The links between human error diversity and software diversity: Implications for fault diversity seeking

Software diversity is known to improve fault tolerance in N-version software systems by independent development. As the leading cause of software faults, human error is considered an important factor in diversity seeking. However, there is little scientific research focusing on how to seek software fault diversity based on human error mechanisms. A literature review was conducted to extract factors that may differentiate people with respect to human error-proneness. In addition, we constructed a conceptual model of the links between human error diversity and software diversity. An experiment was designed to validate the hypotheses, in the form of a programming contest, accompanied by a survey of cognitive styles and personality traits. One hundred ninety-two programs were submitted for the identical problem, and 70 surveys were collected. Code inspection revealed 23 faults, of which 10 were coincident faults. The results show that personality traits seems not effective predictors for fault diversity as a whole model, whereas cognitive styles and program measurements moderately account for the variation of fault density. The results also show causal relations between performance levels and coincident faults: coincident faults are unlikely to occur at skill-based performance level; the coincident faults introduced in rule-based performances show a high probability of occurrence, and the coincident faults introduced in knowledge-based performances are shaped by the content and formats of the task itself. Based on these results, we have proposed a model to seek software diversity and prevent coincident faults.     

Individual differences and the user interface

Individual differences in cognitive functions are relevant in introducing novioes to computing. The interaction between the user and the computer may be improved if these psychological characteristics are taken into account in the design of the user interface and in the design of introductory courses. In.section 1 of this paper an analysis is made of individual differences and of the possibilities of adaptation. The user interface is described as an opportunity for adaptation. Methods of adaptation are systematically related to the changeability of individual differences. Illustrated by an overview of previous experimental work, some principles of adaptation are demonstrated in relation to individual differences on variables that are relevant in human-computer interaction. Prior knowledge of mathematics has been shown to be related to success and failure in learning a programming language, and to motivation for using computers. In section 2 ways to prevent the course drop-out rate by structuring the teaching method are illustrated. Strategies of information processing in the user interface, in relation to metacommunication and teaching, are described in section 3 as another example of an individual difference variable that may be attended to in teaching, resulting in reduction of problem solving time. Some cognitive styles are related to success in programming. The choice of adequate educational examples may improve programming habits, as illustrated in section 4. Style of representation and spatial ability are relevant for the development of mental models of computer system. In section 5 some field studies on teaching novices to work with office systems illustrate these relations. Teaching strategies, educational examples, and metaphors, may neutralize the handicap some novices have because of these variables.     

Antecedents of computer self-efficacy: A study of the role of personality traits and gender

Empirical evidence suggests that computer self-efficacy plays an important role in one’s acceptance and use of new information technology. Little is however known about the antecedents of computer self-efficacy. This paper reports on a study of 143 non-users of a self-checkout library system available at a large Canadian university which was conducted to investigate the relationships between stable personality traits and gender with computer self-efficacy. Results indicate that four of the five stable personality traits, as measured by the Big-5 factors of personality, contribute to explain computer self-efficacy. Taking gender into account, results show that the traits of neuroticism, extraversion, and agreeableness are significantly related to computer self-efficacy for women but not for men. Implications for research and practice are discussed.     

Sources of difficulty in assessing the cognitive effects of learning to program

Abstract  Since the publication of Seymour Papert's 'Mindstorms' in 1980 there has been a steady flow of articles reporting on research which has attempted, in some sense, to test the claims made for programming as an educationally beneficial activity. The overall picture that these articles paint is not a clear one, but they leave a residual impression that the claims are, as yet, unsubstantiated. This paper argues that we are not in need of further controlled experimental studies so much as a clarification of our understanding of the novice programmer's learning task. It reviews a number of studies which have attempted to model the cognitive demands of programming through detailed observation rather than through abstract analysis. It emphasizes the distinction between programming as it is experienced in introductory classes and programming as an idealized cognitive activity.     

The impact of LOGO on gifted children's achievement and creativity

It was hypothesised that problem solving via the Arabic logo programming environment would enhance gifted children's mathematics achievement and their creativity as measured by their performance on Torrance Tests of Creative Thinking (TTCT) and Mathematical Skills Assessment (MSA). The study findings extend previous research by indicating that problem solving via the LOGO programming environment can enhance mathematics achievement and creativity in figural, as well as verbal, domains. The evaluation of a large number of previous studies on the enhancement of creativity concluded that many of these studies have a positive effect. An implication is that computer environments may offer appropriate special provisions to meet the special needs of gifted children. In addition, this experiment provided some evidence that if gifted children work in pairs the need for teacher intervention to motivate the children is decreased. Also, if gifted children choose their own goals this increases their motivation and task commitment but might also restrict the range of mathematical ideas used.     

