During the "Heartbeat 300 Passionate Classroom Sharing Moments" at the 2026 TEAM Model Experts Conference, Teacher Chen Po-Jen from Kezhuang Elementary School in Miaoli County shared how he utilized HiTeach and HiTeach AI to build a "Three-Stage Smarter Classroom Model" consisting of "pre-class individualized learning, in-class differentiated collaboration, and post-output reflection and critical thinking." From Word Clouds and Vocabulary Blossom Tasks to AI grading, peer reviews, and Cloud Mind Maps, Teacher Chen showed how AI becomes more than a grading tool—it serves as an essential learning partner guiding students to understand rubrics, compare perspectives, and expand class-wide thinking.
Teacher Chen Po-Jen shared his pedagogical practice over the past two years guiding his elementary students through HiTeach and HiTeach AI. Moving beyond single-feature demonstrations, Teacher Chen deconstructed his classroom workflow into three cohesive stages: "pre-class individualized learning, in-class differentiated collaboration, and post-output reflection and critical thinking," turning HiTeach AI into a vital tool supporting student preparation, group discussion, feedback, and critical inquiry.
Rooting in pre-class preparation, pinpointing students' learning pain points through Word Clouds and Vocabulary Blossom Tasks, turning static preview into dynamic classroom interaction assets.
Streamlined exploration and cross-group checking through dual-color annotations, presenting class-wide artifacts centrally to help students visualize differing perspectives.
AI grading combined with peer review opens deep debates driven by score discrepancies, making AI feedback the launching pad for expanding class-wide thinking.
For Teacher Chen Po-Jen, achieving genuine differentiated and individualized learning does not begin when class starts. Pre-class preparation is the true origin of the entire instructional workflow.
He asks students to complete tasks before class covering vocabulary, character structures, sentence patterns, rhetoric, and text comprehension. Rather than assigning all tasks at once, these expectations accumulate week by week until students naturally know what preparation is required prior to starting a new lesson.
This arrangement ensures valuable class time is no longer consumed by basic information searching or waiting for student responses. When students have already engaged with vocabulary and sentence patterns beforehand, returning to class allows the teacher to transform static preview material into a dynamic, interactive journey.
For instance, during vocabulary instruction, Teacher Chen utilizes HiTeach's Word Cloud feature to rapidly identify which words students find less familiar. When learning pain points are explicitly visualized, the teacher doesn't need to divide time equally across concepts the class already understands, but can focus explanations specifically on where students are stuck.
In Chinese character learning, students complete "Vocabulary Blossom" tasks beforehand, organizing phrases and definitions. Returning to class, the teacher uses picture tasks, fill-in-the-blank activities, random pick-outs, and even tournament games to let students review using their own preview results. This turns pre-class homework from a mere assignment into essential material for classroom interaction and formative assessment.
Entering the in-class stage, Teacher Chen emphasizes "streamlined exploration" and "differentiated collaboration." In rhetoric instruction, for example, different groups are assigned distinct text pages for annotation—first using blue digital pens, and then swapping pages so groups review one another's work with red annotations. Through this collaborative exchange, every group actively participates in rhetoric identification while comparing their interpretations against peers.
When all group artifacts are displayed side-by-side on screen, students can observe: Why did some groups spot a rhetorical device while others missed it? Where do the variations in understanding lie? Here, HiTeach serves not just as an answer display board, but as a platform for the whole class to inspect reasoning processes together.
Sentence structure and composition tasks further integrate HiTeach AI's automated grading features. Teacher Chen first clarifies the scoring rubrics with students before submitting their sentences into the system for AI grading and feedback. Students receive not only a score but also an explanation of why they earned that score.
This is a cornerstone of individualized learning. Every student receives tailored feedback explaining where their writing meets criteria and where improvements can be made. However, Teacher Chen does not stop at "AI score delivery"—he immediately follows up with peer reviews, where students evaluate peer work using the exact same rubrics.
When discrepancies emerge between AI scores, peer scores, and self-assessments, these gaps become fresh springboards for discussion. Students begin analyzing: Why did the AI judge it this way? Why did my classmate give a different score? How can my response be revised for greater clarity?
HiTeach AI plays a similar role in deep text comprehension. After completing open-ended questions, students first receive AI scores and feedback before entering peer reviews. The teacher then identifies questions with significant score variances to lead targeted class discussions.
This design transforms AI grading from a time-saving mechanism or quick scoring tool into a catalyst for student reflection and whole-class debate. Especially in open-ended questions without single correct answers, Teacher Chen displays contrasting student answers for class voting, comparing AI evaluations against the class's collective consensus.
As students debate "why an answer complies" or "why it falls short," learning evolves from an individual's test result into a collective critical thinking journey. This underscores a core insight shared by Teacher Chen: The value of HiTeach AI is not merely finishing personal tasks, but expanding class-wide thinking.
In Cloud Mind Mapping, Teacher Chen demonstrates HiTeach AI's versatile potential. Beyond standard story mapping, he applies mind maps to essay brainstorming, four-character idiom sentence creation, multi-level text questioning, and AI summaries. Students engage in group co-authoring, class-wide collaboration, or individual tasks, supporting diverse learning contexts.
After completing a text mind map, Teacher Chen uses AI Summaries and uploads the results to the cloud for post-class student review. He also integrates Gemini to visualize concepts, enabling students to review key lesson points quickly through images prior to exams.
Another major value of Cloud Mind Maps is breaking classroom time constraints. If students cannot finish tasks during class, they can access their cloud mind maps via a 6-digit code at home to continue editing. Learning extends beyond the 40-minute bell, allowing students to complete synthesis at their own pace, truly achieving individualized learning.
Teacher Chen also applies this three-stage model to Mathematics. For challenging problems, he allocates the last 5 minutes of class for students to submit answers, executing AI grading during the next class to save in-class waiting time. After AI grading, peer reviews follow, inspecting answers that failed to meet rubrics.
When significant gaps occur between AI ratings and peer ratings, the teacher guides the whole class in reviewing the problem together. This turns mistakes from individual student setbacks into whole-class opportunities to clarify core mathematical concepts and evaluation criteria.
From Language Arts to Mathematics, from vocabulary and sentence patterns to textζ·±η©Ά, essay brainstorming, and mind mapping, Teacher Chen Po-Jen's presentation offers a clear, highly replicable HiTeach AI Three-Stage Smarter Classroom Model.
Stage 1 focuses on pre-class individualized learning. Students complete preview tasks, while teachers precisely capture learning pain points.
Stage 2 centers on in-class streamlined exploration and differentiated collaboration. Through HiTeach's interactive tools, displays, collaboration, and AI summaries, students co-construct understanding between groups and the whole class.
Stage 3 emphasizes post-output reflection and critical thinking. Students do not passively accept AI scores, but compare peer assessments, class consensus, and personal understanding, cultivating critical judgment and higher-order thinking.
In an era where AI enters the classroom, Teacher Chen Po-Jen's practice reminds us: AI's value is not just saving time or grading papers. What matters most is how teachers structure the learning process, making AI feedback the starting point for reflection, letting differences be seen, focusing discussions, and continuously expanding the entire class's intellect.
HiTeach AI in such a classroom is not merely a tool, but an instructional partner connecting pre-class, in-class, and post-output learning trajectories. It assists teachers in mastering learning gaps and empowers students to transition from individual feedback toward collective, deep thinking—realizing differentiated, individualized, and deep learning in smarter classrooms.
