Multicriteria analysis for the evaluation and benchmarking of english language mobile apps for young learners
This study aimed to construct an evaluation and benchmarking Decision Matrix (DM)based on multi-criteria analysis for English mobile applications (E-apps) for younglearners in terms of Listening, Speaking, Reading, and Writing (LSRW) skills. The DM wasconstructed based on the intersection between ev...
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| Format: | thesis |
| Language: | eng |
| Published: |
2019
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| Subjects: | |
| Online Access: | https://ir.upsi.edu.my/detailsg.php?det=6635 |
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| Summary: | This study aimed to construct an evaluation and benchmarking Decision Matrix (DM)based on multi-criteria analysis for English mobile applications (E-apps) for younglearners in terms of Listening, Speaking, Reading, and Writing (LSRW) skills. The DM wasconstructed based on the intersection between evaluation criteria in terms of LSRW and E-apps foryoung learners. The criteria were adopted from a preschool education curriculum knownas the National Preschool Standard Curriculum 2016 standard. The data presented as theDM include six E-apps as alternatives and 17 skills as criteria. Thereafter, the sixE-apps were evaluated by distributing a checklist form amongst three English learning lecturers inearly childhood learning department from local university in Perak. These apps were thenbenchmarked by utilising two experimental MCDM methods, namely, bestworst method (BWM) andTechnique for Order of Preference by Similarity to Ideal Solution (TOPSIS). BWM is used forweighting the evaluation criteria, whereas TOPSIS is used to benchmark the apps andrank them from best to worst. TOPSIS was utilized in two decision-making contexts,namely individual and group contexts. In group decision making, internal and external groupaggregations are applied. For validating the proposed DM, objective and subjective methods wereused. The results showed that (1) the integration of BWM and TOPSIS was effective forsolving benchmarking and ranking problems of E-apps. (2) The ranks of E-apps obtained from internaland external TOPSIS group decision making were the same, with the first index app beingMontessori and the last index app being FunWithFlupe. (3) For objective validation,remarkable differences were observed between the group scores, and they indicated that the internal and external ranking results are identical.(4) For subjective validation,the ranking of experts was exactly similar to the proposed benchmarking DM rankingresults. As conclusion, the proposed DM can be used for evaluation and benchmarkingdifferent E-apps. The implications of this study will benefit(1) English language teachers/designers for understanding how English course contentshould be presented; (2) parents for screening and choosing suitable and reliable English learningapps that will help their children; and (3) kindergarten teachers for choosing anappropriate English app. |
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