Smartphones as smart pedagogical tools: Implications for smartphones as u-learning devices

  • Authors:

  • Dong-Hee Shin;Youn-Joo Shin;Hyunseung Choo;Khisu Beom

  • Affiliations:

  • Department of Interaction Science, Sungkyunkwan University, 90327 International Hall, 53 Myeongnyun-dong 3-ga, Jongno-gu, Seoul 110-745, South Korea;Department of Interaction Science, Sungkyunkwan University, 90327 International Hall, 53 Myeongnyun-dong 3-ga, Jongno-gu, Seoul 110-745, South Korea;Department of Electrical and Computer Engineering, Sungkyunkwan University, 90327 International Hall, 53 Myeongnyun-dong 3-ga, Jongno-gu, Seoul 110-745, South Korea;Department of Journalism and Mass Comm, Sungkyunkwan University, 90327 International Hall, 53 Myeongnyun-dong 3-ga, Jongno-gu, Seoul 110-745, South Korea

  • Venue:
  • Computers in Human Behavior
  • Year:
  • 2011

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Abstract

This study aims at understanding the fundamental factors influencing users' intentions to continually use smartphones as a ubiquitous learning (u-learning) tool. This study examines consumers' experiences with smartphone learning in order to investigate the areas of its development as a u-learning application. In this paper, the modified unified theory of acceptance and usage technology (UTAUT) model is used with constructs from expectation-confirmation theory (ECT). While the findings confirm the significant roles of users' cognitive perceptions, the findings also shed light on the possibility of the smartphone serving as an enabler of u-learning. Users may want to use the smartphone as a telecommunication tool, as well as a u-learning application. The proposed model brings together extant research on smartphones and provides an important cluster of antecedents to eventual technology acceptance via constructs of continuance intention to use and actual usage of u-learning. The empirical findings demonstrate that employing perceived usability and perceived quality would be a worthwhile extension of the UTAUT/ECT in the smartphone learning context, as both were found to be influential in predicting smartphone users' attitudes and behavioral intentions. Practical implications for industry can be drawn from these findings in terms of strategies and new models for u-learning and beyond.