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Abstract Functional electrical stimulation (FES) can support functional restoration of a paretic limb post-stroke. Hebbian plasticity depends on temporally coinciding pre- and post-synaptic activity. A tight temporal relationship between motor cortical (MC) activity associated with attempted movement and FES-generated visuo-proprioceptive feedback is hypothesized to enhance motor recovery. Using a brain–computer interface (BCI) to classify MC spectral power in electroencephalographic (EEG) signals to trigger FES-delivery with detection of movement attempts improved motor outcomes in chronic stroke patients. We hypothesized that heightened neural plasticity earlier post-stroke would further enhance corticomuscular functional connectivity and motor recovery. We compared subcortical non-dominant hemisphere stroke patients in BCI-FES and Random-FES (FES temporally independent of MC movement attempt detection) groups. The primary outcome measure was the Fugl-Meyer Assessment, Upper Extremity (FMA-UE). We recorded high-density EEG and transcranial magnetic stimulation-induced motor evoked potentials before and after treatment. The BCI group showed greater: FMA-UE improvement; motor evoked potential amplitude; beta oscillatory power and long-range temporal correlation reduction over contralateral MC; and corticomuscular coherence with contralateral MC. These changes are consistent with enhanced post-stroke motor improvement when movement is synchronized with MC activity reflecting attempted movement.

Introduction: Non-adherence to recommended secondary preventive anticoagulation in stroke patients with atrial fibrillation (AF) is a common phenomenon, although the introduction of direct oral anticoagulants (DOACs) has simplified anticoagulation management for physicians as well as for patients. Methods: We examined the adherence of secondary preventive anticoagulation in AF patients after re-integration in their social environment 6–12 weeks after stroke unit and rehabilitation clinic treatment and analyzed for predictors for adherence and non-adherence. We conducted a telephone survey in consecutive patients treated between January 2013 and December 2021 at our institutional stroke unit with an acute cerebrovascular ischemic event, and we analyzed discharge letters of rehabilitation clinics of those patients not anticoagulated at follow-up. All patients had known or newly diagnosed AF, and in all, we had recommended secondary preventive anticoagulation. Results: Follow-up information about anticoagulant intake could be obtained in 1,348 of 1,685 patients (80.0%) treated within the study period. Anticoagulation rate was 91.5%, with 83.6% of patients receiving DOACs and 7.9% receiving vitamin K antagonists (VKAs). Adherence to recommended anticoagulation was associated with intake of the recommended anticoagulant already at discharge (adjusted odds ratio [OR], 18.357; confidence interval [CI], 9.637–34.969), recommendation of a specific DOAC and dose (in contrast to “DOAC” as drug category) (adjusted OR, 2.971; CI, 1.173–7.255), a lower modified Rankin Scale at discharge (per point; adjusted OR, 0.813; CI, 0.663–0.996), younger age (per year; OR, 0.951; CI, 0.926–0.976), and the absence of peripheral vascular disease (adjusted OR, 0.359; CI, 0.173–0.746). In patients already anticoagulated at discharge, adherence was 98.5%, irrespective of a patient’s age, functional deficit at discharge, and peripheral vascular disease. Avoidable obstacles for non-adherence in patients not on anticoagulants at stroke unit discharge were (1) non-implementation of recommended anticoagulation by rehabilitation physicians predominantly in patients with moderate-severe or severe stroke disability (2.1%), (2) delegation of anticoagulation start from rehabilitation physicians to general practitioners/resident radiologists (1.3%), and (3) rejection of recommended anticoagulation because of patients’ severe stroke disability (0.5%). Non-avoidable obstacles were contraindications to anticoagulation (2.1%) and patients’ refusal (0.7%). Conclusions: Commencing drug administration already during stroke unit hospitalization and providing an explanation for the selection of the recommended anticoagulant in discharge letters ensures high adherence at patients’ re-integration in their social environment after acute stroke treatment. If drug administration cannot be commenced before discharge, education of rehabilitation physicians by stroke physicians and the involvement of stroke physicians into the post-stroke decision process might hinder avoidable obstacles.

