Learning Curves of Temporary Workers in Manual Order Picking Activities

Person-to-stock order picking is highly flexible and requires minimal investment costs in comparison to automated picking solutions. For these reasons, tradi-tional picking is widespread in distribution and production logistics. Due to its typically large proportion of manual activities, picking causes the highest operative personnel costs of all intralogistics process. The required personnel capacity in picking varies short- and mid-term due to capacity requirement fluctuations. These dynamics are often balanced by employing minimal permanent staff and using seasonal help when needed. The resulting high personnel fluctuation necessitates the frequent training of new pickers, which, in combination with in-creasingly complex work contents, highlights the im-portance of learning processes in picking. In industrial settings, learning is often quantified based on diminishing processing time and cost requirements with increasing experience. The best-known industrial learning curve models include those from Wright, de Jong, Baloff and Crossman, which are typically applied to the learning effects of an entire work crew rather than of individuals. These models have been validated in largely static work environments with homogeneous work contents. Little is known of learning effects in picking systems. Here, work contents are heterogeneous and individual work strategies vary among employees. A mix of temporary and steady employees with varying degrees of experience necessitates the observation of individual learning curves. In this paper, the individual picking performance development of temporary employees is analyzed and compared to that of steady employees in the same working environment.

Assessing the Influence of Brain-based Instructional Methods and Its Impact on Systemic Change for Learning Communities

Background: As scholars who prepare future school leaders to be innovative instructional leaders for their learning communities, we are on the verge of a curriculum design revolution. The application of brain research findings promotes educational reform efforts to systemically change the way in which children experience school. However, most educators, school leaders, board members, and policy makers are ill prepared to reconsider the implications for assessment, pedagogy, school climate, daily schedules, and use of technology. This qualitative study asked future school leaders to reconsider how school leadership preparedness programs prepared them to become instructional leaders for the 21st century. The findings from this study will enhance the field of school leadership, challenging the current emphasis placed on standardized testing, traditional school calendars, assessments, monocultural instructional methods, and meeting the needs of diverse learning communities. [See PDF for complete abstract]

Teaching Tuberculosis Content: Web-Based Resources for Nurse Educators

Introduction: Tuberculosis (TB) is a global health concern with one-third of the world’s population infected. With the goal of eliminating TB, a component of appropriate management of the disease is ensuring baccalaureate nursing students receive current and consistent TB education. [See PDF for complete abstract]

Personalized Tuning of a Reinforcement Learning Control Algorithm for Glucose Regulation

Artificial pancreas is in the forefront of research towards the automatic insulin infusion for patients with type 1 diabetes. Due to the high inter- and intra-variability of the diabetic population, the need for personalized approaches has been raised. This study presents an adaptive, patient-specific control strategy for glucose regulation based on reinforcement learning and more specifically on the Actor-Critic (AC) learning approach. The control algorithm provides daily updates of the basal rate and insulin-to-carbohydrate (IC) ratio in order to optimize glucose regulation. A method for the automatic and personalized initialization of the control algorithm is designed based on the estimation of the transfer entropy (TE) between insulin and glucose signals. The algorithm has been evaluated in silico in adults, adolescents and children for 10 days. Three scenarios of initialization to i) zero values, ii) random values and iii) TE-based values have been comparatively assessed. The results have shown that when the TE-based initialization is used, the algorithm achieves faster learning with 98%, 90% and 73% in the A+B zones of the Control Variability Grid Analysis for adults, adolescents and children respectively after five days compared to 95%, 78%, 41% for random initialization and 93%, 88%, 41% for zero initial values. Furthermore, in the case of children, the daily Low Blood Glucose Index reduces much faster when the TE-based tuning is applied. The results imply that automatic and personalized tuning based on TE reduces the learning period and improves the overall performance of the AC algorithm.

