Training Novice Users in Developing Strategies for Responding to Errors When Browsing the Web

Novice users frequently make errors when learning a new computer task and spend a large portion of their time trying to recover from errors. Three methods for helping novice users respond to errors have been presented in the literature: error management training, exploratory training, and conceptual models. In error management training, errors are presented as opportunities for learning, and users are instructed in strategies for coping with errors. In exploration, users are given an overview of their environment and are taught how to navigate through their task environment. Conceptual models are graphical or mathematical representations of a system that correspond closely to the real-world system. This experiment tested the effectiveness of these different approaches on training novice users to use the Internet. In this experiment, users received 3 hr of training on the World Wide Web and then were asked to perform a set of information retrieval tasks. Performance was measured in two ways: task performance and performance time. Participants who received exploratory training had significantly higher task performance. Participants who received exploration and conceptual models, both individually and together, were able to complete the tasks in less time. Error management had no significant effect on the performance of participants. In the task application of Web browsing, exploration seems to be the most appropriate training method for novice users.     

Learning from errors in a driving simulation: effects on driving skill and self-confidence

Two experiments investigated the effect of making errors during training (error training) on a driving simulator versus learning from examples of errors (guided error training) on driving skill and confidence. Experiment 1 indicated that compared with errorless learning (where participants drove through a training run not designed to elicit errors), error training led to significantly better transfer to driving tests that were analogous to those situations encountered in training and more effective use of strategies for coping with a novel driving situation. Error training also reduced self-confidence in driving skill at the end of training relative to errorless learning. Experiment 2 provided weak evidence of the superiority of guided error training over errorless learning (where the driver in the video did not make any errors) on analogous tests, and no evidence of transfer to a novel test. Furthermore, guided error training did not influence self-confidence in driving skill. The potential value of driving simulators in providing active processing during driver training is discussed, along with the effects of passive and active exposure to errors on driver confidence.     

Learning from errors in a driving simulation: effects on driving skill and self-confidence

Two experiments investigated the effect of making errors during training (error training) on a driving simulator versus learning from examples of errors (guided error training) on driving skill and confidence. Experiment 1 indicated that compared with errorless learning (where participants drove through a training run not designed to elicit errors), error training led to significantly better transfer to driving tests that were analogous to those situations encountered in training and more effective use of strategies for coping with a novel driving situation. Error training also reduced self-confidence in driving skill at the end of training relative to errorless learning. Experiment 2 provided weak evidence of the superiority of guided error training over errorless learning (where the driver in the video did not make any errors) on analogous tests, and no evidence of transfer to a novel test. Furthermore, guided error training did not influence self-confidence in driving skill. The potential value of driving simulators in providing active processing during driver training is discussed, along with the effects of passive and active exposure to errors on driver confidence.     

Does training in the cold improve cold performance?

Despite the well-described physiological response to cold, little is known about how to best train persons to perform motor tasks in cold conditions. It is unclear if principles of training specificity would apply to motor skill training when cold because cold exposure reduces tactile sensitivity and cognitive function, which may reduce rather than enhance training efficacy. The purpose of this study is to determine whether training in the cold facilitates performance in the cold. To do this, we investigated the effect of cold or thermoneutral training on performance of the Grooved Pegboard Task. Twenty persons (11M, 9F, mean age 31.2 ± 5.44 years) visited the lab on two separate days and were randomly assigned to either a cold (5M, 5F) or thermoneutral (6M, 4F) training group. On day one, participants were tested at baseline and then performed 20 repetitions of the task according to their respective group assignment. Prior to each task repetition during training, the cold training group immersed their hand in cold water (2 °C) while the thermoneutral group immersed their hand in thermoneutral water (34 °C). Following training, participants were tested once again (immediate retention test). During testing, participants performed the task twice; once after immersing their hands in cold water and once after immersing their hands in thermoneutral water. On day two, delayed retention tests were performed. Time to completion and number of errors were recorded during testing. There were no differences in time to completion at delayed retention tests between thermoneutral and cold-trained groups (p = 0.434). The incidence of errors was significantly less in the cold-trained group than the thermoneutral training group at delayed retention testing (p = 0.035). The main finding of this study was that dexterity but not speed was improved by cold training. Further research is required but the findings presented here suggest that industries that require motor tasks in the cold could benefit from training employees in cold conditions.     

