The Effect of Block Class Scheduling on the Achievements of Primary School Students in Nature and Biology Classes

The objective of this study was to investigate whether the class scheduling of Nature and Biology classes in blocks results in better learning success for primary school students, and whether this depends on the average student success rate (i.e., student performance categories), age, or prior knowledge. For this study, we have assumed that block scheduling results in better success rates for older lower-performing primary-school students. The research included 773 fifth- to eighth-grade students from 14 Croatian primary schools. The students fell into two groups: one group attending 45-min Nature and Biology lessons twice a week (single-scheduled classes), and another group attending a 90-min lesson once a week (block-scheduled class). To assess the level of student learning success, all students underwent both an initial and final written exam in Nature and/or Biology, specific to each grade. The rmANOVA proved that there was a significant interaction among class scheduling, performance categories, and the initial and final written exam scores of fifth- and seventh-grade students. Such a correlation was not found among the sixth- and eighth-grade students. Our findings further indicate that students achieve better results in block-scheduled classes at the end of primary school education, and that block class scheduling does not necessarily result in improved student achievement, particularly in lower-performing students.

Multi-agent class timetabling for higher educational institutions using prometheus platform

<p>A in a university setting, class scheduling is vital for teaching and learning process. Academic institutions rely on time tables in their day to day activities. University Course Timeframe problem can be resolved by using multi-agent systems-based method which may increase the independence of each department's class scheduling, adaptability in a distributed environment and prevents conflicts between events or resources, and unforeseen allocation through intervention between agents in a dispersed environment. Class timing is performed manually in most of the higher educational institutions, which is a very challenging and time-consuming process. The main objective of the study is to build a multi-agent class timing system that automates the process of class scheduling of higher education institutions (HEIs) using the Prometheus methodology. The implementation of the Prometheus approach in the development of a multi-agent framework has resulted in a complete and comprehensive system covering all phases of software development as applied to the agent systems.</p>

Highly Constrained University Class Scheduling using Ant Colony Optimization

Solving University Class Scheduling Problem (UCSP) is a complex real-world combinatorial optimization task that has been extensively studied over the last several decades. Many meta-heuristic based techniques, including prominent swarm intelligence (SI) methods have been investigated to solve it in different ways. In this study, Ant Colony Optimization (ACO) based two methods are investigated to solve UCSP: ACO based method and ACO with Selective Probability (ACOSP). ACO is the well-known SI method that differs from other SI based methods in the way of interaction among individuals (i.e., ants); and an ant interacts with others indirectly through pheromone to solve a given problem. ACO based method considers probabilistically all the unassigned time slots to select next solution point for a particular course assignment. In contrast, ACOSP probabilistically selects next solution point for a particular course assignment from the selective probabilities. Such selective probability employment with ACO improves performance but reduces computational cost. The performances of the proposed methods have been evaluated comparing with Genetic Algorithm (GA) in solving real-world simple UCSPs. In addition, proposed methods are compared with each other for solving highly constrained UCSPs. Both the proposed methods outperformed GA and ACOSP was the best to solve the given problems.

Design and Application of an Improved Genetic Algorithm to a Class Scheduling System

The current expansion of national colleges and universities or the increase in the number of enrolments requires teaching management to ensure the quality of teaching. The problem of scheduling is a very complicated prob-lem in teaching management, and there are many restrictions. If the number of courses scheduled is large, it will be necessary to repeat the experiment and make adjustments. This kind of work is difficult to accomplish accu-rately by manpower. Moreover, for a comprehensive university, there are many subjects, many professional settings, limited classroom resources, limited multimedia classroom resources, and other factors that limit and constrain the results of class scheduling. Such a large data volume and com-plicated workforce are difficult to complete accurately. Therefore, manpow-er scheduling cannot meet the needs of the educational administration of colleges and universities. Today, computer technology is highly developed. It is very economical to use software technology to design a course schedul-ing system and let the computer complete this demanding and rigorous work. Common course scheduling systems mainly include hill climbing al-gorithms, tabu search algorithms, ant colony algorithms, and simulated an-nealing algorithms. These algorithms have certain shortcomings. In this re-search, we investigated the mutation genetic algorithm and applied the algo-rithm to the student’s scheduling system. Finally, we tested the running speed and accuracy of the system. We found that the algorithm worked well in the course scheduling system and provided strong support for solving the tedious scheduling work of the educational administration staff.

Effects of Block vs. Traditional Scheduling on High School Science Success—Lessons from Biology Classes

Many studies investigate the effects of block vs. traditional class scheduling on the students’ success in high-school science classes. However, it is rare for studies to investigate the interactive effect of class scheduling and students’ average performance on the students’ success. We investigated how block (B) vs. single (S) class scheduling, students’ average performance and their interaction affect students’ success in high school biology course. The study included 281 high school students (1st to 4th grade; 124 students from S-, 157 from B-scheduled classes) participating in: (1) first written exam conducted to evaluate students’ initial knowledge; (2) teaching in block- vs. single-scheduled classes; (3) second written exam conducted to assess students’ achievement after block- vs. single-scheduled classes. Block-scheduled classes improved students’ performance in 3rd grade only. In 1st and 2nd grade, students from single-scheduled classes achieved better results. In 4th grade, there was no significant difference in success among block- vs. single-scheduled classes. Block-scheduled classes did not affect students’ success equally across all student performance categories. When estimating the effects of class scheduling on students’ success, students’ age, prior knowledge, overall performance and complexity of educational topics should be considered.