In-Class Interaction and Students\u27 Motivation in Intensive Course Classes

This brief study is to see the relationship of peer interaction within class as well as the lecturer in-class attitude affected the students\u27 motivation and perception in a university education course where English is taught as a foreign language. The lecturers, each functioned as the language class instructor, managed a 100-minute-session in a class consisted of about twenty students ranged from 18 to 21 years old. The setting was the University of Widya Mandala Catholic University Surabaya in which a sort of matriculation program called Intensive Course becomes a compulsory subject for the freshmen. The hypothesis established confirmed that in-class lecturer\u27s attitude and the peer-interaction affect students\u27 motivation in learning, compared to the material content being exposed. A set of questionnaire was used as an instrument for data collection and distributed to the sample of class participants of Intensive Course program. It was hoped that the result would contribute beneficial findings that confirm whether interactions happened fostered the learning motivation of the class participants and how it affected them. Result showed that the hypothesis was verified to some extent as the students under study stated that the quality of their peer interaction was one of the grounds that contributed security feeling they need to have in order to freely participate in the learning process without having had to fear of making mistakes. The other ground which is also crucial is the trait of the lecturers that motivate them to persistently continue learning English, found to be challenging to most. Such trait is characterized as being understanding and friendly toward students. It is then hoped that the teachers of English as a Foreign language would realize the importance of having necessary teaching personality that accentuate their classe

The effect of feedback during training sessions on learning pattern-recognition based prosthesis control

Human-machine interfaces have not yet advanced to enable intuitive control of multiple degrees of freedom as offered by modern myoelectric prosthetic hands. Pattern Recognition (PR) control has been proposed to make human-machine interfaces in myoelectric prosthetic hands more intuitive, but it requires the user to generate high-quality, i.e., consistent and separable, electromyogram (EMG) patterns. To generate such patterns, user training is required and has shown promising results. However, how different levels of feedback affect effectivity in training differently, has not been established yet. Furthermore, a correlation between qualities of the EMG patterns (the focus of training) and user performance has not been shown yet. In this study, 37 able-bodied participants (mean age 21 years, 19 males) were recruited and trained PR control over five days. Three levels of feedback were tested for their effectiveness: no external feedback, visual feedback and visual feedback with coaching. Training resulted in improved performance from pre-to post-test with no interaction effect of feedback. Feedback did however affect the quality of the EMG patterns where people who did not receive external feedback generated higher amplitude patterns. A weak correlation was found between a principal component, composed of EMG amplitude and pattern variability, and performance. Our results show that training is highly effective in improving PR control regardless of feedback and that none of the quality metrics correlate with performance. We discuss how different levels of feedback can be leveraged to improve PR control training

Serious gaming to generate separated and consistent EMG patterns in pattern-recognition prosthesis control

Pattern-Recognition (PR) control of upper-limb prosthetics has shown inconsistent results outside lab settings, which might be due to the inadequacy of users’ electromyogram (EMG) patterns. To improve the separability and consistency of their EMG, users can receive training. Conventional training uses an internal focus of attention as prosthesis users focus on the muscle contractions of their (phantom) hand together with explicit learning processes facilitated by a coach guiding the user. In this study we investigated if an alternative training paradigm using an external focus of attention exploiting implicit learning processes based on serious gaming without a coach could lead to more separable and consistent EMG. Able-bodied participants (N = 25; mean age 22 years, 13 females) were recruited and followed conventional or game training for five days. In conventional training, participants performed the Motion Test thrice daily and received coaching on how to adapt their muscle contractions. In game training, participants controlled an avatar using a direct mapping from electrode to avatar direction. The participants utilized implicit learning processes, by exploring which muscle contractions made the avatar go in which directions. Performance in both groups was evaluated by using the Motion Test in a pre/post-test design. Training resulted in improved performance, with no differences between training paradigms. Participants who followed game training showed 51% more separated EMG patterns. EMG pattern consistency did not change over training. It was concluded that serious game training using an external focus of attention and implicit learning can be considered as a viable alternative to conventional training.</p

Should Hands Be Restricted When Measuring Able-Bodied Participants To Evaluate Machine Learning Controlled Prosthetic Hands?

