Instructional strategies and tactics for the design of introductory computer programming courses in high school

This article offers an examination of instructional strategies and tactics for the design of introductory computer programming courses in high school. We distinguish the Expert, Spiral and Reading approach as groups of instructional strategies that mainly differ in their general design plan to control students' processing load. In order, they emphasize topdown program design, incremental learning, and program modification and amplification. In contrast, tactics are specific design plans that prescribe methods to reach desired learning outcomes under given circumstances. Based on ACT* (Anderson, 1983) and relevant research, we distinguish between declarative and procedural instruction and present six tactics which can be used both to design courses and to evaluate strategies. Three tactics for declarative instruction involve concrete computer models, programming plans and design diagrams; three tactics for procedural instruction involve worked-out examples, practice of basic cognitive skills and task variation. In our evaluation of groups of instructional strategies, the Reading approach has been found to be superior to the Expert and Spiral approaches

Plan-based delivery composition in intelligent tutoring systems for introductory computer programming

In a shell system for the generation of intelligent tutoring systems, the instructional model that one applies should be variable independent of the content of instruction. In this article, a taxonomy of content elements is presented in order to define a relatively content-independent instructional planner for introductory programming ITS's; the taxonomy is based on the concepts of programming goals and programming plans. Deliveries may be composed by the instantiation of delivery templates with the content elements. Examples from two different instructional models illustrate the flexibility of this approach. All content in the examples is taken from a course in COMAL-80 turtle graphics

A knowledge-based framework to facilitate E-training implementation

Dissertação para obtenção do Grau de Mestre em Engenharia Eletrotécnica e de ComputadoresNowadays, there is an evident increase of the custom-made products or solutions demands with the objective to better fits to customer needs and profiles. Aligned with this, research in e-learning domain is focused in developing systems able to dynamically readjust their contents to respond to learners’ profiles demands. On the other hand, there is also an increase of e-learning developers which even not being from pedagogical curricula, as research engineers, needs to prepare e-learning programmes about their prototypes or products developed. This thesis presents a knowledge-based framework with the purpose to support the creation of e-learning materials, which would be easily adapted for an effective generation of custom-made e-learning courses or programmes. It embraces solutions for knowledge management, namely extraction from text & formalization and methodologies for collaborative e-learning courses development, where main objective is to enable multiple organizations to actively participate on its production. This also pursues the challenge of promoting the development of competencies, which would result from an efficient knowledge-transfer from research to industry

Personalised trails and learner profiling within e-learning environments

This deliverable focuses on personalisation and personalised trails. We begin by introducing and defining the concepts of personalisation and personalised trails. Personalisation requires that a user profile be stored, and so we assess currently available standard profile schemas and discuss the requirements for a profile to support personalised learning. We then review techniques for providing personalisation and some systems that implement these techniques, and discuss some of the issues around evaluating personalisation systems. We look especially at the use of learning and cognitive styles to support personalised learning, and also consider personalisation in the field of mobile learning, which has a slightly different take on the subject, and in commercially available systems, where personalisation support is found to currently be only at quite a low level. We conclude with a summary of the lessons to be learned from our review of personalisation and personalised trails

Knowledge Cartography: Software tools and mapping techniques

Knowledge Cartography is the discipline of mapping intellectual landscapes.The focus of this book is on the process by which manually crafting interactive, hypertextual maps clarifies one’s own understanding, as well as communicating it.The authors see mapping software as a set of visual tools for reading and writing in a networked age. In an information ocean, the primary challenge is to find meaningful patterns around which we can weave plausible narratives. Maps of concepts, discussions and arguments make the connections between ideas tangible and disputable. With 17 chapters from the leading researchers and practitioners, the reader will find the current state–of-the-art in the field. Part 1 focuses on educational applications in schools and universities, before Part 2 turns to applications in professional communitie

Applications of semantic web technology to support learning content development

The Semantic Web is based on ontology technology – a knowledge representation framework – at its core to make meaning explicit and more accessible to automatic processing. We discuss the potential of this technology for the development of content for learning technology systems. We survey seven application types demonstrating different forms of applications of ontologies and the Semantic Web in the development of learning technology systems. Ontology technologies can assist developers, instructors, and learners to organise, personalise, and publish learning content and to discover, generate, and compose learning content. A conceptual content development and deployment architecture allows us to distinguish and locate the different applications and to dis-cuss and assess the potential of the underlying technologies

Symbolic analysis tools-the state of the art

This paper reviews the main last generation symbolic analyzers, comparing them in terms of functionality, pointing out also their shortcomings. The state of the art in this field is also studied, pointing out directions for future research

Semantic adaptability for the systems interoperability

In the current global and competitive business context, it is essential that enterprises adapt their knowledge resources in order to smoothly interact and collaborate with others. However, due to the existent multiculturalism of people and enterprises, there are different representation views of business processes or products, even inside a same domain. Consequently, one of the main problems found in the interoperability between enterprise systems and applications is related to semantics. The integration and sharing of enterprises knowledge to build a common lexicon, plays an important role to the semantic adaptability of the information systems. The author proposes a framework to support the development of systems to manage dynamic semantic adaptability resolution. It allows different organisations to participate in a common knowledge base building, letting at the same time maintain their own views of the domain, without compromising the integration between them. Thus, systems are able to be aware of new knowledge, and have the capacity to learn from it and to manage its semantic interoperability in a dynamic and adaptable way. The author endorses the vision that in the near future, the semantic adaptability skills of the enterprise systems will be the booster to enterprises collaboration and the appearance of new business opportunities

Customisable e-training programmes based on trainees profiles

Dissertation presented at Faculdade de Ciências e Tecnologia of Universidade Nova de Lisboa to obtain the Master degree in Electrical and Computer EngineeringOnline training (e-training) is a major driver to promote the development of competencies and knowledge in enterprises. A lack of customizable e-training programmes based on trainees‟ profiles and of continuous maintenance of the training materials prevents the sustainability of industrial training deployment. This dissertation presents a training strategy and a methodology for building training courses with the purpose to provide a trainee oriented industrial training development. The training strategy intends to facilitate the management of all the training components and tasks to be able to build a training structure focused in a specific planned objective. The methodology for building e-training courses proposes to create customizable training materials in an easier way, enabling various organizations to participate actively on its production. Additionally a customisable training programme framework is presented. It is supported by a compliant ontology-based model able to support adaptable training contents, orchestration service, facilitating the efficiency and acceptance of the e-training programmes delivery

MOT meets AHA!

MOT (My Online Teacher) is an adaptive hypermedia system (AHS) web-authoring environment. MOT is now being further developed according to the LAOS five-layer adaptation model for adaptive hypermedia and adaptive web-material, containing a domain -, goal -, user -, adaptation – and presentation model. The adaptation itself follows the LAG three-layer granularity structure, figuring direct adaptation techniques and rules, an adaptation language and adaptation strategies. In this paper we shortly describe the theoretical basis of MOT, i.e., LAOS and LAG, and then give some information about the current state of MOT. The purpose of this paper is to show how we plan the design and development of MOT and the well-known system AHA! (Adaptive Hypermedia Architecture), developed at the Technical University of Eindhoven since 1996. We aim especially at the integration with AHA! 2.0. Although AHA! 2.0 represents a progress when compared to the previous versions, a lot of adaptive features that are described by the LAOS and the adaptation granulation model and that are being implemented into MOT are not yet (directly) available. So therefore AHA! can benefit from MOT. On the other hand, AHA! offers a running platform for the adaptation engine, which can benefit MOT in return