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    Student profiling in a dispositional learning analytics application using formative assessment

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    How learning disposition data can help us translating learning feedback from a learning analytics application into actionable learning interventions, is the main focus of this empirical study. It extends previous work where the focus was on deriving timely prediction models in a data rich context, encompassing trace data from learning management systems, formative assessment data, e-tutorial trace data as well as learning dispositions. In this same educational context, the current study investigates how the application of cluster analysis based on e-tutorial trace data allows student profiling into different at-risk groups, and how these at-risk groups can be characterized with the help of learning disposition data. It is our conjecture that establishing a chain of antecedent-consequence relationships starting from learning disposition, through student activity in e-tutorials and formative assessment performance, to course performance, adds a crucial dimension to current learning analytics studies: that of profiling students with descriptors that easily lend themselves to the design of educational interventions

    Immersive Telepresence: A framework for training and rehearsal in a postdigital age

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    Intelligence Unleashed: An argument for AI in Education

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    ์ธ๊ณต์ง€๋Šฅ ๊ธฐ๋ฐ˜ ๊ต์œก ํ”Œ๋žซํผ ์‚ฌ์šฉ์— ๋Œ€ํ•œ ์ค‘๊ตญ ๊ต์‚ฌ์˜ ์ธ์‹

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์‚ฌ๋ฒ”๋Œ€ํ•™ ๊ต์œกํ•™๊ณผ, 2021. 2. ์กฐ์˜ํ™˜.์ตœ๊ทผ ๊ต์œก ๋ถ„์•ผ์—์„œ ์ธ๊ณต์ง€๋Šฅ(AI)์˜ ๋„์ž…์ด ํฐ ๊ด€์‹ฌ์„ ๋Œ๊ณ  ์žˆ๋‹ค. ํŠนํžˆ AI ๊ธฐ์ˆ ๊ณผ ํ•™์Šต ๋ถ„์„์ด ๊ฒฐํ•ฉํ•œ ์ธ๊ณต์ง€๋Šฅ ๊ธฐ๋ฐ˜ ๊ต์œก ํ”Œ๋žซํผ์€ ์ง€๊ธˆ๊ป ์‹คํ˜„๋˜๊ธฐ ์–ด๋ ค์› ๋˜ ๋งž์ถคํ˜• ํ•™์Šต(personalized learning)๊ณผ ์ ์‘์  ํ•™์Šต(adaptive learning)์— ๋„์›€์ด ๋  ์ˆ˜ ์žˆ๋„๋ก ๋ฐœ์ „ํ•˜๊ณ  ์žˆ๋‹ค. ์ธ๊ณต์ง€๋Šฅ ๊ธฐ๋ฐ˜ ๊ต์œก