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Journal articles on the topic 'Computer confidence'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Weber, James E., Steven R. Ash, and Paula S. Weber. "Side Effects of Incidental Computer Use: Increased Confidence." Psychological Reports 83, no. 1 (August 1998): 211–14. http://dx.doi.org/10.2466/pr0.1998.83.1.211.

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100 students were administered a pretest based on two of Chickering's 1990 seven vectors of educational development. 67 participated in one of two management classes which required use of computers. 33 acted as a control group with no in-class computer use. Analyses indicate that in addition to intended gains in learning, students also showed related developmental effects including increased confidence in using computers. Changes in scores on perceived Autonomy, controlling for prior computer use and outside exposure to computers, were not significant. Results show some effects from using computers in the classroom to augment instruction.

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2

Lazenby, Paul. "Confidence Intervals: A Computer Approach." Mathematical Gazette 70, no. 451 (March 1986): 23. http://dx.doi.org/10.2307/3615820.

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3

Garcia-Santillan, Arturo, Elena Moreno-Garcia, Milka E. Escalera-Chávez, Carlos A. Rojas-Kramer, and Felipe Pozos-Texon. "Structural Equation Model to Validate: Mathematics-Computer Interaction, Computer Confidence, Mathematics Commitment, Mathematics Motivation and Mathematics Confidence." International Journal of Research in Education and Science 2, no. 2 (March 14, 2016): 518. http://dx.doi.org/10.21890/ijres.81576.

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4

Plumlee, Matthew. "Computer model calibration with confidence and consistency." Journal of the Royal Statistical Society: Series B (Statistical Methodology) 81, no. 3 (March 18, 2019): 519–45. http://dx.doi.org/10.1111/rssb.12314.

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5

Temple, Lori L., and Margaret Gavillet. "The Development of Computer Confidence in Seniors." Activities, Adaptation & Aging 14, no. 3 (December 21, 1989): 63–76. http://dx.doi.org/10.1300/j016v14n03_06.

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6

Bean, Jonathan. "Modeling confidence." Interactions 25, no. 3 (April 23, 2018): 25–27. http://dx.doi.org/10.1145/3194383.

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7

Nash, John B., and Pauline A. Moroz. "An Examination of the Factor Structures of the Computer Attitude Scale." Journal of Educational Computing Research 17, no. 4 (December 1997): 341–56. http://dx.doi.org/10.2190/ngdu-h73e-xmr3-tg5j.

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Previous research regarding the popular Computer Attitude Scale (CAS) has indicated that the computer confidence and computer anxiety subscales measure the same trait. This study, utilizing data yielded from 208 educators, obtained estimates of the reliability of the four subscale version of the forty item CAS; provided detailed information regarding the factor patterns of the CAS subscales; and provided evidence about the differential validity of the CAS among four groups with differing intensity of computer usage. Correlations and exploratory factor analysis were used to analyze the data. The results confirm that the confidence and anxiety subscales are a continuum. A new, smaller, subscale was created to reflect this relationship. Further, a new factor, attitudes toward academic endeavors associated with computer training, was named. The CAS may now be interpreted as a thirty-four-item scale addressing computer liking, perceived usefulness of computers, computer confidence/anxiety, and attitudes toward academic endeavors associated with computer training.

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8

WEBER, JAMES E. "SIDE EFFECTS OF INCIDENTAL COMPUTER USE: INCREASED CONFIDENCE." Psychological Reports 83, no. 5 (1998): 211. http://dx.doi.org/10.2466/pr0.83.5.211-214.

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9

Dyck, Jennifer L., and Janan Al-Awar Smither. "Age Differences in Computer Anxiety: The Role of Computer Experience, Gender and Education." Journal of Educational Computing Research 10, no. 3 (April 1994): 239–48. http://dx.doi.org/10.2190/e79u-vcrc-el4e-hryv.

