Ordinary Differential Equations (ODE) is taken by students in the mathematics, science or engineering programs in Universiti Teknologi MARA (UiTM). This course was originally taught in the traditional way with the lecturer as the instructor. In 2014, this course evolved into the blended-learning mode i.e. a combination of classroom sessions and online sessions using the university learning management system. In 2017, a team of lecturers in the Tapah campus of UiTM decided to develop an instructional design of ODE using the MOOC platform. Students would then use the MOOC during the blended-learning hour. Five modules are offered in this MOOC. Lecture notes are presented using Prezi together with instructional videos and self-checking exercises. 55 students enrolled for the MOOC and were surveyed to gauge the initial impact of the MOOC as an instructional tool. More than 50% of the students said that the MOOC absolutely helped them to better understand the classroom sessions. Most of the students put in maximum effort in accessing the MOOC. The MOOC also helped to build up self-confidence of students in the course material. It is hoped that as the MOOC is further refined and improved, more students will benefit from the MOOC.
The introduction of soft set theory by Molodstov has gained attention by many as it is useful in dealing with uncertain data. It is advantageous to use due to its parameterization form of data. This concept has been used in solving many decision making problems and has been generalized in various aspects in particular to fuzzy soft set (FSS) theory. In decision making using FSS, the objective is to select an object from a set of objects with respect to a set of choice parameter using fuzzy values. Although FSS theory has been extensively used in many applications, the importance of weight of parameters has not been highlighted and thus is not incorporated in the calculation. As it depends on one’s perception or opinion, the importance of the parameters may differ from one decision maker to another. Besides, existing methods in FSS only consider one or two decision makers to select the alternatives. In reality, group decision making normally involves more than two decision makers. In this paper we present a method for solving group decision making problems that involves more than two decision makers based on fuzzy soft set by taking into consideration the weight of parameters. The method of lambda – max which frequently utilize in fuzzy analytic hierarchy process (FAHP) has been applied to determine the weight of parameters and an algorithm for solving decision making problems is presented. Finally we illustrate the effectiveness of our method with a numerical example.
Calculus is one of the most important courses especially for undergraduate students in many fields of study. Some researchers have identified the causes of the high failure rate which includes lack of basic foundation of mathematics and basic concept of differentiation. Aside from that, the main problems that can be seen among students are the difficulty in identifying the type of function in differentiation and identifying the suitable method to solve a particular problem. There are three rules included in differentiation which are the Chain Rule, Product Rule and Quotient Rule. This study is conducted to examine the level of understanding of the students on the function and the derivative techniques after applying derivative game applications in this course. This paper is based on Fuzzy Analytic Hierarchy Process (Fuzzy AHP) which use fuzzy number in pair-wise comparison matrix. The prioritization of students’ understanding in differentiation rules will then be measured by Fuzzy AHP using Lambda-max method. The highest among the three rules in differentiation will considered as a result. The findings of this study indicated that the highest score with 0.4700 is the Chain Rule. This study can help lectures to know the level or understanding among three rules in differentiation and lecturer well prepared their teaching materials in the classroom as well as to reduce the failure rate among students in this course
Students' learning processes and future employment preferences are heavily influenced by their learning environment. It is regarded as a critical aspect in determining the success of an effective curriculum and academic accomplishment of students. The consequences of online e-learning versus face-to-face learning have been discussed in higher education for several years. In this paper, the study attempted to investigate the issues of students' perception and their feedback on online e-learning and face-to-face (F2F) learning. The instruments of data collection were carried out by questionnaire using Google form platform. This research shared the closed-ended questionnaire with 136 Universiti Teknologi MARA Perak Branch students from three different faculties; Faculty of Computer and Mathematical Sciences (FSKM), Faculty of Applied Sciences (FSG) and Faculty of Architecture, Planning and Surveying (FSPU). The data were entered in Microsoft Excel and analysis was carried out using SPSS version 26.0. All the three categorical variables were presented as frequency and percentage. In this research, descriptive statistics were computed and Spearman's rank-order correlation was used to measure the strength and direction of the relationship between the two categorical attributes. The analysis of all the faculties involved in this research show a difference in students' perceptions and experiences in online e-learning and face-to-face learning. Overall results show that most students preferred face-to-face learning compared to online learning.
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