ํ”Œ๋žซํผ(AI-based education platform)์€ ํ•™์Šต์ž์˜ ํ–‰๋™ ์ถ”์  ๋“ฑ์„ ํ†ตํ•ด ์ด๋“ค์˜ ํŠน์„ฑ์„ ๋ถ„์„ํ•˜๊ณ  ์ง„๋‹จ์„ ์ œ๊ณตํ•œ ๋’ค ๋ถ„์„ ๊ฒฐ๊ณผ๋ฅผ ํ† ๋Œ€๋กœ ํ•™์Šต์ž์—๊ฒŒ ์ธ์ง€ ์ˆ˜์ค€์— ๋งž๋Š” ๋งž์ถคํ˜• ํ•™์Šต์ž์›๊ณผ ํ”ผ๋“œ๋ฐฑ์„ ์ œ๊ณตํ•œ๋‹ค. ์ธ๊ณต์ง€๋Šฅ ๊ธฐ๋ฐ˜ ๊ต์œก ํ”Œ๋žซํผ์€ ๊ต์‚ฌ์™€ ํ•™์ƒ์—๊ฒŒ ์‹ค์‹œ๊ฐ„ ํ•™์Šต ๋ฐ์ดํ„ฐ์™€ ๋ถ„์„ ๊ฒฐ๊ณผ, ๊ทธ๋ฆฌ๊ณ  ํ”ผ๋“œ๋ฐฑ์„ ์ œ๊ณตํ•  ์ˆ˜ ์žˆ์–ด ์ธ๊ณต์ง€๋Šฅ ๊ธฐ๋ฐ˜ ๊ต์œก ํ”Œ๋žซํผ์ด ๋งž์ถคํ˜• ํ•™์Šต์— ๊ธ์ •์ ์ธ ์˜๋ฏธ๊ฐ€ ์žˆ๋‹ค๋Š” ์„ ํ–‰ ์—ฐ๊ตฌ๋„ ์žˆ์—ˆ๋‹ค. ๊ทธ๋Ÿผ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ , ๊ธฐ์กด ์—ฐ๊ตฌ๋Š” ๋ชจ๋ธ ๊ฐœ๋ฐœ์˜ ์ฐจ์›์—์„œ๋‚˜ ์—„๋ฐ€ํ•œ ์‹คํ—˜์‹ค ํ™˜๊ฒฝ์—์„œ ์ธ๊ณต์ง€๋Šฅ ๊ธฐ๋ฐ˜ ๊ต์œก ํ”Œ๋žซํผ์˜ ํšจ๊ณผ๋ฅผ ์—ฐ๊ตฌํ•ด์™”์œผ๋ฉฐ, ์ธ๊ณต์ง€๋Šฅ ๊ธฐ๋ฐ˜ ๊ต์œก ํ”Œ๋žซํผ์— ๋Œ€ํ•œ ๊ต์‚ฌ์˜ ์ธ์‹๊ณผ ๊ด€๋ จ๋œ ์—ฐ๊ตฌ๋Š” ๋“œ๋ฌผ์—ˆ๋‹ค. ๊ต์‚ฌ๋Š” ์ธ๊ณต์ง€๋Šฅ ๊ต์œก ๊ธฐ์ˆ ์˜ ์‚ฌ์šฉ์ž์ด๊ธฐ ๋•Œ๋ฌธ์— ์ธ๊ณต์ง€๋Šฅ ๊ต์œก ๊ธฐ์ˆ ์˜ ๊ต์œก ๋„์ž…์— ์žˆ์–ด ๊ต์‚ฌ๋“ค์˜ ์ธ์‹๊ณผ ์˜๊ฒฌ์€ ์ค‘์š”ํ•˜๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์ธ๊ณต์ง€๋Šฅ ๊ธฐ๋ฐ˜ ๊ต์œก ํ”Œ๋žซํผ์„ ํ™œ์šฉํ•˜๋Š” ๊ฒƒ์— ๋Œ€ํ•œ ๊ต์‚ฌ๋“ค์˜ ์ธ์‹์„ ํƒ๊ตฌํ•˜์˜€๋‹ค. ์•„๋ž˜ ์—ฐ๊ตฌ ๋ฌธ์ œ๋ฅผ ๋‹ค๋ฃจ๊ธฐ ์œ„ํ•ด ์งˆ์  ์—ฐ๊ตฌ๋ฅผ ์‹œํ–‰ํ•˜์˜€๋‹ค. ์ฒซ์งธ, ์ค‘๊ตญ ๊ต์‚ฌ๋“ค์€ ์ธ๊ณต์ง€๋Šฅ ๊ธฐ๋ฐ˜ ๊ต์œก ํ”Œ๋žซํผ์ด ์ค‘ํ•™๊ต ๊ต์œก์— ํ™œ์šฉ ์žˆ์–ด ์–ด๋– ํ•œ ์žฅ์ ์ด ์žˆ๋‹ค๊ณ  ์ธ์‹ํ•˜๋Š”๊ฐ€? ๋‘˜์งธ, ์ค‘๊ตญ ๊ต์‚ฌ๋“ค์€ ์ธ๊ณต์ง€๋Šฅ ๊ธฐ๋ฐ˜ ๊ต์œก ํ”Œ๋žซํผ๊ณผ ์ค‘ํ•™๊ต ๊ต์ˆ˜ ํ™œ๋™ ์š”์†Œ ๊ฐ„ ์–ด๋– ํ•œ ๋ชจ์ˆœ์ด ์žˆ๋‹ค๊ณ  ์ธ์‹ํ•˜๋Š”๊ฐ€? ์…‹์งธ, ์ค‘๊ตญ ๊ต์‚ฌ๋“ค์€ ์ธ๊ณต์ง€๋Šฅ ๊ธฐ๋ฐ˜ ๊ต์œก ํ”Œ๋žซํผ์„ ์ค‘ํ•™๊ต ๊ต์œก์— ๋„์ž…ํ•  ๋•Œ ๋ฌด์—‡์ด ํ•„์š”ํ•˜๋‹ค๊ณ  ์ธ์‹ํ•˜๋Š”๊ฐ€? ๋ณธ ์—ฐ๊ตฌ๋Š” ์ค‘๊ตญ ๊ต์‚ฌ๋“ค์„ ์—ฐ๊ตฌ๋Œ€์ƒ์œผ๋กœ ์˜จ๋ผ์ธ ์‹ฌ์ธต ๋ฉด๋‹ด์„ ํ•˜์˜€๋‹ค. ๋ฌธํ—Œ ๋ฆฌ๋ทฐ๋ฅผ ํ†ตํ•ด ๋ฉด๋‹ด ์งˆ๋ฌธ์ง€๋ฅผ ์„ค๊ณ„ํ•˜๋˜ ๋ˆˆ๋ฉ์ดํ‘œ์ง‘๋ฒ• (snowball sampling)์„ ํ†ตํ•ด ์ค‘๊ตญ ์ค‘ํ•™๊ต ๊ต์‚ฌ 14๋ช…์„ ์—ฐ๊ตฌ์ฐธ์—ฌ์ž๋กœ ์„ ์ •ํ•˜์˜€๋‹ค. ์„ ์ •๋œ ๊ต์‚ฌ๋“ค์€ ๋ชจ๋‘ ์ธ๊ณต์ง€๋Šฅ ๊ธฐ๋ฐ˜ ๊ต์œก ํ”Œ๋žซํผ ์‚ฌ์šฉ ๊ฒฝํ—˜์ด ์žˆ์œผ๋ฉฐ ๊ฐ ๊ต์‚ฌ๋ฅผ ๋Œ€์ƒ์œผ๋กœ ์•ฝ 1์‹œ๊ฐ„ ์ •๋„ ๋ฉด๋‹ด์„ ์ง„ํ–‰ํ•˜๊ณ  ๋…น์Œํ•˜์˜€๋‹ค. ๋ฉด๋‹ด์ด ๋๋‚œ ํ›„ ๋…น์Œ ๋‚ด์šฉ์„ ์ „์‚ฌํ•˜์˜€์œผ๋ฉฐ, ์ฃผ์ œ๋ถ„์„์„ ์‚ฌ์šฉํ•˜์—ฌ ๋ฉด๋‹ด ๋‚ด์šฉ์„ ์ดˆ๊ธฐ ์ฝ”๋“œ ์ƒ์„ฑํ•˜๊ณ  ๋ฉด๋‹ด ์ž๋ฃŒ ์†์—์„œ ์ฃผ์ œ๋ฅผ ๋„์ถœํ•˜์˜€๋‹ค. ํŠนํžˆ ์—ฐ๊ตฌ ๋ฌธ์ œ 2๋ฒˆ์˜ ๊ฒฝ์šฐ, ์ธ๊ณต์ง€๋Šฅ ๊ธฐ๋ฐ˜ ๊ต์œก ํ”Œ๋žซํผ ํ™œ์šฉ๊ณผ ๊ต์ˆ˜ ํ•™์Šตํ™œ๋™ ๋‚ด ์—ฌ๋Ÿฌ ์š”์†Œ ๊ฐ„์˜ ๋ชจ์ˆœ์„ ๋ถ„์„ํ•˜๊ธฐ ์œ„ํ•ด ํ™œ๋™์ด๋ก ์„ ์—ฐ๊ตฌ์˜ ํ‹€๋กœ ์ด์šฉํ•˜์˜€๋‹ค. ์ตœ์ข…์ ์œผ๋กœ ์—ฐ๊ตฌ๋ฌธ์ œ 1์— ๋Œ€ํ•œ ์ฃผ์ œ 4๊ฐœ, ์—ฐ๊ตฌ๋ฌธ์ œ 2์— ๋Œ€ํ•œ ์ฃผ์ œ 6๊ฐœ, ์—ฐ๊ตฌ๋ฌธ์ œ 3์— ๋Œ€ํ•œ ์ฃผ์ œ 4๊ฐœ๋ฅผ ๋„์ถœํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋กœ ๊ต์‚ฌ๋“ค์€ ์ธ๊ณต์ง€๋Šฅ ๊ธฐ๋ฐ˜ ๊ต์œก ํ”Œ๋žซํผ์˜ ์žฅ์ ์— ๋Œ€ํ•ด ์ฆ‰๊ฐ์ ์ธ ํ”ผ๋“œ๋ฐฑ ์ œ๊ณต, ๊ต์ˆ˜ํ•™์Šต ์ง€์›, ๊ต์‚ฌ์˜ ์—…๋ฌด๋Ÿ‰ ๊ฐ์†Œ ๋“ฑ์œผ๋กœ ์ธ์‹ํ•˜์˜€๊ณ , ์ธ๊ณต์ง€๋Šฅ ๊ธฐ๋ฐ˜ ๊ต์œก ํ”Œ๋žซํผ์ด ๋‹ค์–‘ํ•œ ๊ต์ˆ˜ํ•™์Šต ์ž์›์„ ํ†ตํ•ฉํ•  ์ˆ˜ ์žˆ๋‹ค๊ณ  ์ธ์‹ํ•˜์˜€๋‹ค. ์•„์šธ๋Ÿฌ ๊ต์‚ฌ๋“ค์€ ์ธ๊ณต์ง€๋Šฅ ๊ธฐ๋ฐ˜ ๊ต์œก ํ”Œ๋žซํผ์˜ ์‚ฌ์šฉ์— ์žˆ์–ด ๊ธฐ์กด์˜ ๊ต์ˆ˜ํ•™์Šต ํ™œ๋™๊ณผ ์ƒ์ถฉ๋œ ๋ถ€๋ถ„์ด ์žˆ๋‹ค๋Š” ์ ์„ ์ธ์‹ํ•˜์˜€๋‹ค. ๊ต์‚ฌ๋“ค์€ ๊ธฐ์กด ์ธ๊ณต์ง€๋Šฅ ๊ธฐ๋ฐ˜ ๊ต์œก ํ”Œ๋žซํผ์˜ ์ถ”์ฒœ ๋ชจ๋ธ์ด ์ฐจ๋ณ„ํ™”๋œ ํ•™์ƒ๋“ค์—๊ฒŒ ์ž˜ ์ ์šฉ๋˜์ง€ ๋ชปํ•œ๋‹ค๋Š” ๊ฒƒ์„ ์ธ์‹ํ•˜์˜€๋‹ค. ๊ทธ๋ฆฌ๊ณ  ๊ธฐ์กด ์ธ๊ณต์ง€๋Šฅ ๊ธฐ๋ฐ˜ ๊ต์œก ํ”Œ๋žซํผ์ด ๋‹ค์–‘ํ•œ ํ•™์Šต ์ž์›์„ ์ž˜ ๋ถ„๋ฅ˜๋˜์ง€ ๋ชปํ•˜๊ธฐ ๋•Œ๋ฌธ์— ๊ต์‚ฌ๋“ค์ด ์‚ฌ์šฉํ•˜๊ธฐ ๋ถˆํŽธํ•˜๋‹ค. ์ธ๊ณต์ง€๋Šฅ ๊ธฐ๋ฐ˜ ๊ต์œก ํ”Œ๋žซํผ์„ ์ด์šฉํ•  ๋•Œ ๊ต์‚ฌ์˜ ์ง€์ ์žฌ์‚ฐ๊ถŒ์„ ๋ณดํ˜ธํ•˜๊ธฐ ์œ„ํ•œ ๋ช…ํ™•ํ•œ ๊ทœ์ œ๊ฐ€ ๋ถ€์กฑํ•˜๋‹ค๊ณ  ์ธ์‹ํ•˜์˜€๋‹ค. ์ด์™€ ํ•จ๊ป˜ ํ•™๋ถ€๋ชจ๋“ค์€ ์ธ๊ณต์ง€๋Šฅ ๊ธฐ๋ฐ˜ ๊ต์œก ํ”Œ๋žซํผ์„ ์‚ฌ์šฉํ•จ์œผ๋กœ์จ ๋ฐœ์ƒํ•  ์ˆ˜ ์žˆ๋Š” ํ•™์Šต์ž์˜ ์ธํ„ฐ๋„ท ๋‚จ์šฉ๊ณผ ์‹œ๋ ฅ ์ €ํ•˜ ๋ฌธ์ œ๋ฅผ ์šฐ๋ คํ•˜์˜€๋‹ค. ๋˜ ์ค‘๊ตญ์˜ ์‚ฌํšŒ๋ฌธํ™”์  ๋ฐฐ๊ฒฝ๊ณผ ๊ต์œก ํŠน์„ฑ์œผ๋กœ ์ธํ•ด ์ธ๊ณต์ง€๋Šฅ ๊ธฐ๋ฐ˜ ๊ต์œก ํ”Œ๋žซํผ์„ ํ™œ์šฉํ•˜๋Š” ๋ฐ ํ•™์ƒ๋“ค์˜ ๊ธ€์”จ ์“ฐ๊ธฐ ๋Šฅ๋ ฅ์— ์˜ํ–ฅ์„ ๋ฏธ์น  ์ˆ˜ ์žˆ์œผ๋ฉฐ, ํ•™๊ต ๋‚ด ์ „์ž๊ธฐ๊ธฐ ์‚ฌ์šฉ ์ œํ•œ๋„ ๋ฐ์ดํ„ฐ ์ˆ˜์ง‘์˜ ์ง€์†์„ฑ๊ณผ ํšจ์œจ์„ฑ์— ์˜ํ–ฅ์„ ๋ฏธ์น  ์ˆ˜ ์žˆ๋‹ค๊ณ  ์ธ์‹ํ•˜์˜€๋‹ค. ๊ต์‚ฌ๋“ค์€ ์œ„์˜ ๋ฌธ์ œ๋“ค์ด ์ธ๊ณต์ง€๋Šฅ ๊ต์œก ํ”Œ๋žซํผ ์‚ฌ์šฉ์— ๋Œ€ํ•œ ๊ทœ์น™ ๋งˆ๋ จ๊ณผ ์ธ๊ณต์ง€๋Šฅ ๊ธฐ์ˆ ์„ ๊ฐœ์„ ํ•จ์œผ๋กœ์จ ์™„ํ™”๋  ์ˆ˜ ์žˆ๋‹ค๊ณ  ์ธ์‹ํ•˜์˜€๋‹ค. ๋˜ํ•œ ๊ต์‚ฌ์˜ ์‹ค์ œ ์š”๊ตฌ์— ๋งž๊ฒŒ ๊ฐœ๋ฐœ๋  ์ˆ˜ ์žˆ๋„๋ก ์ธ๊ณต์ง€๋Šฅ ๊ธฐ๋ฐ˜ ๊ต์œก ํ”Œ๋žซํผ ๊ฐœ๋ฐœ ๊ณผ์ •์— ๊ต์œก ์ „๋ฌธ๊ฐ€์™€ ๊ต์‚ฌ๊ฐ€ ์ฐธ์—ฌํ•  ํ•„์š”๊ฐ€ ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์ค‘๊ตญ ๊ต์‚ฌ๋“ค์ด ์ธ๊ณต์ง€๋Šฅ ๊ธฐ๋ฐ˜ ๊ต์œก ํ”Œ๋žซํผ์— ๋Œ€ํ•œ ์ธ์‹์„ ํƒ์ƒ‰ํ•˜์˜€์œผ๋ฉฐ, ์ธ๊ณต์ง€๋Šฅ ๊ธฐ๋ฐ˜ ๊ต์œก ํ”Œ๋žซํผ์ด ๊ต์ˆ˜ํ•™์Šต์—์„œ์˜ ์žฅ์ ๊ณผ ๋ฌธ์ œ์ ์„ ๋ฐํ˜”๋‹ค. ์•„์šธ๋Ÿฌ ๋ณธ ์—ฐ๊ตฌ๋Š” ์ธ๊ณต์ง€๋Šฅ ๊ธฐ๋ฐ˜ ๊ต์œก ํ”Œ๋žซํผ์ด ๊ต์œก ๋ถ„์•ผ์— ๋Œ€๊ทœ๋ชจ๋กœ ๋„์ž…๋  ์ˆ˜ ์žˆ๋„๋ก ๊ทœ์น™, ์ธ๊ณต์ง€๋Šฅ ๊ธฐ์ˆ , ๊ทธ๋ฆฌ๊ณ  ๊ต์œก ๊ณตํ•™์˜ ์ฐจ์›์—์„œ ์‚ฌ์šฉ ๊ทœ๋ฒ”๊ณผ ๊ธฐ์ˆ  ๊ฐœ์„ ์„ ์ œ์•ˆํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด ํƒ์ƒ‰ํ•œ ๋‚ด์šฉ์ด ํ–ฅํ›„ ๊ต์œก ๋ถ„์•ผ์˜ ์ธ๊ณต์ง€๋Šฅ ๊ธฐ๋ฐ˜ ๊ต์œก ํ”Œ๋žซํผ ๋„์ž…์— ํ™œ์šฉ๋œ๋‹ค๋ฉด ์ธ๊ณต์ง€๋Šฅ ๊ต์œก ๊ธฐ์ˆ ์— ๊ด€ํ•œ ์—ฐ๊ตฌ์˜ ๋ฐœ์ „์—๋„ ๊ธฐ์—ฌํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€๋œ๋‹ค.In recent years, the introduction of artificial intelligence (AI) in education has attracted widespread attention. In particular, the AI-based education platform based on the combination of AI technology and learning analysis brings new light to the long-standing difficulties in personalized learning and adaptive learning. The AI-based education platform analyzes learners' characteristics by collecting their data and tracking their learning behavior. It then generates cognitive diagnosis for learners and provides them with personalized learning resources and adaptive feedback that match their cognitive level based on systematic analysis. With the help of the AI-based education platform, teachers and students can get real-time educational data and analysis result๏ผŒas well as the feedback and treatment corresponding to the results. Previous studies have already demonstrated and proved its positive significance to personalized learning. However, these studies mostly start from a model development perspective or in a rigorous laboratory environment. There has been little research on teachers' perceptions of AI-based education platform. As a direct user of AI educational technologies, teachers' perceptions and suggestions are vital for introducing AIEd in education. In this study, the researcher explored teachers' perceptions of using AI-based education platform in teaching. The study conducted qualitative research to address the following research questions: 1) How do Chinese teachers perceive the advantages of AI-based education platforms for teaching and learning in secondary school? 