In the current educational landscape, where large amounts of data are being produced by institutions, Educational Data Mining (EDM) emerges as a critical discipline that plays a crucial role in extracting knowledge from this data to help academic policymakers make decisions. EDM has a primary focus on predicting students' academic performance.…

Properly predicting students' academic performance is crucial for elevating educational outcomes in various disciplines. Through precise performance prediction, schools can quickly pinpoint students facing challenges and provide customized educational materials suited to their specific learning needs. The reliance on teachers' experience to…

Predictive student models are increasingly used in learning environments due to their ability to enhance educational outcomes and support stakeholders in making informed decisions. However, predictive models can be biased and produce unfair outcomes, leading to potential discrimination against some students and possible harmful long-term…

Predicting and improving the academic achievement of university students is a multifactorial problem. Considering the low success rates and high dropout rates, particularly in open education programs characterized by mass enrollment, academic success is an important research area with its causes and consequences. This study aimed to solve a…

Today, in every academic institution as well as the university system assessing students' performance, identifying the uniqueness of each student and finding solutions to performance problems have become challenging issues. The main purpose of the study is to predict how student performance changes as a result of their behaviours, hobbies,…

Jung and Won's (2018) review of elementary school ER found a lack of understanding of instructional practices for ER with young children. Other researchers have called for further studies into what effective classroom orchestration and interaction look like within ER classrooms (Ioannou & Makridou, 2018; Xia & Zhong, 2019). This study was…

The contents taught in the programming subjects have a great relevance in the formation of computing students. However, these subjects are characterized by high failure rates, as they require logical reasoning and mathematical knowledge. Thus, establishing knowledge through the subject of algorithms can help students to overcome these difficulties…

In this paper, to handle the problem of the quick evolution of cyber-security attacks, we developed the iMonsters board game and proposed the attack and defense knowledge self-evolving algorithm. Three versions of the iMonsters were launched in 2013, 2017, and 2019, respectively. Accordingly, the cyber-security ontology can be refined by the…

Examining students' attitudes towards STEM (science, technology, engineering, and mathematics) fields starting from middle school level is important in their career choices and future planning. However, there is a need to investigate which variables affect students' attitudes towards STEM. Here, we aimed to estimate middle school students'…

Within the last decade, different educational data mining techniques, particularly quantitative methods such as clustering, and regression analysis are widely used to analyze the data from educational games. In this research, we implemented a quantitative data mining technique (clustering) to further investigate students' feedback. Students played…

The widespread adoption of online courses opens opportunities for analysing learner behaviour and optimising web-based learning adapted to observed usage. Here, we introduce a mathematical framework for the analysis of time-series of online learner engagement, which allows the identification of clusters of learners with similar online temporal…

Studied the interpretation of mathematics in terms of algorithmic or coherent views of 1,287 teachers from 12 countries using responses to items from the Third International Mathematics and Science Study (TIMSS). Teachers from four high-achieving Asian countries were more likely to see mathematics as algorithmic than were teachers from four…

A method for predicting freshman performance based on high school grades allows calculation of any student's likely grades in a similar university course. The method is contrasted with several more traditional predictive methods and examined in a study of 3,734 University of Western Australia students. (MSE)

Studied the ability of logical test design (LTD) to predict student performance in reading Roman numerals for 211 sixth graders in Mexico City tested on Roman numeral items varying on LTD-related and non-LTD-related variables. The LTD-related variable item iterativity was found to be the best predictor of item difficulty. (SLD)