Cognancy Patterns in Maguindanaon and English: A Comparative Lexicological Study

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{"abstract":"This study examines the comparative lexicology of Maguindanaon and English, with a focus on cognates, analyzing how true cognates and false cognates influence vocabulary learning. Using a qualitative, corpus-based contrastive methodology, bilingual dictionaries, classroom materials, and teacher consultations were employed to compile and annotate a dataset of word pairs. Findings reveal three primary categories of true cognates: phonologically adapted forms (e.g., radio → radyo), Spanish-mediated borrowings (e.g., office → opisina), and direct borrowings (e.g., bus → bus). These cognates retain semantic and lexical equivalence, functioning as scaffolding tools for learners. Conversely, false cognates, such as \"eye–ay\" (\"eye–foot\") and \"book–buk\" (\"book–hair\"), demonstrate phonological similarity but semantic and categorical divergence, leading to potential misinterpretation. Results underscore the dual role of cognates: while true cognates reduce cognitive load and accelerate acquisition, false cognates risk fossilizing learner errors. The study concludes that vocabulary instruction must strategically balance these dynamics by leveraging true cognates and explicitly addressing false ones.","abstract_source":"original","authors":["Ivan Barroga","Danilo Baradillo"],"date":"2025-10-13","doi":"10.70838/pemj.480102","id":6538,"issue":1,"journal":{"issn":"2822-4353","name":"Psychology and Education: A Multidisciplinary Journal"},"pdf_sha256":"8c534791eb401a7215411c451a36e916897e4cfc206d3b6bc73ea2c4e8843bc1","schema":"scimatic-article/1","title":"Cognancy Patterns in Maguindanaon and English: A Comparative Lexicological Study","volume":48}

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printf '%s' "$(curl -s https://scimatic.org/nft/articles/6538.json | jq -r .canonical_record)" | sha256sum

2. The hash stored on chain (contentHash(6538)):

curl -s https://rpc.scimatic.net -H 'content-type: application/json' \
  -d '{"jsonrpc":"2.0","id":1,"method":"eth_call","params":[{"to":"0x0E596B4bb924937aA35D9b342A90347ed6F05eF8","data":"0xf3e0c290000000000000000000000000000000000000000000000000000000000000198a"},"latest"]}'

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