Computer-Based vs Modular Based-Learning: Motivation on the Academic Performance in Araling Panlipunan among Grade 10 Students

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{"abstract":"This study was conducted to determine the effects of two teaching methods namely, computer-based learning and modular-based learning as motivation in teaching the least mastered competencies in Araling Panlipunan among Grade 10 students in one of the Junior High Schools in Zamboanga City. Quasi-experimental research using the non-randomized pre-test - post-test control group design explored the effectiveness of the two teaching methods. The findings indicated that students in Computer-Based Instruction and Modular-Based Instruction obtained higher scores in the post-test than the pre-test. But the experimental group got slightly higher mean scores as compared to those students who have been taught in the modular-based instruction. However, statistically, no significant difference was found between the two methods. This further indicates that that the students who were exposed to Computer-Based Learning and Modular-Based Learning improved in their level of knowledge in mastering the least learned concepts in Araling Panlipunan. This study revealed that whatever method or approach used as motivation to learn the least mastered competencies in the Grade 10 Araling Panlipunan, be it in Computer-Based Learning and Modular-Based Learning, can be considered effective in achieving life-long and meaningful learning amidst the global pandemic.","abstract_source":"original","authors":["Babe Aubrey Patricio-Lim","Renz Jervy Book"],"date":"2022-12-19","doi":"10.5281/zenodo.7458246","id":879,"issue":4,"journal":{"issn":"2822-4353","name":"Psychology and Education: A Multidisciplinary Journal"},"pdf_sha256":"d6eb0b31f6f6855d6c616059f92791cf079d739a3b601392c6631281653cfa89","schema":"scimatic-article/1","title":"Computer-Based vs Modular Based-Learning: Motivation on the Academic Performance in Araling Panlipunan among Grade 10 Students","volume":6}

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printf '%s' "$(curl -s https://scimatic.org/nft/articles/879.json | jq -r .canonical_record)" | sha256sum

2. The hash stored on chain (contentHash(879)):

curl -s https://rpc.scimatic.net -H 'content-type: application/json' \
  -d '{"jsonrpc":"2.0","id":1,"method":"eth_call","params":[{"to":"0x0E596B4bb924937aA35D9b342A90347ed6F05eF8","data":"0xf3e0c290000000000000000000000000000000000000000000000000000000000000036f"},"latest"]}'

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