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AI in Assessment: Review of AI Possibilities 

By the ETD XLABs e-Assessment Research Group 

Ms Jean Phua, Lead Specialist, Technologies for Learning (TfL), ETD 

Mr Lawrence Wee Loo Kang, Lead Specialist, TfL, ETD 

Dr Suryani Bte Atan, Senior Specialist, TfL, ETD (on secondment to NIE wef July 2020) 

led by Area Lead and Chief of ETD XLabs Mr Chia Hai Siang, Lead Specialist, TfL, ETD


2020 MOE Professional Forum for Research and Practice

Symposia

Technology-enabled Assessment: Now and Next

07 Oct 2020 1425 – 1540

Synopsis

Artificial Intelligence (AI) is the capability of computational technologies to mimic human action and thought. AI has risen as a disruptive technology in recent years. MOE is leading three use cases (Adaptive Learning, Automated Assessment, Learning Companion) under the National AI Strategy to engage AI to achieve personalised education through adaptive learning and assessment.

e-Assessment is the application of computers to assessment processes, including delivery of tests, capture of responses and marking by either computer or human marker (Davies, 2010). In e-Assessment systems, the most common stages are e-Authoring, e-Delivery, e-Scoring, and e-Reporting.
This presentation aims to provide
  1.   a literature scan of how AI technologies can support the different e-assessment stages; 
  2.   an evaluation of the readiness of AI technologies to be applied in the e-assessment stages.

The presentation summarises how AI can enhance e-assessment practices. A variety of proposed solutions are evaluated, for MOE/ETD to consider for implementation with projected timeframe, and allocate R&D efforts. Some areas of interest include the use of Natural Language Processing (NLP) to generate comprehension questions. Input methods such as text to speech , and handwriting to text , although not directly related to AI applications to the e-assessment stages, do have potential in improving students’ e-assessment experiences. A demonstration of existing AI technologies that can already be easily harnessed by students and teachers, such as speech to text, and handwriting to text, will be presented. The presentation serves to inform current and planned MOE/ETD AI-enhanced technology explorations, with the intent to help teachers better customise students’ learning experiences, and suggest possibilities to uplift teachers’ productivity.

Davies, S. (2010). Effective Assessment in a Digital Age. JISC publication.


 

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