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Metacognition and Peer Learning Strategies as Predictors in Problem-Solving Performance in Microbiology †
Journal of Microbiology & Biology Education Pub Date : 2020-02-28 , DOI: 10.1128/jmbe.v21i1.1715
Josephine Itota Ebomoyi 1
Affiliation  

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.

中文翻译:

元认知和同伴学习策略作为解决微生物学问题表现的指标†

这项研究的目的是确定微生物学中学习策略(LS)和问题解决(PS)之间的关系。研究中使用的微生物学问题来自称为“交互式多媒体练习”(IMMEX)的教育软件。测量的解决问题的能力包括:解决能力,获得的分数和经过的时间。假设学生的LS和PS之间存在良好的相关性。由于除学习策略之外的许多因素都可以预测绩效,因此alpha设置为0.10。参与者(N = 65)解决了两套微生物学问题,“ Microquest”(Mq)主要研究微生物的细胞过程和抗生素的作用方式,“ Creeping crud”(Cc)主要研究原因,起源和疾病传播。参与者还使用五点李克特量表对改编的动机策略学习调查表(MSLQ)做出了回应。LS得分是通过平均参与者的项目反应来确定的。回归分析用于确定显着性,以平均绩点(GPA)为对照。在65位参与者中,有48位(73.8%)成功解决了Mq,而52位(80%)解决了Cc。元认知自我调节策略与解决Cc能力显着相关(p <0.10)。同伴学习策略显示与Cc得分有显着(p <0.10)关系。解决Cc所花费的时间明显多于Mq(p <0.001)。这些发现强调了一个事实,即元认知和同伴学习是解决问题的积极预测者,并可能改善微生物学的学习成果。
更新日期:2020-02-28
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