Medienbezogene Kompetenzen von Lehrkräften sind unabdingbar, um Schüler:innen auf Teilhabe, Partizipation und eine verantwortliche Mitgestaltung in einer Kultur der Digitalität vorzubereiten. Konkret benötigen Lehrkräfte hierzu medienbezogene Basis- und Lehrkompetenzen. Für die zielgerichtete und erfolgreiche Förderung dieser Kompetenzen im Rahmen der Lehrkräftebildung sind Instrumente zur Messung dieser Medienkompetenzen hilfreich. Bestehende Instrumente greifen allerdings zumeist auf einfache, nicht selten sehr allgemein formulierte Selbsteinschätzungen zurück. Dies erschwert eine valide Messung von Kompetenzen. In diesem Beitrag wird ein alternativer Messansatz vorgestellt, der Selbsteinschätzungen von Medienkompetenzen mittels Szenarien kontextualisiert und damit präzisiert. Die Szenarien-Basierung führt zu einem validen Messergebnis, hat aber für den Einsatz im Feld den Nachteil, dass die Messung deutlich umfangreicher ausfällt. Dem begegnen wir im vorliegenden Beitrag durch die Entwicklung einer Kurzskala in einem mehrstufigen Verfahren. Auf Basis eines Datensatzes von N = 552 (angehenden) Lehrkräften wird eine szenarienbasierte Kurzskala zur Messung instrumenteller und kritisch-reflexiver Medienkompetenzen sowie medienbezogener Lehrkompetenzen entwickelt. Diese Kurzskala wird in einer weiteren Studie mit N = 204 Lehrkräften nochmals validiert. Die Ergebnisse beider Studien unterstützen die Validität der Kurzskala. Für die Lehrkräftebildung und Forschung wird somit ein akzeptanzförderndes und ressourcenschonendes Instrument bereitgestellt, das eine reliable und valide Messung instrumenteller und kritisch-reflexiver Medienkompetenzen sowie medienbezogener Lehrkompetenzen erlaubt.

Research on diagnosing in teacher education has primarily emphasized the accuracy of diagnostic judgments and has explained it in terms of factors such as diagnostic knowledge. However, approaches to scientific argumentation and information processing suggest differentiating between diagnostic judgment and diagnostic argumentation: When making accurate diagnostic judgments, the underlying reasoning can remain intuitive, whereas diagnostic argumentation requires controlled and explicable reasoning about a diagnostic problem to explain the reasoning in a comprehensible and persuasive manner. We suggest three facets of argumentation for conceptualizing diagnostic argumentation, which are yet to be addressed in teacher education research: justification of a diagnosis with evidence, disconfirmation of differential diagnoses, and transparency regarding the processes of evidence generation. Therefore, we explored whether preservice teachers’ diagnostic argumentation and diagnostic judgment might represent different diagnostic skills. We also explored whether justification, disconfirmation, and transparency should be considered distinct subskills of preservice teachers’ diagnostic argumentation. We reanalyzed data of 118 preservice teachers who learned about students’ learning difficulties with simulated cases. For each student case, the preservice teachers had to indicate a diagnostic judgment and provide a diagnostic argumentation. We found that preservice teachers’ diagnostic argumentation seldom involved all three facets, suggesting a need for more specific training. Moreover, the correlational results suggested that making accurate diagnostic judgments and formulating diagnostic argumentation may represent different diagnostic skills and that justification, disconfirmation, and transparency may be considered distinct subskills of diagnostic argumentation. The introduced concepts of justification, disconfirmation, and transparency may provide a starting point for developing standards in diagnostic argumentation in teacher education.

Recent advancements in artificial intelligence make its use in education more likely. In fact, existing learning systems already utilize it for supporting students’ learning or teachers’ judgments. In this perspective article, we want to elaborate on the role of humans in making decisions in the design and implementation process of artificial intelligence in education. Therefore, we propose that an artificial intelligence-supported system in education can be considered a closed-loop system, which includes the steps of (i) data recording, (ii) pattern detection, and (iii) adaptivity. Besides the design process, we also consider the crucial role of the users in terms of decisions in educational contexts: While some implementations of artificial intelligence might make decisions on their own, we specifically highlight the high potential of striving for hybrid solutions in which different users, namely learners or teachers, are provided with information from artificial intelligence transparently for their own decisions. In light of the non-perfect accuracy of decisions of both artificial intelligence-based systems and users, we argue for balancing the process of human- and AI-driven decisions and mutual monitoring of these decisions. Accordingly, the decision-making process can be improved by taking both sides into account. Further, we emphasize the importance of contextualizing decisions. Potential erroneous decisions by either machines or humans can have very different consequences. In conclusion, humans have a crucial role at many stages in the process of designing and using artificial intelligence for education.

