Learning at the workplace and sustainable employability: a multi-source model moderated by age

This study, among 330 pairs of employees and their supervisors, tested whether self- versus supervisor ratings of five employability dimensions (occupational expertise, corporate sense, personal flexibility, anticipation and optimization, and balance) are associated with different learning characteristics in the workplace, and whether age moderates these relationships. Results of structural equation modelling showed that the learning value of the job positively related to both self- and supervisor ratings of corporate sense, personal flexibility, and anticipation and optimization. Applicability in the job of recently followed training and development programmes was associated with all dimensions of self-rated employability and with supervisor ratings of anticipation and optimization. Regarding the hypothesized age moderation effects, contrary to our expectations, it was found that both learning value and applicability of training and development related more strongly to self-rated anticipation and optimization for younger workers. In addition, age appeared to moderate the otherwise non-significant relationship between learning value and self-rated occupational expertise. Implications for Human Resource Development (HRD) practices are discussed. As learning characteristics are differentially related to the unique employability dimensions, tailor-made development programmes are key. Moreover, it is advocated that having a job with a high learning value is an important factor in the light of the employee’s sustainable employability.     

Perspective on “in the wild” movement analysis using machine learning

Recent advances in wearable sensing and machine learning have created ample opportunities for “in the wild” movement analysis in sports, since the combination of both enables real-time feedback to be provided to athletes and coaches, as well as long-term monitoring of movements. The potential for real-time feedback is useful for performance enhancement or technique analysis, and can be achieved by training efficient models and implementing them on dedicated hardware. Long-term monitoring of movement can be used for injury prevention, among others. Such applications are often enabled by training a machine learned model from large datasets that have been collected using wearable sensors. Therefore, in this perspective paper, we provide an overview of approaches for studies that aim to analyze sports movement “in the wild” using wearable sensors and machine learning. First, we discuss how a measurement protocol can be set up by answering six questions. Then, we discuss the benefits and pitfalls and provide recommendations for effective training of machine learning models from movement data, focusing on data pre-processing, feature calculation, and model selection and tuning. Finally, we highlight two application domains where “in the wild” data recording was combined with machine learning for injury prevention and technique analysis, respectively.     

The value of reflective journaling with advanced piano students

Benefits to using a reflective journal include developing critical awareness and new perspective, problem-solving skills, and independent learning skills. The training of advanced piano students could be enhanced by the addition of journals to assist with their piano practice, specifically when learning new repertoire. Using the model by Plack and colleagues for developing and assessing reflection in reflective journal entries, we examined the journal entries of 18 advanced piano students to explore the development of reflection over a period of four weeks. Results suggest that reflectively trained piano students develop more critical reflection compared to a control group. Reflectively trained students perceive the same benefits to journaling as their counterparts in other disciplines. The most frequently referenced reflective elements include listing practice strategies and expressing feelings about the learning process. The reflective training model used in this study can be implemented by piano teachers and piano students.     

Learning from Our Mistakes: Error Management Training for Mature Learners

This research explored the effects of training goal (learning goal vs. performance goal) and training type (error management vs. error avoidance) on word processing skill acquisition with older workers. Sixty-seven participants were randomly assigned to one of four experimental conditions and attended two interactive tutorial training sessions. Results indicated that error management training lead to significantly higher performance test scores, learning quiz scores, and requests for assistance compared to error avoidant training. Additionally, learning goals generated significantly higher performance test scores and intrinsic motivation levels relative to performance goals. Other applications of error management training are discussed.     

Learning Psychoanalysis: A Classification Based on Students' Learning Trajectories

This study was undertaken in an effort to sharpen selection procedures and improve faculty response to the learning needs of students. Eschewing a traditional anticipatory approach in determining suitability for training, the authors undertook a retrospective study to investigate the learning trajectories of candidates. A learning trajectory is defined as the particular way individuals learn, or fail to learn, as they advance through an Institute's training program. The database of this study grew out of the authors' experience with students in classrooms, in supervision, and from discussions about them in Progression, Selection, and The Evaluation of Learning committees. Realizing the reductionism of categorizing a highly complex and diverse group of individuals, the authors, nonetheless, found that candidates tended to group into five rather distinct categories. This paper discusses in detail the characteristics of these five categories and suggests ways in which this grouping may help in both selection and in planning more effective training for candidates. The authors are fully aware that this study has impressionistic qualities and warrants more rigorous research methods, but hope that it will arouse interest in other psychoanalytic centers and stimulate studies to corroborate, refine, or reject the conclusions reached by this group.     

A temporal common ground for learning: The moderating effect of shared mental models on the relation between team learning behaviours and performance improvement

In this longitudinal study, we integrated a team process and a learning curve perspective on team learning and empirically analysed whether team learning processes lead to performance improvement. In addition, we tested whether this relation is moderated by the similarity of team members’ task, team, and temporal mental models. We tested our model on a sample of 67 teams (314 individuals) competing in a management simulation over five consecutive time periods, using random coefficient modelling (RCM). Our findings suggest that team learning behaviours do not have a direct effect on the team learning curve, but temporal and task mental models are crucial for the translation of team learning behaviours into performance improvement. We found that when teams have similar task and temporal mental models, engaging in team learning processes is beneficial, whereas, when teams have dissimilar task and temporal mental models, it is detrimental to performance improvement. We did not find a significant effect for the moderating role of team mental model similarity. Our study emphasizes the importance of integrating different perspectives on team learning and provides support for the role of team cognition as a catalyst for team learning.     

