Kay Hoeksema

CSCL scripts: modelling features and potential use

The design of collaboration scripts is a new focus of research within the CSCL community. In order to support the design, communication, analysis, simulation and even execution of collaboration scripts, a general specification language to describe collaboration scripts is needed. In this paper, we analyse the suitability and limitations of IMS LD for modelling collaborative learning processes. Based on the analysis, we propose a CSCL scripting language. This paper presents the conceptual framework of this modelling language and the underlying design ideas. Furthermore, two developed CSCL script authoring tools are briefly described. Finally, we discuss potential types of usage and system support possibilities of CSCL scripts.

An interactive maze scenario with physical robots and other smart devices

This paper describes an educational application that combines handhelds (PDAs) and programmable Lego bricks in a classroom scenario that deals with the problem of letting a robot escape from a maze. It is specific to our setting that the problem can be solved both in the physical world by steering a Lego robot and in a simulated software environment on a PDA or on a PC. This approach enables the students to generate successful sets of rules in the simulation and to test these sets of rules later in physical mazes, or to create new types of mazes as challenges for known rule sets. In this paper we describe the technical setting for this scenario, different pedagogical scenarios and we will report an evaluation with a group of students in a school environment.

Modeling CSCL Scripts — a Reflection on Learning Design Approaches

The design of collaboration scripts is a new focus of research within the CSCL research community. In order to support the design, communication, analysis, simulation and also the execution of collaboration scripts, a general specification language to describe collaboration scripts is needed. In this chapter, we analyze the suitability and limitations of IMS LD for modeling collaborative learning processes. Based on the analysis, we propose an approach to designing a CSCL scripting language. This chapter presents the conceptual framework of this modeling language and the solutions to the identified problems of IMS LD for formalizing collaboration scripts. Especially, we compare the two approaches through modeling the same collaboration script by using IMS LD and our own CSCL scripting language.

Technologies and Educational Activities for Supporting and Implementing Challenge-Based Learning

Our Challenge-Based Learning (CBL) method can be described as a special form of problem-based learning, in which the problems are of realistic, open-ended nature. Additionally, CBL contains features of experiential and project-based learning approaches. CBL is supported by the provision of Digital Experimentation Toolkits (DExTs) which comprise materials, initial instructions, references to web resources and specific software tools. Technological challenges lie in the ease of use in accessing these data and in communicating the learners’ requests and specifications to the remote sites. Within this article we describe several classroom scenarios for the usage of DexTs in schools. Examples are the calculation of the epicenter of an earthquake, the calculation of lunar heights and the definition of strategies for navigation in a maze. The activities described in this paper were conducted within the framework of our COLDEX project (Collaborative Learning and Distributed Experimentation, http://www.coldex.info).

Interactive processing of astronomical observations in a cooperative modelling environment

The astronomy domain provides rich opportunities for learning about natural phenomena. It can involve and motivate a variety of mathematical and physical knowledge and skills. However it is difficult to connect astronomic observations to modelling and calculation tools and to embed them into educational scenarios. It is particularly this challenge which is focused in this paper. Concretely, we build on an existing collaborative modelling framework (Cool Modes) and extend it with specific representations to support learning activities in astronomy. A first field test has been conducted with these extensions.