Learning to use a word-processing system as a function of training strategy

Three training strategies were evaluated for their effectiveness in teaching naive computer users to use a word-processing system. One hundred and thirty five women ranging in age from 25 years to 70 years participated in the study. Subjects were trained using one of three techniques (instructor, manual, computer( to perform basic word-processing tasks. The effectiveness of the training strategies was assessed by examining performance on basic word-processing tasks such as typing a letter or memo and editing an existing file. Results showed that for all subjects, computer-based training was a less effective teaching method than either instructor- or manual-based training. In general, subjects who were trained using the computer-based method attempted and completed fewer tasks, took longer to perform tasks, and also made more errors. These findings demonstrate the need for directing efforts towards the development of appropriate training methods for computer tasks     

An investigation of handheld device use by older adults with age-related macular degeneration

This study investigates factors affecting handheld human - computer interaction (HCI) for older adults with Age-related Macular Degeneration (AMD). This is largely an uncharted territory, as empirical investigations of HCI concerning users with visual dysfunction and/or older adults have focused primarily on desktop computers. For this study, participants with AMD and visually healthy controls used a handheld computer to search, select and manipulate familiar playing card icons under varied icon set sizes, inter-icon spacing and auditory feedback conditions. While all participants demonstrated a high rate of task completion, linear regression revealed several relationships between task efficiency and the interface, user characteristics and ocular factors. Two ocular measures, severity of AMD and contrast sensitivity, were found to be highly predictive of efficiency. The outcomes of this work reveal that users with visual impairments can effectively interact with graphical user interfaces on small displays in the presence of low-cost, easily implemented design interventions. Furthermore, results demonstrate that the detrimental influence of AMD and contrast sensitivity on handheld technology interaction can be offset by such interventions. This study presents a rich data set and is intended to inspire future work characterizing and modeling the interactions of individuals with visual impairments with non-traditional information technology platforms and contexts.     

GeeAir: a universal multimodal remote control device for home appliances

In this paper, we present a handheld device called GeeAir for remotely controlling home appliances via a mixed modality of speech, gesture, joystick, button, and light. This solution is superior to the existing universal remote controllers in that it can be used by the users with physical and vision impairments in a natural manner. By combining diverse interaction techniques in a single device, the GeeAir enables different user groups to control home appliances effectively, satisfying even the unmet needs of physically and vision-impaired users while maintaining high usability and reliability. The experiments demonstrate that the GeeAir prototype achieves prominent performance through standardizing a small set of verbal and gesture commands and introducing the feedback mechanisms.     

医用CO_2体积分数检测装置的研制

危重病人的监护需要监测病人通气功能和肺血流等情况,设计了一种装置。采用了非扩散红外线NDIR(nondispersiveinfrared)技术获取信息,旁气流式测量,再用微控制器对信息进行采集、处理,送PC机显示,可实现对病人呼吸中的CO2体积分数的无创、实时和连续监测。     

Learning a menu selection tree: training methods compared

. Menu selection systems sometimes present learning problems for novice users. This comparison of four training methods for novice users found that the global tree diagram of the menu system was superior to command sequence and frame presentation methods, and somewhat better than trial and error. Methods were evaluated on the basis of (1) number of target nodes found, (2) mean number of selections to a target node, (3) recall of the menu structure, and (4) subjective rating of ease of learning.     

Learning how to use a computer-based concept-mapping tool: Self-explaining examples helps

In initial skill acquisition in well-structured domains, example-based learning typically leads to better learning outcomes than learning by doing. Cognitive Load Theory explains this result by the worked-example effect: Example-based learning prevents learners from using load-intensive strategies and focuses their attention on the principles to-be-learned. In two experiments, we investigated the use of examples for acquiring a new learning strategy, namely computer-based concept mapping. Experiment 1 compared learners who studied two examples on how to construct a concept map with learners who practiced concept mapping by constructing two concept maps on their own. We did not find significant differences in learning outcomes. Therefore, in Experiment 2, we introduced a third group of learners who studied examples with the additional support of self-explanation prompts. Self-explaining examples led to better learning outcomes than learning with examples without prompts or practicing. With respect to cognitive load, we found that examples without prompts released learners’ working memory compared to practicing, whereas self-explaining examples led to a higher cognitive load compared to examples without self-explanation.     

