Early adolescents’ enjoyment experienced in learning situations at school and its relation to student achievement

While many studies confirm that positive emotions, including enjoyment, lead to better student achievement, less empirical evidence exists about possible mediator variables that link achievement to enjoyment. It is proposed that achievement and enjoyment form a circular dependency; enjoyment in learning leads to higher achievement but a degree of achievement is required to enjoy learning. This study provides insight into the reverse of the much studied enjoyment to achievement link and provides practical recommendations on how to use these findings. Founded in Control-value theory, which suggests that control and value cognitions are important variables that mediate the connection between enjoyment and achievement, this study explores the reciprocal achievement-cognition-enjoyment link. The reciprocal link was investigated by applying a one year longitudinal design to students of grade 6 and 7 (N = 356). This age group was chosen because early adolescence represents a critical period during which a strong decrease in positive learning emotions is observed. Part of the work involved identifying factors that might be responsible for this negative development. Results of cross-lagged path analysis identified reciprocal effects between student achievement and enjoyment with control and value cognitions functioning as partial mediators. High achievement goes with high control and value cognitions, which in turn positively affect enjoyment. However, cross-lagged correlations could only be partly confirmed. The results are discussed in terms of theoretical and practical implications

Statistical Learning, Syllable Processing, and Speech Production in Healthy Hearing and Hearing-Impaired Preschool Children: A Mismatch Negativity Study

OBJECTIVES The objectives of the present study were to investigate temporal/spectral sound-feature processing in preschool children (4 to 7 years old) with peripheral hearing loss compared with age-matched controls. The results verified the presence of statistical learning, which was diminished in children with hearing impairments (HIs), and elucidated possible perceptual mediators of speech production. DESIGN Perception and production of the syllables /ba/, /da/, /ta/, and /na/ were recorded in 13 children with normal hearing and 13 children with HI. Perception was assessed physiologically through event-related potentials (ERPs) recorded by EEG in a multifeature mismatch negativity paradigm and behaviorally through a discrimination task. Temporal and spectral features of the ERPs during speech perception were analyzed, and speech production was quantitatively evaluated using speech motor maximum performance tasks. RESULTS Proximal to stimulus onset, children with HI displayed a difference in map topography, indicating diminished statistical learning. In later ERP components, children with HI exhibited reduced amplitudes in the N2 and early parts of the late disciminative negativity components specifically, which are associated with temporal and spectral control mechanisms. Abnormalities of speech perception were only subtly reflected in speech production, as the lone difference found in speech production studies was a mild delay in regulating speech intensity. CONCLUSIONS In addition to previously reported deficits of sound-feature discriminations, the present study results reflect diminished statistical learning in children with HI, which plays an early and important, but so far neglected, role in phonological processing. Furthermore, the lack of corresponding behavioral abnormalities in speech production implies that impaired perceptual capacities do not necessarily translate into productive deficits.

Addressing Multilevel Program Complexity by Evaluation Design

In this paper, we present the evaluation design for a complex multilevel program recently introduced in Switzerland. The evaluation embraces the federal level, the cantonal program level, and the project level where target groups are directly addressed. We employ Pawson and Tilley’s realist evaluation approach, in order to do justice to the varying context factors that impact the cantonal programs leading to varying effectiveness of the implemented activities. The application of the model to the canton of Uri shows that the numerous vertical and horizontal relations play a crucial role for the program’s effectiveness. As a general learning for the evaluation of complex programs, we state that there is a need to consider all affected levels of a program and that no monocausal effects can be singled out in programs where multiple interventions address the same problem. Moreover, considering all affected levels of a program can mean going beyond the borders of the actual program organization and including factors that do not directly interfere with the policy delivery as such. In particular, we found that the relationship between the cantonal and the federal level was a crucial organizational factor influencing the effectiveness of the cantonal program.

Differentiating the Multipoint Expected Improvement for Optimal Batch Design

This work deals with parallel optimization of expensive objective functions which are modelled as sample realizations of Gaussian processes. The study is formalized as a Bayesian optimization problem, or continuous multi-armed bandit problem, where a batch of q > 0 arms is pulled in parallel at each iteration. Several algorithms have been developed for choosing batches by trading off exploitation and exploration. As of today, the maximum Expected Improvement (EI) and Upper Confidence Bound (UCB) selection rules appear as the most prominent approaches for batch selection. Here, we build upon recent work on the multipoint Expected Improvement criterion, for which an analytic expansion relying on Tallis’ formula was recently established. The computational burden of this selection rule being still an issue in application, we derive a closed-form expression for the gradient of the multipoint Expected Improvement, which aims at facilitating its maximization using gradient-based ascent algorithms. Substantial computational savings are shown in application. In addition, our algorithms are tested numerically and compared to state-of-the-art UCB-based batchsequential algorithms. Combining starting designs relying on UCB with gradient-based EI local optimization finally appears as a sound option for batch design in distributed Gaussian Process optimization.

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.