高中生正念与学习倦怠：基于自我调节学习模型的视角

基于自我调节学习模型的视角,探究正念对高中生学习倦怠的影响,采用正念注意觉知量表、生命意义感量表、津巴多时间洞察力问卷和青少年学习倦怠量表调查863名高中生。结果表明：（1）正念对高中生学习倦怠具有负向预测作用;（2）正念通过未来时间洞察力与生命意义感的独立中介作用及未来时间洞察力与生命意义感的链式中介作用间接影响学习倦怠。因此,正念可以负向预测高中生学习倦怠,提升未来时间洞察力与生命意义感可以缓解高中生学习倦怠,促进高中生身心健康。     

人工语法学习中意识加工的渐进发展

内隐学习研究致力于探讨学习活动的意识加工程度, 当前相关的研究逻辑从传统的意识二分观转向渐进意识假设。本研究通过对人工语法范式进行改造, 并借鉴加工分离程序的有关思想, 在学习阶段引入双重测量任务, 并根据双重任务成绩计算分离出相应学习时段的意识与无意识成分的贡献分数, 从而考察在内隐学习过程中两种加工成分的动态变化特征。研究结果支持渐进意识假设, 在学习进程中, 无意识成分和意识成分都呈现出渐进发展的趋势; 而随学习的深入, 两种成分呈现出不同的变化模式, 中后期意识加工快速增长, 无意识加工则保持平缓发展, 渐进意识系统整体呈现向外显学习推进的发展态势。     

Conceptual complexity and the bias/variance tradeoff

In this paper we propose that the conventional dichotomy between exemplar-based and prototype-based models of concept learning is helpfully viewed as an instance of what is known in the statistical learning literature as the bias/variance tradeoff. The bias/variance tradeoff can be thought of as a sliding scale that modulates how closely any learning procedure adheres to its training data. At one end of the scale (high variance), models can entertain very complex hypotheses, allowing them to fit a wide variety of data very closely—but as a result can generalize poorly, a phenomenon called overfitting. At the other end of the scale (high bias), models make relatively simple and inflexible assumptions, and as a result may fit the data poorly, called underfitting. Exemplar and prototype models of category formation are at opposite ends of this scale: prototype models are highly biased, in that they assume a simple, standard conceptual form (the prototype), while exemplar models have very little bias but high variance, allowing them to fit virtually any combination of training data. We investigated human learners’ position on this spectrum by confronting them with category structures at variable levels of intrinsic complexity, ranging from simple prototype-like categories to much more complex multimodal ones. The results show that human learners adopt an intermediate point on the bias/variance continuum, inconsistent with either of the poles occupied by most conventional approaches. We present a simple model that adjusts (regularizes) the complexity of its hypotheses in order to suit the training data, which fits the experimental data better than representative exemplar and prototype models.     

Human vs. supervised machine learning: Who learns patterns faster?

The capabilities of supervised machine learning (SML), especially compared to human abilities, are being discussed in scientific research and in the usage of SML. This study provides an answer to how learning performance differs between humans and machines when there is limited training data. We have designed an experiment in which 44 humans and three different machine learning algorithms identify patterns in labeled training data and have to label instances according to the patterns they find. The results show a high dependency between performance and the underlying patterns of the task. Whereas humans perform relatively similarly across all patterns, machines show large performance differences for the various patterns in our experiment. After seeing 20 instances in the experiment, human performance does not improve anymore, which we relate to theories of cognitive overload. Machines learn slower but can reach the same level or may even outperform humans in 2 of the 4 of used patterns. However, machines need more instances compared to humans for the same results. The performance of machines is comparably lower for the other 2 patterns due to the difficulty of combining input features.     

Caring and the Graduate Student: A Phenomenological Study

Given the increasing numbers of adult learners on university campuses, both as undergraduates and graduates, an understanding of adult learning processes is relevant—indeed essential—to the university's response to this student group. While educators have attempted to understand learners in terms of developmental stages, learning styles, and contextual factors, less attention has focused on the dynamics of helping relationships that attend learning or the importance of caring in the learning process. The purpose of this phenomenological study was to explore and explicate the experience of caring as it relates to graduate education from the perspective of the graduate student. The connection between caring relationships and learning was confirmed. Seven components of the caring were identified. Implications for the university center on attention to relationship skills and the creation of a campus community in which caring relationships are encouraged and nurtured.     

Transfer as the productive use of acquired knowledge, skills, and motivations

Historically, the notion of transfer has been very controversial, conceptually as well as empirically. Therefore, there is an obvious need for further inquiry aimed at a better understanding of the processes underlying transfer. Taking into account the recent literature, this article defines transfer as the broad, productive, and supported use of acquired knowledge, skills, and motivations in new contexts and learning tasks. As an illustration, an intervention study is briefly discussed. This study shows the possibility of designing a powerful learning environment that yields transfer effects in accordance with this reconceptualized perspective on transfer.     