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Research in the area of computer anxiety has traditionally concentrated on the younger adult. In this study older adults (55 years and over) were compared to younger adults (30 years and under) on levels of computer anxiety and computer experience. Subjects completed a demographic and computer experience questionnaire, a computer anxiety scale, and a computer attitude scale. Findings indicated that older adults were less computer anxious (as measured by both scales), had more positive attitudes toward computers, and had more liking for computers than younger adults. Older adults also had less computer experience than younger adults. In contrast, however, older subjects indicated less computer confidence than younger subjects. Additionally, for both younger and older adults, higher levels of computer experience were associated with lower levels of computer anxiety, and a more positive attitude toward computers. No gender differences were found for computer anxiety or computer attitudes when computer experience was controlled.

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10

Levine, Tamar, and Smadar Donitsa-Schmidt. "Commitment to Learning: Effects of Computer Experience, Confidence and Attitudes." Journal of Educational Computing Research 16, no. 1 (January 1997): 83–105. http://dx.doi.org/10.2190/qq9m-4yg0-pxy2-hmmw.

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Based on attitude-behavior theory which suggests that beliefs about an object lead to an attitude toward it, and that attitudes are an important precursor of behavior, this study proposes a causal model relating measures of computer-experience (degree of computer use at home and in school), computer-related attitudes (dispositions concerning the computer as an important, interesting, educational, and stereotypical tool), computer-related confidence (degree of confidence when using a computer), and commitment to computer learning (difference between self-perceived current level of computer-application knowledge and perceived level of desired knowledge). The model hypothesizes that computer experience positively affects perceived computer self-confidence and computer related attitudes. The model further hypothesizes that computer attitudes and computer confidence reciprocally affect one other in a positive way, and that both positively affect commitment to computer learning. Questionnaires were administered to 309 seventh to twelfth grade students. The theoretical model was tested by structural equation analysis (LISREL). Contrary to prediction, when attitudes were held constant, computer confidence was found to have a negative effect on commitment to learning. All other causal effects, including reciprocity were confirmed. The contribution and relevance of these findings to future educational research are discussed.

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11

Colley, Ann M., Matthew T. Gale, and Teri A. Harris. "Effects of Gender Role Identity and Experience on Computer Attitude Components." Journal of Educational Computing Research 10, no. 2 (March 1994): 129–37. http://dx.doi.org/10.2190/8na7-daey-gm8p-eun5.

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The effects of prior experience and gender stereotyping upon the computer anxiety, confidence and liking of 144 male and female students who had just commenced their studies at university were examined. Males were found to have lower computer anxiety, higher confidence and greater liking than females. When the effects of prior experience and gender stereotyping were removed however, no significant sex difference on these measures remained. The pattern of associations between experience, gender stereotyping variables and computer attitude measures differed for males and females. Greater experience at home was associated with lower anxiety for both sexes, with higher confidence for males and with greater liking for females. The influence of other family members also differed for the two sexes. The attitudes of both males and females were more positive if they had a brother who used computers, but the influence of father's use was positive for males only, while the influence of mother's use was positive for females only. For females but not males, higher scores on the Masculinity scale of the Bern Sex Role Inventory were associated with more positive computer attitudes. The results demonstrate the importance of experience, particularly in a home context, and of gender stereotyping in determining how males and females perceive computers.

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12

Lenard, Mary Jane, Susan Wessels, and Cindi Khanlarian. "Gender Differences In Attitudes Toward Computers And Performance In The Accounting Information Systems Class." American Journal of Business Education (AJBE) 3, no. 2 (February 1, 2010): 23–30. http://dx.doi.org/10.19030/ajbe.v3i2.382.

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Using a model developed by Young (2000), this paper explores the relationship between performance in the Accounting Information Systems course, self-assessed computer skills, and attitudes toward computers. Results show that after taking the AIS course, students experience a change in perception about their use of computers. Females’ self-evaluation of their computer skills improved significantly after the course, while males’ self-evaluation showed no change. Females also received significantly higher grades compared to males. There was a significant relationship between confidence and self-assessed computer skills. This study shows that the AIS course is successful in developing students’ confidence in using computers. Training that results in accurate self-assessment of skills may influence the choice of careers and one’s future success in those careers.

