Jacobijn Sandberg

Mobile English learning: An evidence-based study with fifth graders

Three groups participated in a study on the added value of mobile technology for learning English as a second language for primary school students. The first group had classroom lessons in English about zoo animals and their characteristics. The second group took classroom lessons and worked with a mobile application on location in a public zoo. The third group received the same treatment as the second but, as an extension, was allowed to take the mobile application home for a fortnight. A pre- and a posttest were conducted to measure the individual change in mastery of a set of targeted English words. The results showed that the group which took the mobile phone home improved the most. However, when the additional learning time, spent apart from school, of this third group was controlled for, the superior performance of the group disappeared. The results indicate that students are motivated to use the application in their spare time and that this benefits their learning. The conclusion is that formal school learning can be augmented by learning in an informal context, away from school.

Methods and techniques for knowledge management: What has knowledge engineering to offer?

Abstract Knowledge engineering has been around for more than a decade, and has achieved some results that will be useful for knowledge management. This paper tries to link both areas and show how the latter can benefit from the achievements of the former. First an overview is given of the major ‘assets’ realized by knowledge engineering. Next it is investigated how requirements from knowledge management could be met by reusing modeling results and ontologies. Two case studies are presented to show how both disciplines could work together to improve the knowledge households of museums. The paper concludes with some observations on the future relation between knowledge engineering and knowledge management.

Deep learning is difficult

As the capacity to learn is one of mens natural capacities, it is easily assumed that learning itself proceeds smoothly and causes no particular difficulties. When learning is confronting difficulties, often external factors are held responsible, not some inherent difficulty in the learning process itself. Explanations for poor learning results found in terms of external factors usually range from pointing out the inadequacy of the subject matter area, the inadequacy of the student sample, to the inadequacy of the didactic approach or means. In this article, we will argue that learning is difficult in itself, and that the three types of explanations are not necessarily sufficient to explain poor learning results. Our conclusion is that the information processing needed for deep learning itself may be hampered because the students do not spontaneously engage in cognitive activities that foster such learning. We will put forward our arguments through describing the various results obtained with experimenting in the tides domain. Three studies are described in which students learn about the tides with a computer tutor.

The added value of a gaming context and intelligent adaptation for a mobile learning application for vocabulary learning

Two groups participated in a study on the added value of a gaming context and intelligent adaptation for a mobile learning application. The control group worked at home for a fortnight with the original Mobile English Learning application (MEL-original) developed in a previous project. The experimental group worked at home for a fortnight with MEL-enhanced, the original application embedded in an adventure game and augmented with intelligent adaptation. Two learning themes were used: Zoo animals and Neighbourhood. Both groups attended lessons at school on Zoo Animals and Neighbourhood during the same periods they were allowed to work with the application at home. A pre- and post-test were conducted to establish the initial vocabulary knowledge and the knowledge acquired during the learning phase. The main results indicated that the students in the experimental condition (MEL-enhanced) outperformed the children from the control group (MEL-original), although the former group did not spend more time with the learning material than the latter, and that the students in the experimental group valued MEL-enhanced more than the children from the control group valued MEL-original.

Using an ontology to automatically generate questions for the determination of situations

We investigate whether the automatic generation of questions from an ontology leads to a trustworthy determination of a situation. With our Situation Awareness Question Generator (SAQG) we automatically generate questions from an ontology. The experiment shows that people with no previous experience can characterize hectic situations rather fast and trust worthy. When humans are participating as a sensor to gather information it is important to use basic concepts of perception and thought.

The role of prescriptive models in learning

The main research question in this article concerns the added value of a prescriptive model in a simulation/gaming environment: KM Quest. KM Quest is meant to support students in the acquisition of both declarative and procedural knowledge in the domain of Knowledge Management (KM). The prescriptive model (KM model) embedded in the KM Quest environment describes the different steps that need to be taken while solving Knowledge Management problems. The main assumption is that because of the KM model, students more easily acquire knowledge about KM and that they need to use their metacognitive skills to a lesser extent since the KM model partly takes over regulation of learning in a new domain. These hypotheses are investigated in an experiment with two conditions: a no-model versus a model condition. The results of 46 students (23 in each condition) show that students in both conditions acquire declarative and procedural knowledge. Students in the model condition acquire more procedural knowledge and more KM model-specific procedural knowledge than students in the no-model condition. The model condition students also outperform the no-model condition students on a transfer test. However, students in the model condition spent much more time in the learning environment than the students in the no-model condition. Some exploratory evidence is presented that suggests that the inclusion of a prescriptive model changes the nature of the regulation: it appears that students in the model condition spend much time on regulating the use of the KM model, while the regulation activities of the no-model students concerns the domain of KM itself.

The solving of simple arithmetic story problems

Soon after their introduction to formal arithmetic, children are confronted with simple arithmetic story problems. The main question of this article is: how do children develop skill in the solving of these simple problems. And furthermore: is it possible to construct simulation models that adequately describe the varied behavior of children at different levels of skill. One of the main problems with the models presented thus far is that they are only capable of describing a limited part of childrens behavior that can be observed in daily life. The models presented in this study are an attempt to overcome this difficulty. Use has been made of the notion of “repair” to enhance the range of performance patterns of the different models. The output of five models has been compared to data gathered in an empirical study with 5-, 6-, 7-, and 8-year-olds. The results indicate that the five models do give a fairly adequate description of the behavior under study. The repair notion has been found to be useful in enlarging the scale of possible performance patterns and, consequently, the models are capable of describing a wide variety of empirical data.

The CREDIT project: Towards a generic framework for assessment and accreditation—a prototype for childcare

Many individuals throughout Europe acquire knowledge and skills in an informal manner for which they find no official recognition. Procedures for assessment and accreditation are meant to help individuals in finding recognition of previously gained competencies. The CREDIT (Capabilities, Registration, Evaluation, Diagnosis and advice through Internet Technology) project develops a computer system that supports the assessment and accreditation process and provides advice on further training possibilities tailored to the level of knowledge and skills of individuals.

Student Models, Scratch.Pads, and Simulation

The paper discusses the status of student models and it is proposed that in order to infer more subtle and complex student models from student’s behaviour, an electronic scratchpad or note-pad might be a valuable tool. A design methodology for these scratch-pads is explored. The method consists of a primary task analysis followed by a analysis of natural notes according to a scoring scheme based upon this task analysis. Special attention is given to notes that can not be classified. It is concluded that the task-analysis covers about 98% of the natural notes but that from the remaining 2% useful design criteria can be extracted. It is proposed that the point of view that for specific domains simulation can be seen as ‘runnable1 scratch-pads, might add futher design-criteria.

Interviews on AI and Education: Allan Collins and Stellan Ohlsson

In the series of interviews on AI and Education, this issue presents Stellan Ohlsson and Allan Collins. Both were asked the same four main questions:• What is your view regarding theories of learning and cognition.• How does your theoretical view relate to education in general?• What part can computers play in education?• What do you think of the future?