Background: Differential learning (DL) is a motor learning method characterized by high amounts of variability during practice and is claimed to provide the learner with a higher learning rate than other methods. However, some controversy surrounds DL theory, and to date, no overview exists that compares the effects of DL to other motor learning methods.Objective: To evaluate the effectiveness of DL in comparison to other motor learning methods in the acquisition and retention phase.Design: Systematic review and exploratory meta-analysis.Methods: PubMed (MEDLINE), Web of Science, and Google Scholar were searched until February 3, 2020. To be included, (1) studies had to be experiments where the DL group was compared to a control group engaged in a different motor learning method (lack of practice was not eligible), (2) studies had to describe the effects on one or more measures of performance in a skill or movement task, and (3) the study report had to be published as a full paper in a journal or as a book chapter.Results: Twenty-seven studies encompassing 31 experiments were included. Overall heterogeneity for the acquisition phase (post-pre; I2 = 77%) as well as for the retention phase (retention-pre; I2 = 79%) was large, and risk of bias was high. The meta-analysis showed an overall small effect size of 0.26 [0.10, 0.42] in the acquisition phase for participants in the DL group compared to other motor learning methods. In the retention phase, an overall medium effect size of 0.61 [0.30, 0.91] was observed for participants in the DL group compared to other motor learning methods.Discussion/Conclusion: Given the large amount of heterogeneity, limited number of studies, low sample sizes, low statistical power, possible publication bias, and high risk of bias in general, inferences about the effectiveness of DL would be premature. Even though DL shows potential to result in greater average improvements between pre- and post/retention test compared to non-variability-based motor learning methods, more high-quality research is needed before issuing such a statement. For robust comparisons on the relative effectiveness of DL to different variability-based motor learning methods, scarce and inconclusive evidence was found.
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The aim of this study was to examine whether it is possible to utilize the fluctuations in human motor behaviour to induce a self-organizing process in the athlete, which takes advantage of individual movement and learning characteristics. This recently developed approach is known as differencial learning and is compared to traditional learning. For that purpose, thirty-four recreational skaters participated and practised the speed skating start. A pre- post-test design was used together with a one week intervention period that included three practice sessions of one hour each. The pre- and post-test consisted out of 5 starts, and for each start, the finish time was recorded at a distance of 49 m, which included split time registrations at 5 m, 10 m, and 25 m. Based on the finish time in the pre-test, the participants were equally distributed over three practice groups: a differencial learning, learning by instruction, and control group. Analyses revealed a significant improvement for the differencial learning group in comparison to the control group. It is concluded that differencial learning is an effective method to teach the skating start to novices.
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What is a pop-up store and how can it be used for organisational counterspacing? The pop-up can be interpreted as a fashionable and hypermodern platform focusing on the needs of a younger generation of consumers that searches for new experiences and is prone to ad hoc decision-making. From this perspective, the pop-up is a typical expression of the experience economy. But it is more. The ephemeral pop-up store, usually lasting from one day to six months, is also a spatial practice on the boundary between place as something stable/univocal and space as something transitory/polyphonic. Organizational theory has criticized the idea of a stable place and proposed the concept of spacing with a focus on the becoming of space. In this article, the pop-up store is introduced as a fashionable intervention into organizational spacing. It suggests a complementary perspective to non-representational theory and frames the pop-up as co-actor engaging everyday users in appropriating space. Drawing on Lefebvre’s notions of differential space, festival and evental moment, theory is revisited and then operationalized in two pop-up store experiments. Apart from contributing to the ongoing theoretical exploration of the spacing concept, this article aims to inspire differential pop-up practices in organisations. https://www.linkedin.com/in/overdiek12345/
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Athletes who wish to resume high-level activities after an injury to the anterior cruciate ligament (ACL) are often advised to undergo surgical reconstruction. Nevertheless, ACL reconstruction (ACLR) does not equate to normal function of the knee or reduced risk of subsequent injuries. In fact, recent evidence has shown that only around half of post-ACLR patients can expect to return to competitive level of sports. A rising concern is the high rate of second ACL injuries, particularly in young athletes, with up to 20% of those returning to sport in the first year from surgery experiencing a second ACL rupture. Aside from the increased risk of second injury, patients after ACLR have an increased risk of developing early onset of osteoarthritis. Given the recent findings, it is imperative that rehabilitation after ACLR is scrutinized so the second injury preventative strategies can be optimized. Unfortunately, current ACLR rehabilitation programs may not be optimally effective in addressing deficits related to the initial injury and the subsequent surgical intervention. Motor learning to (re-)acquire motor skills and neuroplastic capacities are not sufficiently incorporated during traditional rehabilitation, attesting to the high re-injury rates. The purpose of this article is to present novel clinically integrated motor learning principles to support neuroplasticity that can improve patient functional performance and reduce the risk of second ACL injury. The following key concepts to enhance rehabilitation and prepare the patient for re-integration to sports after an ACL injury that is as safe as possible are presented: (1) external focus of attention, (2) implicit learning, (3) differential learning, (4) self-controlled learning and contextual interference. The novel motor learning principles presented in this manuscript may optimize future rehabilitation programs to reduce second ACL injury risk and early development of osteoarthritis by targeting changes in neural networks.
