The future of technology enhanced active learning – a roadmap

The notion of active learning refers to the active involvement of learner in the learning process, capturing ideas of learning-by-doing and the fact that active participation and knowledge construction leads to deeper and more sustained learning. Interactivity, in particular learnercontent interaction, is a central aspect of technology-enhanced active learning. In this roadmap, the pedagogical background is discussed, the essential dimensions of technology-enhanced active learning systems are outlined and the factors that are expected to influence these systems currently and in the future are identified. A central aim is to address this promising field from a best practices perspective, clarifying central issues and formulating an agenda for future developments in the form of a roadmap

Genisa: A web-based interactive learning environment for teaching simulation modelling

Intelligent Tutoring Systems (ITS) provide students with adaptive instruction and can facilitate the acquisition of problem solving skills in an interactive environment. This paper discusses the role of pedagogical strategies that have been implemented to facilitate the development of simulation modelling knowledge. The learning environment integrates case-based reasoning with interactive tools to guide tutorial remediation. The evaluation of the system shows that the model for pedagogical activities is a useful method for providing efficient simulation modelling instruction

An explicit model for learning to structure and analyze decisions by judges

Legal practitioners and legal scientists need to have knowledge of the general rules that apply in the legal system. This involves both knowledge of the legislation and knowledge of the decisions by judges that function as general rules of law. Law students preparing themselves for the legal profession need to acquire these kinds of knowledge. A student has to have knowledge about where to look for decisions, understand the structure of decisions and learn to determine what makes a decision relevant to the body of applicable rules in the legal system. Legal education primarily aims at acquiring insight in the legal sources, their history and background. This basic knowledge is of great importance; legal problem solving is hardly possible without an understanding of the legal knowledge. To illustrate the use of this knowledge in practice, teachers work through decisions as examples. However, it is difficult, if not impossible, to learn by explanation or by imitation alone. A more effective way to obtain expertise is by actually performing the task, i.e. students should do the exercises, while the teacher provides feedback on their solutions. For effective learning, also the solution process should be monitored and provided with feedback. Furthermore it is desirable for students to be able to ask for help at any time during the process. They should also be able to practice over and over again. An ideal situation would have a teacher available for every student, monitoring the student while practicing and providing support where and whenever necessary. However, this being not practically feasible, the second best option is to offer the student electronic support. CASE (Case Analysis and Structuring Environment) is an environment where a law student can practice with finding decisions, with structuring its text and with analysing the decision in order to be able to determine in what way it adds to the body of applicable rules in the legal system. CASE is developed using a principled and structured design approach. A short description of this approach is followed by an analysis of the learning task, the difficulties law students experience and the remedies proposed on the basis of both the task analysis and the stated difficulties. This is followed by a description of architecture, functionality, platform and implementation of CASE and a description of a session with CASE and future work

Understanding requirements engineering process: a challenge for practice and education

Reviews of the state of the professional practice in Requirements Engineering (RE) stress that the RE process is both complex and hard to describe, and suggest there is a significant difference between competent and "approved" practice. "Approved" practice is reflected by (in all likelihood, in fact, has its genesis in) RE education, so that the knowledge and skills taught to students do not match the knowledge and skills required and applied by competent practitioners. A new understanding of the RE process has emerged from our recent study. RE is revealed as inherently creative, involving cycles of building and major reconstruction of the models developed, significantly different from the systematic and smoothly incremental process generally described in the literature. The process is better characterised as highly creative, opportunistic and insight driven. This mismatch between approved and actual practice provides a challenge to RE education - RE requires insight and creativity as well as technical knowledge. Traditional learning models applied to RE focus, however, on notation and prescribed processes acquired through repetition. We argue that traditional learning models fail to support the learning required for RE and propose both a new model based on cognitive flexibility and a framework for RE education to support this model

Emergent requirements for supporting introductory programming

The problems associated with learning and teaching first year University Computer Science (CS1) programming classes are summarized showing that various support tools and techniques have been developed and evaluated. From this review of applicable support the paper derives ten requirements that a support tool should have in order to improve CS1 student success rate with respect to learning and understanding