Identifying product and design feature usage
From The Learning Engineer's Knowledgebase
The identification of product and design feature usage is a category of research questions that investigate how and to what degree a product and its individual elements or features were used by participants.
Definition
Product and design feature use measurement is a category of research questions that is used to determine how much and in what ways each individual part of a product was used by the participants, or how the product as a whole was used. This family of research questions is concerned with identifying whether the product was used as expected. Additionally, these types of questions are interested in identifying the different ways that participants used the product, including whether new or unexpected usage patterns were observed.
The findings from this type of research question can help evaluators claimed that the product was used as expected and worked. Additionally, the information gained from these research questions is valuable for improving the product by knowing how much and in what ways each feature was used. With evaluation data, a design team can refine and improve the product to better meet their expectations and goals to improve and increase usage.
Common Research Questions
In this category of research questions, the actual questions typically take one or more of the following general forms:
- In what ways did a person use a feature of the product?
- How / in what ways did participants interact in the activity?
- Are there different groups or categories of participants in how they participated in activities or used the product?
- How much did people use each feature of the product?
- What paths or sequences of actions did people take when using the product?
- What were the most common things that people used with the product?
- What were the least common things that people used with the product?
- Are there patterns to how people used the product over time?
- Did product usage change over time with participants?
- Do certain aspects about a participant predict how they will use the product, such as their background, experiences, knowledge, perceptions, or needs?
Common analysis methods for design feature use evaluations
- Analytics. Learning analytics and unobtrusively collected participation usage data from digital logfiles can be used to collect data on every interaction that a participant makes with the design feature. Analysis can be performed to understand what, how, and for how long a participant uses the feature.
- Participants' perceived use. In addition to digital logs and analytics, participant perceptions can also be gauged through self report methods to ask the participant about how much they used a feature and what their reasons were for using it. Additionally, think-aloud methods where participants are asked to talk about what they are doing (or what they did), the things they notice while they are performing the task, and the reasons for why they made the decisions that they did can be helpful for evaluators trying to understand how and why people use a design feature.
- Usability study. Usability studies investigate how people use and feel about design features and interfaces. These studies target whether people can easily use interfaces and technology and gauge the participants' emotions regarding their use. Usability studies are aimed to directly improve design features by revealing reasons why and how people use (or do not use) a design feature or interface. Usability studies often use think aloud and task analysis methods to allow the participant to give the researchers explanations and reasons why or why not they perceive something to be a certain way. These methods "make thinking visible" through dialogue where a participant can talk about their experience and how it can be improved.
- Process analysis. Process analyses focuses on identifying the specific patterns of action and verbs among participants. Each categorically distinct verb is identified and coded in the data, being as specific as possible in the code. Patterns of activity can be defined from the codes in an attempt to discover how people use the educational product's features. In this analysis, the focus of this methods is not counting participation or seeing if it met a threshold of expectation, but instead identifying the types of participation exist.
- Thematic analysis. Thematic analyses are a general approach in qualitative studies to identify and categorize the themes within a set of qualitative data. Often, data sets are coded very loosely at high resolution to identify small-level themes in the data. Next, the researcher usually identifies larger themes from the first round of coding, and nests the first level themes into the larger themes. Multiple layers of themes can be created in this method. In the case of design feature use, participation with features can be categorized in a first round of coding, and then larger, more broader themes can be identified that categorize the types of participation that exist. Similar to process analysis, the focus of this methods is not counting participation or seeing if it met a threshold of expectation, but instead identifying the types of participation exist.
- Interaction tracing. Used in many different qualitative analysis approaches, interaction tracing is a family of approaches that track how the sequence of a single person's interactions with an interface, activities, and other people within a learning environment. Usage examples, patterns, and cases of participation can be generated that reveal commonalities in people's use of technologies and design features, as well as specific purposes and timing on part of the participant for using each feature.
As with any evaluation approach, any given specific approach is beyond the scope of this wiki. Each method could be an entire college course of its own. Readers are encouraged to research methods more in depth if they are interested in the research questions that they answer.
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