An AI-based Solution for Enhancing Delivery of Digital Learning for Future Teachers
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 teachin...
Gespeichert in:
Hauptverfasser: | , , , , , , , |
---|---|
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | 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 extremely time consuming. In the paper, we
propose an Artificial Intelligence (AI)-based solution namely VidVersityQG for
generating questions automatically from pre-recorded video lectures. The
solution can automatically generate different types of assessment questions
(including short answer, multiple choice, true/false and fill in the blank
questions) based on contextual and semantic information inferred from the
videos. The proposed solution takes a human-centred approach, wherein teachers
are provided the ability to modify/edit any AI generated questions. This
approach encourages trust and engagement of teachers in the use and
implementation of AI in education. The AI-based solution was evaluated for its
accuracy in generating questions by 7 experienced teaching professionals and
117 education videos from multiple domains provided to us by our industry
partner VidVersity. VidVersityQG solution showed promising results in
generating high-quality questions automatically from video thereby
significantly reducing the time and effort for educators in manual question
generation. |
---|---|
DOI: | 10.48550/arxiv.2112.01229 |