Learning aspect in Italian as additional language. The role of second languages

The study examines the role played by English and Romance languages (L2s) when learning grammatical aspect in Italian as additional language (Ln). Swedish university students of Italian (n = 34), divided according to knowledge of a Romance L2 and English aspectual knowledge, completed an interpretation task of aspectual contrast in Italian. Eight native speakers served as a control group. The findings showed that knowledge of a Romance language as L2 and high English aspectual knowledge exerted a differential influence on learning aspect in Italian. This outcome is discussed in the light of a consistent form-meaning relationship between the L2s and Italian. Yet, with a mismatch between grammatical and lexical aspect, the learners’ judgments differed from the native speakers’ judgments. Thus, our findings also support the idea of the existence of differential learning paths sustained by the L2s when learning complex aspectual configurations.

External Focus or Differential Learning: Is There an Additive Effect on Learning a Futsal Goal Kick?

(1) Background: How to optimally promote the process of acquiring and learning a new motor skill is still one of the fundamental questions often raised in training and movement science, rehabilitation, and physical education. This study is aimed at investigating the effects of differential learning (DL) and the elements of OPTIMAL theory on learning a goal-kicking skill in futsal, especially under the conditions of external and internal foci. (2) Methods: A total of 40 female beginners were randomly assigned to, and equally distributed among, five different interventions. Within a pretest and post-test design, with retention and transfer tests, participants practiced for 12 weeks, involving two 20-min sessions per week. The tests involved a kicking skill test. Data were analyzed with a one-way ANOVA. (3) Results: Statistically significant differences with large effect sizes were found between differential learning (DL) with an external focus, DL with an internal focus, DL with no focus, traditional training with an external focus, and traditional training with control groups in the post-, retention, and transfer tests. (4) Conclusions: The results indicate the clear advantages of DL. It is well worth putting further efforts into investigating a more differentiated application of instructions combined with exercises for DL.

The Effect of Differential Repeated Sprint Training on Physical Performance in Female Basketball Players: A Pilot Study

This pilot study aimed to determine the effects of differential learning in sprint running with and without changes of direction (COD) on physical performance parameters in female basketball players and to determine the feasibility of the training protocol. Nine female basketball players completed 4 weeks of repeated sprint training (RST) with (COD, n = 4) or without (NCOD, n = 5) changes of direction. A battery of sprints (0–10 and 0–25 m), vertical jumps (counter movement jump (CMJ), drop jump, and single-leg CMJs), and COD tests were conducted before and after intervention. NCOD completed two sets of ten sprints of 20 m, whereas COD performed 20 m sprints with a 180 degree turn at 10 m, returning to the starting line. Before each sprint, participants were instructed to provide different fluctuations (i.e., differential learning) in terms of varying the sprint. Both groups had 30 s of passive recovery between two sprints and 3 min between sets. A significant effect of time for the 0–10 m sprint, CMJ, and single leg-CMJ asymmetries were observed. Adding “erroneous” fluctuation during RST seems to be a suitable and feasible strategy for coaches to enhance physical performance in young female basketball players. However, further studies including larger samples and controlled designs are recommended to strengthen present findings.

A learning mechanism shaping risk preferences and a preliminary test of its relationship with psychopathic traits

People tend to avoid risk in the domain of gains but take risks in the domain of losses; this is called the reflection effect. Formal theories of decision-making have provided important perspectives on risk preferences, but how individuals acquire risk preferences through experiences remains unknown. In the present study, we used reinforcement learning (RL) models to examine the learning processes that can shape attitudes toward risk in both domains. In addition, relationships between learning parameters and personality traits were investigated. Fifty-one participants performed a learning task, and we examined learning parameters and risk preference in each domain. Our results revealed that an RL model that included a nonlinear subjective utility parameter and differential learning rates for positive and negative prediction errors exhibited better fit than other models and that these parameters independently predicted risk preferences and the reflection effect. Regarding personality traits, although the sample sizes may be too small to test personality traits, increased primary psychopathy scores could be linked with decreased learning rates for positive prediction error in loss conditions among participants who had low anxiety traits. The present findings not only contribute to understanding how decision-making in risky conditions is influenced by past experiences but also provide insights into certain psychiatric problems.

Repetition without Repetition or Differential Learning of Multiple Techniques in Volleyball?

A variety of approaches have been proposed for teaching several volleyball techniques to beginners, ranging from general ball familiarization to model-oriented repetition to highly variable learning. This study compared the effects of acquiring three volleyball techniques in parallel with three approaches. Female secondary school students (N = 42; 15.6 ± 0.54 years) participated in a pretest for three different volleyball techniques (underhand pass, overhand pass, and overhead serve) with an emphasis on accuracy. Based on their results, they were parallelized into three practice protocols, a repetitive learning group (RG), a differential learning group (DG), and a control group (CG). After a period of six weeks with 12 intervention sessions, all participants attended a posttest. An additional retention test after two weeks revealed a statistically significant difference between DG, RG, and CG for all single techniques as well as the combined multiple technique. In each technique—the overhand pass, the underhand pass, the overhand service, and the combination of the three techniques—DG performed best (each p < 0.001).

