Intelligent tutoring systems for systems engineering methodologies

The general goal is to provide the technology required to build systems that can provide intelligent tutoring in IDEF (Integrated Computer Aided Manufacturing Definition Method) modeling. The following subject areas are covered: intelligent tutoring systems for systems analysis methodologies; IDEF tutor architecture and components; developing cognitive skills for IDEF modeling; experimental software; and PC based prototype

The Early Grade Reading Assessment

The Early Grade Reading Assessment (EGRA) measures students' progress towards reading. EGRA gauges early literacy skills through a 15-minute individual oral assessment of five fundamental reading skills. RTI worked with education experts to develop the EGRA in 2006, and it has been piloted and implemented in more than 40 countries. This volume aims to take stock of the substantial amount of information and experience generated through the use of EGRA, and to share this knowledge with practitioners, policymakers, and international donors. Chapters cover not only particular applications of the instrument but also put EGRA in the context of broader issues and developments in literacy and education.Publishe

An analysis of how visualisation capabilities in dynamic geometric software develop meaning-making of mathematical concepts in selected Grade 11 learners

Visualisation plays a central role in developing mathematical ideas because it can be used to make these ideas explicit and visible, and thus has the potential to advance understanding. This study centred around the GeoGebra Literacy Initiative Project (GLIP), a teacher development initiative in Mthatha that aimed to grow and develop appropriate Information and Communication Technology (ICT) skills in teachers, to harness the teaching and learning potential of GeoGebra. GeoGebra is a dynamic geometric software package that is very interactive and makes use of powerful features to create images which can be moved around the computer screen for mathematical exploration. This research project was located within GLIP and analysed how GeoGebra applets develop conceptual and procedural understanding in selected Grade 11 learners. One aspect of GLIP was for teachers to use GeoGebra applets that they had developed themselves and implemented in their classrooms in pre-determined cycles that were aligned to the curriculum. My study specifically focused on how the selected learners made use of these applets and explored how learning had taken place in terms of developing mathematical meaning-making. This interpretive research study was designed as a case study. The case was a cohort of selected Grade 11 learners who had been taught by GLIP teachers, and my unit of analysis was the learners’ interaction with the applets. A screen capturing software package was used to capture learners’ interactions with the GeoGebra. My data consisted mainly of recorded observations and interviews. An analytical framework derived from the works of Kilpatrick, Swafford, and Findell (2001) and Carter et al. (2009) guided and informed the data analysis of the learners’ activities with the GeoGebra. The theoretical orientation of this study was constructivist learning. An in-depth analysis and detailed descriptions of the participants’ interactions enabled me to gain a comprehensive understanding of their meaning-making processes in a technological classroom context. An analysis across the participants identified distinguishable patterns or differences in the development of the learners’ mathematical proficiency and making sense of mathematical ideas. The research argued that technology enabled visualisation was a powerful tool to not only enrich mathematically activities, but to also enrich conceptual and procedural understanding. The findings recognised that exploration of, or manipulation on mathematical objects in GeoGebra was a key activity in the participants’ meaning-making process. It also enabled learners to offer self-proclaimed theorie

Learning evolution through socioscientific issues

No abstract available.publishe

A study of why some physic concepts in the South African Physical Science curriculum are poorly understood in order to develop a targeted action-research intervention for Newton’s second law

Globally, many students show a poor understanding of concepts in high school physics and lack the necessary problem-solving skills that the course demands. The application of Newton’s second law was found to be particularly problematic through document analysis of South African examination feedback reports, as well as from an analysis of the physics examinations at a pair of well-resourced South African independent schools that follow the Independent Examination Board curriculum. Through an action-research approach, a resource for use by students was designed and modified to improve students’ understanding of this concept, while modelling problemsolving methods. The resource consisted of brief revision notes, worked examples and scaffolded exercises. The design of the resource was influenced by the theory of cognitive apprenticeship, cognitive load theory and conceptual change theory. One of the aims of the resource was to encourage students to translate between the different representations of a problem situation: symbolic, abstract, model and concrete. The impact of this resource was evaluated at a pair of schools using a mixed methods approach. This incorporated pre- and post-tests for a quantitative assessment, qualitative student evaluations and the analysis of examination scripts. There was an improvement from pre- to post-test for all four iterations of the intervention and these improvements were shown to be significant. The use of the resource led to an increase in the quality and quantity of diagrams drawn by students in subsequent assessments

The Shallow and the Deep:A biased introduction to neural networks and old school machine learning

The Shallow and the Deep is a collection of lecture notes that offers an accessible introduction to neural networks and machine learning in general. However, it was clear from the beginning that these notes would not be able to cover this rapidly changing and growing field in its entirety. The focus lies on classical machine learning techniques, with a bias towards classification and regression. Other learning paradigms and many recent developments in, for instance, Deep Learning are not addressed or only briefly touched upon.Biehl argues that having a solid knowledge of the foundations of the field is essential, especially for anyone who wants to explore the world of machine learning with an ambition that goes beyond the application of some software package to some data set. Therefore, The Shallow and the Deep places emphasis on fundamental concepts and theoretical background. This also involves delving into the history and pre-history of neural networks, where the foundations for most of the recent developments were laid. These notes aim to demystify machine learning and neural networks without losing the appreciation for their impressive power and versatility