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In this post I give an overview of the theory, tools, frameworks and best practices I have found until now around the testing (and debugging) of machine learning applications. I will start by giving an overview of the specificities of testing machine learning applications.
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Using path analysis, the present study focuses on the development of a model describing the impact of four judgments of self-perceived academic competence on higher education students' achievement goals, learning approach, and academic performance. Results demonstrate that academic self-efficacy, self-efficacy for self-regulated learning, academic self-concept, and perceived level of understanding are conceptually and empirically distinct self-appraisals of academic competence which have a different impact on student motivation, learning, and academic performance. Furthermore, the current study suggests that students reflecting high scores on the four measures of self-perceived competence, are more persistent, more likely to adopt mastery and/or performance approach goals, less anxious, process the learning material at a deeper level, and achieve better study results. However, this study also warns that high self-perceived competence (e.g., perceived level of understanding), if not accompanied by a mastery goal orientation, can turn into overconfidence resulting in lower persistence levels and poorer study results.
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Motor learning is particularly challenging in neurological rehabilitation: patients who suffer from neurological diseases experience both physical limitations and difficulties of cognition and communication that affect and/or complicate the motor learning process. Therapists (e.g.,, physiotherapists and occupational therapists) who work in neurorehabilitation are therefore continuously searching for the best way to facilitate patients during these intensive learning processes. To support therapists in the application of motor learning, a framework was developed, integrating knowledge from the literature and the opinions and experiences of international experts. This article presents the framework, illustrated by cases from daily practice. The framework may assist therapists working in neurorehabilitation in making choices, implementing motor learning in routine practice, and supporting communication of knowledge and experiences about motor learning with colleagues and students. The article discusses the framework and offers suggestions and conditions given for its use in daily practice.
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Despite the promises of learning analytics and the existence of several learning analytics implementation frameworks, the large-scale adoption of learning analytics within higher educational institutions remains low. Extant frameworks either focus on a specific element of learning analytics implementation, for example, policy or privacy, or lack operationalization of the organizational capabilities necessary for successful deployment. Therefore, this literature review addresses the research question “What capabilities for the successful adoption of learning analytics can be identified in existing literature on big data analytics, business analytics, and learning analytics?” Our research is grounded in resource-based view theory and we extend the scope beyond the field of learning analytics and include capability frameworks for the more mature research fields of big data analytics and business analytics. This paper’s contribution is twofold: 1) it provides a literature review on known capabilities for big data analytics, business analytics, and learning analytics and 2) it introduces a capability model to support the implementation and uptake of learning analytics. During our study, we identified and analyzed 15 key studies. By synthesizing the results, we found 34 organizational capabilities important to the adoption of analytical activities within an institution and provide 461 ways to operationalize these capabilities. Five categories of capabilities can be distinguished – Data, Management, People, Technology, and Privacy & Ethics. Capabilities presently absent from existing learning analytics frameworks concern sourcing and integration, market, knowledge, training, automation, and connectivity. Based on the results of the review, we present the Learning Analytics Capability Model: a model that provides senior management and policymakers with concrete operationalizations to build the necessary capabilities for successful learning analytics adoption.
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We use a randomised experiment to study the effect of offering half of 556 freshman students a learning analytics dashboard and a weekly email with a link to their dashboard, on student behaviour in the online environment and final exam performance. The dashboard shows their online progress in the learning management systems, their predicted chance of passing, their predicted grade and their online intermediate performance compared with the total cohort. The email with dashboard access, as well as dashboard use, has positive effects on student behaviour in the online environment, but no effects are found on student performance in the final exam of the programming course. However, we do find differential effects by specialisation and student characteristics.
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