汉字频率和构词数对非汉字圈学生汉字学习的影响

探讨汉字频率和构词数对非汉字文化圈的留学生汉字学习效果的影响。实验要求被试对已学过的不同频率和构词数的汉字写出拼音并组词,结果显示,汉字频率对汉字学习效果有影响,而且频率效应的大小受笔画数的制约;实验未发现构词数对汉字学习效果的影响。研究结果表明,语言输入的频率是影响汉语习得的一个重要因素     

Unconscious reward facilitates motion perceptual learning

Reward signal plays an important role in guiding human learning behaviour. Recent studies have provided evidence that reward signal modulates perceptual learning of basic visual features. Typically, the reward effects on perceptual learning were accompanied with consciously presented reward during the learning process. However, whether an unconsciously presented reward signal that minimizes the contribution of attentional and motivational factors can facilitate perceptual learning remains less well understood. We trained human subjects on a visual motion detection task and subliminally delivered a monetary reward for correct response during the training. The results showed significantly larger learning effect for high reward-associated motion direction than low reward-associated motion direction. Importantly, subjects could neither discriminate the relative values of the subliminal monetary reward nor correctly report the reward-direction contingencies. Our findings suggest that reward signal plays an important modulatory role in perceptual learning even if the magnitude of the reward was not consciously perceived.     

Ecological Neuropsychology: An Alternative to the Deficit Model for Conceptualizing and Serving Students with Learning Disabilities

The present paper contends that children with learning disabilities are better served when assessment and intervention are conceptualized within an ecological neuropsychology perspective than within the traditional deficit model perspective, which is the predominant approach to intervention in medical and educational settings. The deficit method conceptualizes problems as within the child, and the major consequence of this approach is that little time is spent analyzing the learning environment or other systems that might impact the child's ability to be successful in an academic setting. Therefore, rehabilitation efforts have had limited success. In contrast, ecological neuropsychology is a strength-based approach that considers the child, as well as the systems within which he/she interacts, when assessing, diagnosing, and intervening with students who are experiencing learning difficulties.     

Psychosocial job strain and productivity in human service workers: A test of the demand-control-support model

The aim of the study was to test the main and interactive effects of the key dimensions of the demand-control-support model in predicting levels of strain (specifically emotional exhaustion, depersonalization and job dissatisfaction) and feelings of productivity and competency (personal accomplishment) in a multi-occupational sample of human service workers (N = 813). Controlling for demographics, negative affectivity (NA), and quadratic terms, structural equation analyses showed some support for the additive iso-strain hypothesis: jobs combining high demands, low control and low support produced the lowest levels of satisfaction in workers. High demands and low supports only were associated with high depersonalization, and high emotional exhaustion. Support was also found for the additive active learning hypotheses: jobs combining high demands and high control produced the highest levels of personal accomplishment. The study supports job redesign interventions for improving worker well-being and productivity.     

Categorization,concept learning,and behavior analysis: an introduction

Categorization and concept learning encompass some of the most important aspects of behavior, but historically they have not been central topics in the experimental analysis of behavior. To introduce this special issue of the Journal of the Experimental Analysis of Behavior (JEAB), we define key terms; distinguish between the study of concepts and the study of concept learning; describe three types of concept learning characterized by the stimulus classes they yield; and briefly identify several other themes (e.g., quantitative modeling and ties to language) that appear in the literature. As the special issue demonstrates, a surprising amount and diversity of work is being conducted that either represents a behavior-analytic perspective or can inform or constructively challenge this perspective.     

Promoting teachers’ agency: reflective practice as transformative disposition

Reflective practice has been criticised for having become a standardised method in teacher education and on-the-job training, oftentimes following routines that more likely turn out to be self-affirming than to actually foster change. Also, reflective practice is still widely understood as an individual process. Both aspects are considered problematic and are addressed by employing an activity-theoretical approach that is suggested to be essentially compatible with an existentialist perspective on reflective practice as offered by Thompson and Pascal. Utilising the theory of expansive learning, formative interventionist methodology is proposed to provide a robust framework for developing collaborative and critical reflective practice, which in turn reveals the transformative potential of teachers’ agency, as illustrated by a study accompanying and supporting the development of an Austrian secondary school.     

Perceptual learning effect on decision and confidence thresholds

Practice can enhance of perceptual sensitivity, a well-known phenomenon called perceptual learning. However, the effect of practice on subjective perception has received little attention. We approach this problem from a visual psychophysics and computational modeling perspective. In a sequence of visual search experiments, subjects significantly increased the ability to detect a “trained target”. Before and after training, subjects performed two psychophysical protocols that parametrically vary the visibility of the “trained target”: an attentional blink and a visual masking task. We found that confidence increased after learning only in the attentional blink task. Despite large differences in some observables and task settings, we identify common mechanisms for decision-making and confidence. Specifically, our behavioral results and computational model suggest that perceptual ability is independent of processing time, indicating that changes in early cortical representations are effective, and learning changes decision criteria to convey choice and confidence.