Errors in landmarking and the evaluation of the accuracy of traditional and 3D anthropometry

Body dimensions are based on landmarks of the body, but the magnitude of error in landmark determination is not well known. Therefore, a study was performed in which 40 subjects were marked five times in total by one highly skilled marker and a novice marker. Immediately after marking, a skilled measurer determined 34 body dimensions that were based on the mark locations. Intra- and inter-observer errors in landmarking of 35 landmarks, as well as those in 34 body dimensions were quantified. The error in landmarking was defined as the distance between two marks made on the same landmark by the same marker (intra-observer error) or by two different markers (inter-observer error). To make the first mark invisible when the second mark was made, the first mark was made using an invisible ink pen under black light. Landmarks with large intra-observer errors also had large inter-observer errors. Errors in body dimensions were smaller than landmarking errors in 23 measurements, which suggested that the magnitude of landmarking error would be underestimated from errors in body dimensions. In 15 body dimensions, measurements based on marks made by two different markers were not comparable according to the ISO 20685 criterion. Examination of body dimensions and landmarks with large inter-observer errors suggested that reducing inter-observer landmarking errors was necessary to reduce inter-observer measurement errors, and that a possible solution was to explicitly define landmarks with large errors in more detail so that anthropometrists can pinpoint them on the skin. Quantitative data on the intra- and inter-observer landmarking errors in the present study may be useful as a reference when evaluating and comparing the performance of software for calculating landmark locations for 3D anthropometry.     

Fuzzy hierarchical data fusion networks for terrain location identification problems.

The terrain location identification problem represents a very complicated learning task. Beside of learning from noisy and nondeterministic training data, the training task must learn from a very large size of training data, which may lead to lots of learning problems. A phenomenon called the fake convergence is observed in our implementation. In that case, the training process seemed to converge to a fixed error level, but the actual error is much higher than the converged one. In our study, a fuzzy hierarchical network is proposed to cope with the problem of large training data sets. With this fuzzy hierarchical structure, the learning process can become fast and errors are significantly reduced. Another issue is regarding about embedding domain knowledge into the learning structure of neural fuzzy networks. The idea is simple but effective. The proposed structure is called the fuzzy hierarchical data fusion network and its learning performance is significantly better than that of original fuzzy hierarchical networks. With the use of fuzzy hierarchical data fusion networks, errors indeed can converge and the system becomes practically applicable.     

关于AdaBoost有效性的分析

在机器学习领域,弱学习定理指明只要能够寻找到比随机猜测略好的弱学习算法,则可以通过一定方式,构造出任意误差精度的强学习算法.基于该理论下最常用的方法有AdaBoost和Bagging.AdaBoost和Bagging 的误差分析还不统一;AdaBoost使用的训练误差并不是真正的训练误差,而是基于样本权值的一种误差,是否合理需要解释;确保AdaBoost有效的条件也需要有直观的解释以便使用.在调整Bagging错误率并采取加权投票法后,对AdaBoost和Bagging的算法流程和误差分析进行了统一,在基于大数定理对弱学习定理进行解释与证明基础之上,对AdaBoost的有效性进行了分析.指出AdaBoost采取的样本权值调整策略其目的是确保正确分类样本分布的均匀性,其使用的训练误差与真正的训练误差概率是相等的,并指出了为确保AdaBoost的有效性在训练弱学习算法时需要遵循的原则,不仅对AdaBoost的有效性进行了解释,还为构造新集成学习算法提供了方法.还仿照AdaBoost对Bagging的训练集选取策略提出了一些建议.     

