Technology in Practice (Section 2.31 of the Comprehensive Clinical Psychology: Vol. 2. Professional Issues)

The contemporary practice of psychology requires a prudent balance of traditional and emerging communication methods. Interpersonal interactions in the context of human relationship (e.g., speech, emotional expressions, and nonverbal gestures) have been a vital part of emotional healing throughout many centuries, and research findings in the 1990s underscore the importance of relational factors in effective psychological interventions (Whiston & Sexton, 1993). In addition to the time honored interpersonal communication methods of professional psychology, rapid technological advances have propelled psychologists into another sphere of communication. Today\u27s professional psychologist is increasingly expected to attain mastery in both of these communication methods-the very old and the very new

Use of nonintrusive sensor-based information and communication technology for real-world evidence for clinical trials in dementia

Cognitive function is an important end point of treatments in dementia clinical trials. Measuring cognitive function by standardized tests, however, is biased toward highly constrained environments (such as hospitals) in selected samples. Patient-powered real-world evidence using information and communication technology devices, including environmental and wearable sensors, may help to overcome these limitations. This position paper describes current and novel information and communication technology devices and algorithms to monitor behavior and function in people with prodromal and manifest stages of dementia continuously, and discusses clinical, technological, ethical, regulatory, and user-centered requirements for collecting real-world evidence in future randomized controlled trials. Challenges of data safety, quality, and privacy and regulatory requirements need to be addressed by future smart sensor technologies. When these requirements are satisfied, these technologies will provide access to truly user relevant outcomes and broader cohorts of participants than currently sampled in clinical trials

Nurses' views of using computerized decision support software in NHS Direct

Background. Nurses working in NHS Direct, the 24-hour telephone advice line in England, use computerized decision support software to recommend to callers the most appropriate service to contact, or to advise on self-care. Aims. To explore nurses' views of their roles and the computerized decision support software in NHS Direct. Methods. Qualitative analysis of semi-structured interviews with 24 NHS Direct nurses in 12 sites. Findings. Nurses described both the software and themselves as essential to the clinical decision-making process. The software acted as safety net, provider of consistency, and provider of script, and was relied upon more when nurses did not have clinical knowledge relevant to the call. The nurse handled problems not covered by the software, probed patients for the appropriate information to enter into the software, and interpreted software recommendations in the light of contextual information which the software was unable to use. Nurses described a dual process of decision-making, with the nurse as active decision maker looking for consensus with the software recommendation and ready to override recommendations made by the software if necessary. However, nurses' accounts of the software as a guide, prompt or support did not fully acknowledge the power of the software, which they are required to use, and the recommendation of which they are required to follow under some management policies. Over time, the influence of nurse and software merges as nurses internalize the software script as their own knowledge, and navigate the software to produce recommendations that they feel are most appropriate. Conclusions. The nurse and the software have distinct roles in NHS Direct, although the effect of each on the clinical decision-making process may be difficult to determine in practice

Comprendiendo el potencial y los desafíos del Big Data en las escuelas y la educación

In recent years, the world has experienced a huge revolution centered around the gathering and application of big data in various fields. This has affected many aspects of our daily life, including government, manufacturing, commerce, health, communication, entertainment, and many more. So far, education has benefited only a little from the big data revolution. In this article, we review the potential of big data in the context of education systems. Such data may include log files drawn from online learning environments, messages on online discussion forums, answers to open-ended questions, grades on various tasks, demographic and administrative information, speech, handwritten notes, illustrations, gestures and movements, neurophysiologic signals, eye movements, and many more. Analyzing this data, it is possible to calculate a wide range of measurements of the learning process and to support various educational stakeholders with informed decision-making. We offer a framework for better understanding of how big data can be used in education. The framework comprises several elements that need to be addressed in this context: defining the data; formulating data-collecting and storage apparatuses; data analysis and the application of analysis products. We further review some key opportunities and some important challenges of using big data in educationEn los últimos años, el mundo ha experimentado una gran revolución centrada en la recopilación y aplicación de big data en varios campos. Esto ha afectado muchos aspectos de nuestra vida diaria, incluidos el gobierno, la manufactura, el comercio, la salud, la comunicación, el entretenimiento y muchos más. Hasta ahora, la educación se ha beneficiado muy poco de la revolución del big data. En este artículo revisamos el potencial de los macrodatos en el contexto de los sistemas educativos. Dichos datos pueden incluir archivos de registro extraídos de entornos de aprendizaje en línea, mensajes en foros de discusión en línea, respuestas a preguntas abiertas, calificaciones en diversas tareas, información demográfica y administrativa, discurso, notas escritas a mano, ilustraciones, gestos y movimientos, señales neurofisiológicas, movimientos oculares y muchos más. Analizando estos datos es posible calcular una amplia gama de mediciones del proceso de aprendizaje y apoyar a diversos interesados educativos con una toma de decisiones informada. Ofrecemos un marco para una mejor comprensión de cómo se puede utilizar el big data en la educación. El marco comprende varios elementos que deben abordarse en este contexto: definición de los datos; formulación de aparatos de recolección y almacenamiento de datos; análisis de datos y aplicación de productos de análisis. Además, revisamos algunas oportunidades clave y algunos desafíos importantes del uso de big data en la educació

