Student confidence in using computers

Preprints of the 2 nd Computer Science Education Research Conference pp. 3 7 ISBN Student confidence in using computers The influence of parental adoption of technology ABSTRACT Hugo Breedt Department of Computer Science University of Pretoria Pretoria, South Africa hbreedt@cs.up.ac.za Confidence is an influential factor of student engagement in education. In Computer Science education the lack of confidence is prominent as a barrier to education and attempts to address it have not all been very successful. This paper surveys confidence levels of students in relation to the amount by which their parents adopted technology into their personal lives. Our findings can supply a basis from which an alternative method of addressing confidence can be constructed. Categories and Subject Descriptors K.3.2 [Computers and Education]: Computers and Information Science Education General Terms Management, Human Factors Keywords Technical fluency, Confidence 1. INTRODUCTION The influence of the home environment, specifically parents, on cognitive socialization of children has long been recognized and researched [1, 13]. Cognitive socialization is the process by which we develop cognitively in a social context. Zerubavel [16] explains that this is the process by which we learn to act, think, perceive and interpret the world from within our social context. New technology is developed and changed constantly and rapid. The amount by which new technologies (and specifically computers) are adopted into personal lives varies greatly. This article will relate an introductory computer programming student s confidence in working with computers (as an influential factor of Computer Science education) to the adoption of computers by the student s parents. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. CSERC 2012, Wrocław, Poland Copyright 2012 ACM X-XXXXX-XX-X/XX/XX...$10.00. Vreda Pieterse Department of Computer Science University of Pretoria Pretoria, South Africa vpieterse@cs.up.ac.za 2. LITERATURE REVIEW 2.1 Success factors when learning to program Two major factors contributing to success in programming related subjects that has been identified in the past are the mathematical competence of students [2] and prior use of computers. Rozell and Gardner [12] found that people with prior computer experience exhibited higher performance on computer-related tasks. Durndell and Haag [5] found that computer anxiety and self-efficacy are related to reported use of and attitudes towards the Internet and contend that this finding corroborates the literature on attitudes and anxiety towards computers. Computer programming is cognitively challenging [6, 10]. Computing related courses often are among the subjects at tertiary level with the lowest pass-rates [6]. The distinction between technical fluency and computer literacy is blurred. Goodson and Mangan [7] criticized computer literacy as an ideology and its teaching as vague and often ineffective. They stated, For most people, computer literacy probably means...a general, diffuse familiarity and comfort with computers. In fact, becoming comfortable with computers is frequently seen as being equally, if not more important, than becoming literate, in the sense of possessing technical fluency. The observation that a student that owns her own computer, is probably more computer literate than her peers that don t has long been known [8] and was recently reported [14]. At the heart of Computing education is the Mathematical approach to Computing and Computer Science. Usually a strong emphasis is placed on Mathematics education to form the students base of logic and rigid, formal problem solving. Computing Curricula often require mathematics modules as prerequisites. [4]. 2.2 The Role of Confidence In an analysis on the influence on education, McGivney [9] grouped influencing factors into three groups namely, Situational, Institutional and Dispositional barriers. Situational barriers refer to limitation students experience such as availability of time and finances. The education system typically is catered for a specific group of people. This may be socioeconomic, cultural, gender-related or any other social grouping. The barriers presented to the students of any minority c 2012 3

4 PREPRINTS OF THE CSERC. WROCŁAW, 2012 class due to this bias, is referred to as Institutional Barriers. Lastly, McGivney refers to Dispositional barriers as the constraints due to a student s perceptions and attitude. Institutional and Situational barriers are widely researched and addressed, but often we neglect to take the Dispositional barriers into consideration. We will focus on the very prominent [11, 15] dispositional barrier: confidence. In the context of education, many viewpoints exist on the meaning of confidence [11]. We refer to confidence as trust in one s own ability. It relates to being comfortable and certain within the educational environment due to that trust. Norman & Hyland [11] also showed that confidence is an essential ingredient to valuable engagement and participation in adult learning. They observed that students with more confidence: acclimatize better to different situations take on more responsibility participate and engage more enjoyed learning were less stressed were more motivated interacted more easily with the other In another study, Wilson showed that comfort (which relates to confidence) contributes significantly to education in Computer Science - even more than Mathematics [15]. We rely heavily on secondary level Mathematics as admission requirement for studies in Computing, and rightly so. But we should not underestimate the influence this dispositional barrier might have on the learning experience of the students. We will try to relate the exposure and experience students have from their parents (in relation to the adoption and engagement of computers) to their own confidence - specifically with computers and their expectancy of their performance in the study of Computing. 