Preventing human error: The impact of data entry methods on data accuracy and statistical results

Human data entry can result in errors that ruin statistical results and conclusions. A single data entry error can make a moderate correlation turn to zero and a significant t-test non-significant. Therefore, researchers should design and use human computer interactions that minimize data entry errors. In this paper, 195 undergraduates were randomly assigned to three data entry methods: double entry, visual checking, and single entry. After training in their assigned method, participants entered 30 data sheets, each containing six types of data. Visual checking resulted in 2958% more errors than double entry, and was not significantly better than single entry. These data entry errors sometimes had terrible effects on coefficient alphas, correlations, and t-tests. For example, 66% of the visual checking participants produced incorrect values for coefficient alpha, which was sometimes wrong by more than .40. Moreover, these data entry errors would be hard to detect: Only 0.06% of the errors were blank or outside of the allowable range for the variables. Thus, researchers cannot rely upon histograms and frequency tables to detect data entry errors. Single entry and visual checking should be replaced with more effective data entry methods, such as double entry.     

一种改进的AdaBoost检测算法

针对传统AdaBoost算法在人脸图片训练过程中可能会出现退化现象和训练目标类权重分布过适应的问题,提出一种基于调整正负误差比和设定阈值的改进AdaBoost算法。该算法首先把设定的阈值和当前分类错误样本的权值比较来更新样本的权值,其次通过调整正误差和负误差之间的偏重关系来控制训练样本的偏重。经过实验表明,不同人脸图像库和不同正负样本比不影响该算法的有效性,在LFW非受限人脸图像库正负样本比例为1:1情况下,检测率为86.7%,高于传统AdaBoost算法;弱分类器数目为116,比传统AdaBoost算法多15个。实验结果可以看出所提算法抑制了退化和训练目标类权重过适应现象,有效地提高了人脸图片检测率。     

The impact of mental fatigue on exploration in a complex computer task: rigidity and loss of systematic strategies

We investigated the impact of mental fatigue on exploration in a complex computer task. The exploration behavior of participants who underwent a fatigue manipulation (N = 36) was compared with that of a control (nonfatigued) group (N = 32). A distinction was also made between participants with high or low levels of general computer experience. Results showed that fatigued participants used significantly less systematic exploration and made more errors than did nonfatigued participants. Fatigued participants with low computer experience also showed significantly more rigid behavior than did the other participants. No differences were found on the number of subtasks solved. Compared with low-experience participants, highly experienced participants showed significantly more systematic exploration, less unsystematic trial and error, solved more subtasks, and made fewer errors (marginally significant p = .056). Findings were interpreted as the result of reduced task engagement under fatigue and reduced involvement of executive control on behavior. Actual or potential applications of this research include guidelines to prevent detrimental effects of mental fatigue on exploration behavior.     

基于核岭回归的非线性内模控制

提出一种基于核蛉回归(KRR)建模的内模控制策略.该方法充分利用基干结构风险最小化为学习规则的回归方法的非线性拟合性能,建立内模控制系统,从理论上分析了内模控制系统的稳定性和稳态误差同逆模与内模估计误差的关系问题.仿真表明,在训练样本有限和有噪声污染情况下,该系统较神经网络方法具有更好的控制性能.     

A modified quantized kernel least mean square algorithm for prediction of chaotic time series

A modified quantized kernel least mean square (M-QKLMS) algorithm is proposed in this paper, which is an improvement of quantized kernel least mean square (QKLMS) and the gradient descent method is used to update the coefficient of filter. Unlike the QKLMS method which only considers the prediction error, the M-QKLMS method uses both the new training data and the prediction error for coefficient adjustment of the closest center in the dictionary. Therefore, the proposed method completely utilizes the knowledge hidden in the new training data, and achieves a better accuracy. In addition, the energy conservation relation and a sufficient condition for mean-square convergence of the proposed method are obtained. Simulations on prediction of chaotic time series show that the M-QKLMS method outperforms the QKLMS method in terms of steady-state mean square errors.     

