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Objective: Wrist‐ or ankle‐worn devices are less intrusive than the widely used electroencephalographic (EEG) systems for monitoring epileptic seizures. Using custom‐developed deep‐learning seizure detection models, we demonstrate the detection of a broad range of seizure types by wearable signals. Methods: Patients admitted to the epilepsy monitoring unit were enrolled and asked to wear wearable sensors on either wrists or ankles. We collected patients' electrodermal activity, accelerometry (ACC), and photoplethysmography, from which blood volume pulse (BVP) is derived. Board‐certified epileptologists determined seizure onset, offset, and types using video and EEG recordings per the International League Against Epilepsy 2017 classification. We applied three neural network models—a convolutional neural network (CNN) and a CNN–long short‐term memory (LSTM)‐based generalized detection model and an autoencoder‐based personalized detection model—to the raw time‐series sensor data to detect seizures and utilized performance measures, including sensitivity, false positive rate (the number of false alarms divided by the total number of nonseizure segments), number of false alarms per day, and detection delay. We applied a 10‐fold patientwise cross‐validation scheme to the multisignal biosensor data and evaluated model performance on 28 seizure types. Results: We analyzed 166 patients (47.6% female, median age = 10.0 years) and 900 seizures (13 254 h of sensor data) for 28 seizure types. With a CNN‐LSTM‐based seizure detection model, ACC, BVP, and their fusion performed better than chance; ACC and BVP data fusion reached the best detection performance of 83.9% sensitivity and 35.3% false positive rate. Nineteen of 28 seizure types could be detected by at least one data modality with area under receiver operating characteristic curve >.8 performance. Significance: Results from this in‐hospital study contribute to a paradigm shift in epilepsy care that entails noninvasive seizure detection, provides time‐sensitive and accurate data on additional clinical seizure types, and proposes a novel combination of an out‐of‐the‐box monitoring algorithm with an individualized person‐oriented seizure detection approach. [ABSTRACT FROM AUTHOR]

To explore what social and educational infrastructure is needed to support classroom use of student response systems (Roschelle et al., 2004), this study investigated the ways in which student characteristics and course design choices were related to students' assessments of the contribution of clicker use to their learning and involvement in the classroom. Survey responses of over 1500 undergraduates enrolled in seven large enrollment "clicker courses" offered by three university departments are analyzed. A number of factors contribute to students' positive perception of clickers: a desire to be involved and engaged, a view that traditional lecture styles are not best, valuing of feedback, class standing, previous experience with lecture courses, anticipated course performance, and amount of clicker use in the classroom. These results underscore the importance of considering social and communication elements of the classroom when adopting student response technology. Survey instrument is appended. (Contains 3 tables.)

Distributed work arrangements are gaining in popularity. Such arrangements are enabled through Information and Communication Technologies (ICTs). Problematically, the same ICTs that are implemented to overcome distance felt in these settings can also create the expectation of constant connectivity for individuals, constructing a paradox for teleworkers who find the potential benefits of distributed work negated by the very technologies that made the arrangement possible. To combat this problem, teleworkers sometimes use their ICTs strategically to decrease, rather than increase, the distance they feel from colleagues. Findings indicate this strategic use of ICTs to increase distance are often covert, such that teleworkers can appear to colleagues as if they are working in a manner similar to how they would at an office while, at the same time, reaping the benefits of not being in a central location. Keywords: Telework; Connectivity; Distributed Work; Distance; Organizational Change DOI: 10.1080/00909880903483599

A study was conducted to examine why engineering students are committed to counterproductive practices. Findings indicate that student informants' work practices coincide with lay stereotypes about what 'good engineers' do. Implications for theory on occupational socialization and for the management of engineering work are also identified.

This study examined naturally occurring idea-generation in organizational groups completing an extended problem-solving task. Meetings held by 11 groups engaged in a quality improvement process in a governmental agency were analyzed to identify 37 idea-generation episodes. All groups had available a group decision support system (GDSS), although some opted not to use it. Across all groups, idea productivity was low though fairly efficient, but GDSS--supported idea-generation produced significantly fewer ideas. In general, idea-generation as a process appears to be more complex than has been thought; observed deviations from idealized idea-generation norms were not necessarily dysfunctional. The findings encourage reassessment of the assumptions underlying existing normative models of idea-generation.

We focus on development efforts that use information and communication technologies for educational purposes in developing nations. The oppositional nature of the approaches to development makes constructive dialogue among theoretical perspectives difficult. Using Jackson's (1996) metatheoretical classification scheme, we sort development research based on 4 possible logical relationships between technology as an artifact and the social context. Derivation of the scheme is principled rather than historical and independent of any particular theory. Focusing on assumptions about technology and context brings new understanding of each perspective and can foster a dialogue across the perspectives. Further, we offer that self-organizing systems theory possesses the potential of representing an integrationist perspective in development research.