The teaching of reading in New Zealand special classes : a thesis submitted for the degree of Master of Arts in education

All too frequently the standard work on reading disability dismisses the problem of the slow-learning child in a few lines. Few authorities on reading have attempted to trace, systematically, the implications of their reading research for the child of low intelligence. As a teacher of special class children I feel that one is only free to experiment with the practical and social aspects of special education when a systematic programme, adapted to the needs of low intelligence children, has minimised the difficulties of academic instruction.

The teaching of reading in New Zealand special classes

All too frequently the standard work on reading disability dismisses the problem of the slow-learning child in a few lines. Few authorities on reading have attempted to trace, systematically, the implications of their reading research for the child of low intelligence. As a teacher of special class children I feel that one is only free to experiment with the practical and social aspects of special education when a systematic programme, adapted to the needs of low intelligence children, has minimised the difficulties of academic instruction.

The teaching of reading in New Zealand special classes

All too frequently the standard work on reading disability dismisses the problem of the slow-learning child in a few lines. Few authorities on reading have attempted to trace, systematically, the implications of their reading research for the child of low intelligence. As a teacher of special class children I feel that one is only free to experiment with the practical and social aspects of special education when a systematic programme, adapted to the needs of low intelligence children, has minimised the difficulties of academic instruction.

Reducing the Soleus Stretch Reflex With Conditioning: Exploring Game- and Impedance-Based Biofeedback

People with spasticity, i.e., stretch hyperreflexia, have a limited functional independence and mobility. While a broad range of spasticity treatments is available, many treatments are invasive, non-specific, or temporary and might have negative side effects. Operant conditioning of the stretch reflex is a promising non-invasive paradigm with potential long-term sustained effects. Within this conditioning paradigm, seated participants have to reduce the mechanically elicited reflex response using biofeedback of reflex magnitude quantified using electromyography (EMG). Before clinical application of the conditioning paradigm, improvements are needed regarding the time-intensiveness and slow learning curve. Previous studies have shown that gamification of biofeedback can improve participant motivation and long-term engagement. Moreover, quantification of reflex magnitude for biofeedback using reflexive joint impedance may obtain similar effectiveness within fewer sessions. Nine healthy volunteers participated in the study, split in three groups. First, as a reference the “Conventional” group received EMG- and bar-based biofeedback similar to previous research. Second, we explored feasibility of game-based biofeedback with the “Gaming” group receiving EMG- and game-based biofeedback. Third, we explored feasibility of game- and impedance-based biofeedback with the “Impedance” group receiving impedance and game-based biofeedback. Participants completed five baseline sessions (without reflex biofeedback) and six conditioning sessions (with reflex biofeedback). Participants were instructed to reduce reflex magnitude without modulating background activity. The Conventional and Gaming groups showed feasibility of the protocol in 2 and 3 out of 3 participants, respectively. These participants achieved a significant Soleus short-latency (M1) within-session reduction in at least –15% in the 4th–6th conditioning session. None of the Impedance group participants showed any within-session decrease in Soleus reflex magnitude. The feasibility in the EMG- and game-based biofeedback calls for further research on gamification of the conditioning paradigm to obtain improved participant motivation and engagement, while achieving long-term conditioning effects. Before clinical application, the time-intensiveness and slow learning curve of the conditioning paradigm remain an open challenge.

Sensitivity to error during visuomotor adaptation is similarly modulated by abrupt, gradual and random perturbation schedules

It has been suggested that sensorimotor adaptation involves at least two processes (i.e., fast and slow) that differ in retention and error sensitivity. Previous work has shown that repeated exposure to an abrupt force field perturbation results in greater error sensitivity for both the fast and slow processes. While this implies that the faster relearning is associated with increased error sensitivity, it remains unclear what aspects of prior experience modulate error sensitivity. In the present study, we manipulated the initial training using different perturbation schedules, thought to differentially affect fast and slow learning processes based on error magnitude, and then observed what effect prior learning had on subsequent adaptation. During initial training of a visuomotor rotation task, we exposed three groups of participants to either an abrupt, a gradual, or a random perturbation schedule. During a testing session, all three groups were subsequently exposed to an abrupt perturbation schedule. Comparing the two sessions of the control group who experienced repetition of the same perturbation, we found an increased error sensitivity for both processes. We found that the error sensitivity was increased for both the fast and slow processes, with no reliable changes in the retention, for both the gradual and structural learning groups when compared to the first session of the control group. We discuss the findings in the context of how fast and slow learning processes respond to a history of errors.

