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.     

The Relationship Between Tutoring Mode and Learners’ use of Help Tools in Distance Education

This article presents an experimental study demonstrating how 120 learners use help tools in a virtual learning set-up. More specifically, several types of tutoring are investigated to find out the extent of the use of help tools in each. The effects of two independent variables which may have an impact on the behaviour of learners are studied: (1) whether or not they have access to a human tutor (HT) and (2) the tutor’s means of intervention (reactive or proactive). One of the goals of the study is to determine whether these modes of tutoring can influence positively or negatively distance learners’ use of lexical, conceptual, metacognitive and navigational help tools. The results of analysis of variance show that it is useless to prompt (effect of proactivity) learners to use the help that is available to them but that prompting is sometimes more subtle than initially foreseen. It appears that the presence of an HT pushes learners to use help tools, but this effect (of the presence of the HT) is still relatively weak and therefore may not justify the cost of employing a human tutor. It is also important to show the necessary intrinsic quality of the tools made available in order for a given mode of tutoring to have an effect on their use.     

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.     

Graduated substrata

A graduated substratum is a graphic representation corresponding to the support of a discrete fuzzy set: It is a set of granulations whose diameters are proportional to the membership values of the respective elements they represent. It is used to represent graphically the notions (relation, construction of a relation, application of the mapping rule) developed by Zadeh to apply fuzzy set theory to pattern classification. A connection with neurophysiology is proposed in the form of the identification: Fuzzy set &z.tbnd; Graduated substratum Activated neural population.     

The place of emotions while inspecting schools: reflections of two Ofsted inspectors

This article investigates the role of emotions of inspectors while inspecting schools as reported by inspectors themselves within an education context of increased accountability that arguably privileges rationality over emotions. The study is built on an emotion management framework that regards emotions not only as unavoidably natural and intimately linked to ‘rational’ judgements that people make, but also that such judgements are social constructions used to regulate expression of emotions. In-depth interview data of one retired and another, semi-retired Office for Standards in Education, inspectors were thematically analysed to assess the extent to which their emotions formed part of school inspections. In the absence of an officially sanctioned narrative of inspectors’ emotions during inspections, two kinds of self-prescribed emotions emerged as key findings: emotions for accountability, to which inspectors gave expression, and emotions for improvement, that they suppressed. For an inspection body that needs to ensure both accountability and improvement of schools to justify its viability, these research claims open up a new area of discussion that should lead to a review of inspection body’s stance on emotions and individual inspectors’ self-reflections on the moral as well as professional obligation to pursue both emotions for accountability and improvement.     

On the robustness of Riccati flows to complete model misspecification

Consider the continuous-time matrix Riccati operator Ricc$\left(Q\right)=AQ+Q{A}^{\prime }?QSQ+R$. In this work, we consider the robustness of this operator to direct perturbations of the matrices (A, R, S) and, in particular, the flow robustness of the corresponding Riccati differential equation. For a given class of perturbation, we show that the corresponding differential equation is well defined in the sense it is bounded above and below, it has a well-defined fixed point, and it converges to this fixed point exponentially fast. Moreover, the flow of the perturbed Riccati flow is close to the nominal Riccati flow when the perturbation is small; i.e. we prove a continuity-type condition in the size of the perturbation.