Discovering Error Classes from Discrepancies in Novice Behaviors Via Multistrategy Conceptual Clustering

The automatic discovery of classes of errors that represent misconceptions and other knowledge errors underlying discrepancies in novice behavior is not a trivial task. A novel approach to this problem is described, in which relationships among behavioral discrepancies are analyzed and inductively generalized via an unsupervised, incremental, relational multistrategy conceptual clustering method that takes into account similarities as well as causalities in the data. Performance results on the classification of discrepancy sets and discovery of error classes from discrepancies of buggy PROLOG programs demonstrate the potential of the approach.     

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.     

Ability-training-oriented automated assessment in introductory programming course

Learning to program is a difficult process for novice programmers. AutoLEP, an automated learning and assessment system, was developed by us, to aid novice programmers to obtain programming skills. AutoLEP is ability-training-oriented. It adopts a novel assessment mechanism, which combines static analysis with dynamic testing to analyze student programs. It not only helps students to sufficiently test the programs, but also evaluates whether the programs meet the specification or not. AutoLEP encourages students to find and work through bugs, by providing automatic syntactic and structural checking, and immediate detailed feedback. This can improve students’ learning experience in programming and reduce the workload of the teaching staff. AutoLEP has been used in the C programming course at Harbin Institute of Technology and many other universities since 2004. The feedback on AutoLEP and its incorporation into the introductory programming course has been positive, both by students and teaching staff.     

Evaluating environments for functional programming

Functional programming presents new challenges in the design of programming environments. In a strongly typed functional language, such as ML, much conventional debugging of runtime errors is replaced by dealing with compile-time error reports. On the other hand, the cleanness of functional programming opens up new possibilities for incorporating sophisticated correctness-checking techniques into such environments. C^YNTHIA is a novel editor for ML that both addresses the challenges and explores the possibilities. It uses an underlying proof system as a framework for automatically checking for semantic errors such as non-termination. In addition, C^YNTHIA embodies the idea of programming by analogy—whereby users write programs by applying abstract transformations to existing programs. This paper investigatesC^YNTHIA 's potential as a novice ML programming environment. We report on two studies in which it was found that students using C^YNTHIA commit fewer errors and correct errors more quickly than when using a compiler/text editor approach.     

Crossing the digital divide safely and trustingly: how ecologies of learning scaffold the journey

The article addresses the issue of learning to elearn in borderless programs in a globalised learning landscape and the associated problems of scaffolding the journey across the digital divide. The authors argue that the assumption underlying such courses is that cross-cultural programs are viable because they are conceived and designed to be ‘global’, and that they assume this design to be inclusive. Henning and Van der Westhuizen claim that the global discourse in most domains can take only marginal note of the need to infuse such programs with a local semiotic—a course design criterion for which they argue. They furthermore forward the notion that the majority of the world's prospective elearners need various bridging mechanisms in order to be able to access the broader discourse and that one of these mechanisms can be explored through the metaphor of “information ecologies” as proposed by Nardi and O'Day [Nardi, B.A., & O'Day, V.L. (1999). Information ecologies. Using technology with heart. Cambridge, MA: The MIT Press]. They also conclude that issues of the learners’ trust in the course and its system need to be considered when contemplating programs for diverse target groups. By way of a case study, consisting of three portraitures of adult learners, they explore the limitations of assumed distributed cognition and claim that learning is, in reality, contained/constrained in the familiar local narrative of the novice adult elearners in a rural South African context. The case study illustrates how the resistance to technology and its power base becomes an obstacle for the students and how the support of peers becomes the main scaffolding mechanism for their entry into electronic learning environments. The findings thus show how the social context becomes the facilitator and the scaffold for elearning, more than technology and the curriculum itself.     

Performance effect of matching computer interface characteristics and user skill level

An experiment was conducted to see if matching user interface characteristics to user computer knowledge could improve user performance. User performance was measured by simulation game results, the extent of errors and user response time. Experiment subjects were tested to determine their level of computer knowledge using a pretested instrument. The subjects were randomly assigned to either a novice or experienced oriented interface version of a space manufacturing simulation. Results show that task performance (manufacturing profit) significantly increased when user interface characteristics were matched to user computer knowledge (e.g. novice interface to novice user). The relationship between interface match and user errors was marginally significant. The results of this study are important to software designers and practitioners purchasing software products.     

