Table 2 Self-regulated learning strategies and corresponding AI application scenario IDs, titles and summaries
Strategy | Scenario ID | Scenario title | Scenario summary |
|---|---|---|---|
Activation of prior content knowledge | S01 | Pre-question generator | AI generates pre-questions that activate students' knowledge of what is to be learned |
Setting goals | S02 | Plan organizer | AI helps students set learning goals, suggests action plans, and offers tips based on data drawn from previous courses |
Activation of task value and interest | S03 | Virtual human | AI augments online courses with the appearances and voices of favorite celebrities to keep students focused |
Selection and adaptation of cognitive strategies | S04 | Intelligent suggestions | AI suggests study materials and strategies to students based on an analysis of students' learning styles and academic performance data |
Metacognitive monitoring | S05 | AI analytics | AI provides an analysis of students’ behavioral data (e.g., clickstream or quizzes) and learning context (e.g., course week, exam, and rewatch) |
Selection strategies for managing motivation and affect | S06 | AI companion | AI motivates students to improve their willingness to learn by presenting the benefits of the successful completion of learning |
Help-seeking behavior | S07 | AI agent | AI answers student questions before, during, or after online courses based on answers to questions collected in previous courses |
Reviewing | S08 | Notelink | AI allows students to take pictures of their notes to rediscover and play relevant videos on their smartphones or tablets |
Self-evaluation | S09 | Adaptive quiz | AI provides students with personalized sets of exercise problems that suit their level of knowledge |
Self-satisfaction | S10 | AI reflection | AI helps students reflect on their own by highlighting what they did well and what they lacked based on learning data |