KEYNOTES

Vincent Aleven - An intelligent tutoring system that helps students learn to make good task selection decisions

Intelligent tutoring systems, which provide adaptive, individualized guidance to students when they engage in problem-solving practice, have been successful in helping students learn domain-specific skills and knowledge in many domains, including mathematics. They have not been as strong, however, in helping students learn to self-regulate their learning.  One thing self-regulated learners must do is make good task selection choices, but doing so is challenging. On the other hand, research in advanced learning technologies has shown that under certain circumstances, intelligent tutoring systems can make excellent (individualized) task selection decisions, but they tend to not grant students much (if any) autonomy in this regard. This leads to the question,  how can we have the best of both (many?) worlds: Give students the autonomy to select tasks, help them be motivated to learn and stretch themselves (i.e., a mastery orientation), and help them make good task selection decisions that lead to strong learning outcomes? I will present part of the PhD work of my former student Yanjin Long, who tackled these questions in a classroom study in middle schools, using an intelligent tutoring system for basic equation solving as research platform. No technical background is assumed!

Alexander Renkl - Learning Arrangements with High External Regulation: Why Fostering Learners' Self-regulation is of Special Importance

A typical assumption is that self-regulation is particularly important when students learn in open learning environments with little external guidance (regulation) (e.g., learning from an internet search). Although we see the kernel of truth in this assumption, we argue that fostering learners' self-regulation in learning environments with high external regulation (e.g., teacher-guided, direct instruction) is equally important in order to optimize meaningful learning. In the first part of this presentation, tried-and-tested theories of text learning and of example-based learning are used to show that self-regulation is crucial for effective learning, even when the students receive much guidance (external regulation). In the second part, we provide an overview of some of our own empirical studies showing that fostering students' self-regulation strategies fosters meaningful learning initiated by high external regulation.

PROJECT PRESENTATIES

Jeroen van Merrienboer geeft een inleiding op het thema van de dag. Zijn vier-componenten instructie-ontwerpmodel (4C/ID) ondersteunt het ontwerpen van onderwijs waarin leerlingen steeds meer de gelegenheid krijgen om hun leerproces te sturen, onder andere door ze geleidelijk meer zeggenschap te geven over het selecteren van leertaken. De geleidelijke overdracht van sturing van docent naar leerling is echter geen sinecure en goede richtlijnen daarvoor zijn zeer wenselijk.

Michelle Nugteren presenteert haar onderzoek over het aanleren van zelfregulatievaardigheden. In het bijzonder zal zij ingaan op het selecteren van oefentaken. Aan de hand van een nieuw model zal zij de verschillende factoren die belangrijk zijn voor het selecteren van taken toelichten, zoals het gebruik van zelfinschattingen en motivatie. Met deze factoren kunnen taken worden geselecteerd die goed aansluiten bij het huidige vaardigheidsniveau van de leerling. 

Steven Raaijmakers vertelt over zijn onderzoek naar het verbeteren van zelfregulatievaardigheden met behulp van videovoorbeelden. In deze videovoorbeelden laten fictieve leerlingen zien hoe zij hun leren reguleren. Daarnaast zal hij ingaan op het belang van transfer van deze vaardigheden naar andere vakken. Uit zijn onderzoek is gebleken dat training met videovoorbeelden het zelfgestuurd leren bevordert, maar dat er geen transfer optreedt naar andere vakken.

Jimmie Leppink presenteert zijn onderzoek naar het leren van zelfregulatievaardigheden met metacognitieve checklists.  Deze checklists bevatten richtinggevende vragen die leerlingen kunnen gebruiken tijdens zelfregulatie, bijvoorbeeld vragen over de ervaren moeilijkheid van een uitgevoerde taak en vragen met betrekking tot moeilijkheid en geboden ondersteuning bij een volgende taak. Resultaten laten zien dat sommige vragen het zelfregulatieproces gunstig kunnen beïnvloeden.

Jeroen van Merriënboer will introduce the topic of the day. His four-component instructional design (4C/ID) model supports the design of education in which students are given more and more opportunity to steer their own learning process, amongst others by gradually allowing them to choose their own learning activities. However, as this gradual transition from teacher-directed to student-directed has its challenges, clear guidelines for this transition are needed.

Michelle Nugteren will present her research on the development of self-regulated learning skills. In particular, she will discuss the process of selecting practice tasks. Through a new model, she will discuss a variety of factors that are important in this process, such as self-assessment and motivation, which can help students to choose practice tasks that match their current ability level.

Steven Raaijmakers will present his research on fostering self-regulated learning skills through modeling videos. In these videos, model students demonstrate how they regulate their learning. Additionally, he will discuss the importance of transfer of these skills to other domains. Research has shown that training through modeling videos may stimulate self-regulated learning, but there appears to be no transfer to other domains.

Jimmie Leppink will present his research on the development of self-regulated learning skills through metacognitive checklists. These checklists comprise directive questions that can be used by students to regulate their own learning, for example, questions on the experienced difficulty of a learning task and questions concerning the difficulty and level of instructional support provided in a subsequent learning task. Results demonstrate that some questions can positively influence self-regulated learning.