Interaction and process analysis
From The Learning Engineer's Knowledgebase
The analysis of interactions and processes that people perform within learning experiences is a useful evaluation approach for understanding how and why people act the way they do within designed environments. This approach asks questions about how people interact with other people, with technologies, and how they participate in activities of the product to better understand the processes that are involved with learning in the specific context of the design.
Definition
An interaction and process analysis identifies moments (or interaction events) where individual participants interact with other participants (including teachers or facilitators), with educational technologies, with interfaces, or the other ways they participate within learning activities. After the interaction events are identified (and data are collected on them), the evaluator will analyze the data for patterns, sequences, and processes that can explain how and why certain interactions occurred the way they did.
Interaction and process analysis allows evaluators to better hypothesize and predict (1) how people will participate and learn in the future; (2) how different factors, influences, and design features cause a person to act in certain way; and (3) how increases or decreases in certain interactions or behaviors might influence a person's personal path to learning.
Additional Information
Interaction and process analyses can be quite complex, as they examine the interactions of people with other participants and technologies at a micro level. Nevertheless, such analyses are valuable for revealing information about how and why people do what they do in the learning environment.
Conducting such analyses can be helpful if you want to improve the product, generate new hypotheses about how people learn in specific contexts, and reveal areas of productive participation by looking at the behaviors of people at a very micro level.
An interactional dataset would capture a person's interactions with another person at a very micro level, down to the turns that are taken in speech and sharing. For technology interactions, it would look at the clicks that people do while navigating technology, or using a software system.
For example, the dataset in Table 1 of an in-person conversation would not only record what was said at the exact times they were said, but can also capture whether people were interrupted or any other events were occurring:
| # | Participant | Interaction |
|---|---|---|
| 1 [date/time] | Amy | "Look, I got it to work! The software is running now." |
| 2 [date/time] | Bill | "Sweet. I hope it loads this time." |
| 3 [date/time] | Bill | [takes control of the mouse] |
| 4 [date/time] | Amy | "What, wait. It's doing the same thing again. Ugh. Here, let me try" |
| 5 [date/time] | Amy | [takes control of mouse] |
| 6 [date/time] | Bill | "Maybe you will have better luck getting it to work than me" |
By examining the interactions of people in various situations, researchers might be able to identify patterns that lead to more productive achievement of the learning outcomes, or better explain what things cause people to do certain behaviors. In the case of Table 1, evaluators would examine dialogue or interaction tables like this to see if something someone said or did influences another person to take action. The evaluator would identify areas where people do things, the types of things that they say to another, or the types of actions that are taken by people or technologies. Then, they can analyze what they identify to generate explanations as to how and why different processes of learning occur within a learning environment.
Unlike evaluations that demonstrate whether learning occurred or someone demonstrated competency, the analysis of interactions and processes do not typically seek to argue that learning occurred or that people achieved learning objectives. Instead, this approach seeks to create a story or an explanation as to how and why things occur. It is more aligned with generating hypotheses and theories instead of testing whether people achieved the desired outcomes.
These types of analyses require investigating activity at a micro level and seeing exactly who does what, when. You will need to capture information about every documentable action that someone can take to give yourself as rich of data as possible. Data points for this type of analysis include clicks, views, page navigations, dialogue, information sharing, and other indicators of someone's behavior with the learning product. For in-person learning experiences, you could capture speech, touch, movement, gaze, gesture, proximity, or other physical indicators of people's actions. For games, you also could specially capture players' individual moves and actions that are allowed by the rules (for example, the movement of a chess piece from one side of the board to another).
For every data point that captures an action, be sure to also capture a timestamp that records the date and precise time (typically to the millisecond) so that you can also analyze sequence, duration, idleness, and other time-based factors.
Common research questions in interaction and process analyses
- What kinds of behaviors did people exhibit between each other?
- In what ways did people interact with the technologies and interfaces of the product?
- What different patterns of technology and interface use were observed among participants?
- Did the frequency of behaviors have any impact on how people participated in the activity?
- Did certain interactions with other students possibly cause a change in a participant's behavior?
Common research methods for analyzing people's interactions and learning processes
- Learning analytics can be used to capture, track, and take action on specific patterns of participation among participants. Within digital systems, any interaction between a person and a technology or interface can be captured as data. These data can be automatically analyzed, if a system is programmed to know what to look for. If evaluators are in the process of identifying behaviors and interaction patterns, this method will work less, but the data generated from it can be useful for understanding how people participate with technologies in different ways.
- Qualitative thematic analysis. A basic qualitative analysis is any systematic, principled, and documented approach to interpret data, find connections, and classify or qualify different types of interactions that are occurring. In this type of study, evaluators will collect data on the interactions that people do, categorize and code the data to identify each type of interaction, and analyze the themes and patterns that are present in the dynamics of how people and technology interact. This approach answers questions related to identifying the ways in which people interact and what may cause certain interactions to occur.
- Process analysis. A process analysis looks at the sequential order in activity and interactions to classify types of behavior and generate insights about how the dynamics of interactions between people and technologies affect learning. Similar to thematic analysis, evaluators will collect data on the interactions that people do, categorize and code the data to identify each type of interaction, and analyze the themes and patterns that are present in the dynamics of how people and technology interact.
- Grounded theory. In grounded theory, the evaluator tries to make as few assumptions as possible about the interactions that they observe so that their own assumptions, biases, and interpretations affect the analysis in the least way possible. The evaluator begins their work by examining and describing the actions and interactions that people do and begin to categorize what is happening into multiple layers of activity.
Note: It is beyond the scope of this knowledgebase to expand on each of these methods. It is recommended that researchers and evaluators seek additional training, web resources, or courses on individual methods mentioned above that they may want to use.
Tips and Tricks
- Although they can be complex, analyses on people's interactions within learning environments and the sequential processes of how people learn can reveal much about how a person gets to their end goal. Consider conducting such analyses if you would like to generate a richer understanding of how participants navigate their experience or what types of interactions might influence someone's participation or behavior with the product.
- Be sure to collect multiple points of data about people's specific actions that they take and interactions that occur between people and other people, or between people and technology. This includes dialogue, gaze, speech, text, information sharing, clicks, pageviews, video watching time, button presses, movements of characters (such as in a game), moves of players in games, and page navigation. Also be sure to include the timestamp of every action so you can see the sequence and duration.
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