BackgroundLearning with virtual patients is highly popular for fostering clinical reasoning in medical education. However, little learning with virtual patients is done collaboratively, despite the potential learning benefits of collaborative versus individual learning. ObjectiveThis paper describes the implementation of student collaboration in a virtual patient platform. Our aim was to allow pairs of students to communicate remotely with each other during virtual patient learning sessions. We hypothesized that we could provide a collaborative tool that did not impair the usability of the system compared to individual learning and that this would lead to better diagnostic accuracy for the pairs of students. MethodsImplementing the collaboration tool had five steps: (1) searching for a suitable software library, (2) implementing the application programming interface, (3) performing technical adaptations to ensure high-quality connections for the users, (4) designing and developing the user interface, and (5) testing the usability of the tool in 270 virtual patient sessions. We compared dyad to individual diagnostic accuracy and usability with the 10-item System Usability Scale. ResultsWe recruited 137 students who worked on 6 virtual patients. Out of 270 virtual patient sessions per group (45 dyads times 6 virtual patients, and 47 students working individually times 6 virtual patients minus 2 randomly selected deleted sessions) the students made successful diagnoses in 143/270 sessions (53%, SD 26%) when working alone and 192/270 sessions (71%, SD 20%) when collaborating (P=.04, η2=0.12). A usability questionnaire given to the students who used the collaboration tool showed a usability score of 82.16 (SD 1.31), representing a B+ grade. ConclusionsThe collaboration tool provides a generic approach for collaboration that can be used with most virtual patient systems. The collaboration tool helped students diagnose virtual patients and had good overall usability. More broadly, the collaboration tool will provide an array of new possibilities for researchers and medical educators alike to design courses for collaborative learning with virtual patients.

Teachers routinely observe and interpret student behavior to make judgements about whether and how to support their students' learning. Simulated cases can help pre-service teachers to gain this skill of diagnostic reasoning. With 118 pre-service teachers, we tested whether participants rate simulated cases presented in a serial-cue case format as more authentic and become more involved with the materials compared to cases presented in a whole case format. We further investigated whether participants with varying prior conceptual knowledge (what are symptoms of ADHD and dyslexia) gain more strategic knowledge (how to detect ADHD and dyslexia) with a serial-cue versus whole case format. We found that the case format did not impact authenticity ratings but that learners reported higher involvement in the serial-cue case format condition. Bayes factors provide moderate evidence for the absence of a case format effect on strategic knowledge and strong evidence for the absence of an interaction of case format and prior knowledge. We recommend using serial-cue case formats in simulations as they are a more authentic representation of the diagnostic reasoning process and cognitively involve learners. We call for replications to gather more evidence for the impact of case format on knowledge acquisition. We suggest a further inquiry into the relationship of case format, involvement, and authenticity but think that a productive way forward for designing authentic simulations is attention to aspects that make serial-cue cases effective for diverse learners. For example, adaptive feedback or targeted practice of specific parts of diagnostic reasoning such as weighing evidence.

Abstract A brief survey among members of the German Neurorehabilitation Society aimed to document the hospital capacities (“beds”) for prolonged weaning from a mechanical ventilator for patients with neuro-disabilities that require simultaneous multi-professional neurorehabilitation treatment. Sixty-eight institutions declared to have capacities with a broad distribution across Germany and its federal states. Overall, 1094 “beds” for prolonged weaning (and neurorehabilitation) were reported, 871 together with further information regarding their identification and hence regional location. These units had on average 16.1 beds for prolonged weaning (95% confidence interval 12.6 to 19.6) with a range from 2 to 68 beds per organization. The data indicate substantial capacities for the combined prolonged weaning and neurorehabilitation treatment in Germany. For most “beds” included in this analysis a basic validation was possible. While a reasonable coverage of these specialized service capacities by the survey is likely, the number reported could still be biased by underreporting by non-response. Both the broad variation of number of “beds” for prolonged weaning per unit and their unequal geographical distribution across federal states (per capita rate) warrant a more refined follow-up survey that will provide insights into reasons for the observed pattern of variation for these specialized hospital capacities.

Abstract Introduction Clinical reasoning has been fostered with varying case formats including the use of virtual patients. Existing literature points to different conclusions regarding which format is most beneficial for learners with diverse levels of prior knowledge. We designed our study to better understand which case format affects clinical reasoning outcomes and cognitive load, dependent on medical students’ prior knowledge. Methods Overall, 142 medical students (3 rd to 6 th year) were randomly assigned to either a whole case or serial cue case format. Participants worked on eight virtual patients in their respective case format. Outcomes included diagnostic accuracy, knowledge, and cognitive load. Results We found no effect of case format on strategic knowledge scores pre- vs post-test (whole case learning gain = 3, 95% CI. -.01 to .01, serial cue learning gain = 3, 95% CI. -.06 to .00 p = .50). In both case formats, students with high baseline knowledge (determined by median split on the pre-test in conceptual knowledge) benefitted from learning with virtual patients (learning gain in strategic knowledge = 5, 95% CI .03 to .09, p = .01) while students with low prior knowledge did not (learning gain = 0, 95%CI −.02 to .02). We found no difference in diagnostic accuracy between experimental conditions (difference = .44, 95% CI −.96 to .08, p = .22), but diagnostic accuracy was higher for students with high prior knowledge compared to those with low prior knowledge (difference = .8, 95% CI 0.31 to 1.35, p

