Optimizing an immersion ESL curriculum using analytic hierarchy process
Hui-Wen Vivian Tang
Evaluation and Program Planning, 2011, vol. 34, issue 4, 343-352
Abstract:
The main purpose of this study is to fill a substantial knowledge gap regarding reaching a uniform group decision in English curriculum design and planning. A comprehensive content-based course criterion model extracted from existing literature and expert opinions was developed. Analytical hierarchy process (AHP) was used to identify the relative importance of course criteria for the purpose of tailoring an optimal one-week immersion English as a second language (ESL) curriculum for elementary school students in a suburban county of Taiwan. The hierarchy model and AHP analysis utilized in the present study will be useful for resolving several important multi-criteria decision-making issues in planning and evaluating ESL programs. This study also offers valuable insights and provides a basis for further research in customizing ESL curriculum models for different student populations with distinct learning needs, goals, and socioeconomic backgrounds.
Keywords: Analytic; hierarchy; process; Delphi; method; Multi-criteria; decision-making; Consistency; ratio; Immersion; ESL; program (search for similar items in EconPapers)
Date: 2011
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0149718911000449
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:epplan:v:34:y:2011:i:4:p:343-352
Access Statistics for this article
Evaluation and Program Planning is currently edited by Jonathan A. Morell
More articles in Evaluation and Program Planning from Elsevier
Bibliographic data for series maintained by Catherine Liu ().