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13

Zhang, Yixin, and Sue Espinoza. "Affiliations of Computer Self-Efficacy and Attitudes with Need for Learning Computer Skills." Journal of Educational Computing Research 17, no. 4 (December 1997): 371–83. http://dx.doi.org/10.2190/3gny-apr6-51q8-402n.

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This study investigated relationships concerning computer efficacy, attitudes toward computers, and need for learning computer skills. A total of 296 undergraduate students from a regional state university participated in this study in 1996. Three research questions were measured by Attitudes toward Computer Technologies and Confidence and Desired Knowledge with Computer Technologies. Statistical analyses consisted of simultaneous multiple regression, ANOVA and Tukey's HSD. ANOVA revealed that students from computer classes had more need for learning computing skills than students from a non-computer class. Multiple regression revealed that attitudes toward computers, and computer self-efficacy, were significant predictors of the need for learning computing skills between two groups of students, although students from computer classes demanded a higher level of computing skills than those from a non-computer class.

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14

Liu, Wei, Frank Bretz, and Anthony J. Hayter. "Confidence Sets for Statistical Classification (II): Exact Confidence Sets." Stats 2, no. 4 (November 7, 2019): 439–46. http://dx.doi.org/10.3390/stats2040030.

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Classification has applications in a wide range of fields including medicine, engineering, computer science and social sciences among others. Liu et al. (2019) proposed a confidence-set-based classifier that classifies a future object into a single class only when there is enough evidence to warrant this, and into several classes otherwise. By allowing classification of an object into possibly more than one class, this classifier guarantees a pre-specified proportion of correct classification among all future objects. However, the classifier uses a conservative critical constant. In this paper, we show how to determine the exact critical constant in applications where prior knowledge about the proportions of the future objects from each class is available. As the exact critical constant is smaller than the conservative critical constant given by Liu et al. (2019), the classifier using the exact critical constant is better than the classifier by Liu et al. (2019) as expected. An example is provided to illustrate the method.

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15

Karim, Darvesh. "Exploring Head and Deputy Headteachers’ Attitude Towards Using Computers in Education." International Journal of Information and Communication Technology Education 8, no. 2 (April 2012): 20–32. http://dx.doi.org/10.4018/jicte.2012040102.

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Attitude plays a very significant role in acceptance of any idea or innovation. Research has established the significance of computers and the attitude of headteachers which can either be a hindering or a facilitating factor for computer integration in education. To explore this phenomenon in a Pakistani context, this study was conceptualised, while the subsidiary aim was also to explore the relationship between demographic characteristics of the participants and their attitude. A survey questionnaire was adopted to gather data with a sample of 185 headteachers to assess the four perceived factors’ impact; educational, social, training needs and self-confidence. The results show that the participants’ perceived attitude towards computers in education is positive while their perceived social impact of computers and their self-confidence found to be lower than the educational and training needs. Correlation analyses revealed significant associations between the headteachers’ attitude and the use of computers and prior training. In sub-scales model, prior training contributes to the training needs’ model while use of computer, contributed to the self-confidence model.

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16

Alexandre dit Sandretto, Julien. "Confidence-based Contractor, Propagation and Potential Clouds for Differential Equations." Acta Cybernetica 25, no. 1 (February 3, 2021): 49–68. http://dx.doi.org/10.14232/actacyb.285177.

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A novel interval contractor based on the confidence assigned to a random variable is proposed in this paper. It makes possible to consider at the same time an interval in which the quantity is guaranteed to be, and a confidence level to reduce the pessimism induced by interval approach. This contractor consists in computing a confidence region. Using different confidence levels, a particular case of potential cloud can be computed. As application, we propose to compute the reachable set of an ordinary differential equation under the form of a set of confidence regions, with respect to confidence levels on initial value.

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17

Perrone, Anthony, and David Lester. "Confidence in Personal Computer Use and Locus of Control." Perceptual and Motor Skills 86, no. 1 (February 1998): 162. http://dx.doi.org/10.2466/pms.1998.86.1.162.

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18

Rippey, Robert M. "A computer program for administering and scoring confidence tests." Behavior Research Methods, Instruments, & Computers 18, no. 1 (January 1986): 59–60. http://dx.doi.org/10.3758/bf03200999.

