An Integrative Model of Factors Related to Computing Course Performance

A path modeling approach is adopted to examine inter-relationships between factors influencing computing behavior and computing course performance. Factors considered are gender, personality, intellect and computer attitudes, ownership, and experience. Among many other conclusions, intrinsic motivation is suggested as a major factor which can explain many variables' relationship with course performance. Similarly to the common finding for non-computing specialist students, a male advantage in previous computing experience is observed, gender differences in computer ownership partially explaining this. In the absence of an attitudinal gender difference, the ownership difference is suggested to stem from the perception of computers as objects stereotypically bought by and for males. However, while having implications with respect to the gender imbalance usually observed on programming-oriented and more technically-oriented applications courses, these differences are not shown to confer a male advantage in course performance.

[1]  John P. Charlton,et al.  Psychological Characteristics of Students Taking Programming-Oriented and Applications-Oriented Computing Courses , 1998 .

[2]  Thomas Suddendorf,et al.  Computer Attitudes, Gender and Exploratory Behavior: A Developmental Study , 1996 .

[3]  T. Busch,et al.  Gender, Group Composition, Cooperation, and Self-Efficacy in Computer Studies , 1996 .

[4]  Philip A. Houle,et al.  Toward Understanding Student Differences in a Computer Skills Course , 1996 .

[5]  Alan Durndell,et al.  Gender and computing: persisting differences , 1995 .

[6]  John P. Charlton,et al.  The Development and Validation of the Computer Apathy and Anxiety Scale , 1995 .

[7]  T. Busch.  Gender Differences in Self-Efficacy and Attitudes toward Computers , 1995 .

[8]  P. Corr.  Personality: The psychometric view , 1994 .

[9]  D. D. Wheeler,et al.  The Myers-Briggs Personality Type and Its Relationship to Computer Programming , 1994 .

[10]  David E. Anderson,et al.  Formal Operations and Learning Style Predict Success in Statistics and Computer Science Courses , 1990 .

[11]  Geoffry S. Howard,et al.  Computer Anxiety and Computer Attitudes: An Investigation of Construct and Predictive Validity Issues , 1990 .

[12]  S. M. Chambers,et al.  Gender-Based Factors in Computing Enrollments and Achievement: Evidence from a Study of Tertiary Students , 1989 .

[13]  Mark G. Simkin,et al.  What best predicts computer proficiency? , 1989, CACM.

[14]  Margaret A. Shotton,et al.  Computer Addiction Pb: A Study Of Computer Dependency , 1989 .

[15]  F. Dambrot,et al.  Psychology of Computer Use: II. Sex Differences in Prediction of Course Grades in a Computer Language Course , 1988 .

[16]  Joke Voogt,et al.  Computer literacy in secondary education: the performance and engagement of girls , 1987 .

[17]  David Messer,et al.  Factors affecting microcomputer use and programming ability of secondary school children , 1987 .

[18]  Alan Durndell,et al.  A survey of attitudes to, knowledge about and experience of computers , 1987 .

[19]  Leah R. Pietron,et al.  Cognitive Level and Achievement in Computer Literacy , 1987 .

[20]  I. Miura,et al.  The relationship of computer self-efficacy expectations to computer interest and course enrollment in college , 1987 .

[21]  W Paul Oman,et al.  Identifying student characteristics influencing success in introductory computer science courses , 1986 .

[22]  S. Krug,et al.  A Large Scale Cross-Validation of Second-Order Personality Structure Defined by the 16PF , 1986 .

[23]  Robert D. Smith,et al.  Computer anxiety in management: myth or reality? , 1986, CACM.

[24]  Marlaine E. Lockheed.  Women, girls, and computers: A first look at the evidence , 1985 .

[25]  R. S. Davidson,et al.  Computer Fear and Addiction , 1985 .

[26]  Ronald H. Nowaczyk.  The Relationship of Problem-Solving Ability and Course Performance among Novice Programmers , 1984, Int. J. Man Mach. Stud..

[27]  George P. McCabe,et al.  Predicting the success of freshmen in a computer science major , 1984, CACM.

[28]  D. Jackson,et al.  TAXONOMY OF VOCATIONAL INTERESTS OF ACADEMIC MAJOR AREAS , 1984 .

[29]  Terry R. Hostetler,et al.  Predicting student success in an introductory programming course , 1983, SGCS.

[30]  Charles G. Petersen,et al.  Predicting Academic Success in Introduction to Computers. , 1979 .

[31]  J. Rushton.  Book Review: Degrees of Excellence: the academic achievement game , 1978 .

[32]  Raymond B. Cattell,et al.  The Scientific Analysis of Personality and Motivation , 1977 .

[33]  Peter R. Newsted,et al.  Grade and ability predictions in an introductory programming course , 1975, SGCS.

[34]  H. Eysenck.  Biological Basis of Personality , 1963, Nature.

[35]  W. Saris,et al.  Structural equation modelling , 1999 .

[36]  H. Eysenck.  Personality and intelligence: Psychometric and experimental approaches. , 1994 .

[37]  Judith L. Johnson,et al.  Personality and chronic procrastination by university students during an academic examination period , 1991 .

[38]  Kym Elizabeth Pocius.  Personality factors in human-computer interaction: A review of the literature , 1991 .

[39]  H. Lips,et al.  Gender differences and similarities in attitudes toward computers , 1989 .

[40]  Peter M. Bentler,et al.  EQS : structural equations program manual , 1989 .

[41]  K. Perry,et al.  Sex and Ethnic Group Differences in High School Students' Computer Attitudes and Computer Attributions. , 1988 .

[42]  J. Drever.  The Penguin dictionary of psychology , 1983 .

[43]  Fehr,et al.  Introduction to Personality , 1983 .

[44]  T. Green,et al.  Psychology of Computer Use , 1983 .

[45]  Louis W. Glorfeld,et al.  Predicting Aptitude in Introductory Computing: A Classification Model , 1981 .

[46]  Noel Entwistle,et al.  Styles of learning and teaching , 1981 .

[47]  Noel Entwistle,et al.  Degrees of excellence: The academic achievement game , 1977 .

[48]  Benjamin Kuipers,et al.  Computer power and human reason , 1976, SGAR.