Die Nachfrage nach zukunftsgewandten, problemlösungsorientierten Prüfungsformaten für die Hochschullehre stieg nicht zuletzt aufgrund der COVID-19-Pandemie. Open-Book-Prüfungen, bei denen Unterlagen mitgebracht werden, werden seit Langem als alternatives Prüfungsformat vorgeschlagen. Der vorliegende Beitrag beleuchtet in einer Studie mit 113 Teilnehmenden, ob die Menge und Art mitgebrachter Unterlagen einen Einfluss auf die Performanz in Multiple-Choice-Fragen zu konzeptuellem und prozeduralem Wissen aufweisen. Einen signifikanten, positiven Zusammenhang in Bezug auf die Performanz in beiden Wissensformen wies die Menge an mitgebrachten kommentierten Vorlesungsfolien auf. Diese Befunde werden in Bezug zur ICAP-Theorie gesetzt, die zugrundeliegende Lernaktivitäten beleuchtet.

The idea of this paper is to offer a blueprint, to guide educators setting up a complete digital teaching scenario according to the latest insights of educational research. The COVID-19 pandemic forced higher education institutions all around the world to radically shift their curricula from a mix of face-to-face and remote teaching methods to a fully remote curriculum. Though challenging, this time provides opportunities to implement new educational methods and to improve the quality of digital teaching. The concept of the inverted classroom was modified to meet the special needs of the new online settings. The proposed online Inverted Classroom Model (oICM) includes the following phases: (1) pre-phase, (2) self-learning-phase, (3) synchronous online phase, (4) transfer-phase, and (5) evaluation. Recommendations and potential tools are provided for each phase. The oICM is an innovative and easy to use approach to shape digital teaching and learning processes during and after the COVID-19 pandemic. This blueprint is developed by the committee “Digitalization” of the German Association for Medical Education (GMA), mainly for educators who are familiar with the Inverted Classroom Model (ICM) or similar blended learning formats.

In this article, we investigate diagnostic activities and diagnostic practices in medical education and teacher education. Previous studies have tended to focus on comparing knowledge between disciplines, but such an approach is complicated due to the content specificity of knowledge. We compared 142 learners from medical education and 122 learners from teacher education who were asked to (a) diagnose eight simulated cases from their respective discipline in a simulation-based learning environment and (b) write a justificatory report for each simulated case. We coded all justificatory reports regarding four diagnostic activities: generating hypotheses, generating evidence, evaluating evidence, and drawing conclusions. Moreover, using the method of Epistemic Network Analysis, we operationalized diagnostic practices as the relative frequencies of co-occurring diagnostic activities. We found significant differences between learners from medical education and teacher education with respect to both their diagnostic activities and diagnostic practices. Learners from medical education put relatively more emphasis on generating hypotheses and drawing conclusions, therefore applying a more hypothesis-driven approach. By contrast, learners in teacher education had a stronger focus on generating and evaluating evidence, indicating a more data-driven approach. The results may be explained by different epistemic ideals and standards taught in higher education. Further research on the issue of epistemic ideals and standards in diagnosing is needed. Moreover, we recommend that educators think beyond individuals’ knowledge and implement measures to systematically teach and increase the awareness of disciplinary standards.

Motor recovery following stroke is believed to necessitate alteration in functional connectivity between cortex and muscle. Cortico-muscular coherence has been proposed as a potential biomarker for post-stroke motor deficits, enabling a quantification of recovery, as well as potentially indicating the regions of cortex involved in recovery of function. We recorded simultaneous EEG and EMG during wrist extension from healthy participants and patients following ischaemic stroke, evaluating function at three time points post-stroke. EEG–EMG coherence increased over time, as wrist mobility recovered clinically, and by the final evaluation, coherence was higher in the patient group than in the healthy controls. Moreover, the cortical distribution differed between the groups, with coherence involving larger and more bilaterally scattered areas of cortex in the patients than in the healthy participants. The findings suggest that EEG–EMG coherence has the potential to serve as a biomarker for motor recovery and to provide information about the cortical regions that should be targeted in rehabilitation therapies based on real-time EEG.

