Effect Of Differentiated Instructional Strategy on Students’ Time Management and Achievement in Qualitative Chemical Analysis

Abstract

The ability of individuals to manage time in any organization is essential for quality output. To foster students’ achievement through a procedure that considers their learning style differences and take cognizance of time management. Hence, this study investigated effect of differentiated instructional strategy on students’ time management and achievement in qualitative chemical analysis. The study was conducted in Onitsha Education zone of Anambra State. Four research questions and four hypotheses were formulated to guide the study. The study adopted quasi-experimental research design. The population of the study comprised 1023 SS2 Chemistry students from 15 co-educational Senior Secondary Schools in the zone. Four schools were randomly sampled from the zone for the study. A sample of 124 SS 11 Chemistry students was used for the study which comprised 56 males and 68 females Chemistry students. Two instruments that were used for data collection are Qualitative Analysis Achievement Test (QAAT) and Time Management Rating Scale (TMRS). Qualitative Analysis Achievement Test (QAAT) consisted of practical item questions culled from past WAEC and NECO Chemistry questions. Time Management Rating Scale (TMRS) consisted of 25 items developed by the researcher. The reliability coefficient for QAAT was 0.74 using Kuder-Richardson Formula 20(KR-20). The instruments were trial tested using 20 students from Aguata Education Zone. The reliability coefficient for TMRS was 0.60 using Cronbach’s Alpha. Regular Chemistry teachers from each of the sampled schools who participated in the training by the researcher were used for the study. A pretest was issued to the participating students before the experiment. The experiment lasted for four weeks after which a post-test was administered. The data that were obtained were analysed using mean and standard deviation to answer the research questions and Analysis of Covariance (ANCOVA) was used to t

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