Simulators for medical training: application to vascular ultrasound imaging

Whilst computers are more and more used in the medical and surgical domains, medical education is still very conservative. However, new information technology could bring a lot to this area. In particular, simulators are of paramount interest: they would allow one both to experiment with surgical or imaging techniques for a wide range of pathologies without the need for patients and to quantitatively evaluate the trainees' performances. Ultrasound imaging is a typical area where virtual reality may change educational uses. This paper describes an ultrasound imaging simulator dedicated to the training of physicians for the detection of deep venous thromboses of the lower limbs. Like this one, a lot of other pathologies of soft tissue are diagnosed using ultrasound imaging. Because this examination is difficult and operator‐dependent, developing a simulator is very useful to give common databases of pathological samples on which physicians can both experiment with image acquisition and evaluate their understanding of clinical cases. Real‐time simulation is mandatory. An ultrasound imaging simulator has been developed and is being tested. This paper presents the hardware and software components of the simulator and describes the status of this project. Copyright © 2000 John Wiley & Sons, Ltd.     

Age related differences in learning to use a text-editing system

The increased use of computer technology in most occupations means that many middle-aged and older workers who lack computer experience will need to acquire skills to interact with this technology. This study examined age-group differences in learning to use a text-editing system. One hundred and thirty-five females ranging in age from 25 to 70 participated in the study. They received training under one of three training conditions: instructor-based, online or manual-based. Age differences were assessed by comparing performance on criterion tasks. Results indicated significant differences among the groups in learning success, younger learners being the most successful. There were no significant age by training interactions. The findings indicate a need to develop more effective training strategies to teach older learners to use computer technologies. They also indicate the need for changes in system design because computer applications are difficult for novice users to learn.     

The use of performance profiles in the design of a systematic medical suturing training programme

Systematic training methods are generated by contrasting task knowledge and skill performance profiles of highly experienced workers against those of inexperienced, through task and skills analysis. Training methods are then developed based on performance profile differences rather than similarities. The studies reported in this paper are concerned with the methodology and findings of task and skills analysis used in the development of a systematic training programme for medical suturing. The general conclusions suggest the following: (1) the experienced and inexperienced groups differ in task knowledge on the task components - (a) proper instrument handling, (b) hierarchy of elements that must be followed in attaining symmetric and atraumatic would closures and (c) proper suture tension during instrument knot-tying; (2) inexperienced workers exhibited significantly higher number of anatomical position changes during task performance than the experienced surgeons; (3) due to task knowledge profiles and unique usage of hand, finger and thumb of the favoured and non-favoured hand, the surgeons were approximately three times faster than the students on critical task elements; and (4) the contrasting of performance profiles developed through task and skills analysis is a valuable tool in the development of an analytical training strategies for technical psychomotor surgical skills.     

METKIT: training in how to use measurement as a software management tool

A Science is as mature as its measurement tools. Louis PasteurThe main purpose of this paper is to present the results of the ESPRIT project METKIT, a three-year collaborative technology transfer project in the field of software engineering measurement. METKIT was concerned with developing a set of integrated training courses that show how to implement process improvement programmes and use measurement as a powerful management tool. METKIT can be used by an organization to enable them to provide in-house training to their managers and software developers to enable them to understand control and then improve software development.     

A formal methods approach to medical device review

With software playing an increasingly important role in medical devices, regulatory agencies such as the US Food and Drug Administration need effective means for assuring that this software is safe and reliable. The FDA has been striving for a more rigorous engineering-based review strategy to provide this assurance. The use of mathematics-based techniques in the development of software might help accomplish this. However, the lack of standard architectures for medical device software and integrated engineering-tool support for software analysis make a science-based software review process more difficult. The research presented here applies formal modeling methods and static analysis techniques to improve the review process. Regulation of medical device software encompasses reviews of device designs (premarket review) and device performance (postmarket surveillance). The FDA's Center for Devices and Radiological Health performs the premarket review on a device to evaluate its safety and effectiveness. As part of this process, the agency reviews software development life-cycle artifacts for appropriate quality-assurance attributes, which tend to reveal little about the device software integrity.     

Learning vector quantization with training data selection

In this paper, we propose a method that selects a subset of the training data points to update LVQ prototypes. The main goal is to conduct the prototypes to converge at a more convenient location, diminishing misclassification errors. The method selects an update set composed by a subset of points considered to be at the risk of being captured by another class prototype. We associate the proposed methodology to a weighted norm, instead of the Euclidean, in order to establish different levels of relevance for the input attributes. The technique was implemented on a controlled experiment and on Web available data sets.     

Learning curve analysis of a patient lift-assist device

One of the challenges facing ergonomists in the implementation of an ergonomic solution is addressing the concerns related to their impact on productivity. The focus of the current study was to (1) apply standard learning curve analysis to the learning that takes place as an individual works with a patient handling device and (2) compare the effects of two different training protocols on measures of learning. Eighteen subjects completed 11 replications of a patient transfer task after participating in either an “interactive” training protocol or “see-one-do-one” training protocol. The results show that the learning rate for this task was 83% with no difference as a function of training protocol. The results do indicate that the effect of Training Method was significant (p<0.05) for time to complete the first patient lift task (370 s for the interactive training vs. 475 s for see-one-do-one training). The results of the analysis of the survey data supported the objective results in that the only measure that was responsive to training type (p<0.05) was related to comfort level in performing the patient lift task for the first time. The results emphasize the importance in considering learning when introducing an intervention in the workplace, and showed that in this instance, training type had an immediate impact on productivity, but that this effect diminished over time.     