Problematic internet use,psychopathology, personality,defense and coping

Many international studies in the field of Internet use and Problematic Internet Use (PIU) have shown strong and frequent relationships with psychopathology. However, few researches have investigated the relationships between PIU and personality variables such as defense, coping and pathological traits. The aim of the present study was to explore the rate of PIU among French users and its relationships with psychopathological (depressive symptoms, self-esteem, pathological personality traits) and psychological variables (defense mechanisms and coping strategies). A sample of 786 participants, aged between 18 and 35 years old (M = 23.7; SD = 4.5) has been recruited online and completed several scales assessing PIU, time spent online, socio demographic, psychological and psychopathological variables. More than 20% of the sample had PIU. Compared to non-problematic users, they had significant higher scores of all personality disorder clusters, non-adaptive coping and depressive symptoms. Among the total sample, PIU was predicted by Clusters B and C personality traits, immature and autistic fantasy defense styles, non-adaptive coping strategies and depressive symptoms. Significant gender differences have been retrieved. Psychological and psychopathological variables, including personality traits should be further explored, and gender differences always taken into account when assessing PIU.     

Why we believe the computer when it lies

A survey was conducted on the sample of 60 future engineers in order to determine whether inadequate computer feedback changes the supposed success in problem solving and whether personality traits are also in the function of this change. The research results showed that personality traits fail to influence the formation of beliefs on success. Results also showed that the situation of inadequate feedback results in the changes in beliefs, on the success in problem solving and that the change is in the function of personality traits and established experience-based behavior strategies. In this situation respondents do not form any strategy for attitude conservation, but inadequate computer feedback significantly reduces estimation of their success regardless to the fact that the objective achievement is not reduced.     

Effects of Personality on Pair Programming

Personality tests in various guises are commonly used in recruitment and career counseling industries. Such tests have also been considered as instruments for predicting the job performance of software professionals both individually and in teams. However, research suggests that other human-related factors such as motivation, general mental ability, expertise, and task complexity also affect the performance in general. This paper reports on a study of the impact of the Big Five personality traits on the performance of pair programmers together with the impact of expertise and task complexity. The study involved 196 software professionals in three countries forming 98 pairs. The analysis consisted of a confirmatory part and an exploratory part. The results show that: 1) Our data do not confirm a meta-analysis-based model of the impact of certain personality traits on performance and 2) personality traits, in general, have modest predictive value on pair programming performance compared with expertise, task complexity, and country. We conclude that more effort should be spent on investigating other performance-related predictors such as expertise, and task complexity, as well as other promising predictors, such as programming skill and learning. We also conclude that effort should be spent on elaborating on the effects of personality on various measures of collaboration, which, in turn, may be used to predict and influence performance. Insights into such malleable, rather than static, factors may then be used to improve pair programming performance.     

A Lexical Approach to Study Computer Games and Game Play Experience via Online Reviews

This article proposes a revised lexical approach to understand characteristics of computer games and user experience in game play by analyzing online game reviews. The lexical approach was originally used by psychologists to study personality traits. It was based on a lexical hypothesis stating that personality traits are reflected in the adjectives people have been using to describe personality over a long time. A factor analysis was then conducted to identify the patterns of personality related adjectives (i.e., personality traits). The argument here is that game players have used natural languages to describe computer games and their experiences over time and that the most important characteristics of computer games and game play experience would be reflected in player language. Therefore, the traits of computer games and user experience during game play can be studied by examining the adjectives used by players in online reviews. Based on 696,801 reviews downloaded from three major game websites, the lexical approach was adapted to analyze textual content pertaining to computer games. In two consecutive studies, the most important factors concerning traits of computer games and game play experience were discovered and analyzed. The implications of the revised lexical approach and findings from this project were discussed.     

Personality, individual characteristics, and predisposition to technophobia: some answers, questions, and points to ponder about

Technophobia has been an enduring problem in industrial economies over the last 20 years. Though explanatory models have been proposed to explain the prevalence of technophobia, these efforts have been diffuse, contradictory, and lacking in consistency. Against this background, this paper investigates the role of individual characteristics including: (a) personality variables proposed by the big five theory of personality, (b) cognitive orientation, and (c) math and logic skills on technophobia. Data are gathered from 242 subjects at a private university in Western New York. The research hypotheses are tested using t-tests, and correlation analysis. Interpretation of results and potential directions for future research are presented.     