3. PROBLEM STATEMENT We endorse the factors contributing to the success of novice programmers mentioned in Section 2. While we acknowledge that cognitive abilities and mathematical competence plays an important role, we observed during a semester test for a bridging course in Computer Science, a 13 percentage point higher average in the marks of our students studying Information Technology compared to those study Mathematics, indicating that Mathematics alone is not sufficient for success in Computer Science. In our opinion the level of confidence in using computers may be a significant factor contributing to the success in computing modules. In this study we investigate the confidence levels of our students. 4. APPROACH Making use of the online education system of the University of Pretoria, a survey was published to students enrolled in an introductory course in Computer programming. Our data set includes students from degree programmes in Engineering, Mathematics, Computer Science and Multimedia. No personal information as collected other than from the answers of the survey and anonymity was preserved throughout the data analysis. The survey consisted of 68 questions of which 9 were considered for our research: Demographics: Elementary 1. Gender (male/female) 2. What is your mother tongue (the first language you learned to speak)? Demographics: Reason for enrollment 3. What major subjects do you intend to take at 3rd year level? 4. Did you ever consider majoring in a course involving computing at university? Purpose of our Research 5. How do your parent(s) work on computers? (a) Have never worked on a computer (b) Have worked on a computer only a few times (c) Work with computers as part of their daily job. (d) Work with computers to perform non-work related tasks such as e-mail, Skype, online shopping and/or banking. 6. Which computer will you use to do assignments? (a) Own computer at home (b) Shared computer at home (c) Computer in a lab on campus (d) Computer in a computer room at residence 7. I have lots of self-confidence in working with computers. (Completely Agree, Agree Partly or Completely Disagree) 8. I am confident I could teach someone to use a software package. (Completely Agree, Agree Partly or Completely Disagree) 9. I expect to do well at university (Completely Agree, Agree Partly or Completely Disagree) From this data set we want to research the correlation between the adoption of computers by the parents and the student s: Access to computers Confidence is working with computers 4.1 Demographics of the data set A total of 695 students completed the survey. 75.2% of the students, that completed the survey, are male and only 29% of the students in the data set indicated English in which all courses are presented as their first language. They are all enrolled in an introductory course in computer programming that teaches programming fundamentals from control structures and procedural programming up to and including basic object orientation. For the majority of the students, the year in which the course is taken is their first year at a tertiary educational institution. The course is compulsory not only for Computer Science and Engineering students, but also for first-year students from the following fields:

HUGO BREEDT, VREDA PIETERSE: STUDENT CONFIDENCE IN USING COMPUTERS 5 Multimedia Specifically Multimedia as Information Science and not Art. This degree programme includes Computer Science up to the final year of study. Mathematics Specifically Actuarial Sciences and Financial Mathematics. Computer Science is also an elective module in many of the degree programmes in the Natural Sciences faculty. This, however, is not very common and these students make up a very small percentage of the data set. To further understand the demographics in our data set, we included two questions (Questions 3 and 4) in the survey to research why students enrolled in the course in computer programming. Firstly, we looked at the necessity of computing in careers other than that of Computer Science. Often students are not necessarily interested in a major in computing, but are compelled to take it as a requirement of their career path. In most cases, only fundamentals of computing are required for a degree programme indirectly-related to computing. Usually this results in yet more students enrolling in first-year computing courses. As a first measure of the necessity of computing we identified, from the students answers of question 4 (as mentioned in section 4),all the students taking an introductory course in computer programming who initially did not consider a major in computing. As a further measure, we compared question 4 to question 3 1 : if a student did not consider a major in computing, but expect to take a Computer Science subject up to the final year, it shows that the student is taking Computer Science because of a requirement or a recommendation of the career path (or degree programme) and not because of pure interest in computing. Secondly, we analysed the popularity of careers in computing. We expected computing-related careers to be popular due to the vast amount of opportunities it provides. In general, students pursuing a career in computing have had some exposure to computers enough to be interested in learning more. However, that is not necessarily the case. As the world is computerised and digitalised the (potential) student s exposure to these opportunities is also greatly increased. Similar to the measure of necessity, if a student did consider majoring in a Computing-related course but do not expect to take a Computer Science course in her final year, it gives us an indication of the popularity of careers in computing. 