Helsinki University of Technology

About: Helsinki University of Technology is a based out in . It is known for research contribution in the topics: Artificial neural network & Finite element method. The organization has 8962 authors who have published 20136 publications receiving 723787 citations. The organization is also known as: TKK & Teknillinen korkeakoulu.

Why students drop out CS1 course

Abstract: This study focuses on CS minor students' decisions to drop out from the CS1 course. The high level of drop out percentage has been a problem at Helsinki University of Technology for many years. This course has yearly enrolment of 500-600 students and the drop out percentage has varied from 30-50 percents.Since we did not have clear picture of drop out reasons we conducted a qualitative interview research in which 18 dropouts from the CS1 course were interviewed. The reasons of drop out were categorized and, in addition, each case was investigated individually. This procedure enabled us to both list the reasons and to reveal the cumulative nature of drop out reasons.The results indicate that several reasons affect students' decision to quit the CS1 course. The most frequent reasons were the lack of time and the lack of motivation. However, both of these reasons were in turn affected by factors, such as the perceived difficulty of the course, general difficulties with time managing and planning studies, or the decision to prefer something else. Furthermore, low comfort level and plagiarism played a role in drop out. In addition, drop out reasons cumulated.This study shows that the complexity and large variety of factors involved in students' decision to drop the course. This indicates that simple actions to improve teaching or organization on a CS1 course to reduce drop out may be ineffective. Efficient intervention to the problem apparently requires a combination of many different actions that take into consideration the versatile nature of reasons involved in drop out.

Developing integrated solution offerings for remote diagnostics: A comparative case study of two manufacturers

Abstract: Purpose – This paper analyzes two manufacturing firms entering condition based maintenance business reveals the complex nature of establishing integrated solutions. Existing literature on integrate ...

Task-dependent modulation of 15-30 Hz coherence between rectified EMGs from human hand and forearm muscles

Abstract: The planning and execution of movements involve areas of the cerebral cortex that are separated in their activity both temporally and spatially. However, the mechanism by which these areas combine to produce a co-ordinated movement is unknown. Studies of the activity of neurones in the sensorimotor cortex in monkeys and humans have shown synchronous oscillatory activity in the 15-30 Hz range (Murthy & Fetz, 1992, 1996a; Sanes & Donoghue, 1993; Stancak & Pfurtscheller, 1996; Baker et al. 1997; Donoghue et al. 1998). These synchronous oscillations have been suggested to link the disparate motor signals together in a manner analogous to the perceptual ‘binding’ of stimulus attributes in the visual cortex (Singer & Gray, 1995), where the observed neuronal synchronization is attributed to neurones that participate in the encoding of related information. Sanes & Donoghue (1993) and Murthy & Fetz (1996a) have shown that oscillations in monkey sensorimotor cortex are synchronous over large distances (up to 14 mm), suggesting the involvement of large neuronal populations. However, Murthy & Fetz (1996b) concluded that the oscillatory episodes had no consistent relationship with a variety of motor tasks, and suggested that rather than being involved directly in ‘binding’ during movement execution, the oscillations could be a neuronal correlate of attention during sensorimotor tasks. By contrast, a number of studies have shown that 15-30 Hz oscillations recorded over the sensorimotor cortex in man disappear during a self-paced finger movement, but reappear following movement completion (Jasper & Penfield, 1949; Gastaut, 1952; Salmelin & Hari, 1994; Stancak & Pfurtscheller, 1996). Baker et al. (1997) found that 15-30 Hz local field potential oscillations recorded in monkey primary motor cortex during a precision grip task showed a marked increase during the hold phase of the task. They suggested that the synchronous oscillations could reflect a mode of processing suited to the maintenance of a maintained grip. Oscillatory activity in motor cortex is coherent with the electromyogram (EMG) of active contralateral hand and forearm muscles (Conway et al. 1995; Salenius et al. 1996, 1997a; Baker et al. 1997). In the monkey, Baker et al. (1997) demonstrated that EMG-EMG coherence showed the same task dependence as the cortical signals, indicating that this coherence could be used to gain important insights into the temporal modulation of oscillatory activity at the cortical level. In this study we have extended this investigation to man, searching for modulation of coherent oscillatory activity during different precision grip tasks. We confirm the disappearance of oscillations during even a slow, low force movement, and further show a ‘rebound’ phenomenon whereby coherence is increased following a movement over and above that seen before movement. Using combined magnetoencephalogram (MEG) and EMG in one of the tasks studied, we show that at least part of the coherent oscillations seen in the periphery is likely to be generated in the primary motor cortex. A preliminary account of this work has been published previously (Kilner et al. 1998).