Learning styles and cognitive traits – Their relationship and its benefits in web-based educational systems

Different learners have different needs; they differ, for example, in their learning goals, their prior knowledge, their learning styles, and their cognitive abilities. Adaptive web-based educational systems aim to cater individual learners by customizing courses to suit their needs. In this paper, we investigate the benefits of incorporating learning styles and cognitive traits in web-based educational systems. Adaptivity aspects based on cognitive traits and learning styles enrich each other, enabling systems to provide learners with courses which fit their needs more accurately. Furthermore, consideration of learning styles and cognitive traits can contribute to more accurate student modelling. In this paper, the relationship between learning styles, in particular the Felder–Silverman learning style model (FSLSM), and working memory capacity, a cognitive trait, is investigated. For adaptive educational systems that consider either only learning styles or only cognitive traits, the additional information can be used to provide more holistic adaptivity. For systems that already incorporate both learning styles and cognitive traits, the relationship can be used to improve the detection process of both by including the additional information of learning style into the detection process of cognitive traits and vice versa. This leads to a more reliable student model.     

Software Science and Cognitive Psychology

Halstead proposed a methodology for studying the process of programming known as software science. This methodology merges theories from cognitive psychology with theories from computer science. There is evidence that some of the assumptions of software science incorrectly apply the results of cognitive psychology studies. HAlstead proposed theories relative to human memory models that appear to be without support from psychologists. Other software scientists, however, report empirical evidence that may support some of those theories. This anomaly places aspects of software science in a precarious position. The three conflicting issues discussed in this paper are 1) limitations of short-term memory and number of sub-routine parameters, 2) searches in human memory and programming effort, and 3) psychological time and programming time.     

Modelling programming performance: Beyond the influence of learner characteristics

In the 21st century, the ubiquitous nature of technology today is evident and to a large extent, most of us benefit from the modern convenience brought about by technology. Yet to be technology literate, it is argued that learning to program still plays an important role. One area of research in programming concerns the identification of predictors of programming success. Previous studies have identified a number of predictors. This study examined the effect of a combination of predictors (gender, learning styles, mental models, prior composite academic ability, and medium of instruction) on programming performance. Data were collected anonymously through a website from 131 secondary school students in Hong Kong who opted for computer programming in the Computer and Information Technology curriculum. Partial Least Squares (PLS) modelling was used to test a hypothesized theoretical structural model. All of the five aforementioned variables were either direct or indirect predictors of programming performance and the antecedents accounted for 43.6% of the variance in programming performance. While this study shows the influence of learner characteristics such as gender, learning styles, and mental models on programming performance, it highlights the effect that prior composite academic ability and medium of instruction exert on learning outcomes, which is uncommon among studies of similar purpose. These findings have significant implications for policy makers and educators alike.     

Computer-administered testing with the Rotter Incomplete Sentences Blank

Despite studies finding relatively small differences between computer and traditional methods of administering objective personality and cognitive measures, no similar format equivalence research has been done for projective personality measures. The present study compares two groups of college students' responses to either a traditional administration or a computer administration of the Rotter Incomplete Sentences Blank (ISB). No differences were found for subject characteristics of age or gender. The groups receiving different forms of administration differed on the ISB maladjustment score, a global index of psychological difficulties, with the computer administration group exhibiting fewer test signs of maladjustment than the traditional administration group. However, differences between the two forms were small and nonsignificant after adjusting for attitudes towards computers. The findings suggested that computer ISB administration was likely to yield a similar level of disclosure as the traditional ISB administration when nonclinical levels of maladjustment are present. Suggestions are made for further research, including the use of contrasting samples and additional projective instruments.     

Predicting vigilance: A fresh look at an old problem

Individual differences in vigilance are ubiquitous and relevant to a variety of work environments in industrial, transportation, medical and security settings. Despite much previous work, mostly on personality traits, it remains difficult to identify vigilant operators. This paper reviews recent research that may point towards practically useful predictor variables for vigilance. Theoretical approaches to identifying predictors that accommodate the heterogeneous nature of vigilance tasks are compared. The article surveys recent empirical studies using personality measures, ability tests and scales for stress and coping as predictors of vigilance. Promising new constructs include trait scales linked to fatigue, abnormal personality and the stress state of task engagement. Implications of the data reviewed for occupational selection are discussed. Selection should be based on a multivariate assessment strategy, cognitive task analysis of the operational vigilance task and use of work sample measures to capture typical stress responses to the task. This review paper surveys recent research that may point towards practically useful predictor variables for vigilance. The article surveys recent empirical studies using personality measures, ability tests and scales for stress and coping as predictors of vigilance. Selection should be based on a multivariate assessment strategy.     

The relationship of psychological type to computer aptitude,attitudes, and behavior

Based on a review of research on the relationship of personality factors to human-computer interaction, Pocius (1991) concluded that there was little evidence for a relationship between Jungian psychological types and programming aptitude and mixed evidence regarding psychological type and computer-related attitudes. However, the studies on which Pocius based this conclusion suffered from a number of methodological flaws, including small sample sizes and restricted samples. In the present study, data from 471 introductory psychology students revealed that some dimensions of psychological type were related to computer aptitude, attitudes, and behavior, with psychological type interacting with participant sex in two instances. Implications of these findings are discussed.     