4.1.1 Findings: Popularity We found that, of the students not expecting to take a course in Computer Science at final-year level, only 49.1% did consider a major in Computing. This value is very high: nearly half the enrolled students, not pursuing a career in Computing, have considered it. Careers in Computer Science are popular. Even though popularity is very positive for the field, it can also be a contributing factor to lower pass rates which are common in computing-related subjects. It is one of the reasons, we find students studying degrees in 1 In an analysis of the results of these two questions, we observed a φ-correlation coefficient of 0.401. In evaluation of the survey questions our concern, of misunderstanding the these two questions as implying the same, is diminished. The high, but not complete, correlation is in accordance with our expectation. Computing without ever have worked on a computer before 2. As we mentioned before, computer literacy or rather comfort/confidence in working with computers is a significant ingredient to successful learning of Computing. 4.1.2 Findings: Necessity For an initial measure of necessity, we observed that 35.46% of the students (enrolled in an introductory course in Computing) did not consider a major in Computing. Furthermore, it was found that of the students expecting to take a course in Computing at final-year level, 11.80% did not consider majoring in a course in Computing. That is, 11.80% of the students probably not interested in Computing, need to take it as a major due to a degree requirement or recommendation. Although this value is much lower than that of the popularity it is still worth considering as an influential factor to the lower pass rates. 5. FINDINGS 5.1 Access to computers It does not take much to show the importance of access to computers in the education of Computing. A student with her own computer has more freedom in how the computer is adopted into her personal life and consequently learning emerges. Considering the economic environment (South African students), a rather high 78.7% of the students that participated in the survey indicated that they will be using their own computers to do assignments. When we compared this value between the different groups of computer adoption by the parents, we noted that children of regular computer users (options (c) and (d) of question 5) are more likely to own their own computers (85.6% versus 59.9%). Figure 1 shows the access students have to computers based on whether or not their parents are regular users of computers. From the chart it is clear to see that the students whose parents are not regular computer users tend to rely more on the computer facilities provided by the university. This can be due to socio-economic differences: high-earning careers tend to more often require computer literacy, increasing both the parents computer adoption and the finances available for student s own computer. 5.2 Confidence As a measure of confidence, we asked the student (question 7) to rate her own confidence. Since it takes confidence, independent of actual ability, to give a high rating, we see this as a viable confidence rating. To quantify this rating, we created a confidence score where Agree Completely contributes double to that of Partly Agree (since only three options are presented to the student). Disagree Completely does not contribute to the score. The resulting score was processed to a percentage. Figure 2, shows that the students whose parents are regular computer users are more confident than those parents are not regular users of computers. The students whose parents adopted computers into their personal lives are the most confident. In a close second place, we find the students whose parents are regular users of computers as part 2 observed personally as lecturer

6 PREPRINTS OF THE CSERC. WROCŁAW, 2012 Figure 1: Students access to computers by the computer adoption by their parents. Figure 3: Confidence in conveying computer-related knowledge (Question 8) Figure 2: Self-rated confidence score by computer adoption by parents (question 5) of their occupation. If a parent only make use of a computer in a work environment, that might limit the cognitive socialization on computer usage in the home environment. Also, when a computer is only seen as tool to perform workrelated tasks, the confidence of the parent may be more in performing those specific tasks on a computer rather than in general computer usage. This may also limit the exposure and confidence transferred to the (potential) student. It was also observed that students whose parents have never used a computer before, are by far the least confident. To further understand confidence of students, we created similar scores looking at the students confidence in conveying computer-related knowledge (question 8) and their expectancy of academic performance at the university (question 9). Note that the latter is not for the course in computing specifically, but overall academic performance. We expected a rather strong relationship between questions 7 and 8, and a weaker relationship between questions 7 and 9. In a correlation analysis, a Pearson-correlation coefficient of 0.62 was observed between questions 7 and 8. A very high (maximum of 1) or very low (minimum of 1) coefficient would prove a very strong relationship between the two measures, whereas 0 indicates no correlation. From this value we can infer that there is a relatively strong correlation between a student s confidence in working with computers and her confidence in conveying computer-related knowledge. Figure 3 shows that, like the self-rated confidence, students whose parents are regular users of computers are more confident in conveying computer-related knowledge than those whose parents are not. Contrary to the the selfrated confidence, however, we found that students whose parents have worked on a computer only a few times before are very confident in their ability to teach another how to use a software package. Another interesting result was observed when a similar analysis was done between questions 7 and 9: it produced a Pearson-correlation coefficient of 0.08. There is very weak relationship between a students confidence in working with computers and his general expectancy of academic performance. There exists an opportunity in researching why that is the case (see Section 7). 