La educación ambiental en el ámbito internacional

C ontrary to the values for the aspatial tasks, the spatial ones show a m uch larger proportion o f the use o f interactive structured queries (27.4% and 50.2%, respectively). T he column labelled ‘Total Identify’ corresponds to total num ber o f operations for all identify tasks, both spatial and not. T he colum n labelled ‘Total Distinguish’ corresponds to the total num ber o f operations for all distinguish tasks. F or the ‘identify’, the difference between frequencies o f interactive searches and filtering is rather small (30.6% and 31.6%). F or the ‘distinguish’ tasks, there is a m uch larger proportion o f the use o f query devices (27.1% and 54%, respectively). Therefore, the higher proportion o f filtering actions in the grand total arises because the query devices were used m ore frequently in the ‘distinguish’ tasks and in tasks with a spatial com ponent.

Table 5.17 Frequency o f user operations from computer logs and videos (Compare and Associate tasks) 1 o _{i l} i l0 _{i f}

A

Physical Behaviour (Observed)

1. Search by attribute 19 2.7 8 2.9 11 2.5 10 3.4 9 2.1 2. Search by location 0 0 0 0 0 0 0 0 0 0.0 3. Search interactively 205 28.5 83 30.4 122 27.4 89 30.6 116 27.1 4. Filtering 323 44.9 99 36.3 224 50.2 92.0 31.6 231 54.0 5. H ighlight records 126 17.5 64 23.4 62 13.9 58 19.9 68 16.0 6. Evaluate content 30 4.2 14 5.1 16 3.6 28 9.6 2 0.5 7. M anipulate map 16 2.2 5 1.8 11 2.5 14 4.8 2 0.5

Mental Behaviours (Ob served)

8. D ecid e threshold 342 47.6 107 39.2 235 52.7 102 35.1 240 56.1

(1+4)

9. Select records (2+3) 185 25.7 79 28.9 106 23.8 76 26.1 109 25.5

Total (1 to 7) 719 273 446 291 428

Table 5.18 shows the num ber o f operations for the ‘com pare’ and ‘associate’ tasks only. The column labelled ‘T otal’ is the total num ber o f operations for all ‘com pare’ and ‘associate’ tasks. We can see that interactive searches and filtering account for m ost o f the observed actions (42.5% and 39.9%, respectively). Contrary to the case o f the ‘identify’ and ‘distinguish’ tasks, the difference in frequencies between these two operations is less apparent and the m ost frequent action is the interactive selection and search o f information. The colum n labelled ‘Total N on Spatial’ corresponds to the total num ber o f operations for ‘non-spatial’ tasks, i.e. the ‘com pare non-spatial’ and ‘associate non-spatial’ tasks. For these tasks, interactive searches are sHghdy higher (47.5% and 35%, respectively). The column labelled ‘Total Spatial’ corresponds to total num ber o f operations for ‘spatial’ tasks, i.e.

Chanter 5 Refining Task Characterization

‘com pare’ and ‘associate’ relative to one or m ore spatial features. N ote that the previous pattern is reversed (36.7% and 44.4%, respectively), in other words, filtering operations were m ore frequent. T he column labelled ‘Total C om pare’ corresponds to the total num ber o f operations for all com pare tasks, spatial and none. Interactive searches were the m ost com m on action in this case, accounting for 45% o f all total user behaviour. T he colum n labelled ‘Total Associate’ corresponds to the total num ber o f operations for all associate tasks. I f frequencies are sum med by tasks where an association is made, then there is little difference between the interactive searching and filtering behaviours (39.4% and 39.7%, respectively). This adds to the finding o f Chapter 4 that ‘com pare’ and ‘associate’ are not necessarily a logical progression in the analysis o f spatial data as K napp (1995) asserts, because the higher am ount o f operations required to complete the ‘com pare’ tasks may be indicative o f a higher complexity. O f interest is the fact that all behaviours are perform ed 28.6% m ore times (925 * 100 / 719) than in the ‘identify-distinguish’ experiment. This also adds to the results o f the evaluation in Chapter 4 where it was found that ‘com pare’ and ‘associate’ tasks are o f a different level o f difficulty than ‘identify’, ‘locate’ or ‘distinguish’ tasks.

Table 5.18 User Behaviours frequencies for Compare and Associate tasks (Identify and Distinguish tasks)

1 _{l l}

H

3 I

Physical Behaviour (Observed)

1 .Search by attribute 7 0.8 3 0.6 4 0.9 5 1.0 2 0.5 2. Search by location 1 0.1 0 0.0 1 0.2 0 0.0 1 0.3 3. Search interactively 393 42.5 235 47.5 158 36.7 233 45.0 160 39.4 4. Filtering 364 39.4 173 35.0 191 44.4 203 39.1 161 39.7 5. H ighlight records 128 13.8 65 13.1 63 14.7 65 12.5 63 15.5 6. Evaluate content 20 2.2 17 3.4 3 0.7 12 2.3 8 2.0 7. Manipulate map 12 1.3 2 0.4 10 2.3 1 0.2 11 2,7

Mental Behaviours (Observed)

8. D ecid e threshold 371 40.1 176 35.6 195 45.4 208 40.1 163 40.2

(1+4)

9. Select records (2+ 3) 375 40.5 226 45.7 149 34.7 229 44.1 146 36.0

Total (1 to 7) 925 495 430 519 406

In summary, by inspecting the frequency o f graphical display usage and low level operations perform ed by participants to achieve a goal, it is possible to characterise how subjects addressed certain tasks and analyse how they used the software to solve them. This enables us to make some general comm ents. T he first is that the data provide testimony to the

(Zhaprer 5______________________________________________ Refining I ’ask Characterization

im portance o f immediate feedback from the com puter tool to user actions when perform ing an interactive and visual exploration o f a dataset. This was illustrated by the preference o f the query devices to m ore standard interfaces at which SQL statem ent m ust be typed in full. By sparing the user the effort o f writing syntactically correct queries and executing them for different values, query devices allow users to concentrate on addressing subtantive tasks.

In terms o f the tasks perform ed it was found that, in absolute num bers, spatial tasks account for m ore low level operations than their non-spatial counterparts. This is suggestive not only o f the higher degree o f complexity that spatial tasks may pose, but also o f the different approach that users take when solving them. This is discussed in the following section. Also note that participants m ade considerable use o f the query devices in order to solve spatial tasks. This indicates the benefit that software tools designed for the analysis o f spatial data would gain from providing similar devices.

In absolute num bers, ‘distinguish’ tasks accounted for m ore low level operations than ‘identify’ ones and once again, the query devices were the m ost frequently used graphical widget. In addition, the map was used m ore for the ‘identify’ tasks. This is no t to imply that visual variables are no t used for distinguishing but rather that if users are presented with other graphical devices that facilitate the operation in som e way, they may be likely to use them m ore frequently and even prefer them to using colour coding for assessing, or in this particular case, distinguishing values. Nevertheless, some o f the m ost successful strategies for spatial tasks analysed below included the use o f the m ap’s colour coding as a com ponent. Finally, ‘com pare’ tasks required m ore m anipulations o f the graphical displays or devices while the m ap views were m ore frequendy utilised in tasks o f association. These remarks are not intended in anyway to assess the validity o f Bertin’s visual variables but rather to suggest that their efficacy may be mediated by both the graphical display in which they are em bedded and the task that needs to be addressed. A lthough this point is n o t discussed further in this dissertation, it constitutes a relevant topic which is a good candidate for formal experimental design and usability testing.