![]() ![]() As we have seen, the limit of the sequence is 1-1 is the smallest number that is bigger than all the terms in the sequence. If a sequence has any of these properties it is called monotonic.Īll of the terms \( (2^i-1)/2^i\) are less than 2, and the sequence is increasing. Finally, we deploy our analysis to reply to Timothy Williamson’s objections to intuitionistic treatments of vagueness.\) for all \(i\). We also show that our key results go through in an intuitionistic version of S4M. S4M is one of the modal counterparts of the intuitionistic sentential calculus (IPC) and we use this fact to explain why IPC is the correct sentential logic to use when reasoning with vague statements. S4M opens the way to an account of higher-order vagueness which avoids the paradoxes that have been thought to infect the notion. We argue that the intuitionist’s characteristic rejection of any third alethic value alongside true and false is best elaborated by taking the normal modal system S4M to be the sentential logic of the operator ‘it is clearly the case that’. We offer a proposal that makes strides on both issues. Second, switching from classical to intuitionistic logic, while it may help with the Sorites, does not appear to offer any advantages when dealing with the so-called paradoxes of higher-order vagueness. First, the lack of an accepted semantics for languages containing vague terms has led even philosophers sympathetic to intuitionism to complain that no explanation has been given of why intuitionistic logic is the correct logic for such languages. Its acceptance has been hampered by two factors. Key words: Self- regulated learning strategies, multiple intelligences, academic math performance, Self-regulationĪBSTRACT: Intuitionistic logic provides an elegant solution to the Sorites Paradox. These strategies involve Meta-cognitive (Self- Evaluation), Motivational (Goal Setting and Planning, Rehearsing and Memorizing, Organizing and Transforming), and Behavioral (Environmental and Structuring) processes of self-regulated learning. Thus, high self-regulated learners have used powerful self-regulated strategies in regulating their learning to attain high academic mathematics performance. The learners’ high level of self- regulation has also significant relationship with logical/ mathematical intelligence, and high academic performance in mathematics. It was found out that students with high self-regulation utilized higher frequencies of self-regulation strategies compared to their low self-regulated peers. ![]() A Pearson Correlation using SPSS 23.0 also unravel the significant correlation between high level of academic self-regulation and logical/ mathematical intelligence, as well as the academic mathematics performance. ![]() A qualitative method was used to delve into the different self-regulated strategies of high and low self-regulated learners. The respondents of the study were grade 10 students comprised of fifteen (15) high self-regulated and fifteen (15) low self-regulated learners of Bulak National High School, in the Cebu Province Division for school year 2016- 2017. Hence, this study looked into the self-regulated learning strategies, multiple intelligences, and academic mathematics performance of high and low self-regulated learners. ![]() These processes embodied the students’ self-regulated learning. ABSTRACT Mathematics education experts elaborate that motivational, meta-cognitive, and behavioral processes are as important as cognitive processes of students’ mathematics learning. ![]()
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