Experience Sampling Method
Goal: Assess participants' moods and emotions at different time intervals. This method can be used to understand the audience's lifestyle, interests, moods, and emotions, similar to the Day Reconstruction method. This can be used to inform the design of a game. Or it can also be used to gauge participants' emotions and moods after and during playing a game to assess the game's influence on participants' moods and emotions.
Procedure: This method relies on participants going about their lives as usual. At a certain interval in time participants are asked to stop what they are doing and make notes of their experience in real-time. Notes are often structured around the place, time, feelings, social environment (who is with them or around them), and what they are doing. A related method is event-contingent Experience Sampling where participants are asked to stop based on an event to note their experience. This is a field study, thus participants are asked to make these notes while they are going about their lives as usual.
Data Collection: Data collected are notes distributed over several intervals in time.
Data Analysis: This data is then analyzed qualitatively over time to develop a model of the audience's emotions and moods over time. This can be used to assess the game's impact on participants' life or to understand the audience profiles.
Sunny Consolvo, M. Walker. (2003). Using Experience Sampling Method to Evaluate Ubicomp Applications. Pervasive Computing.
Reed Larson and Mihaly Csikszentmihalyi. (1983). The Experience Sampling Method. New Directions for Methodology of Social and Behavioral Science. Vol. 15, pp. 41-56.
Refined Experience Sampling Method
Goal: Like Experience Sampling, this method aims to understand participants' moods and emotions as they engage with a game or mobile app. It is a field study method, and thus it preserves ecological validity.
Procedure: A refined ESM(rESM) consists of a data collected phase. This data can be collected automatically through mobile devices or triggered by user-generated events, such as the start of a game. The rESM is based on the integration of qualitative and qualitative methods. Some researchers developed a system(MyExperience ) for tracing and capturing user feedback on mobile phones.It combines automatic logging of sensor data and targeted, in situ user experience sampling to collect real usage data on mobile phones. And since MyExperience tool is open source software, it lowers the barrier for researchers to collect in situ usage data by providing a rich set of extensible sensors and actions with a lightweight XML-based configuration. (See http://myexperience.sourceforge.net/)
Cherubini, M., & Oliver, N. (2009). A refined experience sampling method to capture mobile user experience. arXiv preprint arXiv:0906.4125.
Froehlich, J., Chen, M. Y., Consolvo, S., Harrison, B., & Landay, J. A. (2007, June). MyExperience: a system for in situ tracing and capturing of user feedback on mobile phones. In Proceedings of the 5th international conference on Mobile systems, applications and services (pp. 57-70). ACM.
Hazlett, Richard L. "Measuring emotional valence during interactive experiences: boys at video game play." Proceedings of the SIGCHI conference on Human Factors in computing systems. ACM, 2006.
Przybylski, Andrew K., C. Scott Rigby, and Richard M. Ryan. "A motivational model of video game engagement." Review of general psychology 14.2 (2010): 154.
Day Reconstruction Method
Goal: This method enables researchers to understand participants' lifestyles and activities during the day. Often used as a way to gather information on the target audience to inform the design process.
Procedure: Participants are recruited and asked to go about their lives as usual. They are then asked to develop a journal entry reconstructing a day in their lives. Participants are given a timeline (a day clock) where they put major life/day events. The day events help to elicit a more accurate prompt of the topic studied, such as food intake, stress level, etc. This is a field study.
Data Collection: Data collected are activities over several intervals in time within a day. All data is self-reported.
Data Analysis: This data is then analyzed qualitatively to develop a profile or several profiles for the target audience that can then be used for design.
Kahneman, D., Krueger, A. B., Schkade, D. A., Schwarz, N., & Stone, A. A. (2004). A survey method for characterizing daily life experience: the day reconstruction method. Science (New York, N.Y.), 306(5702), 1776–80.
Goal: This method enables researchers to understand the lifestyles, behaviors, and customs of a population group. Often used as a way to gain foundational knowledge of the cultural practices of a population of interest.
Procedure: Researchers will "insert" themselves into a community and observe their daily lives, recording what they witness as they do. Additional methods, such as interviews, may be employed to gain further information about the group.
Data Collection: Data collected are detailed logs of observed customs, behavioral patterns, and other aspects of the observed individuals' lives.
Data Analysis: Data is typically analyzed qualitatively
Rapid Ethnography Method:
“Rapid ethnography” is a collection of field methods intended to provide a reasonable understanding of users and their activities given significant time pressures and limited time in the field.
Three key ideas exist for the rapid ethnography method:
Narrow the focus of the field research appropriately before entering the field. Zoom in on the important activities.
Use key informants such as community guides or liminal group members. (Note that more researchers may disrupt the natural setting)
Second, use multiple interactive observation techniques (such as interactive feature conceptualization, structured interviews, activity walkthroughs, and contextual inquiry) to increase the likelihood of discovering exceptional and useful user behavior.
Third, use collaborative and computerized iterative data analysis methods (such as cognitive mapping, pictorial storytelling, and scenario analysis)
Collaborative data analysis:
Brewer, John. Ethnography. McGraw-Hill Education (UK), 2000.
Millen, D. R. (2000, August). Rapid ethnography: time deepening strategies for HCI field research. In Proceedings of the 3rd conference on Designing interactive systems: processes, practices, methods, and techniques (pp. 280-286). ACM.