Search

The effect of explicit, implicit, and analogy learning methods on developing selective attention skills in young novice participants was examined under normal and stressful conditions. The 60 novice participants, aged 11-12 years old, followed a video simulation intervention program of 12 sessions (3 times * 4 weeks). They were tested four times (pre-test, post-test, retention, and stress test) to evaluate their reaction time and accuracy in selective attention skills. The differences among the groups and the measurements were analysed using a two-way mixed factorial ANOVA (4 groups * 4 measurements), and post-hoc Bonferroni evaluated significant differences among the groups. The results showed that all three experimental groups improved their performance in response reaction time and accuracy from the pre-test to the post-test and maintained their scores on the retention test. However, the analogy group had the best scores, followed by the implicit group, and they were both better than the explicit group. According to the stress test, the analogy and the implicit group remained unaffected while the explicit group showed a decrease in both reaction time and accuracy. Training by analogy was more effective in improving selective attention in novices in both normal and stressful conditions. Analogy learners probably developed an advanced mechanism that allowed them to quickly and accurately select the most useful information from the sport setting even in stressful conditions. This research highlights the advantages of simulation techniques; future research may assess selective attention in real conditions.

Objective Clinicians may use implicit or explicit motor learning approaches to facilitate motor learning of patients with stroke. Implicit motor learning approaches have shown promising results in healthy populations. The purpose of this study was to assess whether an implicit motor learning walking intervention is more effective compared with an explicit motor learning walking intervention delivered at home regarding walking speed in people after stroke in the chronic phase of recovery. Methods This randomized, controlled, single-blind trial was conducted in the home environment. The 79 participants, who were in the chronic phase after stroke (age = 66.4 [SD = 11.0] years; time poststroke = 70.1 [SD = 64.3] months; walking speed = 0.7 [SD = 0.3] m/s; Berg Balance Scale score = 44.5 [SD = 9.5]), were randomly assigned to an implicit (n = 38) or explicit (n = 41) group. Analogy learning was used as the implicit motor learning walking intervention, whereas the explicit motor learning walking intervention consisted of detailed verbal instructions. Both groups received 9 training sessions (30 minutes each), for a period of 3 weeks, targeted at improving quality of walking. The primary outcome was walking speed measured by the 10-Meter Walk Test at a comfortable walking pace. Outcomes were assessed at baseline, immediately after intervention, and 1 month postintervention. Results No statistically or clinically relevant differences between groups were obtained postintervention (between-group difference was estimated at 0.02 m/s [95% CI = −0.04 to 0.08] and at follow-up (between-group difference estimated at −0.02 m/s [95% CI = −0.09 to 0.05]). Conclusion Implicit motor learning was not superior to explicit motor learning to improve walking speed in people after stroke in the chronic phase of recovery. Impact To our knowledge, this is the first study to examine the effects of implicit compared with explicit motor learning on a functional task in people after stroke. Results indicate that physical therapists can use (tailored) implicit and explicit motor learning strategies to improve walking speed in people after stroke who are in the chronic phase of recovery.

espanolComenzando con las diferencias entre el pronostico y la prediccion y profundizando en la prediccion, se presenta un modelo basado en el conocimiento. Se analiza la evolucion de las bolsas de valores, asi como como les han afectado las epidemias y pandemias previas a las bolsas de valores y como esta siendo afectado actualmente por el covid-19. El modelo definido se aplica a un caso de uso utilizando Case-Based Reasoning (CBR): hace una analogia entre la crisis de 2008 con la crisis del covid-19 en 2020 para predecir si los mercados de valores tardaran mas o menos en recuperarse. EnglishStarting with the differences between forecasting and prediction and going deeper into prediction, a knowledge-based model is presented. The evolution of the stocks markets are analyzed, as well as how the epidemics and pandemics prior to the stock markets have affected them and how it is currently being affected by covid-19. The defined model is applied to a use case using Case-Based Reasoning (CBR): it makes an analogy between the 2008 crisis with the covid-19 crisis in 2020 to predict whether the stock markets will take more or less time to recover.

The present study investigated the differential effects of analogy and explicit instructions on early stage motor learning and movement in a modified high jump task. Participants were randomly assigned to one of three experimental conditions: analogy, explicit light (reduced informational load), or traditional explicit (large informational load). During the two-day learning phase, participants learned a novel high jump technique based on the ‘scissors’ style using the instructions for their respective conditions. For the single-day testing phase, participants completed both a retention test and task-relevant pressure test, the latter of which featured a rising high-jump-bar pressure manipulation. Although analogy learners demonstrated slightly more efficient technique and reported fewer technical rules on average, the differences between the conditions were not statistically significant. There were, however, significant differences in joint variability with respect to instructional type, as variability was lowest for the analogy condition during both the learning and testing phases, and as a function of block, as joint variability decreased for all conditions during the learning phase. Findings suggest that reducing the informational volume of explicit instructions may mitigate the deleterious effects on performance previously associated with explicit learning in the literature.