PSYU-X2248 Statistics Assessment

Study 1

As a first step, the honours student researcher aimed to synthesise the factors that are known to influence

viewers’ uncanniness feelings based on the previous literature. More specially, the student investigated the factors of abnormality of the facial features, participants’ categorisation difficulty, the perceived experience, and the perceived agency of the robot.

To do this, the honours student used 90 short animated robot video clips as their stimuli. These video clips were gathered from previous studies that demonstrated the existence of the uncanny valley effect (i.e., the red line in figure 1, or, with the animated robots appearing more human-like, participants felt creepier or uneasier). Twenty participants’ rating data (10 females and 10 males, with a mean age of 20.5, SD = 4.5) were collected via an online survey. In the survey, participants were asked to rate the following five aspects of each video clip:

1. Rate how many abnormal facial features they noticed in the animated robot (using an actual human face as the judging criterion);
2. Put the animated robot into a “living” or a “nonliving” category, and rate the difficulty in making that

decision (measured on a 0-10 scale, with a higher score indicating greater difficulty);

3. Rate the degrees they think the animated robot can experience and feel;
4. Rate the degrees they think the robot can act (with 3 and 4 similarly measured on a 0-10 scale, with a higher score indicating a higher level of experience or agency);
5. Rate how much the animated robots in the video clip give them an unnerving/uneasy feeling (measured on a 1-100 scale, with a higher score indicating a higher level of unnerving or uneasy feeling).

Using this data, the student investigated whether the abnormality of the facial features, participants’ categorisation difficulty, the perceived experience, and the perceived agency jointly predicted the uneasy feeling participants may have experienced in Study 1. Based on the previous literature, the student hypothesised that all the factors mentioned above but the perceived agency should significantly predict uneasy feeling, with the perceived experience having the strongest effect.

“Study1.dta” includes the rating data (averaged across the 20 participants) for the 90 video clips. In the dataset, the “id” was the ID of each video clip; the number of abnormal features was labelled as “nfeatures”; the difficulty associated with categorisation was labelled as “catdiff”; the perceived level of experience was

labelled as “experience”; the perceived level of agency was labelled as “agency”; the unnerving/uneasy

rating was labelled as “unnerving”.

Study 2

In Study 2, the student aimed to conceptually replicate Gary and Wegner’s Experiment 2 (2012) using different experimental stimuli, measurements, and a different design. Forty-five animated robot video clips selected from Study 1 were used in Study 2. Among the 45 animated robots (in the video clips), 15 were

rated as having high experience but low agency (i.e., the experience condition), 15 as having low experience but high agency (i.e., the agency condition), and the final 15 had low ratings on both experience and agency (i.e., the control condition). Participants’ fixation times on the animated robot while watching the video clips were recorded by a non-invasive eye-tracking device and used as an index of how much they felt unnerved about the animated robot – participants would avoid looking at the animated robots when they felt uneasy, therefore, resulting in shorter fixation times on the animated robots. Finally, the student employed a between-subject design (cf. the within-subject design in Gary and Wegner’s, 2012) so that each participant only viewed 15 video clips in one of the three conditions and did not feel fatigued by the end of the experiment.

Following Gary and Wegner’s results, the student hypothesised that participants’ average fixation times on the animated robots across the 15 videos in the experience condition should be shorter (avoid looking because of the unnerving feeling) than those in either the agency or the control condition. However, the average gaze times on the animated robots should not differ between the agency and control conditions. Sixty participants (university students) took part in this experiment in total, with each participant being randomly assigned to one of the three video clip groups (i.e., the experience, the agency, and the control group).

As shown in dataset “Study2.dta”, each participant has one data point (a single row per participant), and there are 4 variables. Participants’ gender was labelled as “gender”, age as “age”, the type of videos they viewed was labelled as “vdtype”, and the average fixation times on the animated robots across 15 videos was labelled as “avgfd”, with higher scores on this variable represents longer fixation times (in seconds) looking at the animated robots.

Study 3 

For the final study, the honours student was interested in exploring whether the uncanny valley effect (i.e., viewers deem robots with human experience creepier than robots without human experience) may manifest itself differently for viewers with different video game experiences. The student hypothesises that experienced video game players are often exposed to all kinds of digital avatars that fall within the uncanny valley, and this familiarity with digital avatars may lessen any uncanny valley effects one experiences (e.g., Seyama & Nagayama, 2007).

In the final study, this student used two of the three video types: video clips with animated robots perceived as having high experience but low agency (i.e., the experience condition), and video clips with animated robots perceived as having low experience and agency (i.e., the control condition) from Study 2. The video clips rated as having high agency but low experience were dropped to simplify the study. As in Study 2, a between-subject design was used such that each participant only viewed one of the two video types.

Extending Study 2, Study 3 recruited participants from two participant groups: experienced video game players and novices, thereby employing a 2 (video clip types: experience vs. control) × 2 (participant groups: experienced video game players vs. novices) design. A total of 80 participants took part in Study 3 (20

participants in each of the four groups). Participants’ average fixation times on the animated robots were recorded while viewing the video clips and used as an index for uneasiness.

The student expected a main effect of video types: there should be shorter average fixation times on the animated robots in the experience than in the control video clips; a main effect of participant group: experienced video game players should have longer average fixation times on the aminated robots than that of the video game novices; and most importantly, the student predicted an interaction between the video types and participant groups – specifically, the difference between the two video types (i.e., the uncanny effect) in the averaged fixation times on the animated robots would be smaller for experienced video game players than novices.

As shown in dataset “Study3.dta”, each participant has one data point (a single row per participant). There are 6 variables: participants’ gender was labelled as “gender”, age (numeric) as “age”, the type of videos as “vdtype”, the participant group as “ppgroup”, each unique combination of the video type and the participant group was labelled as “condition”, and the average fixation times on the animated robots across 15 video

clips was labelled as “avgfd”.

Your task

Please help the honours student researcher conduct the appropriate analysis for each of the three studies, including all necessary statistical steps (e.g., necessary descriptive statistics, assumptions checking, statistical analysis etc.) before interpreting the results.