Closing the communications loop on the computerized peer‐assessment of essays

The use of self‐ and peer‐assessment is not new to higher education. Traditionally its use has required the complex and time‐consuming management of coursework submissions by the tutor, in an attempt to maintain validity and anonymity of the assessment process. In the last few years a number of computerized systems have been developed that are capable of automatically supporting, managing and performing the assessment process. The requirement for student anonymity and the release of the tutor from the process of marking have reduced the ability to develop the iterative process of feedback. This feedback is considered essential in supporting student learning and developing reflective practice. This paper describes the enhancement of a computerized assessment system to support anonymous computer‐mediated discussion between marker and marked having previously performed peer‐assessment. A detailed description is provided of the integrated assessment process, and an analysis of the use of this anonymous discussion is presented. Anonymous student feedback is presented and analyzed with respect to the perceived benefits of using the system with respect to enhancing the student learning process

Transforming a competency model to assessment items

The problem of comparing and matching different learners’ knowledge arises when assessment systems use a one-dimensional numerical value to represent “knowledge level”. Such assessment systems may measure inconsistently because they estimate this level differently and inadequately. The multi-dimensional competency model called COMpetence-Based learner knowledge for personalized Assessment (COMBA) is being developed to represent a learner’s knowledge in a multi-dimensional vector space. The heart of this model is to treat knowledge, not as possession, but as a contextualized space of capability either actual or potential. The paper discusses the automatic generation of an assessment from the COMBA competency model as a “guideon- the–side”

Closing the communications loop on the computerized peer‐assessment of essays

The use of self‐ and peer‐assessment is not new to higher education. Traditionally its use has required the complex and time‐consuming management of coursework submissions by the tutor, in an attempt to maintain validity and anonymity of the assessment process. In the last few years a number of computerized systems have been developed that are capable of automatically supporting, managing and performing the assessment process. The requirement for student anonymity and the release of the tutor from the process of marking have reduced the ability to develop the iterative process of feedback. This feedback is considered essential in supporting student learning and developing reflective practice. This paper describes the enhancement of a computerized assessment system to support anonymous computer‐mediated discussion between marker and marked having previously performed peer‐assessment. A detailed description is provided of the integrated assessment process, and an analysis of the use of this anonymous discussion is presented. Anonymous student feedback is presented and analyzed with respect to the perceived benefits of using the system with respect to enhancing the student learning process

Do Engineering Students Learn Ethics From an Ethics Course?

The goal of the present research is to develop machine-assisted methods that can assist in the analysis of students’ written compositions in ethics courses. As part of this research, we analyzed Social Impact Assessment (SIA) papers submitted by engineering undergraduates in a course on engineering ethics. The SIA papers required students to identify and discuss a contemporary engineering technology (e.g., autonomous tractor trailers) and to explicitly discuss the ethical issues involved in that technology. Here we describe the ability of three machine tools to discriminate differences in the technical compared to ethical portions of the SIA papers. First, using LIWC (Language Inquiry and Word Count) we quantified differences in analytical thinking, expertise and self-confidence, disclosure, and affect, in the technical and ethical portions of the papers. Next, we applied MEH (Meaning Extraction Helper) to examine differences in critical concepts in the technical and ethical portions of the papers. Finally, we used LDA (Latent Dirichlet Allocation) to examine differences in the topics in the technical and ethical portions of the papers. The results of these three tests demonstrate the ability of machine-based tools to discriminate conceptual, affective, and motivational differences in the texts that students compose that relate to engineering technology and to engineering ethics. We discuss the utility and future directions for this research.Cockrell School of Engineerin

Debatable issues in automated ECG reporting

Although automated ECG analysis has been available for many years, there are some aspects which require to be re-assessed with respect to their value while newer techniques which are worthy of review are beginning to find their way into routine use. At the annual International Society of Computerized Electrocardiology conference held in April 2017, four areas in particular were debated. These were a) automated 12 lead resting ECG analysis; b) real time out of hospital ECG monitoring; c) ECG imaging; and d) single channel ECG rhythm interpretation. One speaker presented the positive aspects of each technique and another outlined the more negative aspects. Debate ensued. There were many positives set out for each technique but equally, more negative features were not in short supply, particularly for out of hospital ECG monitoring

An Overview of Health Law Research and an Annotated Bibliography

This analysis and the following bibliography are designed to meet the needs of researchers attempting to locate information in the field of health law. The analysis is written from the perspective of law librarians, but the same information retrieval problems apply to health administrators, hospital and medical counsel, and academic lawyers interested in health law and administration