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Making Energy Savings Easier: Usability Metrics for Thermostats

Daniel Perry, Cecilia Aragon, Alan Meier, Therese Peffer, and Marco Pritoni

Journal of Usability Studies, Volume 6, Issue 4, August 2011, pp. 226 - 244

Article Contents


Methods

The thermostat usability study consisted of 31 participants (9 female, 22 male), ranging in age from 18 to 65. The primary method of recruitment was through online classified postings to sections for “creative gigs” and “labor gigs” in the San Francisco Bay area. Twenty-nine participants were recruited from this post while two were recruited from a similar posting to a university email list. All participants were given a financial incentive for taking part in the study. While participants were not screened to be representative of the United States demographic population, the recruitment postings did produce a range of participants from varied occupations and backgrounds including construction workers, business managers, non-profit staff, maintenance workers, and students. Any participants who worked in the design or manufacturing of thermostats were screened out of the study. Participants were asked to rate their previous experience with programmable thermostats. Seventeen people reported their experience level with programmable thermostats as “low,” eight as “moderate,” and five reported having “no experience with programmable thermostats” (one participant gave no response).

We tested five thermostat interfaces: three primarily touchscreen thermostats, one button-based, and one Web-based thermostat (Table 1). These devices were selected to represent a range of commercially-available devices and prices.

Table 1. Description of Thermostats Tested

Table 1

The experimental design included both between-subjects and within-subjects variables. We identified five tasks that represented fundamental residential PT use cases in daily life.

Task Description

We developed a list of five tasks reflecting the important functionalities of PTs. These tasks were also chosen in consideration of their effect on residential energy efficiency.

Set Heat—Task 1

In this task users were asked to imagine it was winter and that they would like to set their thermostat to HEAT mode. The HEAT-OFF switch is a common control found in typical thermostats for at least the past 60 years. The setting was OFF at the start of the task.

Time & Day—Task 2

In this task users were asked to set the thermostat to the current day and time. The time settings were programmed to Monday at 12:00 a.m. for the start of the task. This task was not performed on the WEB thermostat because time settings could not be modified from the Web portal. Also, setting the day was excluded for the TCH device because this adjustment could only be performed with a settings code provided in the manual.

Current Settings—Task 3

In this task users were asked to identify and read aloud the temperature that the thermostat was set to reach at that current time.

Future Settings—Task 4

In this task users were expected to determine the temperature setting for a future period (Thursday at 9:00 p.m.) and to read this temperature aloud. They were specifically told that they did not need to change any of the temperature program settings but only identify the temperature already programmed.

Vacation/Hold—Task 5

In this task users were asked to imagine they were going on a five-day trip in the winter and needed to set their thermostat to maintain the same temperature during the time they were away. As long as the temperature was consistent for the five days, there was no additional value placed on the methods for which this task was achieved or the temperature selected.

Experimental Design

The thermostat interfaces (except WEB) were mounted on a wooden platform approximately 1.5 meters from the floor. Each participant performed the same five tasks on two of the five thermostat interfaces (Table 2). The interface order was randomized for each subject to account for possible learning effects, and all permutations were tested. In total 12 to 13 subjects performed the series of tasks on each interface over the course of the study. Each task was video recorded for researcher analysis.

Table 2. Experimental Design

Table 2

*Task 2 TCH consisted of only setting the time not the date.

Two computerized surveys were administered prior to any interaction the subject had with the thermostat interfaces. The purpose of the surveys was to record the subjects’ age range as well as their self-rated experience level with programmable thermostat interfaces.

After subjects performed each task, they filled out a self-evaluation of their performance on that particular task. This computerized self-evaluation was based on the NASA Task Load Index (NASA, 2010) and consisted of four questions regarding users’ mental demand, performance, effort, and frustration levels on a 7-point scale from low (easy) to high (challenging).

Subjects were verbally informed that if they were unable to perform a task they could move on to the next task by informing the experimenter they were “not able to perform this task.” If subjects needed clarification on the task requirements or instructions, the experimenter was permitted to answer relevant questions, otherwise the experimenter was not permitted to talk or to assist the subject in any way during the course of the task.

Experimental Conditions

The study was conducted during the summer months in a lab setting in Berkeley, California. Subjects were specifically asked to imagine that it was winter and that they wanted to heat their residence. Heat mode was chosen instead of cool mode due to the temperate climate in Northern California in which residents would not necessarily have air conditioning. Subjects were reminded before each task that they should imagine it was wintertime in their home and that they should evaluate or select temperatures for heating.

A video recording of each session was used to input numerous categories of data including task completion, time on task, function path (buttons and function interactions), interaction motions (press, slide, hold, etc.), interaction errors, and experimenter observations regarding users’ confusion during the task.

A code for the buttons, functions, and interaction motions on each interface was developed for recording purposes.

Interaction errors were recorded as actions with no effect, or ane, defined as any action that did not change the state of the thermostat. The ane actions included failed attempts at opening the device’s cover or flap, touching text or icons that were not touch sensitive, pressing buttons or functions that did not change the device’s state within the current mode, and performing any interaction motion on the interface that did not change the state.

User confusion was recorded as any hesitation or pause (three seconds or greater) between functions. The experimenter also recorded all verbal expressions of the subject that could indicate confusion or an emotional response to the interface. These verbal observations included phrases that expressed confusion, task success, task failure, extreme exasperation, or surprise.

 

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