6. CONCLUSION Due to the increase popularity and necessity of computing related courses, both as a career choice and as part of another degree programme, factors influencing successful learning of Computer Science become essential to research and address. Literature [15] shows the importance of comfort and confidence for a valuable learning experience. In terms of Computer related studies, this comfort and confidence is very closely related (if not similar) to Computer Literacy and play therefore a very important role in the students approach to and experience of a computing-related course. We looked at the influence that parental computer adoption has on a student studying computer science and found that, probably by cognitive socialization and constructed knowledge due to exposure, the student whose parents adopted computers into their personal lives or work environment are more confident and therefore also more computer literate than a student whose parents aren t regular users of computers. When addressing the problem of low pass rates, we ve mostly focused on the student and only the secondary education system. There seems to be a greater approach necessary in terms of exposure and adoption. The home environment is the best place for this, however might not always be practical. Computer literacy courses often do not address this sufficiently [7]. For the education of Computer Science, a programme of computer adoption and con-

HUGO BREEDT, VREDA PIETERSE: STUDENT CONFIDENCE IN USING COMPUTERS 7 Figure 4: Students expectancy to do well by computer adoption by parents fidence within the home environment might prove to show positive results within a few years. This directly relates to students access to computers. We expect that earlier access to computers will also show a positive effect on the success of students in studying Computer Science. With tertiary education, it will be worth stressing the importance of access to computers in terms of allocation of financial aid. 7. FUTURE RESEARCH Strategies on how the community can be exposed to computers (specifically for adoption into personal lives) should be researched. These strategies will be influenced by the demographics of the community and general solutions might not be practical or optimal in all societies. It will, therefore, be worth developing exposure strategies both within and outside of the educational system. It was observed in the data set (see Figure 4) that more students with parents that aren t regular computer users (compared to those with parents that use computers regularly) expect to perform well academically even though their confidence is lower. A research opportunity exists to find out whether it is a general trend and why that might be the case. A comparative study analysing the same measures in a different cultural and socio-economic milieu, will prove useful to identify general trends. Deci et al. [3] described the application of self-determination theory within an educational environment to promote confidence and motivation in students. Influences of the home environment and social context on a student s approach in studying computing, should be researched. Factors should be identified that can result in early motivation to embrace computers. 8. REFERENCES [1] J. Bempechat. The Role of Parent Involvement in Children s Academic Achievement. ERIC Clearinghouse on Urban Education, N.Y. New York, 1990. [2] J. Conejero, J. Juan-Huguet, S. Morillas, J. Mas, and E. Vendrell. Assessment of the learning competence of mathematics for freshmen of the computer science degree. In Education Engineering (EDUCON), 2010 IEEE, pages 231 236, april 2010. [3] E. L. Deci, R. J. Vallerand, L. G. Pelletier, and R. M. Ryan. Motivation and education: The self-determination perspective. Educational Psychologist, 26(3-4):325 346, 1991. [4] M. Doyle, D. Kasturiratna, B. Richardson, and S. Soled. Computer science and computer information technology majors together: Analyzing factors impacting students success in introductory programming. In Frontiers in Education Conference, 2009. FIE 09. 39th IEEE, pages 1 6, oct. 2009. [5] A. Durndell and Z. Haag. Computer self efficacy, computer anxiety, attitudes towards the internet and reported experience with the internet, by gender, in an east european sample. Computers in Human Behavior, 18(5):521 535, 2002. [6] P. Golding, O. Donaldson, and V. Tennant. Application of modified perceived learning problem inventory (plpi) to investigate performance in introductory programming. In Frontiers in Education Conference, 2009. FIE 09. 39th IEEE, pages 1 6, oct. 2009. [7] I. F. Goodson and J. M. Mangan. Computer literacy as ideology. British Journal of Sociology of Education, 17(1):65 79, 1996. [8] N. A. Martinez, Micheal E.; Mead. Computer Competency: A first national assessment. National Assessment of Educational Progress at Educational Testing Service, Rosedale Road, Princeton, NJ, USA, 1988. [9] V. McGivney. Participation and non-participation: a review of the literature. In S. S.. D. Z. R. Edwards, editor, Adult Learners, Education and Training, pages 17 22, London, UK, 1993. Routledge/Open University Press. [10] I. C. Mow. Issues and difficulties in teaching novice computer programming. In M. Iskander, editor, Innovative Techniques in Instruction Technology, E-learning, E-assessment, and Education, pages 199 204. Springer Netherlands, 2008. [11] T. Norman, Marie & Hyland. The role of confidence in lifelong learning. Educational Studies, 29(2-3):261 272, 2003. [12] E. Rozell and W. Gardner. Cognitive, motivation, and affective processes associated with computer-related performance: a path analysis. Computers in Human Behavior, 16(2):199 222, 2000. [13] J. Toby. Orientation to education as a factor in the school maladjustment of lower-class children. Social Forces, 35(3):259 266, March 1957. [14] J. L. Vigdor and H. F. Ladd. Scaling the digital divide: Home computer technology and student achievement. http://www.nber.org/papers/w16078, May 2012. [15] B. C. Wilson. A study of factors promoting success in computer science including gender differences. Computer Science Education, 12(1-2):141 164, 2002. [16] E. Zerubavel. Social mindscapes: an invitation to cognitive sociology. Harvard University Press, Canada, 1999.