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Integrating Instant Response System (IRS) as an In-Class Assessment Tool into Undergraduate Chemistry Learning Experience: Student Perceptions and Performance

  • Tzy-Ling Chen
  • Yan-Fu Lin
  • Yi-Lin Liu
  • Hsiu-Ping Yueh
  • Horn-Jiunn Sheen
  • Wei-Jane Lin
Chapter

Abstract

Since being introduced nearly a decade ago, the use of instant response systems (IRS) (also referred to as a “clicker”) has been extensively adopted on college campuses, and is particularly popular among instructors of large lecture classes. The available evidence supports that IRS offers a promising avenue for future developments in pedagogy, though findings on advantages of effective use of IRS in relation to improving or enhancing student learning are inconclusive. Considering this unique attribute of IRS, the main purpose of the present study aims to examine the degree to which students perceive or believe that using IRS in class has an effect on their understanding of course content, engagement in classroom learning, and preparation to take class tests. Moreover, multiple student performance evaluation results are used to explore correlations between student perceptions of IRS and their actual learning outcomes. This chapter presents 151 undergraduate students’ learning experiences of a basic chemistry class incorporating IRS as an in-class assessment tool at National Chung Hsing University in Taiwan. Based on research findings, overall student perceptions on the use of IRS in class were positive. In addition, certain interactions between students’ perceptions on IRS use and their performance in learning basic chemistry were identified in the present study. Although students’ perceived benefits and effectiveness of IRS use are revealed, the research indicates that further studies are needed to probe what specifically about the use of IRS contributes to certain learning outcomes of a large chemistry class in higher education.

Keywords

Instructional Design Student Perception Classroom Learning Test Tool Interactive Technology 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Tzy-Ling Chen
    • 1
  • Yan-Fu Lin
    • 2
  • Yi-Lin Liu
    • 3
  • Hsiu-Ping Yueh
    • 3
  • Horn-Jiunn Sheen
    • 4
  • Wei-Jane Lin
    • 5
  1. 1.Graduate Institute of Bio-Industry ManagementNational Chung Hsing UniversityTaichungRepublic of China
  2. 2.Department of ChemistryNational Chung Hsing UniversityTaichungRepublic of China
  3. 3.Department of Bio-Industry Communication and DevelopmentNational Taiwan UniversityTaipeiRepublic of China
  4. 4.Institute of Applied MechanicsNational Taiwan UniversityTaipeiRepublic of China
  5. 5.Department of Library and Information ScienceNational Taiwan UniversityTaipeiRepublic of China

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