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19

Levine, Tamar, and Smadar Donitsa-Schmidt. "Computer use, confidence, attitudes, and knowledge: A causal analysis." Computers in Human Behavior 14, no. 1 (January 1998): 125–46. http://dx.doi.org/10.1016/s0747-5632(97)00036-8.

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20

SEN, TARUN, and WARREN J. BOE. "Confidence and accuracy in judgements using computer displayed information." Behaviour & Information Technology 10, no. 1 (January 1991): 53–64. http://dx.doi.org/10.1080/01449299108924271.

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21

Gardner, Donald G., Richard L. Dukes, and Richard Discenza. "Computer use, self-confidence, and attitudes: A causal analysis." Computers in Human Behavior 9, no. 4 (December 1993): 427–40. http://dx.doi.org/10.1016/0747-5632(93)90033-o.

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22

Shashaani, Lily. "Gender-Differences in Computer Experience and its Influence on Computer Attitudes." Journal of Educational Computing Research 11, no. 4 (December 1994): 347–67. http://dx.doi.org/10.2190/64md-htkw-pdxv-rd62.

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This study of 902 boys and 828 girls in secondary school shows that gender-differences in computer experience has a direct relationship to computer attitudes. The data analysis supports the hypothesis that male students have more computer experience than female students. This experience is measured by the number of computer classes attended, the amount of computer usage, and having access to a home computer. Boys showed more positive attitudes toward computers than girls. The number of classes students attended, and the amount of computer usage was positively related to computer interest, computer confidence (for boys), and perceived computer utility. Home computer ownership was not related to computer attitudes. The association between computer attitudes and computer experience was stronger for males than females.

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23

Bohlin, Roy M., and Nancy P. Hunt. "Course Structure Effects on Students' Computer Anxiety, Confidence and Attitudes." Journal of Educational Computing Research 13, no. 3 (October 1995): 263–70. http://dx.doi.org/10.2190/yb6q-hx39-11kk-gkyl.

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This study investigated the effects of course structure variables on the computer anxiety, confidence, and attitudes of pre- and in-service teachers. These course structure variables included the number of weeks the course met (course length) and the number of meetings per week (course frequency). Differences in course structure had significant effects on changes in the students' computer anxiety, confidence, liking, and perceptions of usefulness. With equivalent number of course hours, students in courses that met more times per week and that met over a longer time period had significantly greater changes in their computer anxiety, confidence, and attitudes. Implications of these findings include reconsideration of computer class configurations for teachers.

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24

Sevin, Rebecca, and Whitney Decamp. "From Playing to Programming: The Effect of Video Game Play on Confidence with Computers and an Interest in Computer Science." Sociological Research Online 21, no. 3 (August 2016): 14–23. http://dx.doi.org/10.5153/sro.4082.

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Research on the effects of playing video games has been limited by a preoccupation with possible negative repercussions. Nevertheless, research has shown that video games can have positive effects on young players’ social lives. The existing body of research, however, has largely ignored the more computer-related aspects of video game play and its effects. This study provides empirical evidence to support theoretical arguments about the relationship between playing video games and computers. The type of scientific thinking encouraged by video games and the technological abilities needed to play video games is suggested to result in an increase in players’ confidence with computers and interest in computer science. These potential relationships are examined using data from over 1,000 undergraduate students to empirically assess the relationship between video game play and: 1) confidence with computers, and 2) interest in computer science. The results indicate that game play is statistically significant as a predictor of confidence and interest. In comparison to the other predictors in the model, the strength of the effect from playing video games is relatively very strong. The findings suggest that exposure to video games as a recreational technology help inform players’ abilities with non-recreational technology and build an interest in technology in general.

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25

Kolko, Jon. "Teaching confidence in process." Interactions 22, no. 2 (February 25, 2015): 22–23. http://dx.doi.org/10.1145/2716280.

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26

MacKowiak, Kate. "Deaf College Students and Computers: The Beneficial Effect of Experience on Attitudes." Journal of Educational Technology Systems 17, no. 3 (March 1989): 219–29. http://dx.doi.org/10.2190/63gg-4d8w-abc6-wdew.

