Disentangling school leadership and its ties to instructional practices – an empirical comparison of various leadership styles

This paper investigates the direct and indirect ties between various leadership styles, namely, instructional, transformational, transactional, and laissez-faire leadership, and the instructional practices of teachers by applying a structural equation model. For this purpose, we analyzed survey data of n = 3,746 teachers from 126 schools collected by the Hamburg school inspection in Germany between 2012 and 2015. The underlying model is based on Leithwood’s framework for guiding research on leader effects on learning and instruction. First, the results show that a bi-factor model seems to be the best measurement model. Next, it is shown that mediating variables are influenced by a leadership core as well as by different leadership facets. Third, we found that for influencing complex instructional practices like cognitive activation with challenging content, a combination of leadership styles is most promising, while for classroom management instructional leadership is the only and, thus, the primary determinant.     

Latent semantic analysis as a tool for learner positioning in learning networks for lifelong learning

As we move towards distributed, self‐organised learning networks for lifelong learning to which multiple providers contribute content, there is a need to develop new techniques to determine where learners can be positioned in these networks. Positioning requires us to map characteristics of the learner onto characteristics of learning materials and curricula. Considering the nature of the network envisaged, maintaining data on these characteristics and ensuring their integrity are difficult tasks. In this article we review the usability of Latent Semantic Analysis (LSA) to generate a common semantic framework for characteristics of the learner, learning materials and curricula. Although LSA is a promising technique we identify several research topics that must be addressed before it can be used for learner positioning.     

A computational approach to socially distributed cognition

In most Interactive Learning Environments (ILEs), the human learner interacts with an expert in the domain to be taught. We explored a different approach: the system does not know more than the learner, but learns by interacting with him. A human-computer collaborative learning (HCCL) system includes a micro-world, in which two learners jointly try to solve problems and learn, the human learner and a computerized co-learner. This paper presents the foundations of this artificial co-learner. The collaboration between learners is modelled as “socially distributed cognition’ (SDC). The SDC model connects three ideas: (i) a group is a cognitive system, (ii) reflection is a dialogue with oneself, (iii) social processes are internalised. The key has been to find a computational connection between those ideas. The domain chosen for illustration is the argumentation concerning how some changes to an electoral system affect the results of elections. This argumentation involves a sequence of arguments and their refutations. The basic principle is that learners ‘store’ the structure of this argumentation (dialogue pattern) and ‘replay’ it individually later on. The verbs ‘store’ and ‘replay’ do not refer to a simple ‘record and retrieve’ process. Storage is implemented as the incremental and parameterised evolution of a network of arguments, here called a ‘dialogue pattern’. The learning outcome is a structuration of knowledge (rules) into situation-specific models, used to guide reasoning. We conducted experiments in two settings: with a human and an artificial learner or with two artificial learners. The common findings of these two experiments is that the SDC model generates learning effects provided that the discussion is intensive, i.e. that many arguments are brought into dialogue. The importance of this variable also appears in Hutchins’ (1991) modelling of the evolution of the confirmation bias in groups. It is argued than computational models are heuristic tools, allowing researchers to isolate variables for designing empirical studies with human subjects.     

Comparative study of the cognitive sequelae of school-aged victims of Shaken Baby Syndrome

OBJECTIVE: Shaken Baby Syndrome (SBS) is now recognized as being the main cause of severe traumatic brain injury in infancy. However, our understanding of the impact of this type of abuse on child development remains sketchy. The main objective of the current study was therefore to shed light on the cognitive dysfunctions that are particular to SBS victims once they are school-aged. METHOD: A clinical group was formed of 11 children diagnosed with SBS who had been admitted between 1988 and 1999 to a tertiary pediatric hospital in Quebec, Canada. The children were matched for age, gender, socio-economic status, and family composition to 11 healthy Quebec children, who made up the control group. A battery of composite tests was developed to assess the children's main cognitive functions and was administered individually to the 22 children. A univariate t-test was used to compare the performances of the two groups. RESULTS: The mean age of the children in the clinical and control groups at the time of the assessment was 87.64 months and 90.18 months, respectively. Pairing and birth data were equivalent for both groups. Significant weaknesses were noted in the clinical group for intelligence quotient (IQ), working memory, mental organization, alternation, and inhibition. These deficits seemed to have a greater impact on the verbal sphere of the children's mental functioning. CONCLUSION: Primary results point to the anterior cerebral regions of the brain as the principal site of dysfunctions that persist years post-trauma. It is important to consider these results longitudinally, even in children apparently less extensively affected, since the frontal regions only reach maturity at the end of adolescence.     

Accurate DRL performance in the pigeon: Comparison between perching and treadle pressing

Homing pigeons were reinforced for emitting a perching response according to differential-reinforcement-of-low-rate (DRL) schedules. The spacing requirement between successive perchings was progressively increased by 1-sec steps up to 70 sec and then abruptly decreased to 60, 40, and 20 sec. IRT/OP (interresponse time/opportunity) functions were maximal near the time of reinforcement. The coefficients of variation of the IRT distributions (ratio between the interquartile range and median IRT) fluctuated around .32, testifying for equivalent levels of adjustment throughout the critical IRT range. The ratio between reinforced and total IRTs ranged between .90 and .20. These data contrast with the performance of another group of pigeons reinforced for a treadle-pressing response according to DRL schedules (flatter IRT/OP functions, high coefficients of variation, and low efficiencies). Despite these differences in temporal regulation between perching and treadle-pressing DRL, response rates and reinforcement rates followed the same trend in both cases: they decreased as schedule value increased. The DRL perching results are similar to previous results obtained in the same species when perching duration was reinforced.