适合汉语全拼输入的提示性软键盘的研发与验证

本研究设计了两种基于汉语全拼输入的提示性软键盘:加粗加黑和颜色提示,并通过实证性研究验证了这两种提示性软键盘对汉字输入绩效的影响。结果表明,两种提示性软键盘均优于非提示性软键盘,在打字速度、使用方便程度、喜爱程度和总体评价上均更好,加粗加黑提示性软键盘还显著提升了输入正确率。该结果为基于汉字输入的提示性软键盘的研发和使用提供了科学依据和数据支持,也将为相关键盘的投入市场做出贡献。     

Whisker: A client—server high-performance multimedia research control system

We describe an original client-server approach to behavioral research control and the Whisker system, a specific implementation of this design. The server process controls several types of hardware, including digital input/output devices, multiple graphical monitors and touchscreens, keyboards, mice, and sound cards. It provides a way to access this hardware for client programs, communicating with them via a simple text-based network protocol based on the standard Internet protocol. Clients to implement behavioral tasks may be written in any network-capable programming language. Applications to date have been in experimental psychology and behavioral and cognitive neuroscience, using rodents, humans, nonhuman primates, dogs, pigs, and birds. This system is flexible and reliable, although there are potential disadvantages in terms of complexity. Its design, features, and performance are described.     

Skilled typing performance and keyboard design

This article discusses the major control principles of fluent typing and their relevance to the design of keyboards. This research was supported by a grant (C00232213) from the U.K. Economic and Social Research Council.     

A quantitative model for designing keyboard layout

This study analyzed the quantitative relationship between keytapping times and ergonomic principles in typewriting skills. Keytapping times and key-operating characteristics of a female subject typing on the Qwerty and Dvorak keyboards for six weeks each were collected and analyzed. The results showed that characteristics of the typed material and the movements of hands and fingers were significantly related to keytapping times. The most significant factors affecting keytapping times were association frequency between letters, consecutive use of the same hand or finger, and the finger used. A regression equation for relating keytapping times to ergonomic principles was fitted to the data. Finally, a protocol for design of computerized keyboard layout based on the regression equation was proposed.     

InputLogger: General-purpose logging of keyboard and mouse events on an Apple Macintosh

Event logging, particularly logging of event-timing information, is often used in human-computer interaction research in investigations of the ways in which people use computers and in the evaluation of input devices and applications. This paper describes InputLogger, a low-level input-event recorder for the Apple Macintosh. It differs from other keystroke loggers in that it records accurate timing information for all keyboard and mouse events while being application independent. It is capable of logging any Macintosh session. InputLogger has been used to gather data on the difficulties experienced by people with motor disabilities using ordinary keyboards and mice. It would be appropriate for many other experimental applications.     

Response time accuracy in Apple Macintosh computers

The accuracy and variability of response times (RTs) collected on stock Apple Macintosh computers using USB keyboards was assessed. A photodiode detected a change in the screen’s luminosity and triggered a solenoid that pressed a key on the keyboard. The RTs collected in this way were reliable, but could be as much as 100 ms too long. The standard deviation of the measured RTs varied between 2.5 and 10 ms, and the distributions approximated a normal distribution. Surprisingly, two recent Apple-branded USB keyboards differed in their accuracy by as much as 20 ms. The most accurate RTs were collected when an external CRT was used to display the stimuli and Psychtoolbox was able to synchronize presentation with the screen refresh. We conclude that RTs collected on stock iMacs can detect a difference as small as 5–10 ms under realistic conditions, and this dictates which types of research should or should not use these systems.     

Warning: This keyboard will deconstruct— The role of the keyboard in skilled typewriting

Skilled actions are commonly assumed to be controlled by precise internal schemas or cognitive maps. We challenge these ideas in the context of skilled typing, where prominent theories assume that typing is controlled by a well-learned cognitive map that plans finger movements without feedback. In two experiments, we demonstrate that online physical interaction with the keyboard critically mediates typing skill. Typists performed single-word and paragraph typing tasks on a regular keyboard, a laser-projection keyboard, and two deconstructed keyboards, made by removing successive layers of a regular keyboard. Averaged over the laser and deconstructed keyboards, response times for the first keystroke increased by 37%, the interval between keystrokes increased by 120%, and error rate increased by 177%, relative to those of the regular keyboard. A schema view predicts no influence of external motor feedback, because actions could be planned internally with high precision. We argue that the expert knowledge mediating action control emerges during online interaction with the physical environment.     

