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author:

Lin, Yi (Lin, Yi.) [1] (Scholars:林一) | Lan, Yangfan (Lan, Yangfan.) [2] | Wang, Shunbo (Wang, Shunbo.) [3]

Indexed by:

EI Scopus SCIE

Abstract:

In education, learning concentration is closely related to the quality of learning, and teachers can adjust their teaching methods accordingly to improve the learning outcomes of students. Particularly in head-mounted virtual reality interactions, current methods for assessing learning concentration cannot be fully applied to new interactive environments because immersion shaping and cognitive formation differ from the conventional education. Therefore, in this study, a learning concentration assessment method is proposed to measure the learning concentration of students in head-mounted virtual interaction, using the expression score, visual focus rate, and task mastery as evaluation indicators. In addition, the weights of the evaluation indicators can be configured to be included in the calculation of learning concentration depending on the characteristics of different types of courses. The results of a usability evaluation indicate that the learning concentration of students can be effectively evaluated using the proposed method. By developing and implementing strategies for optimizing learning effects, the learning concentration and assessment scores of students increased by 18% and 15.39%, respectively.

Keyword:

Head-mounted virtual reality interaction Learning concentration Virtual reality education Weight configuration

Community:

  • [ 1 ] [Lin, Yi]Fuzhou Univ, Coll Phys & Informat Engn, Fuzhou 350018, Peoples R China
  • [ 2 ] [Lan, Yangfan]Fuzhou Univ, Coll Phys & Informat Engn, Fuzhou 350018, Peoples R China
  • [ 3 ] [Wang, Shunbo]Fuzhou Univ, Coll Phys & Informat Engn, Fuzhou 350018, Peoples R China

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Source :

VIRTUAL REALITY

ISSN: 1359-4338

Year: 2022

Issue: 2

Volume: 27

Page: 863-885

4 . 2

JCR@2022

4 . 4 0 0

JCR@2023

ESI Discipline: COMPUTER SCIENCE;

ESI HC Threshold:61

JCR Journal Grade:1

CAS Journal Grade:3

Cited Count:

WoS CC Cited Count: 6

SCOPUS Cited Count: 8

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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