2) How do Chinese teachers perceive the contradictions between AI-based education platforms and the secondary school system? 3๏ผ‰How do Chinese teachers suggest applying AI-based education platforms in secondary school? And it referred to the in-depth online interview with Chinese teachers who had experience with AI-based education platform. Interview questions were constructed through the literature review, and 14 secondary school teachers were selected by the snowball sampling method. The interviews lasted for an average of one hour per teacher and were transcribed from the audio recordings to text documents when finished. Afterward, the data were analyzed using thematic analysis, including generating initial codes, searching and reviewing the categories, and deriving the themes finally. Notably, for research question two, the researcher used the activity theory framework to analyze the contradictions among the use of the AI-based education platform and the various elements of the teaching and learning activities. Finally, four themes for research question 1, six themes for research question 2, and four themes for research question 3 were derived. As for the advantages, teachers believe that AI-based education platforms can provide instant feedback, targeted and systematic teaching support, and reduce teachers' workload. At the same time, AI-based education platforms can also integrate teaching resources in different areas. Teachers also recognized that the AI-based education platforms might trigger contradictions in existing teaching activities. They are aware of the situation that the recommended model of the AI-based education platform is not suitable for all levels of students; that a large number of learning resources are not classified properly enough to meet the needs of teachers, and that there lack clear rules and regulations to protect teachers' intellectual property rights