The ability to reason with representations is pivotal for successful learning in Organic Chemistry and is closely linked to representational competence. Given the visual nature of this discipline, this comprises competency in extracting and processing relevant visual information. With regard to the resonance concept, proficiency in identifying…

This study explores how pre-service mathematics teachers' spatial visualisation skills evolved during a Cognitive Load Theory (CLT) based education. The study used the qualitative theory-testing case study method, which guided the identification of participants, the design of technology-supported education, and the data collection and analysis…

Background: Both learning and problem solving are major goals of complex problem solving in engineering education. The order of knowledge construction and problem solving in learning through problem solving, however, has not been explained in current literature. Objectives: To understand their relationships, this study compared the effects of…

The study focuses on the identification of relationships and/or rules between computational thinking (CT) concepts among the undergraduate students of Applied Informatics due to their attitudes towards mathematics. We analyze three CT concepts -- decomposition, pattern recognition, and algorithmic thinking. We assume that students who have a…

Pattern recognition is an aspect of computational thinking and a vital competency for solving mathematical problems. By recognizing patterns, one can develop possible solutions. This paper aims to describe the pattern recognition of prospective mathematics teachers in solving mathematical problems from a semiotic perspective. This study based on a…

The purpose of this study was to explicate one preservice middle grades mathematics teacher's Knowledge of Content and Students (KCS) in the context of multiple solution strategies. This study's purpose is to underline the importance of preservice teachers' KCS and provide possible investigative methods for evaluating preservice teachers' KCS.…

As the demand for skilled data scientists has grown, university level statistics and data science courses have become more rigorous in training students to understand and utilize the tools that their future careers will likely require. However, the mechanisms to assess students' use of these tools while they are learning to use them are not well…

The authors present mathematics problems related to the packaging of sporting goods which they used to motivate and engage their students in the USA. This article reports on a series of questions/problems that were explored in groups by the students in a college class designed for sophomores, as part of a program to prepare them to be teachers at…

The purpose of this study was to demonstrate that transfer ability (positive and negative) varies depending on the nature of the problems, using the knowledge transfer matrix, as well as being dependent on the individual differences of the learner. A total of 178 participants from the United States and New Zealand completed measures of prior…

The pattern, which is a key concept in understanding the mathematical information and concepts, is the basis in comprehending mathematical relations and in understanding mathematical order and logic. The fact that students discover the relationships contained within the patterns and generalize them helps them develop their skills to better…

Road map problems ask students to integrate their knowledge of organic reactions with pattern recognition skills to "fill in the blanks" in the synthesis of an organic compound. Students are asked to identify familiar organic reactions in unfamiliar contexts. A practical context, such as a medicinally useful target compound, helps…

This paper deals with two types of logical problems--recognition problems and reverse engineering problems, and with the interrelations between these types of problems. The recognition problems are modeled in the form of a visual representation of various objects in a common pattern, with a composition of represented objects in the pattern.…

Many people believe that environmental factors promote giftedness and invest in many programs to adopt gifted students providing them with challenging activities. Intellectual giftedness is founded on fluid intelligence and extends to more specific abilities through the growth and inputs from the environment. Acknowledging the roles played by the…

A basic and classical assumption in the machine learning research area is "randomness assumption" (also known as i.i.d assumption), which states that data are assumed to be independent and identically generated by some known or unknown distribution. This assumption, which is the foundation of most existing approaches in the literature, simplifies…

In building intelligent tutoring systems, it is critical to be able to understand and diagnose student responses in interactive problem solving. However, building this understanding into a computer-based intelligent tutor is a time-intensive process usually conducted by subject experts. Much of this time is spent in building production rules that…