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- Title
- THE RELATIONSHIP OF PIAGETIAN FORMAL OPERATIONS AND OTHER COGNITIVE FACTORS TO COMPUTER PROGRAMMING ABILITY (DEVELOPMENT).
- Creator
- CAFOLLA, RALPH, Florida Atlantic University, Kauffman, Dan
- Abstract/Description
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The purpose of this study was to determine if success in writing computer programs is related to level of cognitive development, verbal ability, math reasoning, and grade point average. This study presents a model that predicts computer programming ability. Twenty-three subjects were drawn from students enrolled in BASIC programming classes at Broward Community College. Each subject was given the School and College Ability Test (SCAT II) test to assess math and verbal levels and the Inventory...
Show moreThe purpose of this study was to determine if success in writing computer programs is related to level of cognitive development, verbal ability, math reasoning, and grade point average. This study presents a model that predicts computer programming ability. Twenty-three subjects were drawn from students enrolled in BASIC programming classes at Broward Community College. Each subject was given the School and College Ability Test (SCAT II) test to assess math and verbal levels and the Inventory of Piaget's Developmental Tasks (IPDT) to assess level of cognitive development. Grade point averages were obtained from the registrar. The instructor's final examination, which consisted of generating BASIC programs, was used as a measure of programming ability. Each student was given 45 hours of instruction in BASIC by the instructor and had access to laboratory facilities equipped with IBM Personal Computers. Pearson r correlations were performed using each predictor (grade point average, verbal ability, math reasoning, and level of cognitive development) as independent variables and computer programming ability as the dependent variable. The correlations were all significant. To determine how well all four factors together predict programming ability, multiple regression analysis was performed using all of the predictors as independent variables and computer programming ability as the dependent variable. This study supports prior research showing that grade point average, math reasoning and verbal ability were each significant predictors of success in computer programming. Results showed that level of cognitive development is linearly predictive of success in computer programming. Results of the regression showed that level of cognitive development, when combined with verbal reasoning, is linearly predictive of programming ability.
Show less - Date Issued
- 1986
- PURL
- http://purl.flvc.org/fcla/dt/11886
- Subject Headings
- Computer programming, Cognition
- Format
- Document (PDF)
- Title
- A comparison of demographics, motivation, and learning strategies of college students taking traditional campus-based courses and Internet-based distance learning courses.
- Creator
- Maupin, Deborah L., Florida Atlantic University, Cafolla, Ray
- Abstract/Description
-
The purpose of this study was to examine some the differences between students in traditional face-to-face courses and those in distance learning courses. Differences in teaming strategies, motivation, and demographics were examined. The study used an online version of the Motivated Strategies for Learning Questionnaire (MSLQ) to assess the motivation and learning strategies used by college students. The instrument was administered to 111 students at a 4-year, public university in the...
Show moreThe purpose of this study was to examine some the differences between students in traditional face-to-face courses and those in distance learning courses. Differences in teaming strategies, motivation, and demographics were examined. The study used an online version of the Motivated Strategies for Learning Questionnaire (MSLQ) to assess the motivation and learning strategies used by college students. The instrument was administered to 111 students at a 4-year, public university in the southeast region of the United States during the Spring of 2003. The subjects included 64 students enrolled in the traditional campus-based version of Applied Educational Technology and 47 students enrolled in the distance learning version of the same course. The study found significant differences in the demographic characteristics of both groups. Chi-square tests revealed that 6 of the 10 demographic variables (marital status, class level, ethnicity, household income, number of distance learning courses previously taken, and the number of hours per week spent studying for the course) demonstrated statistical significance. Independent samples t tests were used to explore differences in motivation and learning strategies in the two groups. Of the six motivation variables tested (intrinsic goal orientation, task value, control for learning beliefs, self-efficacy, and test anxiety), only two demonstrated statistical significance (p < .01). Distance learning students reported higher levels of intrinsic goal orientation and control for learning beliefs. The study found few differences in the learning strategies reported by the subjects. Of the nine learning strategies tested (rehearsal, help seeking, metacognitive self-regulation, organization, critical thinking, time and study environment, effort regulation, and peer learning), only one demonstrated statistical significance (p <; .01). Students participating in the traditional campus-based course reported higher levels of help seeking behavior than their distance learning peers. A model was developed to predict student choice of distance learning courses using demographic, learning strategies, and motivation variables. Using discriminant analysis, the model correctly classified 75.7% of the cross-validated cases. A second discriminant analysis, using only the variables found to be significant in the t tests and chi-square analysis was also conducted. This model correctly classified 79.3% of the cross-validated groups. As distance learning becomes more prevalent in higher education, it is important to examine the characteristics of students participating in distance education courses. The results of this study indicated that differences existed between the distance learning group and the traditional group. An understanding of those differences may lead to improved design and delivery of distance learning courses.
Show less - Date Issued
- 2003
- PURL
- http://purl.flvc.org/fcla/dt/12064
- Subject Headings
- Distance education, Learning strategies, Motivation in education, Internet in higher education
- Format
- Document (PDF)