OBJECTIVE: When evaluating methods for machine-learning controlled prosthetic hands, able-bodied participants are often recruited, for practical reasons, instead of participants with upper limb absence (ULA). However, able-bodied participants have been shown to often perform myoelectric control tasks better than participants with ULA. It has been suggested that this performance difference can be reduced by restricting the wrist and hand movements of able-bodied participants. However, the effect of such restrictions on the consistency and separability of the electromyogram's (EMG) features remains unknown. The present work investigates whether the EMG separability and consistency between unaffected and affected arms differ and whether they change after restricting the unaffected limb in persons with ULA. METHODS: Both arms of participants with unilateral ULA were compared in two conditions: with the unaffected hand and wrist restricted or not. Furthermore, it was tested if the effect of arm and restriction is influenced by arm posture (arm down, arm in front, or arm up). RESULTS: Fourteen participants (two women, age=53.4±4.05) with acquired transradial limb loss were recruited. We found that the unaffected limb generated more separated EMG than the affected limb. Furthermore, restricting the unaffected hand and wrist lowered the separability of the EMG when the arm was held down. CONCLUSION: Limb restriction is a viable method to make the EMG of able-bodied participants more similar to that of participants with ULA. SIGNIFICANCE: Future research that evaluates methods for machine learning controlled hands in able-bodied participants should restrict the participants' hand and wrist

User training for machine learning controlled upper limb prostheses:a serious game approach

BACKGROUND: Upper limb prosthetics with multiple degrees of freedom (DoFs) are still mostly operated through the clinical standard Direct Control scheme. Machine learning control, on the other hand, allows controlling multiple DoFs although it requires separable and consistent electromyogram (EMG) patterns. Whereas user training can improve EMG pattern quality, conventional training methods might limit user potential. Training with serious games might lead to higher quality EMG patterns and better functional outcomes. In this explorative study we compare outcomes of serious game training with conventional training, and machine learning control with the users' own one DoF prosthesis. METHODS: Participants with upper limb absence participated in 7 training sessions where they learned to control a 3 DoF prosthesis with two grips which was fitted. Participants received either game training or conventional training. Conventional training was based on coaching, as described in the literature. Game-based training was conducted using two games that trained EMG pattern separability and functional use. Both groups also trained functional use with the prosthesis donned. The prosthesis system was controlled using a neural network regressor. Outcome measures were EMG metrics, number of DoFs used, the spherical subset of the Southampton Hand Assessment Procedure and the Clothespin Relocation Test. RESULTS: Eight participants were recruited and four completed the study. Training did not lead to consistent improvements in EMG pattern quality or functional use, but some participants improved in some metrics. No differences were observed between the groups. Participants achieved consistently better results using their own prosthesis than the machine-learning controlled prosthesis used in this study. CONCLUSION: Our explorative study showed in a small group of participants that serious game training seems to achieve similar results as conventional training. No consistent improvements were found in either group in terms of EMG metrics or functional use, which might be due to insufficient training. This study highlights the need for more research in user training for machine learning controlled prosthetics. In addition, this study contributes with more data comparing machine learning controlled prosthetics with Direct Controlled prosthetics

Invertebrate abundance increases with vegetation productivity across natural and agricultural wader breeding habitats in Europe

Grassland breeding waders have been steadily declining across Europe. Recent studies indicating a dramatic decline in grassland invertebrates' abundance and biomass, the key food of most grassland wader chicks, suggest a likely driver of the demise of waders. While agricultural intensification is generally inferred as the main cause for arthropod decline there is surprisingly little information on the relationship between land use intensity and total arthropod abundance in grasslands. Here, we explored those relationships across several key wader breeding habitats by surveying ground-active, aerial and soil-dwelling invertebrate communities in five European countries that range from natural undisturbed bogs to intensively managed grasslands. Using maximum vegetation growth and soil moisture content we investigated how they shape the size of the invertebrate community within and across different countries. We found predominantly positive relationships between grassland invertebrate abundance, biomass and body weight with increasing vegetation growth and soil moisture. Maximum vegetation growth was strongly positively related to ground-active invertebrate abundance and biomass and abundance of soil dwelling invertebrates (mainly earthworms). Body weight of aerial invertebrates furthermore increased with increasing maximum vegetation growth. Our results provide little support for the hypothesis that agricultural practices associated with intensification of grassland management result in an abundance decline of invertebrate prey for wader chicks. Conservation practices aiming to enhance wader chick survival require a careful balancing act between maintaining habitat productivity to secure high prey abundance, and keeping productivity low enough to maintain open swards that do not need to be cut before chicks have fledged