Learning to use a spreadsheet by doing and by watching

An important practical question is: how should instruction for computer skills be designed to facilitate effective learning? The reported study examines the instructional efficacy of animated demonstrations within active and passive learning contexts of teaching basic spreadsheet skills. Four content-matched instructional regimes were compared: the commercially available tutorial (a ‘scenario machine’), an animated demonstration of this tutorial being used, and problem solving supported by either the user manual or a set of task-specific demonstrations. Acquired spreadsheet skills were then tested on a standard task. Results indicate a clear learning advantage of problem solving, over prompted interaction (the scenario machine). The study suggests two distinctive roles that animations could exploit within computer instruction. Simply watching an animated demonstration can provide a useful introduction to complex interfaces; additionally, animations can be an effective ‘example following’ resource for more active problem-solving.     

Active Learning with Bootstrapped Dendritic Classifier applied to medical image segmentation

We perform the segmentation of medical images following an Active Learning approach that allows quick interactive segmentation minimizing the requirements for intervention of the human operator. The basic classifier is the Bootstrapped Dendritic Classifier (BDC), which combine the output of an ensemble of weak Dendritic Classifiers by majority voting. Weak Dendritic Classifiers are trained on bootstrapped samples of the train data setting a limit on the number of dendrites. We validate the approach on the segmentation of the thrombus in 3D Computed Tomography Angiography (CTA) data of Abdominal Aortic Aneurysm (AAA) patients simulating the human oracle by the provided ground truth. The generalization results in terms of accuracy and true positive ratio of the classification of the entire volume by the classifier trained on one slice confirm that the approach is worth its consideration for clinical practice.     

Three-dimensional simulation of a nanophotonics device with use of fullwave software

Using the FullWAVE software (www.rsoftdesign.com) that implements the finite-difference FDTD-method of solving Maxwell’s equations, we simulate the performance of a three-dimensional nanophotonics device comprising a sub-wavelength diffraction grating, a wide and a narrow planar waveguide, and a photonic crystal (PhC) Mikaelian lens located in a thin silicon film coated on a substrate containing a three-period Bragg mirror, with each period made up of silicon + silica layer. The device is intended to couple a focused laser beam with the focal spot of 3 × 4.6 μm² and wavelength 1.55 μm into a planar waveguide of width 500 nm, resulting in a 125-fold “compression” of the input beam cross-section. The modeling has shown that the coupling efficiency amounts to 32% of the energy of the linearly polarized elliptic Gaussian beam focused onto the grating and 52% when a plane wave segment is incident onto the grating. For comparison, the grating-unaided coupling of light into the same device by the butt-coupling of light into the wide waveguide’s silicon film gives the efficiency as low as 8%. The article is published in the original.     

The potential of training to increase acceptance and use of computerized decision support systems for medical diagnosis

OBJECTIVE: The goals of this study were to understand the reasons underlying the limited use of medical decision-support tools and to explore the potential of a computer-based tutorial to mitigate barriers to use. BACKGROUND: Medical decision-support tools such the Acute Cardiac Ischemia Time-Insensitive Predictive Instrument (ACI-TIPI) have demonstrated statistical validity and clinical impact for patient safety but have seen limited adoption and use. METHODS: The study developed a brief Web-based "demystifying" ACI-TIPI tutorial employing case-based training and evaluated the effectiveness of that tutorial in changing self-reported attitudes and behaviors. RESULTS: Clinicians using the tutorial reported greater understanding of how to use the ACI-TIPI score appropriately and increased confidence in the score. Case studies in the tutorial that provided examples of how to use the score for actual cases were rated as especially helpful. CONCLUSION: This study suggests that a primary barrier to the use of statistical decision support tools for patient diagnosis is lack of training or experience in combining a population-based numerical risk score with other diagnostic information about the individual patient's case that is not considered in that score. The results of this study indicate that there is a potential for a relatively brief tutorial to increase acceptance and use of decision support tools for medical diagnosis. APPLICATION: These findings have the potential for the identification of methods to help clinicians learn how to use statistical and probabilistic information to better assess risk and to promote integration of decision support tools into medical decision making for improvement of patient safety.     

Assessment of a medical information system: the mediating role of use and user satisfaction on the success of human interaction with the mobile healthcare system (iHeart)

Cognition, Technology & Work - iHeart is a mobile healthcare system which monitors and tracks patients with hypertension and arrhythmia. This empirical study aims to assess the interaction...