Metronome LKM: An open source virtual keyboard driver to measure experiment software latencies

Experiment software is often used to measure reaction times gathered with keyboards or other input devices. In previous studies, the accuracy and precision of time stamps has been assessed through several means: (a) generating accurate square wave signals from an external device connected to the parallel port of the computer running the experiment software, (b) triggering the typematic repeat feature of some keyboards to get an evenly separated series of keypress events, or (c) using a solenoid handled by a microcontroller to press the input device (keyboard, mouse button, touch screen) that will be used in the experimental setup. Despite the advantages of these approaches in some contexts, none of them can isolate the measurement error caused by the experiment software itself. Metronome LKM provides a virtual keyboard to assess an experiment’s software. Using this open source driver, researchers can generate keypress events using high-resolution timers and compare the time stamps collected by the experiment software with those gathered by Metronome LKM (with nanosecond resolution). Our software is highly configurable (in terms of keys pressed, intervals, SysRq activation) and runs on 2.6–4.8 Linux kernels.     

Measuring keyboard response delays by comparing keyboard and joystick inputs

The response characteristics of PC keyboards have to be identified when they are used as response devices in psychological experiments. In the past, the proposed method has been to check the characteristics independently by means of external measurement equipment. However, with the availability of different PC models and the rapid pace of model change, there is an urgent need for the development of convenient and accurate methods of checking. The method proposed here consists of raising the precision of the PC’s clock to the microsecond level and using a joystick connected to the MIDI terminal of a sound board to give the PC an independent timing function. Statistical processing of the data provided by this method makes it possible to estimate accurately the keyboard scanning interval time and the average keyboard delay time. The results showed that measured keyboard delay times varied from 11 to 73 msec, depending on the keyboard model, with most values being less than 30 msec.     

August Dvorak (1894-1975): Early expressions of applied behavior analysis and precision teaching

August Dvorak is best known for his development of the Dvorak keyboard. However, Dvorak also adapted and applied many behavioral and scientific management techniques to the field of education. Taken collectively, these techniques are representative of many of the procedures currently used in applied behavior analysis, in general, and especially in precision teaching. The failure to consider Dvorak's instructional methods may explain some of the discrepant findings in studies which compare the efficiency of the Dvorak to the standard keyboard. This article presents a brief background on the development of the standard (QWERTY) and Dvorak keyboards, describes parallels between Dvorak's teaching procedures and those used in precision teaching, reviews some of the comparative research on the Dvorak keyboard, and suggests some implications for further research in applying the principles of behavior analysis.     

The death of handwriting: secondary effects of frequent computer use on basic motor skills

The benefits of modern technologies such as personal computers, in-vehicle navigation systems, and electronic organizers are evident in everyday life. However, only recently has it been proposed that the increasing use of personal computers in producing written texts may significantly contribute to the loss of handwriting skills. Such a fundamental change of human habits is likely to have generalized consequences for other basic fine motor skills as well. In this article, the authors provide evidence that the skill to produce precisely controlled arm-hand movements is related to the usage of computer keyboards in producing written text in everyday life. This result supports the notion that specific cultural skills such as handwriting and typing shape more general perceptual and motor skills. More generally, changing technologies are associated with generalized changes of the profile of basic human skills.     

RTbox: A device for highly accurate response time measurements

Although computer keyboards and mice are frequently used in measuring response times (RTs), the accuracy of these measurements is quite low. Specialized RT collection devices must be used to obtain more accurate measurements. However, all the existing devices have some shortcomings. We have developed and implemented a new, commercially available device, the RTbox, for highly accurate RT measurements. The RTbox has its own microprocessor and high-resolution clock. It can record the identities and timing of button events with high accuracy, unaffected by potential timing uncertainty or biases during data transmission and processing in the host computer. It stores button events until the host computer chooses to retrieve them. The asynchronous storage greatly simplifies the design of user programs. The RTbox can also receive and record external signals as triggers and can measure RTs with respect to external events. The internal clock of the RTbox can be synchronized with the computer clock, so the device can be used without external triggers. A simple USB connection is sufficient to integrate the RTbox with any standard computer and operating system.     

The masked priming toolbox: an open-source MATLAB toolbox for masked priming researchers

The Masked Priming Toolbox is an open-source collection of MATLAB functions that utilizes the free third-party PsychToolbox-3 (PTB3: Brainard, Spatial Vision, 10, 433-436, 1997; Kleiner, Brainard & Pelli, Perception, 36, 2007; Pelli, Spatial Vision, 10, 437-442, 1997). It is designed to allow a researcher to run masked (and unmasked) priming experiments using a variety of response devices (including keyboards, graphics tablets and force transducers). Very little knowledge of MATLAB is required; experiments are generated by creating a text file with the required parameters, and raw and analyzed data are output to Excel (as well as MATLAB) files for further analysis. The toolbox implements a variety of stimuli for use as primes and targets, as well as a variety of masks. Timing, size, location, and orientation of stimuli are all parameterizable. The code is open-source and made available on the Web under a Creative Commons License.     