Designing and evaluating a crew resource management training for manufacturing industries

This article presents the evaluation of crew resource management (CRM) training specifically designed for employees within manufacturing industries. The central objective of this training program was to improve teamwork, communication, and stress management skills as well as to increase the workers' situational awareness of potential errors that can occur during the manufacturing process. Eighty employees, all of whom were working in a production unit for gearbox manufacturing, participated in the training program in this study. Effectiveness of the CRM training course was evaluated. The results showed a significant improvement in a wide range of CRM‐relevant categories, especially in teamwork‐related skills, in addition to an increase in the workers' situational awareness after the training program. When comparing the data regarding human error occurring in gear production that were derived from the trained group and a control group, mixed results were produced. Based on the results, it can be stated that CRM training, which was originally developed for the aviation industry, can be transferred to the manufacturing industry. © 2010 Wiley Periodicals, Inc.     

Cognitive flexibility and adaptability to environmental changes in dynamic complex problem-solving tasks

People who show good performance in dynamic complex problem-solving tasks can also make errors. Theories of human error fail to fully explain when and why good performers err. Some theories would predict that these errors are to some extent the consequence of the difficulties that people have in adapting to new and unexpected environmental conditions. However, such theories cannot explain why some new conditions lead to error, while others do not. There are also some theories that defend the notion that good performers are more cognitively flexible and better able to adapt to new environmental conditions. However, the fact is that they sometimes make errors when they face those new conditions. This paper describes one experiment and a research methodology designed to test the hypothesis that when people use a problem-solving strategy, their performance is only affected by those conditions which are relevant to that particular strategy. This hypothesis is derived from theories that explain human performance based on the interaction between cognitive mechanisms and environment.     

Cognitive flexibility and adaptability to environmental changes in dynamic complex problem-solving tasks

People who show good performance in dynamic complex problem-solving tasks can also make errors. Theories of human error fail to fully explain when and why good performers err. Some theories would predict that these errors are to some extent the consequence of the difficulties that people have in adapting to new and unexpected environmental conditions. However, such theories cannot explain why some new conditions lead to error, while others do not. There are also some theories that defend the notion that good performers are more cognitively flexible and better able to adapt to new environmental conditions. However, the fact is that they sometimes make errors when they face those new conditions. This paper describes one experiment and a research methodology designed to test the hypothesis that when people use a problem-solving strategy, their performance is only affected by those conditions which are relevant to that particular strategy. This hypothesis is derived from theories that explain human performance based on the interaction between cognitive mechanisms and environment.     

Soft computing methods applied to train station parking in urban rail transit

This paper presents three models - a linear model, a generalized regression neural network (GRNN) and an adaptive network based fuzzy inference system (ANFIS) - to estimate the train station parking (TSP) error in urban rail transit. We also develop some statistical indices to evaluate the reliability of controlling parking errors in a certain range. By comparing modeling errors, the subtractive clustering method other than grid partition method is chosen to generate an initial fuzzy system for ANFIS. Then, the collected TSP data from two railway stations are employed to identify the parameters of the proposed three models. The three models can make the average parking errors under an acceptable error, and tuning the parameters of the models is effective in dynamically reducing parking errors. Experiments in two stations indicate that, among the three models, (1) the linear model ranks the third in training and the second in testing, nevertheless, it can meet the required reliability for two stations, (2) the GRNN based model achieves the best performance in training, but the poorest one in testing due to overfitting, resulting in failing to meet the required reliability for the two stations, (3) the ANFIS based model obtains better performance than model 1 both in training and testing. After analyzing parking error characteristics and developing a parking strategy, finally, we confirm the effectiveness of the proposed ANFIS model in the real-world application.     