Issues in porting software from c to c++

This paper describes an experiment in the development of a small piece of software in both the languages C and C++ in a university setting. The C++ codes were found to be more modular than the corresponding C codes. Some of the other effects of C++ on program quality are very briefly discussed. The paper also discusses some of the errors that C programmers may make as novice C++ programmers, and the testing of object-oriented programs. Some of the error types possible in C++, but not in C, include delays in the flushing of output buffers and polymorphism.     

Using statistics to make expert systems “user-acquainted”

The user-acquainted feature collects user-specific data regarding the types of advice that have been sought over time and uses this historical information to update the probabilities to affect the firing of its rules and the ordering of the recommendations of the expert system. These updates are done on auser-specific basis so that the expert can more closely emulate a true expert by providing more informed advice. One example of a place where evidence suggests that such a feature would be useful is in the area of debugging of computer programs, especially in support of novice programmers who tend, as individuals, to commit similar classes of errors over time, but who, as a group, commit very different types of errors. We conjecture that the user-acquainted feature, which can keep track of the tendencies of the users and take them into account in the evaluation of diagnostics, will be more effectiveand efficient in determining the fault. In this paper, we discuss the statistical analyses necessary to implement this feature in an expert system for debugging errors in SAS.     

Learning Game-Specific Spatially-Oriented Heuristics

This paper describes an architecture that begins with enough general knowledge to play any board game as a novice, and then shifts its decision-making emphasis to learned, game-specific, spatially-oriented heuristics. From its playing experience, it acquires game-specific knowledge about both patterns and spatial concepts. The latter are proceduralized as learned, spatially-oriented heuristics. These heuristics represent a new level of feature aggregation that effectively focuses the program's attention. While training against an external expert, the program integrates these heuristics robustly. After training it exhibits both a new emphasis on spatially-oriented play and the ability to respond to novel situations in a spatially-oriented manner. This significantly improves performance against a variety of opponents. In addition, we address the issue of context on pattern learning. The procedures described here move toward learning spatially-oriented heuristics for autonomous programs in other spatial domains.     

Debug It: A debugging practicing system

This study reported the research findings on improving programming skills of novice programmers by way of debugging practices. There were two objectives of the debugging training: (1) to uncover and to correct any misconceptions of the programmers; and (2) to improve the debugging abilities of the programmers. To meet these objectives, a model of debugging practices, DebugIt, was presented. The proposed model called for supervised debugging practices on short programs involving frequently committed programming errors. A system, DebugIt:Loop, was developed specifically for debugging practices on programs with loop related errors. Two sets of experiments were conducted with 26 college students and 46 senior high school students enrolled in introductory Pascal courses. For each experiment, students were randomly assigned into the experimental group (using DebugIt:loop for debugging practice) and the control group (using traditional programming practices). A posttest was administered to compare the debugging and errorless programming abilities among the students in the two groups. The statistical procedure of an ANCOVA was used to analyze the gathered data. The results showed that this model of supervised debugging practices was effective in improving novice programmers' programming skills.     

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.     

A probe effect in concurrent programs

This paper reports on an experimental study of the probe effect, defined as an alteration in the frequency of run-time computational errors observed when delays are introduced into concurrent programs. If the concurrent program being studied has no synchronization errors, then there is no probe effect. In the presence of synchronization errors, the frequency of observable output errors for a sample experimental program starts at a high value for small delays, oscillates rapidly as the delay is increased, and apparently settles at zero errors for larger values of delay. Thus, for sufficiently large delays, the probe effect can almost completely mask synchronization errors in concurrent programs. For sufficiently large concurrent process sets, even small values of embedded delay may mask synchronization errors, provided side effects in shared memory are not included in the observation.     

