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Which types of learners are suitable for augmented reality? A fuzzy set analysis of learning outcomes configurations from the perspective of individual differences

Abstract

Considering the individual differences in previous content knowledge, skill, and attitude, which types of learners are suitable for AR is a valuable but complex question. The study used quasi-experimental design, and divided 97 10th-grade students into two groups: traditional group (N = 48) and AR group (N = 49), who participated in 4-week organic microstructure teaching. Pre-test, post-test, delayed test, and remedy test were used to collect data of students’ individual differences (foundation of learning in chemistry, spatial ability, and attitude towards AR) and learning (immediate and lasting) outcomes. Whether AR is used or not and three individual differences were taken as causal conditions, which jointly influence the learning outcomes. FsQCA was used to deal with the non-linear and asymmetric relationship among the causal conditions, and to obtain the configurations of good or poor learning outcomes. The results show that, (i) using AR usually contributes to a sufficient configuration of good learning outcomes, (ii) especially is beneficial to lasting learning outcomes, (iii) but it is still not the necessary condition, and (iv) using AR by some types of students causes poor outcomes instead. Which types of students are suitable or not suitable to use AR is also be discussed. The study emphasizes the importance of personalized use of educational technology.

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Notes

  1. 1.

    In this study, we take consistency0.9 as sufficiency; and take 0.8consistency < 0.9 as quasi-sufficiency.

  2. 2.

    In the first category, the outcomes do not change: Whether learning is with/without AR aids, the learning outcomes are the same (may be good, poor, or not sure). In the second category, learning with AR aids is conducive to good outcomes: learning with AR aids can cause good outcomes sufficiently, while learning without AR aids does not necessarily or sufficiently cause poor outcomes; Or learning with AR aids can only cause uncertain outcomes, while learning without AR aids can cause poor outcomes sufficiently. In the third category, learning without AR aids is conducive to good outcome: it is symmetric with the second category.

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Acknowledgements

The authors thank 97 students who volunteered to participate in this study.

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YL and PZ are co-first authors.

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Correspondence to Yizhou Ling.

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Appendices

Appendix A

Terms, meanings, and examples of set theory involved in this study are listed in Table A1 (Li, 2020; Rihoux & Ragin, 2017).

Table A1 Terms, meanings, and examples of set theory

Appendix B

Related to causal conditions/outcomes are listed in Table A2, including variables, causal conditions/outcomes, and the corresponding data collection methods.

Table A2 Variables, causal conditions/outcomes, and the corresponding data collection methods

Appendix C

CMPT and CMDT were developed according the requirements of parallel tests. Part of sample questions in CMPT and CMDT are listed in Appendix Table A3.

Table A3 Part of sample questions in CMPT and CMDT

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Ling, Y., Zhu, P. & Yu, J. Which types of learners are suitable for augmented reality? A fuzzy set analysis of learning outcomes configurations from the perspective of individual differences. Education Tech Research Dev 69, 2985–3008 (2021). https://doi.org/10.1007/s11423-021-10050-3

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Keywords

  • Augmented reality
  • Individual difference
  • Learning outcomes
  • Qualitative comparative analysis