2023 article

Machine-Generated Questions Attract InstructorsWhen Acquainted with Learning Objectives

ARTIFICIAL INTELLIGENCE IN EDUCATION, AIED 2023, Vol. 13916, pp. 3–15.

By: M. Shimmei n, N. Bier* & N. Matsuda n

author keywords: Question Generation; MOOCS; Learning Engineering
UN Sustainable Development Goal Categories
4. Quality Education (OpenAlex)
Sources: ORCID, Web Of Science, NC State University Libraries
Added: June 26, 2023

2021 article

Learning Association Between Learning Objectives and Key Concepts to Generate Pedagogically Valuable Questions

ARTIFICIAL INTELLIGENCE IN EDUCATION (AIED 2021), PT II, Vol. 12749, pp. 320–324.

By: M. Shimmei n & N. Matsuda n

author keywords: Question generation; MOOCS; Learning engineering
TL;DR: The results from the survey using Amazon Mechanical Turk suggest that the QUADL method can be a step towards generating questions that effectively contribute to students’ learning. (via Semantic Scholar)
Sources: ORCID, Web Of Science, NC State University Libraries
Added: October 13, 2021

2019 article

Evidence-Based Recommendation for Content Improvement Using Reinforcement Learning

ARTIFICIAL INTELLIGENCE IN EDUCATION, AIED 2019, PT II, Vol. 11626, pp. 369–373.

By: M. Shimmei n & N. Matsuda n

Contributors: M. Shimmei n & N. Matsuda n

author keywords: Learning-engineering; Self-improving online courseware; Reinforcement learning
TL;DR: An evidence-based learning-engineering method for validating the quality of instructional elements on online courseware is proposed and can detect more than a half of the ineffective educational elements on three types of courseware containing various ratios of ineffective instructional elements. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (Web of Science; OpenAlex)
Sources: Web Of Science, NC State University Libraries, ORCID
Added: December 2, 2019

Education

Updated: June 8th, 2020 08:52

2018 - present

North Carolina State University Raleigh, NC, US
Computer Science

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