1. Gender Issues in Systems Design and User Satisfaction for e- testing software Prepared by Sahel AL-Habashneh. Department of Business information systems Salford Business Information systems

2. Gender Issues in Systems Design and User Satisfaction for e-testing software Design : Art & Engineering There are two main concept in any design the artistic side and the engineering side. Design Guidelines are the middle layer structure and are based on principles specific to a particular domain of design.

3. Research main idea Since the interaction with other people defer according to many factors such as personality, age and gender. Therefore, these factors have to effect interaction between human and computers. This effect will appear in the main medium of the HCI which is the interface or the web design in the case of human web interaction which is the area of my investigation in this research.

4. Research hypothesis This study investigated the following : user acceptance of web interface varies depending on user gender.

5. Page elements Link elements Graphic elements Page formatting Gender

6. Research objectives Objective 1: to examine and collect data and recommendations from literature on Gender factors, user satisfactions, Web design, research methodology. Objective 2: to develop a model and examine if the recommendations identified by this research from the literature review are applicable for both genders.

7. Research aim To identify if user satisfaction defer according to gender. And identify what aspects of the interface responsible for the increase or decrease of user satisfaction for each gender.

8. The e-testing software The e-testing software which is part from the al-balqua university website is a tool to evaluate student level in two main topic English language level and computer skills level. The e-testing software is an in-house development with the use of Oracle 9 build in back end system as the data bank linked with a DHTML pages. The exams come in the multiple choice question formats. Though tell now the system is not linked to the registration system where the student results in this exam will be stored.

9. According to Nielsen (2000) there are four main categories which form any webpage Text elements: which mainly the group of letters and words in the webpage which form the page and its properties. Link elements: it deals with the parts of webpage that facilitate the navigation wither text or graphs. Graph elements: the pictures or the text saved as pictures as well as the animation in the webpage. Page formatting elements: this part mainly is everything else which does not go under the other three parts.

10. Text elements Page Text Page title Page abstract Body text link text Continent percentage Navigation percentage Information quality

11. Link elements Links: Text Links Link graphics Within page link Embedded links Redundant links Navigation quality

12. Graphic elements: Graphics Graphical links Graphical ads Animation Graphic quality

13. Page Formatting Measures Color Combinations Fonts:. Line length Leading Framesets Interactive Elements Screen Size Screen Coverage Text density Scrolling Style sheets

14. Quantitive research A survey as a data collection tool developed then a pilot test conducted which results on a slight changes in the survey mainly the linguistic terms, the number of participant is 135 student distributed as :

15. Gender the males were (84) with a (62.2%). females were (51) with a (37.8%) percent.

16. Results H1.1: user satisfaction of Page elements varies depending on user gender. Method: Compare means one way ANOVA used to test the hypothesis Result: user gender has no effect on user satisfaction of Page elements.

17. Results H1.2:user satisfaction of link elements varies depending on user gender. Method: Compare means one way ANOVA used to test the hypothesis Result: User gender has no effect on user satisfaction of link elements.

18. Results H1.3:user satisfaction of graphic elements varies depending on user gender. Method: Compare means one way ANOVA used to test the hypothesis Result: user gender has no effect on user satisfaction of graphic elements.

19. Results H1.4:user satisfaction of Page formatting measures varies depending on user gender. Method: Compare means one way ANOVA used to test the hypothesis Result: User gender has no effect on user satisfaction of Page formatting measures.

20. Results The result of the first survey was inaccurate for the following reasons: Even that a pilot test conducted but the users in the pilot test were IT professional they realized the terms exactly where in the real survey the users were with little or no experience in the field. The survey was long with many questions which the users in order to get through with it they didn’t read it carefully. Maybe a selection for one of the main website design element will give more accurate results.

21. Results The fact that the examined web site “web testing website” is a one task website which is to test and record the student results as well as the users are focussed on passing the exam. The researcher found after conducting the survey that many of them don’t really remember much about the website other than the question and the multiple choices an administrator of the web testing in Albalqua University asked to enquire the student and most of them didn’t remember much about the website.

22. Results The quantitive study methodology gives a big picture with statistically noticeable facts therefore it may not work in this case where a investigation and a fact finding research study is the aim of this study therefore the researcher will investigated another research methodology to conduct this research.

23. What’s next? Though the results of the quantities bit produce a negative results interim of linking gender with satisfaction of web design the researcher still believe that its still much to discover in the relation between both.

24. Future research plan Future research plan will consider the qualitative method: Reformatting the survey to conduct it in an interview and focus group. Analyse the results. Optimistically I will come up with either to validate the recommendation from the previous research or a set of new recommendation customized according to gender and experience using the internet.