Founder of HABOOK TEAM Model, Professor Power Wu, was invited by the Department of Education at National Chengchi University (NCCU) to deliver a specialized keynote in the flagship teacher education course "Secondary School Teaching Practicum," chaired by Professor Yi-Hwa Chang. Under the theme "AI-Empowered 5 Modules for Collaborative Classroom Learning & The Self-Directed Learning Communication Book," Prof. Wu guided 20 prospective secondary school educators through system functional breakdowns, whole-class interactive inquiries, multifaceted group collaboration, and hands-on tablet practice. The session demonstrated how AI lands authentically in real classrooms to empower group co-construction, differentiated instruction, and individualized post-class self-directed learning pathways.
The keynote opened with a thought-provoking icebreaker: "What are the essential elements required to deliver an exceptional lesson?" Prof. Wu invited every student to submit their pedagogical reflections in real time via the HiTeach Smart Classroom System. The prospective teachers responded enthusiastically, sharing diverse perspectives including teacher-student interaction, peer collaboration, empathy and respect for learners, classroom management techniques, and curriculum engagement. Unlike traditional classrooms where only a few hand-raising students can answer orally, HiTeach empowered every candidate to express their thoughts simultaneously and equitably, allowing the instructor to grasp the entire class's cognitive landscape in seconds.
Facing a rich volume of submitted textual responses, Prof. Wu showcased HiTeach's robust AI Text Analytics capabilities:
Through automated summarization, structuring, analysis, and categorization, scattered individual inputs were immediately transformed into structured, actionable instructional telemetry—laying a firm pedagogical foundation for subsequent group co-construction.
In the lecture's core chapter, Prof. Wu dissected the latest development in the HiTeach ecosystem: the "AI-Empowered 5 Modules for Collaborative Classroom Learning." He analyzed the operational mechanisms and pedagogical strategies of each module, leading NCCU students in direct hands-on exercises that synthesized auditory, visual, and experiential learning:
Centered on learner needs, offering 1-on-1 dialogue, problem-solving heuristics, mnemonic generation, and adaptive questioning extensions.
Extracts cohort keywords to form word clouds, utilizing natural language recognition for automated thematic clustering and structured mind mapping.
Assists teachers in grading subjective assignments at scale, integrating self-assessment, peer review rubrics, and dynamic scoring dashboards.
Synthesizes multi-group deliberation trajectories, cross-referencing and consolidating collective artifacts into a representative cohort consensus.
Supports prompt design, lesson planning, and task generation, transforming static materials into gamified quiz challenges and board-game style dynamics.
During the group collaboration phase, Prof. Wu organized the 20 students into four task forces corresponding to the AI-clustered themes: "Interaction & Collaboration," "Instructional Methods & Guidance," "Respect & Empathy for Students," and "Classroom Management & Learning Atmosphere." Each group critically reviewed the raw AI-organized data—eliminating redundancies, bridging omissions, and augmenting findings with practical teaching methodologies. In the classroom management group, for instance, candidates actively contributed concrete field practices, such as "positive reinforcement token economies, establishing classroom routines, absolute fairness, and personalized reward incentives."
Prof. Wu then projected the four group outputs side-by-side on the HiTeach main canvas and triggered the "AI Summary" feature. The system synthesized the refined outputs into an integrated, comprehensive instructional guideline representing the collective wisdom of all prospective educators.
In the subsequent whole-class co-authoring exercise, Prof. Wu initiated a creative collective task: "A Sentence for Professor Chang." Candidates engaged enthusiastically in real-time cloud co-writing, generating high classroom vibrancy and solidarity. The trajectory—from "Individual Answering $\rightarrow$ AI Text Analytics $\rightarrow$ Group Co-construction $\rightarrow$ AI Cohort Summary $\rightarrow$ Whole-Class Co-editing"—vividly demonstrated a next-generation smart classroom where instructional data flows seamlessly and every single voice is made visible.
Demonstrating the AI Study Companion, Prof. Wu highlighted that the AI Companion is engineered around authentic pedagogical needs. It seamlessly bridges formal assessment quizzes, real-time feedback, and instructional digital content pushed by the educator. After completing exercises, students can summon the AI Study Companion to diagnose their problem-solving rationale. If misconceptions occur, learners can select "Adaptive Practice" or "Extended Questioning," prompting the AI to tailor new practice items targeted directly at their specific gaps.
Professor Power Wu emphasized to the prospective teachers: "Classroom AI must never be unconstrained; instructional agency must permanently remain in the hands of the teacher." HiTeach's architecture allows teachers to autonomously toggle student-end AI access according to instructional rhythm and precisely assign specific items or readings for AI-assisted inquiry. This ensures that AI acts as an empowering co-pilot for differentiated teaching rather than a disruptive distraction.
In an English vocabulary self-directed learning simulation, Prof. Wu pushed a packet of 12 specialized academic terms, guiding candidates to use the AI Study Companion to discover personalized retention and comprehension pathways. Learning was no longer about rote memorization, but active verification through "inquiry prompts, structural explanations, mnemonic generation, and scaffolded adaptive quizzes." The teacher can instantly deploy follow-up diagnostic quizzes, closing the loop on precision teaching.
Beyond synchronous in-class collaboration, Prof. Wu demonstrated how the "Self-Directed Learning Communication Book" extends independent learning trajectories after class. Students use a short PIN via HiTeach.cc to log in from any web device, review their assessment telemetry, revisit their personal error log for reinforcement, and consult the AI Study Companion for in-depth remediation.
The Self-Directed Learning Communication Book operationalizes three core evidence-based strategies from modern cognitive science: Retrieval Practice, Interactive Feedback, and Spaced Practice. This methodology assists learners in transferring transient classroom exposure into durable long-term memory, steadily cultivating an individualized, self-regulated learning portfolio.
Throughout the keynote, NCCU pre-service teachers exhibited exceptional professional inquiry, discussing curriculum alignment in secondary schools, multi-tiered task design, and individualized intervention for struggling students. This immersive practicum blending theoretical frameworks, live system demonstrations, and hands-on tablet engagement planted forward-looking seeds of AI smart education in Taiwan's future secondary education leaders.
