From ADL Team Member… Peter Berking: A Socratic Method Learning Experience
Implications for Group Learning with Intelligent Tutoring Systems
In the 1980s I taught in an education project called Project SEED which teaches algebra and calculus to elementary school students who are classified as both belonging to a minority and within a poverty-level demographic. If this sounds interesting on its own merit, consider that the project employed a learning paradigm called the Discovery Method, an approach I would classify as "Socratic Learning."
The fundamental principle of this method is that students are guided (through carefully-crafted teacher questions) to "invent" the target content themselves. The teacher does not use lecture or materials to didactically convey the subject matter. Advantages of using this method are:
- Inspiring a deep understanding and thorough retention of subject matter through the experience of "inventing" it
- Intrinsically incorporating an active and engaging learning process
- Fostering self-confidence in the learners' capacity to learn, as well as in their general intellectual abilities (especially when they "invent" subject matter that is beyond their grade level, as in the case of Project SEED).
This approach is not well suited for factually-oriented subject matter, such as history and foreign languages. In such cases, a mix of rote learning techniques (for the factual material that requires memorization) and Socratic (for the material that can be deduced, reasoned, and inferred through thought process alone) might be used.
The following describes a typical scenario of a Project SEED class taught using Socratic Learning:
- The teacher asks a question and calls on a student with hand raised, who responds with their answer.
- The teacher asks the rest of the class to use hand signals (for example, thumbs-up or thumbs-down) to show whether they agree or disagree with the student's answer and/or reasoning.
- The teacher asks the original responder to choose students who are showing disagreement, to explain why they disagree. The process continues until all different ideas in the class are aired. During this process, the teacher NEVER shows any indication of whether an idea is "right" or "wrong." All answers/opinions have equal weight and are accepted by the teacher/facilitator.
- The teacher facilitates a discussion in which he or she draws students into testing the quality of the reasoning of each idea, asking questions that reduce them to their simplest logical components, expose their underlying assumptions, assess their internal consistency and consistency with previously established knowledge, apply them to example cases, etc. As in the previous step, the teacher is careful to not promote an atmosphere of "right" or "wrong;" instead, encourages a lively debate.
- Through skillful facilitation and questioning by the teacher, the class inevitably reaches a consensus on one idea (signaling such with an "I agree" hand signal) due to its compelling logic and intellectual integrity (i.e., the "correct answer").
- The teacher shows students a textbook treatment on the subject that they have invented, validating/ checkpointing their invention and bolstering their confidence in their intellectual abilities.
This scenario example applies to children in a K-12 educational setting. However, the principles and some of the techniques can be applied to adults in an educational or corporate training setting as well.
In terms of rendering this approach through technology, an Intelligent Tutoring System (ITS) such as AutoTutor® already models many elements of Socratic Learning and effectively reproduces the dynamic questioning skills of a Socratic teacher. However, current ITSs are designed only for one-on-one tutoring.
ITSs could be designed for synchronous group learning as well. There are significant advantages for students to learn Socratic style in groups; perhaps most important is that students can get and give feedback to peers, drawing on the greater pool of intelligence and knowledge afforded by a group versus a single student to "invent" the material.
Here is a scenario for how an ITS could operate to support synchronous group learning.
- Students log in to the ITS at the prescribed time. They are not necessarily co-located (the ITS is a web application)
- The ITS announces "what we are going to explore/ investigate today" (i.e., in traditional education-speak, the learning objectives), reminds students of the principles of good participation in Socratic learning (participation is key, there are no wrong answers, etc.), and displays information about who is logged on in this session (through displaying either pictures, avatars, or videos) to personalize the students to each other and promote a sense of teamwork.
- The ITS displays each student's "participation points", which they have earned in past sessions by giving answers, explaining their disagreement with an answer, etc. These points are strictly based on amount of participation, NOT the content or quality of their ideas, or how popular their ideas were with other students. A gauge shows how close they are to the next milestone/reward level (similar to an online game).
- The ITS starts with an open-ended question (e.g., "Now that you know how exponents work from the last session, what do you think a number to the zero power equals?")
- Student operate their ITS terminal controls to indicate that they have an answer.
- The ITS randomly selects a student and asks that person to say their answer (privately communicated to the ITS). The ITSs voice recognition module processes it, stores it, and says it back to all students in its synthetic voice, with no attribution. This anonymity is necessary in most situations, where a few bright students would end up dominating the dialogue – other students tend to get lazy and not participate when they know that the source of the answer is someone who seems to be able to progress the group's understanding much quicker than others, and therefore "probably has the answer that we will all end up agreeing on". A system setting on the ITS can override this anonymity of the sources of answers and comments (for some groups it is helpful to identify sources).
- The ITS asks (all using synthetic voice – very little of this scenario involves text on screen – and avatar appearance that is particularized for each student according to their demographic characteristics) students to indicate agreement or disagreement with the answer.
- The responses are compiled and anonymously broadcast. It proceeds at this point sort of like an "idea auction". "Disagreers" make "bids" by explaining their disagreement/answer, and others hear these explanations and vote among the original answer and the alternative answers. If the group is large, the answers are paraphrased by the ITS and students get to select from a list that appears on the screen to hear the full comment for any of the paraphrased answers. Students can request more explanation from a particular student (anonymous) who has given an answer or registered disagreement. The ITS states it back to the student.
- Once a quorum of students has participated through voting on which answer sounds best to them (the original or some other answer with its associated reasoning), the ITS crunches the data and uses its Artificial Intelligence (AI) module to determine the next question to progress the group in higher and higher levels of rigorous investigation of the possibilities.
- Students can indicate at any time what they believe their final answer to the original question is (all answers are qualified by students on their terminal as "final" or "temporary"). When a quorum of these is reached (close to 100% asserting the same final answer), the ITS announces that there is a consensus and explains what it is. If the consensus coalesces around the "wrong" answer, the ITS continues to ask questions.
- The ITS congratulates everyone and compares their contributions with a Wikipedia or other scholarly entry on the subject, which situates their answer.
This manner of teaching and learning describes one approach to recognizing that learners of all ages are not showing up as "blank slates," but instead bring all manner of previous knowledge and intelligence to bear on their own and others' learning and are not seen as passive "knowledge receptacles." Leveraging these notions to effectively meet educational and training objectives on a large scale is an important challenge for next generation education/training technology.