The Effect of the Covid 19 Pandemic on the Online Learning Process

This study aims to determine the effect of the COVID-19 pandemic on the process of utilizing online learning. The informants consisted of 10 primary school teachers of Muhammadiyah 1 gempol. The implementation of online learning uses case studies with a qualitative approach. The results of this study revealed that inadequate facilities and infrastructure, less than optimal delivery of material, the burden of purchasing internet quota, internet connection that sometimes becomes slow, learning styles that tend to be visual, and the teacher's lack of flexibility in controlling student activities Learning at Muhammadiyah 1 Gempol Elementary School in this study uses online learning or commonly referred to as distance learning (from home) with the guidance of parents and teachers at school. Students do online learning and interact with teachers using several applications used such as Google Classroom, Zoom, Google Meet and Whatsapp Group.

Feedback From Facial Expressions Contribute to Slow Learning Rate in an Iowa Gambling Task

Facial expressions of emotion can convey information about the world and disambiguate elements of the environment, thus providing direction to other people’s behavior. However, the functions of facial expressions from the perspective of learning patterns over time remain elusive. This study investigated how the feedback of facial expressions influences learning tasks in a context of ambiguity using the Iowa Gambling Task. The results revealed that the learning rate for facial expression feedback was slower in the middle of the learning period than it was for symbolic feedback. No difference was observed in deck selection or computational model parameters between the conditions, and no correlation was observed between task indicators and the results of depressive questionnaires.

Learning Invariant Object and Spatial View Representations in the Brain Using Slow Unsupervised Learning

First, neurophysiological evidence for the learning of invariant representations in the inferior temporal visual cortex is described. This includes object and face representations with invariance for position, size, lighting, view and morphological transforms in the temporal lobe visual cortex; global object motion in the cortex in the superior temporal sulcus; and spatial view representations in the hippocampus that are invariant with respect to eye position, head direction, and place. Second, computational mechanisms that enable the brain to learn these invariant representations are proposed. For the ventral visual system, one key adaptation is the use of information available in the statistics of the environment in slow unsupervised learning to learn transform-invariant representations of objects. This contrasts with deep supervised learning in artificial neural networks, which uses training with thousands of exemplars forced into different categories by neuronal teachers. Similar slow learning principles apply to the learning of global object motion in the dorsal visual system leading to the cortex in the superior temporal sulcus. The learning rule that has been explored in VisNet is an associative rule with a short-term memory trace. The feed-forward architecture has four stages, with convergence from stage to stage. This type of slow learning is implemented in the brain in hierarchically organized competitive neuronal networks with convergence from stage to stage, with only 4-5 stages in the hierarchy. Slow learning is also shown to help the learning of coordinate transforms using gain modulation in the dorsal visual system extending into the parietal cortex and retrosplenial cortex. Representations are learned that are in allocentric spatial view coordinates of locations in the world and that are independent of eye position, head direction, and the place where the individual is located. This enables hippocampal spatial view cells to use idiothetic, self-motion, signals for navigation when the view details are obscured for short periods.

Fast and Slow Learning in Human-Like Intelligence

In this chapter we review the extent to which rapid one-short learning or fast-mapping exists in human learning. We find that it exists in both children and adults, but that it is almost always accompanied by slow consolidated learning in which new knowledge is integrated with existing knowledge-bases. Rapid learning is also present in a broad range of non-human species, particularly in the context of high reward values. We argue that reward prediction errors guide the extent to which fast or slow learning dominates, and present a Complementary Learning Systems neural network model (CTDL) of cortical/hippocampal learning that uses reward prediction errors to adjudicate between learning in the two systems. Developing human-like artificial intelligence will require implementing multiple learning and inference systems governed by a flexible control system with an equal capacity to that of human control systems.

Sensitivity to Error During Visuomotor Adaptation is Similarly Modulated by Abrupt, Gradual and Random Perturbation Schedules

It has been suggested that sensorimotor adaptation involves at least two processes (i.e., fast and slow) that differ in retention and error sensitivity. Previous work has shown that repeated exposure to an abrupt force field perturbation results in greater error sensitivity for both the fast and slow processes. While this implies that the faster relearning is associated with increased error sensitivity, it remains unclear what aspects of prior experience modulate error sensitivity. In the present study, we manipulated the initial training using different perturbation schedules, thought to differentially affect fast and slow learning processes based on error magnitude, and then observed what effect prior learning had on subsequent adaptation. During initial training of a visuomotor rotation task, we exposed three groups of participants to either an abrupt, a gradual, or a random perturbation schedule. During a testing session, all three groups were subsequently exposed to an abrupt perturbation schedule. Comparing the two sessions of the control group who experienced repetition of the same perturbation, we found an increased error sensitivity for both processes. We found that the error sensitivity was increased for both the fast and slow processes, with no reliable changes in the retention, for both the gradual and structural learning groups when compared to the first session of the control group. We discuss the findings in the context of how fast and slow learning processes respond to a history of errors.