Prompted Self-explanation

Self-explaining is defined as a "content-relevant articulation uttered by the student after reading a line of text" (Chi, 2000; p. 165) or after studying a step in a worked-out example. A self-explanation may contain a meta-cognitive statement and/or a self-explanation inference.

• A meta-cognitive statement is an assessment, made by the student, of his or her own current understanding of the line of text or example step.
• A self-explanation inference is "an identified pieced of knowledge generated...that states something beyond what the sentence explicitly said" (Chi, 2000; p. 165).

Prompting is defined as an external cue that is intended to elicit the activity of self-explaining. Prompts are typically generated by a person, tutoring system, or a verbal reminder embedded in the learning material.

See also prompted self-explanation hypothesis.

Examples

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Here are the instructions to self-explain, taken from Chi et al. (1994):

"We would like you to read each sentence out loud and then explain what it means to you. That is, what
new information does each line provide for you, how does it relate to what you've already read, does it give
you a new insight into your understanding of how the circulatory system works, or does it raise a question
in your mind. Tell us whatever is going through your mind–even if it seems unimportant."

These prompts were reworded to be used in Hausmann & VanLehn (2007):

• What new information does each step provide for you?
• How does it relate to what you've already seen?
• Does it give you a new insight into your understanding of how to solve the problems?
• Does it raise a question in your mind?

These prompts were then included as text, just below a worked-out example. The example was presented as a video taken of the Andes interface, with a voice-over narration describing the user-interface actions (see Table below). In this example, the student is learning how to solve the following problem:

A charged particle is in a region where there is an electric field E of magnitude

14.3 V/m at an angle of 22 degrees above the positive x-axis. If the charge on the particle

is -7.9 C, find the magnitude of the force on the particle P due to the electric field E.

An example of prompting for self-explanining

Now that all the given information has been entered, we need to apply our knowledge of physics to solve the problem.     One way to start is to ask ourselves, “What quantity is the problem seeking?” In this case, the answer is the magnitude of the force on the particle due to the electric field.     We know that there is an electric field. If there is an electric field, and there is a charged particle located in that region, then we can infer that there is an electric force on the particle. The direction of the electric force is in the opposite direction as the electric field because the charge on the particle is negative.     We use the Force tool from the vector tool bar to draw the electric force. This brings up a dialog box. The force is on the particle and it is due to some unspecified source. We do know, however, that the type of force is electric, so we choose “electric” from the pull-down menu. For the orientation, we need to add 180 degrees to 22 degrees to get a force that is in a direction that is opposite of the direction of the electric field. Therefore we put 202 degrees. Finally, we use “Fe” to designate this as an electric force. [ PROMPT ]     Now that the direction of the electric force has been indicated, we can work on finding the magnitude. We must choose a principle that relates the magnitude of the electric force to the strength of the electric field, and the charge on the particle. The definition of an electric field is only equation that relates these three variables. We write this equation, in the equation window. [ PROMPT ]

Note. PROMPT = "Please begin your self-explanation."

References

Chi, M. T. H. (2000). Self-explaining: The dual processes of generating and repairing mental models. In R. Glaser (Ed.), Advances in Instructional Psychology (pp. 161-238). Mahwah, NJ: Erlbaum. [1]

Chi, M. T. H., DeLeeuw, N., Chiu, M.-H., & LaVancher, C. (1994). Eliciting self-explanations improves understanding. Cognitive Science, 18, 439-477. [2]

Hausmann, R. G. M., & VanLehn, K. (2007). Explaining self-explaining: A contrast between content and generation. In R. Luckin, K. R. Koedinger & J. Greer (Eds.), Artificial intelligence in education: Building technology rich learning contexts that work (Vol. 158, pp. 417-424). Amsterdam: IOS Press. [3]