优先归纳逻辑程序的极限行为

虽然对归纳逻辑程序的极限行为至今并没有深入的研究，但是通常在分析正在执行的增量式或在线归纳学习算法时，必须考虑这种程序的极限行为．某些归纳学习算法如果不考虑极限行为可能运行到最后会发生错误．如果给定一个递增的例子集合序列，一个归纳逻辑程序会产生一个相应的具有集合论极限的Horn逻辑程序序列，则此归纳逻辑程序是收敛的，并且如果该Horn逻辑程序序列关于例子集合序列的极限是极限正确的，则此归纳逻辑程序是极限正确的，还说明GOLEM系统不是极限正确的．为了解决这个问题，提出了一个极限正确的称为优先GOLEM系统的归纳逻辑系统，并证明了在一定的限制下，优先GOLEM系统的算法是极限正确的．     

Using eye movements to evaluate a PC-based risk awareness and perception training program on a driving simulator

OBJECTIVE: Evaluation of the effects of a PC-based training program on risk perception in a driving simulator. BACKGROUND: Novice drivers have a fatality rate some eight times higher than that of the most experienced group of drivers, primarily because of the novice driver's inability to predict ahead of time the risks that will appear in the roadway. Current driver education programs, at least those in the United States, do not emphasize the teaching of risk awareness skills to novice drivers. METHOD: A PC-based risk awareness and perception training program was developed and evaluated. The training involved using plan (top-down) views of 10 risky scenarios that helped novice drivers identify where potential risks were located and what information should be attended. Both the 24 trained novice drivers and 24 untrained novice drivers were evaluated on an advanced driving simulator. The eye movements of both groups of drivers were measured. The evaluation on the driving simulator included both scenarios used in the training and others not used in training. RESULTS: The set of trained novice drivers were almost twice as likely as untrained drivers to fixate appropriately either on the regions where potential risks might appear or on signs that warned of potentially risky situations ahead, both for the scenarios they had encountered in training and for novel scenarios. APPLICATION: The PC training program developed, which is portable and can be widely used, has great promise in improving risk perception for novice drivers on the road.     

Predicative methodology

Summary We introduce a predicative semantics of programs and show its use in programming. With it, logic errors can be detected and reported when they are made, just like syntax errors. Programming paradigms are stated precisely as theorems. The use of paradigms in larger programs is shown to be the same as the mathematician's use of theorems in the proof of larger theorems.     

Awareness of Organizational Expertise

Comprehension of computer programs involves identifying important program parts and inferring relationships between them. The ability to comprehend a computer program is a skill that begins its development in the novice programmer and reaches maturity in the expert programmer. This research examined the beginning of this process, that of comprehension of computer programs by novice programmers. The mental representations of the program text that novices form, which indicate the comprehension strategies being used, were examined. In the first study, 80 novice programmers were tested on their comprehension of short program segments. The results suggested that novices form detailed, concrete mental representations of the program text, supporting work that has previously been done with novice comprehension. Their mental representations were primarily procedural in nature, with little or no modeling using real‐world referents. In a second study, the upper and lower quartile comprehenders from Study 1 were tested on their comprehension of a longer program. Results supported the conclusions from Study 1 in that the novices tended towards detailed representations of the program text with little real‐world reference. However, the comprehension strategies used by high comprehenders differed substantially from those used by low comprehenders. Results indicated that the more advanced novices were using more abstract concepts in their representations, although their abstractions were detailed in nature.     

Performance consequences of alternating directional control-response compatibility: evidence from a coal mine shuttle car simulator

OBJECTIVE: To investigate error and reaction time consequences of alternating compatible and incompatible steering arrangements during a simulated obstacle avoidance task. BACKGROUND: Underground coal mine shuttle cars provide an example of a vehicle in which operators are required to alternate between compatible and incompatible steering configurations. METHODS: This experiment examines the performance of 48 novice participants in a virtual analogy of an underground coal mine shuttle car. Participants were randomly assigned to a compatible condition, an incompatible condition, an alternating condition in which compatibility alternated within and between hands, or an alternating condition in which compatibility alternated between hands. RESULTS: Participants made fewer steering direction errors and made correct steering responses more quickly in the compatible condition. Error rate decreased over time in the incompatible condition. A compatibility effect for both errors and reaction time was also found when the control-response relationship alternated; however, performance improvements over time were not consistent. Isolating compatibility to a hand resulted in reduced error rate and faster reaction time than when compatibility alternated within and between hands. CONCLUSION: The consequences of alternating control-response relationships are higher error rates and slower responses, at least in the early stages of learning. APPLICATION: This research highlights the importance of ensuring consistently compatible human-machine directional control-response relationships.