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The impact of individual differences on deaf college students' attitudes toward computers was investigated. Three components of computer attitudes were examined: liking, anxiety, confidence. Mean scores for each component were calculated. Subjects ( n = 131) were students of both sexes who responded to a questionnaire (alpha .89 for the fall semester and .92 for the spring semester). A t-test did not yield significant differences in the two administrations. The sample positively responded to lack of computer anxiety, and indicated computer liking. Students' confidence level was low. Analyses of variance procedures (.05 level of significance) were run to determine the effect of age, sex, computer experience and major on attitudes. Age, sex, and major were not statistically significant. Computer experience had main affect on all three components of computer attitudes. Interaction by age, sex, experience, and major, was statistically significant for computer anxiety only.

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27

Kim, Dongjoon, Heewon Kye, Jeongjin Lee, and Yeong-Gil Shin. "Confidence-Controlled Local Isosurfacing." IEEE Transactions on Visualization and Computer Graphics 27, no. 1 (January 1, 2021): 29–42. http://dx.doi.org/10.1109/tvcg.2020.3016327.

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28

Chu, Li-Li. "The Effects of Web Page Design Instruction on Computer Self-Efficacy of Preservice Teachers and Correlates." Journal of Educational Computing Research 28, no. 2 (March 2003): 127–42. http://dx.doi.org/10.2190/k79g-2pyy-vvu6-x988.

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This study tested the effects of Web page design instruction on improving computer self-efficacy of preservice teachers. A sample of 206 preservice teachers participated in this research. A pretest-posttest design experiment, including a 14-week instruction of Web page design, was conducted. The instruction of Web page design significantly improved the computer self-efficacy of preservice teachers. Various computer experiences, including weekly computer use, weekly Internet use, the use frequencies of word processing, e-mail, games, and presentation software, were significantly related to computer self-efficacy. The use frequencies of word processing and computer graphic software, weekly computer use, and age were the significant predictors of computer self-efficacy. The preservice teachers owning higher perception of computer self-efficacy revealed more confidence on Web page design self-efficacy. Generally, it is confirmed that most educators believe that increasing the opportunities to learn and use computers may facilitate the confidence and competence of preservice teachers.

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29

Houston, Louis M. "The Probability of a Confidence Interval Based on Minimal Estimates of the Mean and the Standard Deviation." Journal of Applied Mathematics 2013 (2013): 1–4. http://dx.doi.org/10.1155/2013/131424.

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Using two measurements, we produce an estimate of the mean and the sample standard deviation. We construct a confidence interval with these parameters and compute the probability of the confidence interval by using the cumulative distribution function and averaging over the parameters. The probability is in the form of an integral that we compare to a computer simulation.

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30

Wang, Linbo, Tianchen Xia, Yanwen Guo, Ligang Liu, and Jue Wang. "Confidence-driven image co-matting." Computers & Graphics 38 (February 2014): 131–39. http://dx.doi.org/10.1016/j.cag.2013.10.014.

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31

Ames, Pat C. "Gender and Learning Style Interactions in Students' Computer Attitudes." Journal of Educational Computing Research 28, no. 3 (April 2003): 231–44. http://dx.doi.org/10.2190/m8cu-de21-bjf1-84mn.

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University students' attitudes toward computers were assessed as a function of learning style. Analyses of responses provided by 232 students to a learning style assessment instrument and a computer attitude survey revealed that specific learning styles were associated with an affinity for (liking of), confidence in, and anxiety about the use of computers. Within those learning styles, gender differences were discovered when students manifested a clearly dominant style. The findings indicate that computer-based or computer-assisted instruction may not be appropriate for all students and that curriculum modifications to account for learning style differences may increase the effectiveness of and reduce the aversion to computers in the classroom. Additional research into the relationship between learning styles and computer attitudes may also provide assistance relative to increasing the enrollment of females in technology-oriented courses of study.

