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It has always been a challenge for teachers to engage and motivate students to learn mathematics, due to the abstractness of some topics and the need for visual representation and technological resources. This study explores the effectiveness of using a technological approach on student achievement in mathematics, in general. A pre/post-test design was followed with a control and experimental group both learning the same topic over a 3-week period. A sample size of 35 (Experimental group = 18 and Control group = 17) high school students of 4th form level (Grade 10/Senior High) was taken with experimental group students taught using an interactive technological approach—GeoGebra software, in particular; while the control group learned the same material using the traditional approach without technology. GeoGebra is free software which can be used to teach different topics in mathematics education. Analysis of Covariance (ANCOVA) is applied in the study, and the findings shows that technology is an effective tool in teaching the topic of Coordinate Geometry concepts. It can be concluded that the student who was taught with the use of technology showed a higher level of conceptual understanding compared to the students who learned using the traditional method.

A process management technique, called process mining, received much attention recently. Process mining can extract organizational or social structures from event logs recorded in an information system. However, when constructing process models, most process mining searches consider only the topology information among events, but do not include the time information. To overcome the drawbacks, a time-interval genetic process mining framework is proposed. First, time-intervals between events are derived for all event sequences. A discretization procedure is then developed to transform time-interval data from continues type to categorical type. Second, the genetic process mining method which is based on global search strategy is applied to generate time-interval process models. Finally, a precision measure is defined to evaluate the quality of the generated models. With the measure, managers can select the best process model among a set of candidate models without human involvement.

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Current construction worksite layout planning heavily relies on 2D paper media where the worksite planners sketch the future layout adjacent to their real environment. This traditional approach turns out to be ineffective and prone to error because only experienced and well-trained planners are able to generate the effective layout design with paper sketch. Augmented Reality (AR), as a new user interface technology, introduces a completely new perspective for construction worksite planning. This paper describes the concept and prototype of an AR-based construction planning tool, AR Planner with virtual elements sets and tangible interface. The focus of the paper is to identify and integrate worksite planning rules into the AR planner with the purpose of intelligently preventing potential planning errors and process inefficiency, thus maximizing the overall productivity. Future work includes refining and verifying AR Planner in realistic projects.