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Causal complexities to evaluate the effectiveness of remedial instruction

Author

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  • Dai, Chien-Yun
  • Huang, Duen-Huang

Abstract

This study investigates 3 models of remedial instruction, e-learning, blended learning, and traditional instruction, to vocational high school students with low mathematics achievement to analyze whether student achievement improves significantly and how each instruction model facilitates improvement. This study applies partial least squares (PLS) and fuzzy set/Qualitative Comparative Analysis (fsQCA) to analyze the effectiveness and causal complexities of the 3 models. The results indicate that all 3 models facilitate substantial academic progress, the e-learning model being the most effective. The combinations of 6 negative antecedents cause the learning problems of the students. After the changes of a few of these antecedents through the use of remedial instruction, the students improve their scores. FsQCA provides antecedent combinations to show the causal complexities; hence, provides more accurate explanations than does the PLS.

Suggested Citation

  • Dai, Chien-Yun & Huang, Duen-Huang, 2015. "Causal complexities to evaluate the effectiveness of remedial instruction," Journal of Business Research, Elsevier, vol. 68(4), pages 894-899.
  • Handle: RePEc:eee:jbrese:v:68:y:2015:i:4:p:894-899
    DOI: 10.1016/j.jbusres.2014.11.048
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    References listed on IDEAS

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    1. Woodside, Arch G., 2012. "Incompetency training: Theory, practice, and remedies," Journal of Business Research, Elsevier, vol. 65(3), pages 279-293.
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    Cited by:

    1. Paulo Ferreira & Andreia Dionísio, 2016. "Entrepreneurship rates: the fuzzy-set approach," Eastern European Business and Economics Journal, Eastern European Business and Economics Studies Centre, vol. 2(2), pages 111-128.
    2. Coduras, Alicia & Clemente, José Antonio & Ruiz, Jesús, 2016. "A novel application of fuzzy-set qualitative comparative analysis to GEM data," Journal of Business Research, Elsevier, vol. 69(4), pages 1265-1270.
    3. Sascha Kraus & Domingo Ribeiro-Soriano & Miriam Schüssler, 2018. "Fuzzy-set qualitative comparative analysis (fsQCA) in entrepreneurship and innovation research – the rise of a method," International Entrepreneurship and Management Journal, Springer, vol. 14(1), pages 15-33, March.

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