• Corpus ID: 244799414

An AI-based Solution for Enhancing Delivery of Digital Learning for Future Teachers

  title={An AI-based Solution for Enhancing Delivery of Digital Learning for Future Teachers},
  author={Yong-Bin Kang and Abdur Rahim Mohammad Forkan and Prem Prakash Jayaraman and Natalie Wieland and Elizabeth Kollias and Hung Du and Steven Thomson and Yuan-Fang Li},
There has been a recent and rapid shift to digital learning hastened by the pandemic but also influenced by ubiquitous availability of digital tools and platforms now, making digital learning ever more accessible. An integral and one of the most difficult part of scaling digital learning and teaching is to be able to assess learner’s knowledge and competency. An educator can record a lecture or create digital content that can be delivered to thousands of learners but assessing learners is… 



Artificial intelligence for education: Knowledge and its assessment in AI-enabled learning ecologies

The key finding is that artificial intelligence—in the context of the practices of electronic computing developing over the past three quarters of a century—will never in any sense “take over” the role of teacher, because how it works and what it does are so profoundly different from human intelligence.

Automatic Question Generation for Repeated Testing to Improve Student Learning Outcome

An automatic question generation (AQG) system that combines syntax-base and semantics-base is proposed that will help teachers use machines to automatically generate short answer questions to reduce the time for teachers to write exam questions.

A Systematic Review of Automatic Question Generation for Educational Purposes

There is little focus in the current literature on generating questions of controlled difficulty, enriching question forms and structures, automating template construction, improving presentation, and generating feedback, and the need to further improve experimental reporting, harmonise evaluation metrics, and investigate other evaluation methods that are more feasible.

QG-net: a data-driven question generation model for educational content

QG-Net, a recurrent neural network-based model specifically designed for automatically generating quiz questions from educational content such as textbooks, is introduced and outperforms state-of-the-art neuralNetwork-based and rules-based systems for question generation.

Automatic question generation and answer assessment: a survey

The purpose of this survey is to summarize the state-of-the-art techniques for generating questions and evaluating their answers automatically and to present a survey of automatic question generation and assessment strategies from textual and pictorial learning resources.

Human-centered artificial intelligence in education: Seeing the invisible through the visible

Adoption of artificial intelligence in higher education: a quantitative analysis using structural equation modelling

It has been found that the model can help the authorities to facilitate adoption of AI in higher education and taken help of many adoption theories and models including ‘Unified Theory of Acceptance and Use of Technology’ (UTAUT) model.

Digital higher education: a divider or bridge builder? Leadership perspectives on edtech in a COVID-19 reality

This sequential mixed-method approach investigated how 85 higher education leaders in 24 countries experienced this rapid digital transformation, and identified the multiple and overlapping factors that contribute to an institution’s ability to realize the potential of digital education.

Motivating and Engaging Students Using Educational Technologies

  • Brett D. Jones
  • Education
    Handbook of Research in Educational Communications and Technology
  • 2020
The aim of this chapter is to examine learners’ motivation and engagement in educational settings, with a focus on educational technologies. This chapter is intended to serve a variety of audiences,

Automatic Multiple Choice Question Generation From Text: A Survey

  • D. ChS. Saha
  • Business
    IEEE Transactions on Learning Technologies
  • 2020
A generic workflow for an automatic MCQ generation system is outlined and the list of techniques adopted in the literature is discussed, including the evaluation techniques for assessing the quality of the system generated MCQs.