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RAA4: Usability Heuristics for Grid Computing Applications

04 Nov

1. APA Citation:

Rusu Cristian, Roncagliolo Silvana, Tapia Gonzalo, Hayvar Danae, Rusu Virginica, Gorgan Dorian (2011). Usability Heuristics for Grid Computing Applications. Proceedings from ACHI 2011: The Fourth International Conference on Advances in Computer-Human Interactions. Gosier, Guadeloupe, France, 53-58.

The link is http://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=3&ved=0CDcQFjAC&url=http%3A%2F%2Fwww.thinkmind.org%2Fdownload.php%3Farticleid%3Dachi_2011_3_20_20040&ei=LqmVUJeNKMj40gHp3ICgBw&usg=AFQjCNGCYO3bknnRhqANwYQKhUt2dTwMfg&sig2=ClFbqVWcMM2nEJk3vwlbjQ

2. Purpose:

The purpose of this paper is quite straightforward. Grid computing is an emerging information technology which relies on different types of computing resources, located in various geographic locations. The number of users is increasing while technical knowledge of grid users is expected to decrease in the future. The discrepancy will lead to usability issues when applying Grid Computing. That’s the reason why the paper explores usability evaluation of Grid Computing application with appropriate heuristic evaluations from user-centered perspective.

3. Methods:

Based on the well known Nielsen’s 10 heuristics and extensively analyzing GreenView, GreenLand and some other Grid Computing applications, the article developed 12 new usability heuristics with the following template: ID, name and definition; explanation; examples; benefits and problems. Furthermore, the author groups the 12 heuristics in three categories: design and aesthetics, navigation, errors and help. The following table presents the mapping between Grid Computing 12 heuristics and Nielsen’s 10 heuristics.

TABLE I.   MAPPING BETWEEN GRID COMPUTING HEURISTICS AND NIELSEN’S HEURISTICS

From the table, we can see that the new heuristics particularize Nielsen’s heuristic especially H1 and H2 denote N3, H8 and H9 denotes N3 based on the characteristics of Grid Computing applications. The other components of the new heuristic also provide more specific means than Nielsen’s heuristic either emphasizing the complex tasks or specific requirements of Grid Computing applications. Overall, the author puts Nielsen’s heuristics into the context of Grid Computing applications and synthesizes the new heuristics for Grid Computing application.

In order to evaluate the new heuristics, the author use GreenView and GreenLand as case studies. Two groups of 4 evaluators each examined GreenView. One group only performs 12 new heuristics and the other group only uses the Nielsen’s 10 heuristics respectively. In the same way, GreenLand was examined by two groups of 3 evaluators each. The two group use different evaluation methods either. All the evaluators had similar experience in Nielsen’s evaluation and using Grid Computing applications, but lack experience in usability evaluation of Grid Computing applications.

4. Main Findings:

In the GreenView and GreenLand case studies, the results are shown in Table 2 and Table 3.

TABLE 2.   NUMBER OF USABILITY PROBLEMS IDENTIFIED IN GREENVIEW, BY HEURISTICS

TABLE 3.   NUMBER OF USABILITY PROBLEMS IDENTIFIED IN GREENLAND, BY HEURISTICS

After analyzing the data, the results were:

  • 11 problems (38%) were identified by both groups of evaluators,
  • 12 problems (41%) were identified only by the group that used Grid Computing heuristics,
  • 6 problems (21%) were identified only by the group that used Nielsen’s heuristics.

We can see that more usability problems (12 problems about 41% in Greenview and 22 problems about 46% in Greenland) were found by new heuristics than Nielsen’s heuristics. The results seem to prove that new heuristics is better than Nielsen’s heuristics in Grid Computing applications. Although there are 6 problems in Greenview and 12 problems in Greenland were not identified by the new heuristics, the author mentioned that the reason may be that there are no appropriate heuristics, or the heuristics are not properly specified. we should also consider that evaluators using new heuristics probably ignored the problems subjectively.

What’s more, in order to validate the second hypothesis, the researchers conducted a usability test with 5 users focusing on the 6 usability problems identified only by Nielsen’s heuristics in Greenview. The result was that all these issues were not severe by users. On the contrary, the most problems identified only by Grid Computing heuristics were qualified as sever.

5. Analysis:

Given that Jakob Nielsen’s heuristics are most-used usability heuristics, I think it is the bible heuristics for user interface design. This author presented a different new perspective for evaluation methods. Though in this paper the new method can only be used for Grid Computing application, I feel it can have good application in other emerging information technology. Of course, it remains to be proven useful and effective.

After all, the set of 12 specific usability heuristics still relies on Nielsen’s 10 heuristics. The new heuristics is just particularized for Grid Computing environments. That inspires me to find other specific evaluation methods situated in certain domains such as augmented reality systems or cloud computing applications. Follow a classic pattern is so easy which is almost brainless and we have to maintain active vigilance. In my future research, I will ask myself if the method can be appropriated to support my requirements. If not, make bold adaptations of the original methods and explore some discoveries. It is very likely that you will find an exciting new continent!

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1 Comment

Posted by on November 4, 2012 in Research Article Analyses

 

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One response to “RAA4: Usability Heuristics for Grid Computing Applications

  1. Mihaela

    November 7, 2012 at 4:22 pm

    Yes, adapting new methods to particular contexts is often useful – good takeaway for you from this article!

    Random fact: I think a lot of the authors of this paper are Romanian, judging by their names.

    Good RAA. Your points on Bb.

     

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