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32

Zhang, Xiangyu, Neelam Gupta, and Rajiv Gupta. "Pruning dynamic slices with confidence." ACM SIGPLAN Notices 41, no. 6 (June 11, 2006): 169–80. http://dx.doi.org/10.1145/1133255.1134002.

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33

Leung, Ka-Yee, and Manhung Siu. "Articulatory-feature-based confidence measures." Computer Speech & Language 20, no. 4 (October 2006): 542–62. http://dx.doi.org/10.1016/j.csl.2005.08.003.

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34

Qi, Jin Quan. "Design and Research of Computer System High Confidence Fault Tolerant." Applied Mechanics and Materials 644-650 (September 2014): 3361–64. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.3361.

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For high security and reliability of system critical areas, this paper designed a high-confidence fault-tolerant computer system, which combined high credibility technology with high organic reliability integration. High trusted computing technology used TCM structure to build a trusted password support system and achieve the platform integrity, identity authentication and data security. Redundant fault-tolerant technology to ensure the system, which activated in case of an error, is still able to provide uninterrupted service. Simulation results show the effectiveness and implementation of the technical solution approaches.

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35

Buchan, I. E. "Computer software that can calculate confidence intervals is now available." BMJ 310, no. 6989 (May 13, 1995): 1269–70. http://dx.doi.org/10.1136/bmj.310.6989.1269b.

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36

Silver, N. Clayton, Joanne Ullman, and Caleb J. Pick. "COMPCOR: A Computer Program for Comparing Correlations Using Confidence Intervals." Psychology and Cognitive Sciences - Open Journal 1, no. 1 (August 4, 2015): 26–28. http://dx.doi.org/10.17140/pcsoj-1-104.

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37

Corston, Rod, and Andrew M. Colman. "Gender and Social Facilitation Effects on Computer Competence and Attitudes toward Computers." Journal of Educational Computing Research 14, no. 2 (March 1996): 171–83. http://dx.doi.org/10.2190/7vw3-w6rv-6dcp-70mn.

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Subjects (36 male, 36 female), aged from fifteen to fifty-two years, performed a computer-based tracking task under one of six audience conditions in an experiment designed to investigate the effects of gender and social facilitation on performance. In addition to the computer task, each subject completed a fifteen-item questionnaire designed to identify levels of computer usage, computer-related anxiety, confidence and competence when using computers, and attitudes toward computers and computer users. Males performed significantly better than females, and a significant social facilitation effect was found. A significant Gender × Audience interaction was found, with females performing very much better in the presence of a female audience than alone or with a male audience. The implications for educational policy and practice are briefly discussed.

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38

Rotich, Paul K., Richard K. Ronoh, and Joseph M Mubichakani. "Attitude towards Computers among Primary School Teachers in Kenya: A Case of Siongiroi Divison, Bomet County." International Journal Of Engineering And Computer Science 7, no. 02 (February 21, 2018): 23596–605. http://dx.doi.org/10.18535/ijecs/v7i2.13.

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In the quest of equipping the pupils with the digital skills required to work in the 21st century knowledge economy, the government of Kenya plans to provide laptops to every primary school class one pupil. If this is to be successful, the question of teacher attitude towards computers is central. This paper presents the results of a survey to study and examine the attitudes of the primary school teachers towards computers. In addition, the study investigated the effects of age, gender, teaching experience, level of education, and computer experience on computer attitude. Data for this study was collected among 114 primary school teachers from Siongiroi Division, Bomet County, Kenya. Measurement tools used was the Computer Attitude Scale (CAS) by Loyd and Gressard (1984). The data acquired was analyzed using descriptive statistics and an analysis of variance (ANOVA).The results indicated that although the teachers have positive attitudes towards computers, they have low confidence level in using the computers. The study also found that the primary school teachers, despite their differences in gender, age, teaching experience and level of education, did not differ significantly (in statistical sense) in their computer attitude. Since teachers portray positive attitudes toward computers, efforts should be geared towards reinforcing the existing positive attitudes. This study highlights the importance of uplifting teachers’ confidence level in using computers

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39

Chin, Shiu-Kai. "High-confidence design for security." Communications of the ACM 42, no. 7 (July 1999): 33–37. http://dx.doi.org/10.1145/306549.306560.

