Metacognition and Peer Learning Strategies as Predictors in Problem-Solving Performance in Microbiology

The objective of this study was to determine the relationship between learning strategies (LS) and problem solving (PS) in microbiology. Microbiology problems utilized for the study were from educational software known as “Interactive Multimedia Exercises” (IMMEX). Problem-solving performances measu...

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Autor principal:	Josephine Itota Ebomoyi
Formato:	article
Lenguaje:	EN
Publicado:	American Society for Microbiology 2020
Materias:	Special aspects of education LC8-6691 Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/04abcae539574bb9980f40bfde7312cb
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spelling	oai:doaj.org-article:04abcae539574bb9980f40bfde7312cb2021-11-15T15:04:42ZMetacognition and Peer Learning Strategies as Predictors in Problem-Solving Performance in Microbiology10.1128/jmbe.v21i1.17151935-78851935-7877https://doaj.org/article/04abcae539574bb9980f40bfde7312cb2020-01-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/jmbe.v21i1.1715https://doaj.org/toc/1935-7877https://doaj.org/toc/1935-7885The objective of this study was to determine the relationship between learning strategies (LS) and problem solving (PS) in microbiology. Microbiology problems utilized for the study were from educational software known as “Interactive Multimedia Exercises” (IMMEX). Problem-solving performances measured included: the ability to solve, scores obtained and elapsed time. It was hypothesized that there would be a good correlation between students’ LS and PS. Since many factors besides learning strategies predict performance, alpha was set at 0.10. Participants (N = 65) solved two sets of microbiology problems “Microquest” (Mq), which focuses on microbial cellular processes and mode of action of antibiotics, and “Creeping crud” (Cc), which focuses on the cause, origin, and transmission of diseases. Participants also responded to the adapted Motivated Strategy Learning Questionnaire (MSLQ) using a five-point Likert scale. Scores for LS were determined by averaging the item responses of participants. Regression analysis was used to determine significance, with Grade Point Average (GPA) as a control. Of the 65 participants 48 (73.8%) successfully solved Mq while 52 (80%) solved Cc. Metacognitive self-regulated strategy was significantly (p < 0.10) related to ability to solve Cc. Peer learning strategy showed a significant (p < 0.10) relationship with Cc scores. Time spent solving Cc was significantly more than time spent on Mq (p < 0.001). These findings emphasize the fact that metacognition and peer learning are positive predictors for problem solving and could potentially improve learning outcomes in microbiology. The implications for curriculum development are discussed.Josephine Itota EbomoyiAmerican Society for MicrobiologyarticleSpecial aspects of educationLC8-6691Biology (General)QH301-705.5ENJournal of Microbiology & Biology Education, Vol 21, Iss 1 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Special aspects of education LC8-6691 Biology (General) QH301-705.5
spellingShingle	Special aspects of education LC8-6691 Biology (General) QH301-705.5 Josephine Itota Ebomoyi Metacognition and Peer Learning Strategies as Predictors in Problem-Solving Performance in Microbiology
description	The objective of this study was to determine the relationship between learning strategies (LS) and problem solving (PS) in microbiology. Microbiology problems utilized for the study were from educational software known as “Interactive Multimedia Exercises” (IMMEX). Problem-solving performances measured included: the ability to solve, scores obtained and elapsed time. It was hypothesized that there would be a good correlation between students’ LS and PS. Since many factors besides learning strategies predict performance, alpha was set at 0.10. Participants (N = 65) solved two sets of microbiology problems “Microquest” (Mq), which focuses on microbial cellular processes and mode of action of antibiotics, and “Creeping crud” (Cc), which focuses on the cause, origin, and transmission of diseases. Participants also responded to the adapted Motivated Strategy Learning Questionnaire (MSLQ) using a five-point Likert scale. Scores for LS were determined by averaging the item responses of participants. Regression analysis was used to determine significance, with Grade Point Average (GPA) as a control. Of the 65 participants 48 (73.8%) successfully solved Mq while 52 (80%) solved Cc. Metacognitive self-regulated strategy was significantly (p < 0.10) related to ability to solve Cc. Peer learning strategy showed a significant (p < 0.10) relationship with Cc scores. Time spent solving Cc was significantly more than time spent on Mq (p < 0.001). These findings emphasize the fact that metacognition and peer learning are positive predictors for problem solving and could potentially improve learning outcomes in microbiology. The implications for curriculum development are discussed.
format	article
author	Josephine Itota Ebomoyi
author_facet	Josephine Itota Ebomoyi
author_sort	Josephine Itota Ebomoyi
title	Metacognition and Peer Learning Strategies as Predictors in Problem-Solving Performance in Microbiology
title_short	Metacognition and Peer Learning Strategies as Predictors in Problem-Solving Performance in Microbiology
title_full	Metacognition and Peer Learning Strategies as Predictors in Problem-Solving Performance in Microbiology
title_fullStr	Metacognition and Peer Learning Strategies as Predictors in Problem-Solving Performance in Microbiology
title_full_unstemmed	Metacognition and Peer Learning Strategies as Predictors in Problem-Solving Performance in Microbiology
title_sort	metacognition and peer learning strategies as predictors in problem-solving performance in microbiology
publisher	American Society for Microbiology
publishDate	2020
url	https://doaj.org/article/04abcae539574bb9980f40bfde7312cb
work_keys_str_mv	AT josephineitotaebomoyi metacognitionandpeerlearningstrategiesaspredictorsinproblemsolvingperformanceinmicrobiology
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Metacognition and Peer Learning Strategies as Predictors in Problem-Solving Performance in Microbiology

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