This perspective piece explores the transformative potential and associated challenges of large language models (LLMs) in education and how those challenges might be addressed utilizing playful and game-based learning. While providing many opportunities, the stochastic elements incorporated in how present LLMs process text, requires domain expertise for a critical evaluation and responsible use of the generated output. Yet, due to their low opportunity cost, LLMs in education may pose some risk of over-reliance, potentially and unintendedly limiting the development of such expertise. Education is thus faced with the challenge of preserving reliable expertise development while not losing out on emergent opportunities. To address this challenge, we first propose a playful approach focusing on skill practice and human judgment. Drawing from game-based learning research, we then go beyond this playful account by reflecting on the potential of well-designed games to foster a willingness to practice, and thus nurturing domain-specific expertise. We finally give some perspective on how a new pedagogy of learning with AI might utilize LLMs for learning by generating games and gamifying learning materials, leveraging the full potential of human-AI interaction in education.

Many established technologies are limited in analyzing the executive functions in motion, especially while walking. Functional near-infrared spectroscopy (fNIRS) fills this gap. The aim of the study is to investigate the inter-session reliability (ISR) of fNIRS-derived parameters at the prefrontal cortex while walking in people with multiple sclerosis (MS) and healthy control (HC) individuals. Twenty people with MS/HC individuals walked a 12 m track back and forth over 6 min. The primary outcomes were the absolute and relative reliability of the mean, slope coefficient (SC), and area under the curve (A) of the oxy-/deoxyhemoglobin concentrations (HbO/HbR) in the Brodmann areas (BA) 9/46/10. The SC and the A of HbO exhibited a fair ISR in BA10 in people with MS. For the mean and A of the HbR, almost all areas observed revealed a fair ISR. Overall, the ISR was better for HbR than HbO. A fair to excellent ISR was found for most BA of the prefrontal cortex in HC individuals. In total, the ISR of the analyzed fNIRS-derived parameters was limited. To improve the ISR, confounders such as fatigue and mind wandering should be minimized. When reporting the ISR, the focus should be on the mean/A rather than SC.

Functional electrical stimulation and robot-assisted gait training are techniques which are used in a clinical routine to enhance the rehabilitation process of stroke patients. By combining these technologies, therapy effects could be further improved and the rehabilitation process can be supported. In order to combine these technologies, a novel algorithm was developed, which aims to extract gait events based on movement data recorded with inertial measurement units. In perspective, the extracted gait events can be used to trigger functional electrical stimulation during robot-assisted gait training. This approach offers the possibility of equipping a broad range of potential robot-assisted gait trainers with functional electrical stimulation. In particular, the aim of this study was to test the robustness of the previously developed algorithm in a clinical setting with patients who suffered a stroke. A total amount of N = 10 stroke patients participated in the study, with written consent. The patients were assigned to two different robot-assisted gait trainers (Lyra and Lokomat) according to their performance level, resulting in five recording sessions for each gait-trainer. A previously developed algorithm was applied and further optimized in order to extract the gait events. A mean detection rate across all patients of 95.8% ± 7.5% for the Lyra and 98.7% ± 2.6% for the Lokomat was achieved. The mean type 1 error across all patients was 1.0% ± 2.0% for the Lyra and 0.9% ± 2.3% for the Lokomat. As a result, the developed algorithm was robust against patient specific movements, and provided promising results for the further development of a technique that can detect gait events during robot-assisted gait training, with the future aim to trigger functional electrical stimulation.

The Wellbeing Game uses game design elements to promote wellbeing. Players document their daily activities in the game and categorize them to one or more of five wellbeing-related factors. The users join teams and can create team events to work together and improve their wellbeing status. The present study aims to review the application and the theoretical base of ‘The Wellbeing Game’, to adapt it to the German context, and to evaluate its health effects in different settings. Additional aims are to analyze the current state of research regarding the links between health, wellbeing, and gamification and to identify crucial game design elements that have to be implemented in the application in order to address the needs of competence, autonomy, and social relatedness according to the self-determination theory.

Previous research has focused on self-assessments rather than objective assessments for assessing teachers' technological knowledge (TK). Notwithstanding, empirical studies have failed to show stable relationships between self-assessments and objective assessments. In this study, we investigate the extent to which scenario-based self-assessments of (student) teachers' (N = 75) TK can serve as anchors by helping them to identify the relevant skills that are required in concrete and authentic situations and might be therefore effective to bring the results of objective and subjective measures closer together using a path analytical model. Overall, the results suggest that scenario-based self-assessment is promising for the approximation of the results of objective assessment measures, especially for operational technical skills.