We are investigating how speech can be used in the learning platform to provide adaptive intelligent support within structured and exploratory activities. In particular, we are currently looking into how such support is able to respond to students’ emotions, deduced from speech. Emotions play a significant role in students’ learning behaviour – positive emotions can enhance learning, while negative emotions can inhibit it. We are investigating how the intelligent support can transfer a negative emotion like frustration or boredom, into a positive one, such as enjoyment.
Additionally, we are investigating how students can be supported in their reasoning through different representations when learning fractions. Our aim is to recommend the representation which is the most effective for a particular student as well as the demands of the task. For example, a student might have a particular misconception in solving a task. The support would detect this misconception and recommend a representation to the student that helps her or him to overcome the misconception.
Additionally, if the student is unfamiliar with a particular representation, she or he could be supported in their reasoning when learning fractions. Here, properties of the representation could be explained. Once the representation becomes familiar, deeper knowledge about the problem domain could be gained.
Paul is working to create three fractions that are equivalent to 1/2.
He has low knowledge of the task and struggles to formulate a plan of action. He feels bored because the task seems too difficult to him. The system recognizes that the student is hesitating to perform an action and asks the student to express his feelings verbally by responding to the question: “How do you feel”. Paul answers: “I am bored, I want to do something else”. This answer is then processed by the system’s speech recognition software, which detects that the student is bored. This information is then used by the task-dependent support to transform the negative emotion into a positive one, by helping the student to formulate a plan of action to perform the task.
Cindy is working on creating a fraction that is equivalent to 3/4.
From the five different representations she can see (symbol, number line, area/region, set of objects, and liquid measures) she selects the number line to create this fraction. However, she believes that 3/4 is not placed between 0 and 1, but above 1, and then she gets confused. The task-dependent support recognizes this misconception and recommends the area/region of the representation to Cindy. This enables her to see 3/4 as part of a whole.