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40

Sarkar, Vivek. "Building confidence in multicore software." Communications of the ACM 53, no. 6 (June 2010): 96. http://dx.doi.org/10.1145/1743546.1743571.

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41

Morris, R. Franklin, N. A. Jr., and Evelyn H. Thrasher. "Implications for e-commerce: the influence of math and computer confidence on computer self-efficacy." International Journal of Electronic Marketing and Retailing 3, no. 1 (2010): 15. http://dx.doi.org/10.1504/ijemr.2010.030505.

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42

Wang, Jialei, Peilin Zhao, and Steven C. H. Hoi. "Soft Confidence-Weighted Learning." ACM Transactions on Intelligent Systems and Technology 8, no. 1 (October 3, 2016): 1–32. http://dx.doi.org/10.1145/2932193.

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43

Schaeffer, Donna M., and Patrick C. Olson. "Securing Confidence With Data Escrow." International Journal of Management & Information Systems (IJMIS) 22, no. 2 (December 5, 2018): 1–6. http://dx.doi.org/10.19030/ijmis.v22i2.10225.

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In the past several years, the general public has had concerns about hacking and identity theft. Headlines in news media include computer system breaches at popular and respected companies like Target and universities like The University of California at Berkeley. This paper explores options available for providing the general public with the benefits of the information age while mitigating against the security risks. We begin with a discussion of it is reasonable for the general public to expect organizations engaged primarily in commerce to provide for their cybersecurity. We then look at how electronic transactions are currently secured. We conclude with a consideration of the “protocols” or “institutions” that might provide for security for consumers.

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44

Ferson, Scott, and Marco De Angelis. "Computing with confidence." International Journal of Approximate Reasoning 137 (October 2021): 67–68. http://dx.doi.org/10.1016/j.ijar.2021.07.001.

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45

Chen, Milton. "Gender and Computers: The Beneficial Effects of Experience on Attitudes." Journal of Educational Computing Research 2, no. 3 (August 1986): 265–82. http://dx.doi.org/10.2190/wdry-9k0f-vcp6-jccd.

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This study examines gender differences in computer attitudes and experiences of adolescents. A sample of students from five Bay Area high schools was surveyed for their uses of computers before and during their high school years, in both formal instruction and informal settings. Adolescent males had greater total exposure to computers, based primarily on higher enrollments in computer programming classes and participation in voluntary experiences, such as home computer use. Fewer gender differences were found in enrollment in classes using computers for purposes other than programming. Overall, males held more positive attitudes of interest in and confidence with computers than did females. Controlling for amount of computer experience, however, males and females responded with similar levels of interest. Social influences, especially those among peer groups, are explored as important factors for differential rates of participation in computer activities.

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Wang, A. T. "Finite-Simulation Error Bounds for Estimated K-Year Forces." Journal of Offshore Mechanics and Arctic Engineering 111, no. 4 (November 1, 1989): 273–77. http://dx.doi.org/10.1115/1.3257095.

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Computer simulations have been used frequently to calculate design loads associated with a specific return period for offshore structures. However, two important questions persistently confront engineers who simulate load events on computers to estimate k-year forces: 1) How accurate is the estimated k-year force (say, 100-yr force) obtained through a computer simulation of n years (e.g., n = 1000) compared to that which would result from a much longer simulation? 2) When can we stop a computer simulation? Or how many simulation years are needed to reach a specified level of reliability for a certain k-year force? This paper presents solutions to these two questions under the assumption that the input parameters are completely known and the formulas used to compute loads are one hundred percent correct. Given a confidence level C (e.g., C = 80 or 90 percent) and an arbitrary but fixed number of simulation years, a method is identified to find an estimated k-year force and an error bound α, such that Pr(|estimator−k-yearforce|<α)>C (1) In addition, when the required confidence C and error bound α are given, a procedure is given to stop a computer simulation as soon as inequality (1) is satisfied. These results are not dependent on the statistical distribution of the underlying force distribution. Therefore, one does not have to assume that forces are of a specific probability distribution (such as lognormal, exponential, etc.).