Does variability in human performance outweigh imprecision in response devices such as computer keyboards?

In chronometric research, it is well-known that many response devices used with personal computers, especially computer keyboards, suffer from measurement inaccuracies due to infrequent polling. In this article, it is investigated whether it is worth being concerned by this added error, given that human performance inherently exhibits a considerable degree of variability. By comparing inaccuracy due to response device imprecision with the level of variability already present in human performance, it is shown that the former is very unlikely to have a negative impact on statistical outcomes. In other words, millisecond resolution of response devices, although desirable, is not a general requirement.     

Using Arduino microcontroller boards to measure response latencies

Latencies of buttonpresses are a staple of cognitive science paradigms. Often keyboards are employed to collect buttonpresses, but their imprecision and variability decreases test power and increases the risk of false positives. Response boxes and data acquisition cards are precise, but expensive and inflexible, alternatives. We propose using open-source Arduino microcontroller boards as an inexpensive and flexible alternative. These boards connect to standard experimental software using a USB connection and a virtual serial port, or by emulating a keyboard. In our solution, an Arduino measures response latencies after being signaled the start of a trial, and communicates the latency and response back to the PC over a USB connection. We demonstrated the reliability, robustness, and precision of this communication in six studies. Test measures confirmed that the error added to the measurement had an SD of less than 1 ms. Alternatively, emulation of a keyboard results in similarly precise measurement. The Arduino performs as well as a serial response box, and better than a keyboard. In addition, our setup allows for the flexible integration of other sensors, and even actuators, to extend the cognitive science toolbox.     

键盘时间精度的一个图示法研究

以4个实验,用图示法对键盘的时间精度作了比较分析。实验1表明PES心理实验系统反应键和键盘都有良好的时间精度。实验2表明键盘的时间精度具有很大的个体差异,范围从1-2毫秒到40多毫秒,其中PS2的键盘普遍不理想。实验3表明键盘的时间精度不受转接器和计算机主频的影响。实验4使用了3名操作者,证实了这种方法的效果基本不受操作者个体差异的影响。研究演示了图示法在计算机控制的心理学实验中确定仪器的时间精度的作用,提示了实验中需要针对具体的实验条件判断时间精度是否符合实验要求,来确定是否选用特殊的反应键或者选择何种键盘作为反应的方式。     

The impacts of ignoring individual mobility across clusters in estimating a piecewise growth model

A three-level piecewise growth model (3L-PGM) can be used to break up nonlinear growth into multiple components, providing the opportunity to examine potential sources of variation in individual and contextual growth within different segments of the model. The conventional 3L-PGM assumes that the data are strictly hierarchical in nature, where measurement occasions (level 1) are nested within individuals (level 2) who are members of a single cluster (level 3). However, in longitudinal research, it is sometimes difficult for data structures to remain purely clustered during a study, such as when some students change classrooms or schools over time. One resulting data structure in this situation is known as a multiple membership structure, where some lower-level units are members of more than one higher-level unit. The new multiple membership PGM (MM-PGM) extends the 3L-PGM to handle multiple membership data structures frequently found in the social sciences. This study sought to examine the consequences of ignoring individual mobility across clusters when estimating a 3L-PGM in comparison to estimating a MM-PGM. MM-PGM estimates were less biased (especially in the cluster-level coefficient estimates), although we found substantial bias in cluster-level variance components across some conditions for both models.     

Incorporating Student Mobility in Achievement Growth Modeling: A Cross-Classified Multiple Membership Growth Curve Model

Multiple membership random effects models (MMREMs) have been developed for use in situations where individuals are members of multiple higher level organizational units. Despite their availability and the frequency with which multiple membership structures are encountered, no studies have extended the MMREM approach to hierarchical growth curve modeling (GCM). This study introduces a cross-classified multiple membership growth curve model (CCMM-GCM) for modeling, for example, academic achievement trajectories in the presence of student mobility. Real data are used to demonstrate and compare growth curve model estimates using the CCMM-GCM and a conventional GCM that ignores student mobility. Results indicate that the CCMM-GCM represents a promising option for modeling growth for multiple membership data structures.