Automation failures on tasks easily performed by operators undermine trust in automated aids

OBJECTIVE: We tested the hypothesis that automation errors on tasks easily performed by humans undermine trust in automation. BACKGROUND: Research has revealed that the reliability of imperfect automation is frequently misperceived. We examined the manner in which the easiness and type of imperfect automation errors affect trust and dependence. METHOD: Participants performed a target detection task utilizing an automated aid. In Study 1, the aid missed targets either on easy trials (easy miss group) or on difficult trials (difficult miss group). In Study 2, we manipulated both easiness and type of error (miss vs. false alarm). The aid erred on either difficult trials alone (difficult errors group) or on difficult and easy trials (easy miss group; easy false alarm group). RESULTS: In both experiments, easy errors led to participants mistrusting and disagreeing more with the aid on difficult trials, as compared with those using aids that generated only difficult errors. This resulted in a downward shift in decision criterion for the former, leading to poorer overall performance. Misses and false alarms led to similar effects. CONCLUSION: Automation errors on tasks that appear "easy" to the operator severely degrade trust and reliance. APPLICATION: Potential applications include the implementation of system design solutions that circumvent the negative effects of easy automation errors.     

Errors enacted during endoscopic surgery-a human reliability analysis

The aim of the study was to document the nature and incidence of surgical errors enacted during laparoscopic surgery in order to direct future research and surgical training. A modified Human Reliability Analysis (HRA) approach, based on direct observation, was adopted to categorise and record errors encountered during the practice of laparoscopic cholecystectomy. This study confirmed the applicability and usefulness of an observational methodology in the assessment of human error in endoscopic surgical performance. The study identified aspects of the design and usage of instruments, surgical training and the differences between tasks which needed further directed research in order to identify underlying performance shaping factors (PSFs) and so reduce error rates.     

Effects of different real-time feedback types on human performance in high-demanding work conditions

Experiencing stress during training is a way to prepare professionals for real-life crises. With the help of feedback tools, professionals can train to recognize and overcome negative effects of stress on task performances. This paper reports two studies that empirically examined the effect of such a feedback system. The system, based on the COgnitive Performance and Error (COPE) model, provides its users with physiological, predicted performance and predicted error-chance feedback. The first experiment focussed on creating stressful scenarios and establishing the parameters for the predictive models for the feedback system. Participants (n=9) performed fire-extinguishing tasks on a virtual ship. By altering time pressure, information uncertainty and consequences of performance, stress was induced. COPE variables were measured and models were established that predicted performance and the chances on specific errors. In the second experiment a new group of participants (n=29) carried out the same tasks while receiving eight different combinations of the three feedback types in a counterbalanced order. Performance scores improved when feedback was provided during the task. The number of errors made did not decrease. The usability score for the system with physiological feedback was significantly higher than a system without physiological feedback, unless combined with error feedback.This paper shows effects of feedback on performances and usability. To improve the effectiveness of the feedback system it is suggested to provide more in-depth tutorial sessions. Design changes are recommended that would make the feedback system more effective in improving performances.     

Multimedia training in the pig industry

This paper evaluates the effectiveness of a multimedia training program designed specifically for stockpeople in the pig industry. The information was presented in either multimedia or printed manual format with and without the presence of a trainer. Care was taken to ensure that layout and content was the same for both formats. The study comprised two pilot studies to assess the validity of the instruments, followed by a main study in which 92 stockpeople participated in one of four training conditions. Immediately following training, stockpeople completed a Knowledge and a Satisfaction Questionnaire and 6 weeks post-training repeated the Knowledge Questionnaire. Results did not support the hypothesis that participants in the multimedia group would perform and retain content better than participants in the manual group. The trainer had an overall deleterious effect on recall of the information in both groups. There was support for the hypothesis that participants in the multimedia group would be more satisfied with their media than the manual group. Novelty effects did not appear to account for the observed differences between media groups.