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Farida, Anisatul, and Ratna Puspita Indah. "Pengembangan Model Pembelajaran ARCS (Attention, Relevance, Confidence, Satisfaction) Dengan Wolfram Mathematica." Jurnal Derivat: Jurnal Matematika dan Pendidikan Matematika 6, no. 2 (January 11, 2020): 47–53. http://dx.doi.org/10.31316/j.derivat.v6i2.496.

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AbstractThis study aimed to develop a computer-based ARCS kind of classroom that valid, practical, and effective.This research adopting both qualitative and quantitative research and development with a method developed by Gall and the Borg. This research subject was students of engineering information Duta Bangsa Universityperiod 2018 / 2019.An instrument in this research consists of ( 1 ) an instrument assessment valid components model and devices supporting learning, ( 2 ) an instrument assessment practicality of faculty and students, and ( 3 ) instrument effectiveness of which includes sheets of the test results learning and chief appreciation students to learning linear algebra computer-based.The subject of this research is 25 students who took linear algebra. The study showed that Kind of classroom computer-based ARCS that met the criteria of valid, practical, and effective. Practicality ARCS kind of classroom computer-based based on ( 1 ) assessments from he got from his lecturers have reached very practical criteria; ( 2 ) assessing the from students we have achieved very practical criteria. The current effectiveness of ARCS kind of classroom computer-based based on ( 1 ) the results of THB students, fulfilled the criteria the current effectiveness of with the percentage 76 %, ( b ) appreciation students learning ARCS against computer-driven which reached the criteria for good. It is also can be said that there is a correlation between appreciation students learning arcs against computer-based learning about mathematics with the results of the first significance 5 % with a correlation coefficient r = 0,715 Keywords: Kind of classroom ARCS, computer, linear algebra.

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Busch, Tor. "Gender Differences in Self-Efficacy and Attitudes toward Computers." Journal of Educational Computing Research 12, no. 2 (March 1995): 147–58. http://dx.doi.org/10.2190/h7e1-xmm7-gu9b-3hwr.

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This study is aimed to investigate gender differences regarding computer attitudes and perceived self-efficacy in the use of computers among 147 college students. At the end of a computer course, the students completed a questionnaire designed to measure self-efficacy, computer anxiety, computer liking, and computer confidence. The results revealed gender differences in perceived self-efficacy regarding completion of complex tasks in both word processing and spreadsheet software. No gender differences were found in computer attitudes or self-efficacy regarding simple computer tasks. Male students had previously had more computer experience in programming and computer games and reported that they had previously had more encouragement from parents and friends.

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Melesko, Jaroslav, and Vitalij Novickij. "Computer Adaptive Testing Using Upper-Confidence Bound Algorithm for Formative Assessment." Applied Sciences 9, no. 20 (October 14, 2019): 4303. http://dx.doi.org/10.3390/app9204303.

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There is strong support for formative assessment inclusion in learning processes, with the main emphasis on corrective feedback for students. However, traditional testing and Computer Adaptive Testing can be problematic to implement in the classroom. Paper based tests are logistically inconvenient and are hard to personalize, and thus must be longer to accurately assess every student in the classroom. Computer Adaptive Testing can mitigate these problems by making use of Multi-Dimensional Item Response Theory at cost of introducing several new problems, most problematic of which are the greater test creation complexity, because of the necessity of question pool calibration, and the debatable premise that different questions measure one common latent trait. In this paper a new approach of modelling formative assessment as a Multi-Armed bandit problem is proposed and solved using Upper-Confidence Bound algorithm. The method in combination with e-learning paradigm has the potential to mitigate such problems as question item calibration and lengthy tests, while providing accurate formative assessment feedback for students. A number of simulation and empirical data experiments (with 104 students) are carried out to explore and measure the potential of this application with positive results.

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Sachs, Gary, Daniel DeBonis, and Claudia Baldassano. "Use of computer interviews to increase diagnostic confidence for bipolar disorders." International Clinical Psychopharmacology 26 (September 2011): e132-e133. http://dx.doi.org/10.1097/01.yic.0000405858.53517.89.

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