when using the platform. Besides, parents are also concerned about the potential risk of internet addiction and vision problems using AI-based education platforms. Moreover, the use of the AI-based education platform may also affect students' ability to write Chinese characters due to the socio-historical background and educational characteristics in China. Furthermore, the restricted use of electronic devices on campus may also impact the consistent and effective education data collection. Teachers believe that these problems can be solved by improving rules and AI technology. Moreover, to make the platform more in line with the actual teaching requirements, teachers and education experts can also be involved in the development process of AI-based education platform. This study explored how Chinese teachers perceive the AI-based education platform and found that the AI-based education platform was conducive to personalized teaching and learning. At the same time, this study put forward some suggestions from the perspective of rules, AI technology, and educational technology, hoping to provide a good value for the future large-scale introduction of AI-based education platforms in education.CHAPTER 1. INTRODUCTION 1 1.1. Problem Statement 1 1.2. Purpose of Research 7 1.3. Definition of Terms 8 CHAPTER 2. LITERATURE REVIEW 10 2.1. AI in Education 10 2.1.1 AI for Learning and Teaching 10 2.1.2 AI-based Education Platform 14 2.1.3 Teachers' Perception on AI-based Education Platform 18 2.2. Activity Theory 20 CHAPTER 3. RESEARCH METHOD 23 3.1. Research Design 23 3.2. Participants 25 3.3. Instrumentation 26 3.3.1 Potential Value of AI System in Education 26 3.4. Data Collection 33 3.5. Data Analysis 34 CHAPTER 4. FINDINGS 36 4.1. Advantages of Using AI-based Education Platform 36 4.1.1 Instant Feedback 37 4.1.2 Targeted and Systematic Teaching Support 42 4.1.3 Educational Resources Sharing 46 4.1.4 Reducing Workload 49 4.2. Tensions of Using AI-based Education Platform 51 4.2.1 Inadequately Meet the Needs of Teachers 52 4.2.2 Failure to Satisfy Low and High Achievers 54 4.2.3 