Improving memory in elderly adults by instructing them in professional actors' learning strategies

This study examined a new type of cognitive intervention. For four weeks, participants (ages 65 to 82) were instructed in professional acting techniques, followed by rehearsal and performance of theatrical scenes. Although the training was not targeted in any way to the tasks used in pre- and post-testing, participants produced significantly higher recall and recognition scores after the intervention. It is suggested that the cognitive effort involved in analyzing and adopting theatrical characters' motivations (and then experiencing those characters' mental/emotional states during performance) is responsible for the observed improvement. A secondary strand of this study showed that participants who were given annotated scripts in which the implied goals of the characters were made explicit demonstrated significantly faster access to the stored material, as measured by a computer latency task.

The Role of BDNF, Leptin and Catecholamines in Reward Learning in Bulimia Nervosa

Background: A relationship between bulimia nervosa (BN) and reward-related behavior is supported by several lines of evidence. The dopaminergic dysfunctions in the processing of reward-related stimuli have been shown to be modulated by the neurotrophin brain derived neurotrophic factor (BDNF) and the hormone leptin. Methods: Using a randomized, double-blind, placebo-controlled, crossover design, a reward learning task was applied to study the behavior of 20 female subjects with remitted BN (rBN) and 27 female healthy controls under placebo and catecholamine depletion with alpha-methyl-para-tyrosine (AMPT). The plasma levels of BDNF and leptin were measured twice during the placebo and the AMPT condition, immediately before and 1 h after a standardized breakfast. Results: AMPT-induced differences in plasma BDNF levels were positively correlated with the AMPT-induced differences in reward learning in the whole sample (p = 0.05). Across conditions, plasma BDNF levels were higher in rBN subjects compared to controls (diagnosis effect; p = 0.001). Plasma BDNF and leptin levels were higher in the morning before compared to after a standardized breakfast across groups and conditions (time effect; p < 0.0001). The plasma leptin levels were higher under catecholamine depletion compared to placebo in the whole sample (treatment effect; p = 0.0004). Conclusions: This study reports on preliminary findings that suggest a catecholamine-dependent association of plasma BDNF and reward learning in subjects with rBN and controls. A role of leptin in reward learning is not supported by this study. However, leptin levels were sensitive to a depletion of catecholamine stores in both rBN and controls.

DAT1 polymorphism determines L-DOPA effects on learning about others' prosociality.

Despite that a wealth of evidence links striatal dopamine to individualś reward learning performance in non-social environments, the neurochemical underpinnings of such learning during social interaction are unknown. Here, we show that the administration of 300 mg of the dopamine precursor L-DOPA to 200 healthy male subjects influences learning about a partners' prosocial preferences in a novel social interaction task, which is akin to a repeated trust game. We found learning to be modulated by a well-established genetic marker of striatal dopamine levels, the 40-bp variable number tandem repeats polymorphism of the dopamine transporter (DAT1 polymorphism). In particular, we found that L-DOPA improves learning in 10/10R genoype subjects, who are assumed to have lower endogenous striatal dopamine levels and impairs learning in 9/10R genotype subjects, who are assumed to have higher endogenous dopamine levels. These findings provide first evidence for a critical role of dopamine in learning whether an interaction partner has a prosocial or a selfish personality. The applied pharmacogenetic approach may open doors to new ways of studying psychiatric disorders such as psychosis, which is characterized by distorted perceptions of others' prosocial attitudes.

Testing the 'Learning for Sustainabiliy' Approach in a Training for Trainers: Contribution to new learning theory and approaches

Mainstreaming the LforS approach is a challenge due to dive rging institutional priorities, customs, and expectations of classically traine d staff. A workshop to test LforS theory and practice, and explore how to mainstream it, took place in a concrete context in a rural district of Mozambique, focusing on agricultural, forest and water resources. The evaluation showed that the principles of interaction applied pe rmitted to link rational know ledge with practical experience through mutual learning and iterative self-reflection. The combination of learning techniques was considered usef ul; participants called for further opportunities to apply the LforS methodology, proposing next steps.