The relationship between learning styles and cognitive traits – Getting additional information for improving student modelling

Student modelling is an important process for adaptive virtual learning environments. Student models include a range of information about the learners such as their domain competence, learning style or cognitive traits. To be able to adapt to the learners’ needs in an appropriate way, a reliable student model is necessary, but getting enough information about a learner is quite challenging. Therefore, mechanisms are needed to support the detection process of the required information. In this paper, we investigate the relationship between learning styles, in particular, those pertaining to the Felder–Silverman learning style model and working memory capacity, one of the cognitive traits included in the cognitive trait model. The identified relationship is derived from links between learning styles, cognitive styles, and working memory capacity which are based on studies from the literature. As a result, we demonstrate that learners with high working memory capacity tend to prefer a reflective, intuitive, and sequential learning style whereas learners with low working memory capacity tend to prefer an active, sensing, visual, and global learning style. This interaction can be used to improve the student model. Systems which are able to detect either only cognitive traits or only learning styles retrieve additional information through the identified relationship. Otherwise, for systems that already incorporate learning styles and cognitive traits, the interaction can be used to improve the detection process of both by including the additional information of a learning style into the detection process of cognitive traits and vice versa. This leads to a more reliable student model.     

Using fuzzy logic applied to software metrics and test cases to assess programming assignments and give advice

Programming is an important competence in Computer Science and Engineering studies. Students have to pass the related programming subjects proving that they have acquired the necessary knowledge and skills. Such knowledge and skills will be essential for their academic training and future careers. However, students of programming subjects have to solve deep cognitive challenges. One of our objectives is to help them overcome these challenges.To overcome the first difficulties the students may encounter while developing their assignments, we will present an approach that provides a first assessment of the students’ solution. This will allow the system to estimate a mark on a student assignment; so it can provide some kind of adaption and guidance in the learning process. It will allow the students to ask the system what is wrong with the solution they are developing, without teacher intervention. Thus, our aim is to create a system that assists the students in understanding what they are doing and helps the teachers in their labour in the classroom.Although the assessment technique we will show can be extrapolated to other programming areas, this paper focuses on a concrete one, namely Programming Algorithms. In this respect, throughout the paper we will show how to process and analyse algorithms written by students as solutions to programming assignments, something that is ongoing in those computer supported systems for learning to program. As a result, a proposal for assessing algorithms applying Fuzzy Logic to software metrics and test cases will be explained. In addition, the Computer Assisted Environment for Learning Algorithms (COALA) environment will be exposed in order to validate our proposals. Furthermore, we will explain the developed empirical study and also analyse and explain the results. These results seem to point out that the proposals are successful enough, but we must continue working on this research line to provide evaluations that are closer to those provided manually by a teacher.     

Is students’ computer use at home related to their mathematical performance at school?

Recent research has provided evidence that students’ computer use at home is positively associated with their performance at school. However, most of the previous studies have failed to take into account the multiple determination of school performance and, in addition, to explain why using computers at home should benefit students’ academic achievement. The study described in this article takes a step towards filling this gap by circumventing the theoretical and methodological problems of previous research. First, we analyzed students’ home computer use and their performance in mathematics while accounting for other factors that have been found to affect students’ achievement. Second, we investigated possible differences in students’ school performance depending on how they used the computer. Based on the data from German students who took part in the Programme for International Student Assessment (PISA) in 2003, our results showed that students’ access to a computer was not linked with their performance in mathematics. In addition, it did not matter how often students used a computer at home. A positive effect on mathematical achievement was, however, observed for a small group of students who used the computer in a self-determined way that largely engaged them in problem-solving activities. Overall, the findings indicate that for the majority of students the computer had no substantial influence on their academic achievement. At the same time, the results are suggestive of ways in which performance in mathematics might be enhanced through the use of computers.     

A concept map-embedded educational computer game for improving students' learning performance in natural science courses

Many recent studies have reported the benefits of educational computer games in promoting students' learning motivations. On the other hand, however, the effect of digital game-based learning in improving students' learning performance has been questioned. Several previous studies have reported that without properly integrating learning strategies into gaming scenarios, the effectiveness of educational computer games could be limited, or may be even worse than that of the conventional technology-enhanced learning approach. In this study, a concept map-embedded gaming approach is proposed for developing educational computer games by integrating concept mapping as part of the gaming scenarios to help students organize what they have learned during the game-based learning process. Moreover, a role-playing game has been developed for an elementary school natural science course based on the proposed approach. From the experimental results, it is found that the concept map-embedded gaming approach can significantly improve the students' learning achievement and decrease their cognitive load. Moreover, the students who learned with the proposed approach revealed a significantly higher degree of perceived usefulness than those who learned with the conventional game-based learning approach.