# Using Educational Chatbots with Metacognitive Feedback to Improve Science Learning
## 3 Methods
### The ECDA-MF Learning Model  
This model contains two phases: self-assessment and metacognitive feedback, as shown in Figure 1. In the self-assessment phase, students assess whether they have mastered a learning module. Then, the chatbot presents different questions based on the student's assessment results in the metacognitive feedback phase. Self-assessment phase: The self-assessment phase is initiated after students complete a learning module and click the \"go on learning\" button. The EC guides students in evaluating their knowledge acquisition by prompting them to assess whether they have mastered the preceding learning module. If students believe they have mastered it, they can click the \"understand\" button; otherwise, they can click the \"don't understand\" button. Metacognitive feedback phase: The content of metacognitive feedback depends on students' self-assessment, i.e., understand or don't understand. A question-based approach is used to design metacognitive feedback, guiding students to think and reflect on the learning process of preceding modules through targeted questions. The questions are adapted from previous studies and tailored for this research [40; 60; 61], as shown in Figure 1. Firstly, because the learning materials involve many complex concepts, students need to understand each learning module and establish connections between modules. Therefore, our metacognitive feedback is designed to induce monitoring of cognition of students. Secondly, metacognitive feedback varies according to the results of the student's self-assessment and the progress of the learning process. Specifically, if students press the \"understand\" button, the EC will ask questions to instruct students to evaluate, reflect, monitor, or regulate the learning process, as well as plan learning strategies. The questions adopted are as follows: (1) Are you satisfied with your current learning performance? (Evaluate and reflect); (2) Are you confident in mastering the above content? (Evaluate); (3) Can you explain the above concepts to others? (Monitor or regulate) (4) How do you better complete subsequent learning? (Plan). Conversely, if students press the \"don't understand\" button, the EC will ask some questions to prompt students to monitor the learning process from knowledge comprehension, effort, and concentration. Additionally, it will guide students to evaluate and reflect on their learning journey to find the reason for any comprehension issues in time. The questions adopted are as follows: (1) Are there any concepts you don't understand? (Monitor subject understanding); (2) Do you make an effort to understand the above content? (Monitor effort); (3) How focused are you on learning? (Monitor concentration); (4) What is the most challenging part? (Evaluate and reflect). Thirdly, each learning module utilizes a single metacognitive question to prevent fatigue and inattention arising from repeated questions. Followed by the metacognitive question, the EC provides a sentence about the students' possible metacognitive performance to which they respond on a five-point Likert-type scale ranging from 1 (strongly disagree) to 5 (strongly agree). A round of metacognitive feedback dialogue is exemplified below:EC: Now, let's look at the heartbeat process. Your heartbeat has two phases: systolic and diastolic. During diastole, your ventricles relax, and the valves open, allowing blood to flow from the atria to the ventricles. Student: go on learning  
EC: [PERSON], have you understood the process of a heartbeat? Student: understand  
EC: Can you explain the above content to others? EC: I can explain the above content to others. [1 very disagree] [2 disagree] [3 not always] [4 agree] [5 very agree]  
Student: (press one button)  
Figure 1: The ECDA-MF learning model. The proposed ECDA-MF learning model offers two advantages. Firstly, it expands upon the conventional EC learning model by prioritizing metacognitive feedback during dynamic assessment.