5주차 조선대

Main ideas / lessons conveyed

Purpose of the session

• The instructor (Hwang Dong) explains that, due to holidays and long weekends, regular classes couldn’t run, so the content is delivered via video.
• Sessions 1–6 materials will be uploaded to Google Classroom, and formative assessment grades will reflect this work.
• Because a project-based approach without written assessment would be difficult to evaluate objectively, the instructor plans occasional “tactile tests” (hands-on/physical tests).

Session structure

• The instructor combines:
  • Session 5 topic: “Changes in the classroom environment due to EdTech AI”
  • A brief introduction to Session 6: multimedia design principles and why they improve learning effectiveness.

What EdTech is and why it’s used

• EdTech = Education + Technology
• EdTech applies IT tools to:
  • facilitate and supplement learning
  • provide concrete experiences
  • explain content that cannot be conveyed effectively through verbal explanation alone
• EdTech is broader than AI; it also includes (at least) AI, big data, AR/VR, and IoT.
• Example given: smartphone-controlled power strips as a concept related to IoT that can be applied broadly across everyday life and education.

Distinguishing EdTech vs. e-learning

• e-learning is a subset/area within EdTech.
• e-learning mainly refers to delivering instruction efficiently to many learners via online resources.
• EdTech’s goals emphasize:
  • individualized/customized learning
  • rich learning experiences that can still work in classroom settings
• Meeting those goals typically requires data + AI + AR/VR, and related technologies.

Shift in education’s paradigm and teacher roles

• Driven by the Fourth Industrial Revolution, where technology goes beyond one-way transmission of rote knowledge.
• The focus shifts from memorization to:
  • creativity
  • problem-solving
  • faster learning in new fields
  • personalized learning
• The relationship shifts from:
  • a vertical teacher → student model
  • to collaborative learning, where teachers and students learn together
• Teacher roles evolve from “teaching” to roles such as:
  • content creator
  • program manager
  • connector of content creators
  • coach (using questions to draw out strengths rather than giving direct answers)

Interaction facilitation: three pillars

Interaction is not only organizing group discussion. It includes three types:

1. Instructor ↔ learner interaction

   • asking questions
   • receiving answers
   • giving feedback

2. Learner ↔ learner interaction

   • enabling discussion of opinions about content and reasoning

3. Content ↔ learner interaction

   • learners engage with content through interactive platforms
   • (The instructor notes viewers are experiencing this now through the video platform’s question prompts.)

The instructor emphasizes that future education must support all three pillars.

Why teachers may be “replaced” and what to prepare for

• The instructor cites futurists/education figures suggesting robot/AI tutoring could replace or sharply reduce the teacher’s knowledge-transmitting role in about 5–7 years.
• Therefore, teachers should be prepared to:
  • use EdTech + AI to teach effectively in that environment
  • use coaching-like questioning to draw out learners’ potential
  • provide tailored lessons

AI learning paradigms (progression of stages)

Paradigm 1: behaviorism / intelligent tutoring

• AI teaches using a stimulus-response approach.
• The system:
  • checks prior knowledge
  • identifies key learning elements
  • provides materials
  • if correct → progresses
  • if not → retrains
• Example: Santa TOEIC
  • diagnostic items at the start (originally “10,” now described as “12”)
  • uses large learning data (e.g., “300 million pieces”) to estimate an optimal path
  • dashboards guide learners toward weaker areas while supporting strengths
• Example system: Space Learning (math)
  • AI explains solutions, then prompts the learner to attempt the next question
  • evaluates correctness and identifies errors
• Example content/platform: Khan Academy
  • organized by grade/unit
  • practice, hints, videos, and “check answer” feedback
  • typical flow: attempt → feedback (“please try again” / “well done”) → next question

Paradigm 2: cognitive/social constructivism — AI as a support/collaboration partner

• Learners become collaborators actively using AI.
• AI supports learning through conversation
  • illustrated with a robot example named Gio, described as an interactive learning partner.

Paradigm 3: complexity theory / human-centrism — learner as leader

• The learner becomes the driver of learning.
• AI is used to enhance learner capabilities.
• Example idea: using GPT so the learner can direct personal learning control (how to learn, what to focus on).

Extending support beyond tutoring: AR/VR + metaverse

• The instructor argues AI tutoring can evolve into more real-world experiential learning, such as:
  • virtual trips
  • metaverse experiences
  • AR/VR learning activities
• Example: Google Cardboard
  • a cheap VR viewer contrasted with expensive VR devices
• Mentioned context: an older (“7 years ago”) educational VR-style demo for biology/human body learning.

Final point: teacher role changes by the level of AI automation

• Based on OECD content, teacher roles vary depending on AI automation level, described in Stages 1–5.

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Methodology / instruction-like content

A) Evaluation / assessment approach described

• Use tactile/occasional tests rather than evaluating only through projects.
• Rationale:
  • project-only evaluation without written assessment may reduce objectivity.
• Grades:
  • reflect activity/content from Sessions 1–6 uploaded to Google Classroom.

B) How interaction should be designed (three pillars)

• Pillar 1: Instructor ↔ learner

  • ask questions
  • collect learners’ responses (thoughts)
  • provide feedback

• Pillar 2: Learner ↔ learner

  • create an environment for learners to discuss opinions
  • require learners to explain why they think that way

• Pillar 3: Content ↔ learner

  • ensure platforms can prompt interaction (e.g., questions during learning)
  • help learners experience learning through interactive delivery

C) AI automation stages (teacher role progression)

• Stage 1 (AI supports teacher; teacher manages environment)

  • teacher controls/manages the learning environment
  • teacher receives dashboards/data on student progress/performance
  • AI identifies tendencies, misunderstandings, and learning progress

• Stage 2 (partially automated group management; teacher controls timing/feedback)

  • AI selects content first
  • teacher chooses the timing of feedback
  • teacher may manage notifications or group organization

• Stage 3 (conditional automation; teacher remains central/observant)

  • AI more strongly influences configuration of the learning environment
  • teacher observes AI operations
  • teacher provides selected questions and feedback tailored to progress

• Stage 4 (highly assimilated / teacher not needed)

  • AI completely controls configuration of the learning environment
  • monitoring may be unnecessary
  • learners select goals, receive training, practice, and get AI feedback

• Stage 5 (complete automation)

  • AI replaces all teacher roles:
    • content provision
    • analysis
    • notifications
    • feedback at appropriate times

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Speakers / sources featured (as stated)

• Hwang Dong — instructor specializing in AI-based digital learning environment design (primary speaker)
• Thomas Frä — director of the Da Vinci Institute, futurist (quoted about robots replacing teachers)
• Ansun Sheldon — British educationalist (quoted about robots replacing human teachers)
• OECD — referenced as the source for the AI automation stage framework