General Computer Application Knowledge

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					Gender and Computers
General Computer Application
Knowledge
   Is There a Difference Between the Genders?



           Laurie J. Patterson, Ed.D.
     University of North Carolina Wilmington
• Background
 ▫   Theories
 ▫   Computer Usage
 ▫   Game Examples
 ▫   Computer Competency
• Study
 ▫   Class Format
 ▫   Skill Tests
 ▫   Results
 ▫   Surprises?
NCES Statistics
• Between 1984 and 1996, there was an increase of
  girls and boys who used a computer in 8th grade
• By 11th grade, the number of boys who used
  computers increased while the number of girls who
  used them remained at the same 8th grade level
• Between 2000 and 2004, girl usage increased and
  they were as likely as boys to use computers…
  however their numbers are still low
Males and Females
• Females stop participating in science, math, and
  engineering                                @UNCW
 ▫ including computer science             50 CS Pre-Majors:
                                             8 female 16%
                                          40 CS Majors:
• Why?                                       4 female 10%

 ▫ no documentable reason why the
   number of females enrolled in or remaining in
   computer courses decreases…
Females and Computers
• Research suggests that males and females see the world of
  computers differently
  ▫ Males conceptualize the idea of how cyberspace is comprised and use the Internet
    to gather information or ideas to promote themselves
  ▫ Females view cyberspace as way to collaborate with others and use the Internet for
    communication
• Elementary school:
  ▫ Both boys and girls show equal mathematics and science interest and abilities
• Junior high school:
  ▫ Fewer girls take mathematics or science courses
  ▫ Boys are five times more likely to enroll in a computer course
• High school:
  ▫ Girls enroll in very few mathematics or science courses.
  ▫ Girls who do continue to enroll in mathematics frequently receive less attention
    from their instructors than boys do.
Theories
 • Support systems (or lack thereof)
• Stereotypes
  Hormones
• Few role models or mentors
• “Too” hard/not fun
• Lack of exposure to computers
• Different needs/uses of computers
              BLO
Support Systems
Lack of Exposure
•   Anxiety
•   Constantly learning how to do something new
•   Technology constantly changing
•   Low confidence levels
Confidence and Use
• Inter-correlation between computer confidence
  and interest in/enjoyment of computers

 ▫ Males may use computers to gather information or
   promote themselves

 ▫ Females may use computers to communicate and
   collaborate
Computer Use
• As young children, boys are already using
  mathematics concepts with their toys.
 ▫ Many of their “action toys,” such as sling shots, b-
   b guns, and video games utilize velocity and
   angles.
Computer Use
 • Video games can also reinforce gender stereotypes.
   ▫ There are very few active females in the games.
   ▫ 1995 study of elementary school-level software, only 12% of
     the characters were gender-identifiable as female
   ▫ number of females playing video games has increased since
     1999 study
      estimated that 70% of game players are male
      behavior of the individuals in the games is still
       stereotypical…females are passive and need saving
       • many of the games geared towards girls focus on stereotypical
         girl interests such as fashion and makeup
                                 stereotypes
Video Game Usage
• Games “may” reinforce gender stereotypes
 ▫ females need rescuing
 ▫ females are passive
• 70% of game players are male
 ▫ Action games use mathematical
   concepts of angles and velocity
 ▫ “Girl” games pet and walk the
   dog… or work with fashion and
   makeup
Pool




       http://www.youtube.com/watch?v=jx9hrwO7Dd8
Pool




       http://www.youtube.com/watch?v=23pmcFfF-XI
http://www.youtube.com/watch?v=qVr6NGqPKjo
http://www.youtube.com/watch?v=NE6CKEsWQuI
http://www.nintendo-difference.com/jeu8499-cosmetic-paradise.htm
Video Game Usage
• There are very few active females in the games.
• 1995 study of elementary school-level software,
  only 12% of the characters were gender-
  identifiable as female
 ▫ Number of females playing
   video games has increased
   since 1999
•What’s being done to get girls (and boys) interested in
computers?

•Or at least working with them?
Computer Competency
 • States have implemented
   K-12 computer
   competency
   requirements
 • Colleges/Universities
   have also implemented
   computer competency
   requirements
Computer Competency Requirements
• UNCW’s computer-competency requirement
 “The university requires that all students prior to
   graduation develop competency in basic computer
   skills including knowledge of campus use policies,
   facility with standard applications, and awareness
   of legal and ethical issues. Students in each major
   must satisfy the requirements in computer
   competency as specified by that major.”
National Educational Technology Standards
for Students

  •   Basic operation and concepts
  •   Social, ethical, and human issues
  •   Technology productivity tools     CSC 105   Usage!