Intellectual Property Violation 56 4.2.4 Guardian's Concern 57 4.2.5 School Rules about the Use of Electronic Devices 58 4.2.6 Implication for Chinese Character Education 59 4.3. Suggestion of Using AI-based Education Platform 61 4.3.1 Improving Rules of Using the AI-based Education Platform 61 4.3.2 Improving Rules of Protecting Teachers Right 62 4.3.3 Improving AI Technology 64 4.3.4 Participatory Design 66 CHAPTER 5. DISCUSSION AND CONCLUSION 68 5.1. Discussion 68 5.2. Conclusion 72 REFERENCE 75 APPENDIX 1 98 APPENDIX 2 100 ๊ตญ๋ฌธ์ดˆ๋ก 112Maste

    AI-enabled adaptive learning systems: A systematic mapping of the literature

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    Mobile internet, cloud computing, big data technologies, and significant breakthroughs in Artificial Intelligence (AI) have all transformed education. In recent years, there has been an emergence of more advanced AI-enabled learning systems, which are gaining traction due to their ability to deliver learning content and adapt to the individual needs of students. Yet, even though these contemporary learning systems are useful educational platforms that meet studentsโ€™ needs, there is still a low number of implemented systems designed to address the concerns and problems faced by many students. Based on this perspective, a systematic mapping of the literature on AI-enabled adaptive learning systems was performed in this work. A total of 147 studies published between 2014 and 2020 were analysed. The major findings and contributions of this paper include the identification of the types of AI-enabled learning interventions used, a visualisation of the co-occurrences of authors associated with major research themes in AI-enabled learning systems and a review of common analytical methods and related techniques utilised in such learning systems. This mapping can serve as a guide for future studies on how to better design AI-enabled learning systems to solve specific learning problems and improve usersโ€™ learning experiences.publishedVersio
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