Implementing ACL Injury Prevention in Daily Sports Practice—It’s Not Just the Program: Let’s Build Together, Involve the Context, and Improve the Content

Although the benefits of current anterior cruciate ligament (ACL) injury prevention programmes have been demonstrated in efficacy studies, they, unfortunately, have had limited public health impact to date. For example, the incidence of ACL injuries continues to rise in adolescent athletes. Raising awareness and educating coaches and athletes is not enough to facilitate the widespread, sustained use of these programmes in the real-world setting. Considering the profound burden of ACL injuries, it is necessary to continue to improve the current ACL injury prevention programmes through co-creation. First, the uptake of the programmes should be optimized by a better appreciation and understanding of the individual, socio-cultural and environmental context (i.e., community). Second, the content of the programmes should be optimized to better reflect the demands of the sport by creating more ownership and increasing motivation (incorporating challenging, sport-specific and fun elements) with the end-users. In addition, implicit motor learning, random practice and differential learning are concepts that should be integrated when practising to obtain the most optimal results when learning or finetuning skills.

The Relation Between Complexity and Resilient Motor Performance and the Effects of Differential Learning

Complex systems typically demonstrate a mixture of regularity and flexibility in their behavior, which would make them adaptive. At the same time, adapting to perturbations is a core characteristic of resilience. The first aim of the current research was therefore to test the possible relation between complexity and resilient motor performance (i.e., performance while being perturbed). The second aim was to test whether complexity and resilient performance improve through differential learning. To address our aims, we designed two parallel experiments involving a motor task, in which participants moved a stick with their non-dominant hand along a slider. Participants could score points by moving a cursor as fast and accurately as possible between two boxes, positioned on the right- and left side of the screen in front of them. In a first session, we determined the complexity by analyzing the temporal structure of variation in the box-to-box movement intervals with a Detrended Fluctuation Analysis. Then, we introduced perturbations to the task: We altered the tracking speed of the cursor relative to the stick-movements briefly (i.e., 4 s) at intervals of 1 min (Experiment 1), or we induced a prolonged change of the tracking speed each minute (Experiment 2). Subsequently, participants had three sessions of either classical learning or differential learning. Participants in the classical learning condition were trained to perform the ideal movement pattern, whereas those in the differential learning condition had to perform additional and irrelevant movements. Finally, we conducted a posttest that was the same as the first session. In both experiments, results showed moderate positive correlations between complexity and points scored (i.e., box touches) in the perturbation-period of the first session. Across the two experiments, only differential learning led to a higher complexity index (i.e., more prominent patterns of pink noise) from baseline to post-test. Unexpectedly, the classical learning group improved more in their resilient performance than the differential learning group. Together, this research provides empirical support for the relation between complexity and resilience, and between complexity and differential learning in human motor performance, which should be examined further.

Null Effects of Different Amounts of Task Variation in Both Contextual Interference and Differential Learning Paradigms

Various motor learning approaches, such as Schema Theory, Contextual Interference or Differential Learning, have proposed that varying the task during skill acquisition prompts superior learning. However, past research has mainly compared task variation in an experimental group to no task variation in a control group. Past research has more rarely compared specific intervention groups and/or addressed how varying amounts of task variation may affect skill learning. Our aim in this study was to compare motor learning of golf putting across four groups of novice golfers randomly assigned to these conditions: (a) a contextual interference group who putted at varied putting distances and had varied repetitive weekly schedule patterns, (b) a differential learning group who putted at multiple putting distances, putting amplitudes, and putting movements and had no repetitions, (c) an identical differential learning as in (b) except that participants also varied the putter, and (d) a control group who experienced no practice variations. Participants were 42 university students randomly divided into the four groups. All groups completed eight training sessions of 36 putts per session over four weeks, a pretest, posttest, two retention tests (one and three weeks after posttest) and transfer tasks (different floor). Average hit ratios and minimal distances to the hole were captured and analyzed by Scheirer-Ray-Hare test and Mann-Whitney post-hoc tests. Results showed improved hit ratios from pre- to post-test for all groups, and a stable retention performance for the variable training groups in contrast to the control group ( p = .003). Transfer performance was low for all variable training groups with a significantly lower control group performance on transfer test 2 ( p = .008). In conclusion, variable training schedules in all experimental groups benefited motor learning relative to controls, and differences in the amount of task variation between groups with variable training schedules did not affect skill acquisition.