  •   Technology communications tools
  •   Technology research tools
  •   Technology problem-solving and decision-
      making tools
Study…Fall 2004
• Skill Assessment Software implemented into one
  of UNCW’s computer competency courses
 ▫ Assessment software “mimic’d” the look of
   productivity software and allowed for students to
   “use” the software
 ▫ Tested using Word, Excel, PowerPoint, and Access
   skill assessments
Skill Testing
• Fall Semester 2004:
  ▫ SAM Skill tests were implemented across all sections
  ▫ Applications used within this course are Microsoft’s
    productivity applications
• SAM mimics the application
• Students see what appears to be the application’s
  interface
• Instructions appear at the bottom of the screen
• Tests were used by 75 sections of CSC 105 between
  Fall 2004 and Spring 2007, reaching 2,306 students
Student Assessments
• Reached an average of 384 students across an
  average of 12 sections each semester…averaging
  32 students in each section.
• Students were allowed to “test out” of the
  various applications.
• To “test out” of the application, students had to
  receive a 70-80% score in the test.
Student Assessments
• Students could also take the test to determine their
  existing skill level and could work through the training
  and retake the test as a post-test.
• It was not a requirement that students take the pre-test.
• Students who did not successfully pass the assessment
  were required to do several lab exercises that walked
  them through the many skills and they would then
  complete a post-test.
• Post-tests presented the information using a different
  scenario.
Assessment Reviews
• Comparison of:
 ▫ each individual’s pre-test to the post-test.
   These individuals completed lab exercises in the
   application between the two tests.
 ▫ post-test scores for those individuals who did not take
   a pre-test but instead undertook the training.
 ▫ scores for individuals, by gender, who took the pretest
   and did no additional work.
 ▫ scores for individuals who had tested out … to those
   who had taken the training first and then taken the
   post-test.
Assessment comparisons
• Pretest results compared to the same
  individual’s post-test results
 ▫ Pretest ~ Lab work ~ Post test
• Post-test scores after working with the
  application
 ▫ Lab work ~ Post test
• Pretest only scores
 ▫ Pre test ~ Test out
Access
Pretest ~ Lab work ~ Post test
             278 students took the test
                       n=162        n=116
 • Pretest Mean (group)             • Posttest Mean (group)
   46.56                              82.47
    – Female mean: 46.43               ▫ Female mean: 82.27
    – Male mean: 46.75                 ▫ Male mean: 82.75



   No statistically significant difference between the genders
Access
Lab work ~ Post test
            473 students took the test
                     n=287         n=186
 • Mean (group) 85.08             • tcrit(.05):1.65
   ▫ Female mean: 85.44               – calculated t value:
   ▫ Male mean: 84.52                   .872245083




  No statistically significant difference between the genders
Access
Pretest ~ Test out
             415 students took the test
                       n=184        n=231
 • Mean (group) 76.42              • tcrit(.05):1.97
   – Female mean: 76.15                – calculated t value:
   – Male mean: 76.69                    .227773728




   No statistically significant difference between the genders
Excel
Pretest ~ Lab work ~ Post test
             435 students took the test
                      n=250         n=185
 • Pretest Mean (group)            • Posttest Mean (group)
   37.54                             80.00
    – Female mean: 36.18               – Female mean: 80.32
    – Male mean: 39.38                 – Male mean: 80.50



   No statistically significant difference between the genders
Excel
Lab work ~ Post test
             381 students took the test
                       n=225        n=156
 • Mean (group) 77.71              • tcrit(.05):1.65
   – Female mean: 78.08                – calculated t value: .
   – Male mean: 77.17                    .597779342




   No statistically significant difference between the genders
Excel
Pretest ~ Test out
             337 students took the test
                       n=175        n=162
 • Mean (group) 81.85              • tcrit(.05):1.97
   – Female mean: 82.06                – calculated t value:
   – Male mean: 81.62                    .19522623




   No statistically significant difference between the genders
PowerPoint
Pretest ~ Lab work ~ Post test
             244 students took the test
                       n=149        n=95
 • Pretest Mean (group)            • Posttest Mean (group)
   56.87                             87.89
    – Female mean: 58.32               – Female mean: 89.41
    – Male mean: 54.59                 – Male mean: 85.51



   No statistically significant difference between the genders
PowerPoint
Lab work ~ Post test
             213 students took the test
                       n=126        n=87
 • Mean (group) 89.26              • tcrit(.05):1.65
   – Female mean: 90.08                – calculated t value:
   – Male mean: 88.08                     1.476781041



   No statistically significant difference between the genders
PowerPoint
Pretest ~ Test out
             770 students took the test
                       n=415        n=355
 • Mean (group) 88.43              • tcrit(.05):1.97
   – Female mean: 87.88                – calculated t value:
   – Male mean: 89.08                    1.254268287




   No statistically significant difference between the genders
Word
Pretest ~ Lab work ~ Post test
             474 students took the test
                       n=162        n=116
 • Pretest Mean (group)            • Posttest Mean (group)
   65.44                             84.14
    – Female mean: 67.36               – Female mean: 84.89
    – Male mean: 62.84                 – Male mean: 83.13



   No statistically significant difference between the genders
Word
Lab work ~ Post test
             183 students took the test
                        n=112       n=71
 • Mean (group) 84.63              • tcrit(.05):1.65
   – Female mean: 85.83                – calculated t value:
   – Male mean: 82.73                    1.629429123




   No statistically significant difference between the genders
Word
Pretest ~ Test out
             586 students took the test
                      n=306         n=280
 • Mean (group) 85.92              • tcrit(.05):1.97
   – Female mean: 86.16                – calculated t value:
   – Male mean: 85.66                    .52504364




   No statistically significant difference between the genders
Results/Discussion
• No real statistical difference between females
  and males with regard to MS Office productivity
  software
• Supports NECS findings that males and females
  are equal with regard to computer usage
Results/Discussion
• Does it support the suggestion that there are
  different uses of computers between the
  genders?
 ▫ females higher in software that allows for
   communication and collaboration
   (PowerPoint and Word)
Surprises
• Females also higher in the more “difficult”
  software:
 ▫ Access                            “Males may
    Lab work ~ Post test
     Female mean: 85.44                  use
     Male mean: 84.52               computers to
 ▫ Excel                                gather
    Lab work ~ Post test          information or
     Female mean: 85.44
     Male mean: 84.52
                                       promote
    Pre test ~ Test out            themselves.”
     Female mean: 82.06
     Male mean: 81.62

				
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posted:7/14/2013
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