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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 (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 comp

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2

Lazenby, Paul. "Confidence Intervals: A Computer Approach." Mathematical Gazette 70, no. 451 (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 (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 (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 (1989): 63–76. http://dx.doi.org/10.1300/j016v14n03_06.

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6

Bean, Jonathan. "Modeling confidence." Interactions 25, no. 3 (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 (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. Th

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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 (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

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Levine, Tamar, and Smadar Donitsa-Schmidt. "Commitment to Learning: Effects of Computer Experience, Confidence and Attitudes." Journal of Educational Computing Research 16, no. 1 (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-appl

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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 (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 experie

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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 (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-a

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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 (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-c

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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 (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

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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 (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 fac

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16

Alexandre dit Sandretto, Julien. "Confidence-based Contractor, Propagation and Potential Clouds for Differential Equations." Acta Cybernetica 25, no. 1 (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 confiden

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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 (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 (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 (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 (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 (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 (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, comp

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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 (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 gr

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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 (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 pla

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25

Kolko, Jon. "Teaching confidence in process." Interactions 22, no. 2 (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 (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 o

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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 (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 (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 comp

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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 (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 c

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32

Zhang, Xiangyu, Neelam Gupta, and Rajiv Gupta. "Pruning dynamic slices with confidence." ACM SIGPLAN Notices 41, no. 6 (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 (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 th

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35

Buchan, I. E. "Computer software that can calculate confidence intervals is now available." BMJ 310, no. 6989 (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 (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 (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 eff

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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 (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 w

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Chin, Shiu-Kai. "High-confidence design for security." Communications of the ACM 42, no. 7 (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 (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 (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 (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

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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 (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

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46

Wang, A. T. "Finite-Simulation Error Bounds for Estimated K-Year Forces." Journal of Offshore Mechanics and Arctic Engineering 111, no. 4 (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

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47

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 (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 shee

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48

Busch, Tor. "Gender Differences in Self-Efficacy and Attitudes toward Computers." Journal of Educational Computing Research 12, no. 2 (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 stude

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49

Melesko, Jaroslav, and Vitalij Novickij. "Computer Adaptive Testing Using Upper-Confidence Bound Algorithm for Formative Assessment." Applied Sciences 9, no. 20 (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 greate

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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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