Datenanalyse; Lernprozess; Lernverhalten; Lerntheorie; Methode; Klassifikation; Modell; Empirische Forschung; Experimentelle Untersuchung; Übersicht
Abstract (english):
Multimodality in learning analytics and learning science is under the spotlight. The landscape of sensors and wearable trackers that can be used for learning support is evolving rapidly, as well as data collection and analysis methods. Multimodal data can now be collected and processed in real time at an unprecedented scale. With sensors, it is possible to capture observable events of the learning process such as learner's behaviour and the learning context. The learning process, however, consists also of latent attributes, such as the learner's cognitions or emotions. These attributes are unobservable to sensors and need to be elicited by human‐driven interpretations. We conducted a literature survey of experiments using multimodal data to frame the young research field of multimodal learning analytics. The survey explored the multimodal data used in related studies (the input space) and the learning theories selected (the hypothesis space). The survey led to the formulation of the Multimodal Learning Analytics Model whose main objectives are of (O1) mapping the use of multimodal data to enhance the feedback in a learning context; (O2) showing how to combine machine learning with multimodal data; and (O3) aligning the terminology used in the field of machine learning and learning science. (DIPF/Orig.)
DIPF-Departments:
Informationszentrum Bildung
Trusted Learning Analytics
Drachsler, Hendrik
Journal Article
| In: Synergie | 2018
38696 Endnote
Author(s):
Drachsler, Hendrik
Title:
Trusted Learning Analytics
In:
Synergie, (2018) 6, S. 40-43
URN:
urn:nbn:de:0111-dipfdocs-191419
URL:
http://www.dipfdocs.de/volltexte/2020/19141/pdf/Synergie_2018_6_Drachsler_Trusted_learning_analytics_A.pdf
Publication Type:
3a. Beiträge in begutachteten Zeitschriften; Beitrag in Sonderheft
Language:
Englisch
Keywords:
Lernen; Lernprozess; Datenanalyse; Daten; Vertrauen; Datenschutz; Rechtsgrundlage; Ethik; Infrastruktur; Forschungsdesign; Datenerfassung; Tool; Visualisierung; Projekt
Abstract:
Data science in education has been coined as 'Learning Analytics', an umbrella term for research questions from overlapping research domains such as psychology, educational science, computer and data science. Despite the great enthusiasm currently surrounding LA, there are substantial questions for research and organisational development that have brought the implementation of LA to a hold, and in some prominent cases have even reversed it due to concerns by governments, stakeholders and civil rights groups about privacy and ethics applied to the handling of personal data. The new General Data Protection Regulation 2018 (GDPR) adds another layer of the complexity to the application of LA in Europe. This all raises a climate that demands a different approach to Learning Analytics in Europe and especially in Germany. Within this article, we shortly describe what Learning Analytics is, highlight the concerns that come with the application of LA, and finally draw a new approach towards LA that we call: Trusted Learning Analytics. (DIPF/Orig.)
DIPF-Departments:
Informationszentrum Bildung
JCAL special issue on multimodal learning analytics
Drachsler, Hendrik; Schneider, Jan
Journal Article
| In: Journal of Computer Assisted Learning | 2018
38547 Endnote
Author(s):
Drachsler, Hendrik; Schneider, Jan
Title:
JCAL special issue on multimodal learning analytics
In:
Journal of Computer Assisted Learning, 34 (2018) 4, S. 335-337
DOI:
10.1111/jcal.12291
URN:
urn:nbn:de:0111-dipfdocs-169218
URL:
http://www.dipfdocs.de/volltexte/2019/16921/pdf/Drachsler_2018_JCAL_Special_Issue_A.pdf
Publication Type:
3a. Beiträge in begutachteten Zeitschriften; Beitrag in Sonderheft
Language:
Englisch
Keywords:
Lernprozess; Analyse; Digitale Medien; Datenerfassung; Methode; Datenanalyse; E-Learning; Lernverhalten; Einführung
DIPF-Departments:
Informationszentrum Bildung
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