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Observation of an expert or novice model promotes the learning of a motor skill. In two experiments, we determined the effects of a mixed observation schedule (a combination of expert and novice models) on the learning of a sequential timing task. In Experiment 1, participants observed a novice, expert, or both novice and expert models. The results of retention/transfer tests revealed that all observation groups and a physical practice group learned the task and outperformed a control group. However, observing a novice model was not as effective as observing expert and mixed models. Importantly, a mixed schedule of novice and expert observation resulted in a more stable movement time and better generalization of the imposed relative timing pattern than observation of either a novice or expert model alone. In Experiment 2, we aimed to determine whether a certain type of novice performance (highly variable, with or without error reduction with practice) in a mixed observation schedule would improved motor learning. The observation groups performed as well as a physical practice group and significantly better than a control group. No significant difference was observed with the type of novice model used in a mixed schedule of observation. The results suggest that mixed observation provides an accurate template of the movement (expert observation) that is enhanced when contrasted with the performance of less successful models.
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http://dx.doi.org/10.1007/s00221-011-2882-x | DOI Listing |
J Prof Nurs
September 2025
College of Nursing, Brigham Young University, 566 KMBL, Provo, UT 84602, United States of America.
Background: Formal mentoring within the nursing profession has been recognized as an effective approach in teaching critical thinking, leadership skills, communication, and professional socialization. Unfortunately, few baccalaureate nursing programs teach skills specific to mentoring, both as mentees and mentors within a formalized program.
Methods: A peer mentoring program with senior students mentoring sophomore students was developed based on Benner's (1984) novice-to-expert theory during the COVID-19 pandemic.
Asian Nurs Res (Korean Soc Nurs Sci)
September 2025
Daejeon Eulji University Hospital, Daejeon, South Korea. Electronic address:
Purpose: In this study, we aimed to develop and test the validity and reliability of the Korean version of the Novice Nursing Practitioner Role Transition (K-NNPRT) scale.
Methods: This scale was developed through forward translation, expert panel endorsement, and back translation and revised based on cognitive interviews. Data for the psychometric test were collected from 248 nurses who provide advanced care in Korea.
Med Teach
September 2025
NordSim, Center for Skills Training and Simulation, Aalborg University Hospital, Aalborg, Denmark.
Background: Assessing skills in simulated settings is resource-intensive and lacks validated metrics. Advances in AI offer the potential for automated competence assessment, addressing these limitations. This study aimed to develop and validate a machine learning AI model for automated evaluation during simulation-based thyroid ultrasound (US) training.
View Article and Find Full Text PDFJ Voice
September 2025
Bielefeld University, P.O. Box 10 01 31, Bielefeld D-33501, Germany. Electronic address:
To this day, the assessment of human voices remains a challenge due to (i) inconsistencies in subjective ratings and (ii) the lack of objective measurements for the perceptual impressions of voice characteristics. This can lead to significant consequences in applied fields such as speech therapy, where the assessment of voices is crucial for a successful treatment. In this paper, we address the explanation of voice and its characteristics from two different angles: In a first study, 22 speech therapists in training assessed a set of 20 non-pathological voices regarding 20 voice characteristics before and after receiving an expert explanation.
View Article and Find Full Text PDFFront Artif Intell
August 2025
Department of Philosophy, Universitat Autonoma de Barcelona, Barcelona, Spain.
This paper examines some challenges of using natural language prompting in Generative AI (GenAI) for creative practices in design and the arts. While GenAI is purported to "democratize" creativity by offering a new mode of creation, we argue that it comes with a significant mortgage-particularly one in relation to expert performance, skill acquisition, and embodied engagement. Drawing from Dreyfus and Dreyfus, we show that creativity grounded in internalized expert knowledge cannot be reduced to rule-following or meaningfully externalized in instructions, i.
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