Deliverable 4.4 - INSEAD CALT

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AtGentive IST-4-027529-STP - Attentive Agents for Collaborative Learners4.1.4 DesignWord valence (2: positive versus negative) and animation valence (3: positive,negative and neutral) were manipulated in a within-subjects design. The order of thetrials was randomised between participants.4.2 ResultsOn the average, some 8% of the trials resulted in errors. The mean error rates foreach condition are shown in Table 5. It is clear that errors were not randomlydistributed but rather triggered by specific factors. As expected, a strong effect ofword-animation consistency emerged (χ 2 =15.97 p < .001). Participants exposed topositive animations were more likely to commit an error when evaluating a negativeword rather than a positive one. Vice versa, participants exposed to negative wordswere more likely to commit errors when evaluating a positive word than a negativeone.A general tendency for negative words to generate more errors than positive oneswas also evident. The gap between the negative and the positive words emergedboth in the neutral comparison and by looking at the consistent conditions.AnimationWordPositive NegativePositive 3% 6%Negative 18% 9%Neutral 4% 8%Table 5. Mean error rates in the 6 experimental conditionsAnalysing the distribution of errors across individual subjects, it emerged that somepeople were more prone to interferences (the individual error rates ranged from 0 to45%). The difference between native and non-native speakers was significant(χ 2 =15.97 p < .001). Non-native speakers tended to commit on average 4% moreerrors than native speakers.Before the correct reaction times (RT) were analysed, the outliers in each cell wereremoved, using a simple recursive procedure {Van Selst, 1994 #268}. The mean andstandard deviation used for determining the cutoff for the first selection werecomputed using the entire sample. All RTs differing more than 4 standard deviations(SDs) from the mean were considered outliers and were removed from the sample.The mean and the SD of the resulting distributions were then computed and theprocedure was repeated until no outliers remained. Following this procedure, a totalof 2.8% of the trials were deleted.The remaining RT data were then averaged across participants and experimentalconditions and entered as dependent variables into a 2-way repeated measuresANOVA, with word (2) and animation (3) as factors. There was a significant effect ofword valence F (1,18) = 4.3 p = .05. Positive words were processed faster thannegative ones (mean difference = 44 msec). The main effect of animation and theinteraction word*animation were not significant (F < 1).Del <strong>4.4</strong>: AtGentive Final Evaluation Report – Appendix A page 16
AtGentive IST-4-027529-STP - Attentive Agents for Collaborative Learners1,500word1,40012Reaction Times (msec)1,3001,2001,100PositiveNegativeanimationNeutralFigure 6. Mean reaction times as a function of animation and word (1=positive; 2= negative)4.3 DiscussionOverall, the experiment provided mixed support to the persona effect. The analysis ofthe errors proved a clear conflict between consistent and inconsistent conditions,confirming that non-verbal cues from the agent were processed and interfered withword naming. In particular, the evaluation of negative words was strongly affected bythe concurrent presentation of a positive emotion. On the average, the amount oferrors was sizable (8%), significantly higher that the error percentage (3%) reportedin (Stenberg et al., 1998), where participants were exposed to a combination of wordand pictures. The difference may be due to the stronger effectiveness of videos inconveying emotions and capturing participants’ attention or to the mixture of nativeand non-native English speakers tested in our sample.The analysis of the reaction times showed a more complex framework. The onlyreliable effect was the positive valence advantage, explaining how negative words aresystematically processed slower than positive words.These findings raise an important question: why might we have found a clearinterference effect only for a test measuring accuracy and not for a test measuringspeed? Test sensitivity does not seem to be the answer. Indeed, the stroop taskliterature suggests that reaction times are more sensitive to detect smaller attentionalconflicts than errors (MacLeod, 1991). Alternative explanations include possibleDel <strong>4.4</strong>: AtGentive Final Evaluation Report – Appendix A page 17
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