Context Aware e-Learning Objects and their Types from the Perspective of the Object-Oriented Paradigm

The contribution of this article demonstrates how to identify context-aware types of e-Learning objects (eLOs) derived from the subject domains. This perspective is taken from an engineering point of view and is applied during requirements elicitation and analysis relating to present work in constructing an object-oriented (OO), dynamic, and adaptive model to build and deliver packaged e-Learning courses. Consequently, three preliminary subject domains are presented and, as a result, three primitive types of eLOs are posited. These types educed from the subject domains are of structural, conceptual, and granular nature. Structural objects are responsible for the course itself, conceptual objects incorporate adaptive and logical interoperability, while granular objects congregate granular assets. Their differences, interrelationships, and responsibilities are discussed. A major design challenge relates to adaptive behaviour. Future research addresses refinement on the subject domains and adaptive hypermedia systems.

Decision Support Models for Composing and Navigating through e-Learning Objects

Libraries of learning objects may serve as basis for deriving course offerings that are customized to the needs of different learning communities or even individuals. Several ways of organizing this course composition process are discussed. Course composition needs a clear understanding of the dependencies between the learning objects. Therefore we discuss the metadata for object relationships proposed in different standardization projects and especially those suggested in the Dublin Core Metadata Initiative. Based on these metadata we construct adjacency matrices and graphs. We show how Gozinto-type computations can be used to determine direct and indirect prerequisites for certain learning objects. The metadata may also be used to define integer programming models which can be applied to support the instructor in formulating his specifications for selecting objects or which allow a computer agent to automatically select learning objects. Such decision models could also be helpful for a learner navigating through a library of learning objects. We also sketch a graph-based procedure for manual or automatic sequencing of the learning objects.

From Concrete to Abstract: Teaching for Transfer of Learning when Using Manipulatives

One of the most important uses of manipulatives in a classroom is to aid a learner to make connection from tangible concrete object to its abstraction. In this paper we discuss how teacher educators can foster deeper understanding of how manipulatives facilitate student learning of math concepts by emphasizing the connection between concrete objects and math symbolization with, preservice elementary teachers, the future implementers of knowledge. We provide an example and a model, with specific steps of how teacher educators can effectively demonstrate connections between concrete objects and abstract math concepts.

Learning about Self Far From Home: A Pre-service Teacher’s Intercultural Development During an International Program

Preparing teachers to effectively teach culturally diverse students, teacher educators advocate for the use of cross-cultural field experiences, including international study abroad programs. This paper reports on a qualitative case study of two pre-service teachers’ intercultural development during a semester-long teacher education study abroad program in London, England. Findings indicate that international experiences provide a catalyst to move pre-service teachers forward in their intercultural development. Implications include the need for multicultural teacher educators to take a developmental approach to pre-service teacher education informed by theories of intercultural development and cultural learning developed within intercultural communications.

Commentary on "Expanded Learning Time in Schools"

As co-founder of KIPP, I know from experience and research that more time in school works. A well-designed extended-time program can help underserved students catch up academically, and prepare them for the rigors of higher education. Implementing extended time more widely poses challenges, but there are also creative solutions to these challenges.

A Step in the Right Direction: Development of the Computerized Assessment for Preschool Social Emotional Learning (CAPSEL)

Invited commentary on "Computerizing Social-Emotional Assessment for School Readiness".

Computerizing Social-Emotional Assessment for School Readiness: First Steps toward an Assessment Battery for Early Childhood Settings

The transition into formal schooling is a crucial foundation that can set children on a cycle of success or failure in both academic and social domains. A child’s abilities to express healthy emotions, understand emotions of self and others, regulate emotion, attention, and behavior, make good decisions regarding social problems, and engage in a range of prosocial behaviors, all work together to promote a successful school experience. However, many children have deficits in these skills by school entry, and educators lack the requisite tools to identify, track and assess skills these children need to learn. Thus, because social-emotional learning (SEL) is so crucial, assessment tools to pinpoint children’s skills and progress are vitally necessary. Previous work by the authors and other researchers has led to the development of strong assessment tools; however, these tools are often developed solely for research use, not practitioner application. In the following, using our assessment battery as an example, we will discuss the steps necessary to adapt SEL assessment for computer-based administration and optimal utility in early childhood education programs.