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dc.contributor.author Wakhata, Robert
dc.contributor.authorMutarutinya, Védaste
dc.contributor.authorBalimuttajjo, Sudi
dc.date.accessioned2024-04-09T12:26:50Z
dc.date.available2024-04-09T12:26:50Z
dc.date.issued2023
dc.identifier.citationWakhata, R., Mutarutinya, V., & Balimuttajjo, S. (2023, April). Exploring the impact of Stein et al.’s levels of cognitive demand in supporting students’ mathematics heuristic problem-solving abilities. In Frontiers in Education (Vol. 8, p. 949988). Frontiers Media SA.en_US
dc.identifier.urihttp://ir.must.ac.ug/xmlui/handle/123456789/3557
dc.description.abstractThe present study explored the impact of Stein et al.’s levels of cognitive demand (LCD) on evaluation and instructional methods in applying the knowledge of equations and inequalities to learn the topic of linear programming (LP). The framework provided by Stein et al. was used to map students’ LP cognitive demands. Students’ specific proficiency levels in solving LP tasks using Stein et al.’s LCD hierarchical framework were investigated. A mixed-method approach with a pre-test and post-test pre-intervention pilot study involving a non-equivalent control group design was applied. The participants were 175 grade 11 students from Mbale district, eastern Uganda. Two pre-interventional LP tests (pre-test and post-test) were administered to the students to examine their cognitive demands. This was followed by an intervention involving application of Stein et al.’s LCD in learning LP. The results showed that before pre-intervention, the performance of urban school’s average post-test scores was higher than that of the rural school. Students from the rural secondary school improved greatly relative to their peers from the urban school. Moreover, only 25.1% of students performed at the highest level of Stein et al.’s LCD (doing mathematics). The post-test scores were better relative to the pre-test (M = 56.51 ± 20.88 vs. 42.23 ± 22.49; p < 0.05). Overall, there was a statistically significant difference between students’ average grades in the pre-interventional pre-test and the post-test (Cohen’s d = 0.81 > 0.5), 95% CI [−18.00, −10.56]). Holding other factors constant, the significant differences in students’ scores were mainly due to the application of suitable tasks which were later mediated by the application of Stein et al.’s LCD instructional approach. This study, therefore, recommends that mathematics educators should effectively apply Stein et al.’s LCD to vary mathematics tasks given to students. This approach enhances students’ cognitive levels, supports students’ heuristic problem-solving abilities, critical thinking skills, and application of mathematics in real-life.en_US
dc.language.isoen_USen_US
dc.publisherIn Frontiers in Educationen_US
dc.subjectLevels of cognitive demanden_US
dc.subjectLinear programming tasksen_US
dc.subjectProblem-solving heuristicsen_US
dc.subjectSecondary school mathematicsen_US
dc.subjectEquationsen_US
dc.subjectInequalitiesen_US
dc.titleExploring the impact of Stein et al.’s levels of cognitive demand in supporting students’ mathematics heuristic problem-solving abilitiesen_US
dc.typeArticleen_US


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