Learning by starch potato growers: learning in small businesses with no employees

In small businesses with no employees, learning environments have a low learning readiness. Consequently, learners need to rely on their own agency to shape their learning experiences. Results from a study of agricultural entrepreneurs indicated that the components of motivation and self-regulated learning strategies shape learner's agency and explain learning environment configuration in small businesses with no employees. Configuration of the learning environment was found to be a weak determinant of the learning performance of these learners. However, results showed that prior performance of learners in small businesses with no employees dictates how their agency operates and what learning effect is achieved; higher prior performance results in higher learning effects. We conclude that mechanisms that underlie learning in traditional learning environments work similarly in learning environments in small businesses with no employees.     

A comparison of electronic and paper-based assignment submission and feedback

This paper presents the results of a study evaluating student perceptions of online assignment submission. 47 students submitted assignments and received feedback via features within the Virtual Learning Environment Blackboard™. The students then completed questionnaires comparing their experience of online submission and feedback with traditional methods.
Results indicated that 88% of students reported a time saving and many reported financial benefits using online submission. 93% of students preferred having their feedback available online rather than printed and handed to them. Overall, students preferred online assignment management to postal or physical hand-in. The main disadvantage of electronic submission appeared to be student distrust of the receipt system.
The use of online assignment submission and management is recommended for use in Higher Education establishments where students may be remote. It is most suitable for assignments that do not require inclusion of many images.     

Communication skills training exploiting multimodal emotion recognition

The teaching of communication skills is a labour-intensive task because of the detailed feedback that should be given to learners during their prolonged practice. This study investigates to what extent our FILTWAM facial and vocal emotion recognition software can be used for improving a serious game (the Communication Advisor) that delivers a web-based training of communication skills. A test group of 25 participants played the game wherein they were requested to mimic specific facial and vocal emotions. Half of the assignments included direct feedback and the other half included no feedback. It was investigated whether feedback on the mimicked emotions would lead to better learning. The results suggest the facial performance growth was found to be positive, particularly significant in the feedback condition. The vocal performance growth was significant in both conditions. The results are a significant indication that the automated feedback from the software improves learners’ communication performances.     

An interactive learning and course development environment: Context,theoretical and empirical considerations

In this contribution, a theoretical and empirical framework based on work carried out at the Open universiteit (Ou) for a new approach towards the design, production and delivery of flexible, interactive learning materials for distance education is presented.

In the Research and Development centre of the Ou, a project has concentrated on the innovation of current approaches. This framework can also be considered as an advance organizer to reading the remaining articles from the Open universiteit in this issue of Distance Education.

A key feature of the innovation is that during the design phase, course developers have to define ‘models’ of the materials to be developed: a content model, a support model, a student model and the learning path. From a flexibility point of view especially, the ‘student model’ is of importance since it defines the student variables that will be taken into account when developing/ presenting alternative materials (basic content and/or embedded support). A computer‐based system, the ‘Interactive Learning and Course Development Environment (ILCE)’, was developed to support the work of course development teams and tutors on the one hand, and students on the other hand. The development system supports the work of the developers; the delivery system supports the study process of students. The delivery is realised as an on‐line course, on the World Wide Web.

Students start working with the ILCE‐system by following an intake procedure. They can make choices in relation to student variables that have been defined in the student model (profession, study intentions, context, etc.). Next, they can ‘on the fly’ generate a course. Rom the large repository of learning materials only those materials are selected and compiled that are in line with the student model of this specific student Furthermore, they can choose to study the materials on screen and/or make prints of the materials. Of course, in printing the materials they lose the interactive and dynamic possibilities of the computer learning environment     

Computers and language learning: misguided assumptions

There has been a rapid increase in the availability of computer assisted instruction (CAI) software for teaching oral language skills. Despite the growing popularity of CAI in education, such an approach to language teaching fragments and isolates language learning from the context of its use and conflicts with current theory and research in language development and learning. The greatest potential for microcomputers in language learning may be as a medium for increasing student opportunities for using language by bringing students and teachers together around a shared activity.