Construct-it: A board game to enhance built environment students’ understanding of the property life cycle

This article investigates the development of a board game entitled ‘Construct-it’ as an innovative pedagogical approach (as proof of concept) to augmenting the applied knowledge and understanding of built environment students studying property life cycle analysis. A largely qualitative and inductive methodological approach is conducted to identify and investigate the various pertinent theoretical frameworks that could be adopted; conduct a critical synthesis of extant literature; and develop Construct-it, a game intuitively grounded in practice-based knowledge. The study reveals that games provide a fun, engaging and challenging means of educating students at higher education institutions. It also notes a significant dearth of literature in terms of applying games to students enrolled on built environment programmes. Construct-it can enhance the student’s learning experience and knowledge of pertinent industry practice and standards and can complement traditional classroom teaching approaches. The study concludes with directions for the future work required to enhance the development of the novel pedagogical proof of concept presented. Such work will require robust testing and validation of the game to measure its impact on the student learning experience. </jats:p

Developing Learning Trajectory For Enhancing Students’ Relational Thinking

Algebra is part of Mathematics learning in Indonesian curriculum. It takes one half of the teaching hours in senior high school, and one third in junior high school. However, the learning trajectory of Algebra needs to be improved because teachers teach computational thinking by applying paper-and-pencil strategy combining with the concepts-operations-example-drilling approach. Mathematics textbooks do not give enough guidance for teachers to conduct good activities in the classroom to promote algebraic thinking especially in the primary schools. To reach Indonesian Mathematics teaching goals, teachers should develop learning trajectories based on pedagogical and theoretical backgrounds. Teachers need to have knowledge of student’s developmental progressions and understanding of mathematics concepts and students’ thinking. Research shows that teachers’ knowledge of student’s mathematical development is related to their students’ achievement. In fostering a greater emphasis on algebraic thinking, teachers and textbooks need to work more closely together to develop a clearer learning trajectory. Having this algebraic thinking, students developed not only their own character of learning and thinking but also their attitude, attention and discipline. Key Words: Learning Trajectory, Relational Thinkin

Predicting the academic success of architecture students by pre-enrolment requirement: using machine-learning techniques

In recent years, there has been an increase in the number of applicants seeking admission into architecture programmes. As expected, prior academic performance (also referred to as pre-enrolment requirement) is a major factor considered during the process of selecting applicants. In the present study, machine learning models were used to predict academic success of architecture students based on information provided in prior academic performance. Two modeling techniques, namely K-nearest neighbour (k-NN) and linear discriminant analysis were applied in the study. It was found that K-nearest neighbour (k-NN) outperforms the linear discriminant analysis model in terms of accuracy. In addition, grades obtained in mathematics (at ordinary level examinations) had a significant impact on the academic success of undergraduate architecture students. This paper makes a modest contribution to the ongoing discussion on the relationship between prior academic performance and academic success of undergraduate students by evaluating this proposition. One of the issues that emerges from these findings is that prior academic performance can be used as a predictor of academic success in undergraduate architecture programmes. Overall, the developed k-NN model can serve as a valuable tool during the process of selecting new intakes into undergraduate architecture programmes in Nigeria

Becoming the Expert - Interactive Multi-Class Machine Teaching

Compared to machines, humans are extremely good at classifying images into categories, especially when they possess prior knowledge of the categories at hand. If this prior information is not available, supervision in the form of teaching images is required. To learn categories more quickly, people should see important and representative images first, followed by less important images later - or not at all. However, image-importance is individual-specific, i.e. a teaching image is important to a student if it changes their overall ability to discriminate between classes. Further, students keep learning, so while image-importance depends on their current knowledge, it also varies with time. In this work we propose an Interactive Machine Teaching algorithm that enables a computer to teach challenging visual concepts to a human. Our adaptive algorithm chooses, online, which labeled images from a teaching set should be shown to the student as they learn. We show that a teaching strategy that probabilistically models the student's ability and progress, based on their correct and incorrect answers, produces better 'experts'. We present results using real human participants across several varied and challenging real-world datasets.Comment: CVPR 201

Spot the Difference! Visual plagiarism in the visual arts.

Over recent years there has been considerable investment in the use of technology to identify sources of text-based plagiarism in universities. However, students of the visual arts are also required to complete numerous pieces of visual submissions for assessment, and yet very little similar work has been undertaken in the area of non-text based plagiarism detection. The Spot the Difference! project (2011-2012), funded by JISC and led by the University for the Creative Arts, seeks to address this gap by piloting the use of visual search tools developed by the University of Surrey and testing their application to support learning and teaching in the arts and specifically to the identification of visual plagiarism. Given that most commonly used search technologies rely on text, the identification and evidencing of visual plagiarism is often left to the knowledge and experience of academic staff, which can potentially result in inconsistency of detection, approach, policies and practices. This paper outlines the work of the project team, who sought to investigate the nature, scope and extent of visual plagiarism in the arts education sector

Giftedness as property: Troubling whiteness, wealth, and gifted education in the US

The purposes of this article are to illumine the racist genealogy of gifted education policies and practices in the United States, to demonstrate how deficit discourses continue today, and to provide personal examples from the field of how educators can begin to question the status quo, resist taken-for-granted assumptions, and alternatively make substantive changes at the local level. I also aim to demonstrate how giftedness is an example of whiteness as property, or unearned white privilege, that, unintentionally or not, maintains a social caste system in school

Using materials from the history of mathematics in discovery-based learning

This paper reports on attempt to integrate history of mathematics in discovery-based learning using technology. Theoretical grounding of the idea is discussed. An exploratory environment on triangle geometry is described. It is designed to support and motivate students' activities in learning through inquiry. Conjectures about properties of Lemoine point and Simson line are produced and proved by students using e-learning textbook