Education and self-regulation of learning for gifted pupils: Systemic design and development.

Gifted pupils differ from their age-mates with respect to development potential, actual competencies, self-regulatory capabilities, and learning styles in one or more domains of competence. The question is how to design and develop education that fits and further supports such characteristics and competencies of gifted pupils. Analysis of various types of educational interventions for gifted pupils reflects positive cognitive or intellectual effects and differentiated social comparison or group-related effects on these pupils. Systemic preventive combination of such interventions could make these more effective and sustainable. The systemic design is characterised by three conditional dimensions: differentiation of learning materials and procedures, integration by and use of ICT support, and strategies to improve development and learning. The relationships to diagnostic, instructional, managerial, and systemic learning aspects are expressed in guidelines to develop or transform education. The guidelines imply the facilitation of learning arrangements that provide flexible self-regulation for gifted pupils. A three-year pilot in Dutch nursery and primary school is conducted to develop and implement the design in collaboration with teachers. The results constitute prototypes of structured competence domains and supportive software. These support the screening of entry characteristics of all four-year old pupils and assignment of adequate play and learning processes and activities throughout the school career. Gifted and other pupils are supported to work at their actual achievement or competency levels since their start in nursery school, in self-regulated learning arrangements either in or out of class. Each pupil can choose other pupils to collaborate with in small groups, at self-chosen tasks or activities, while being coached by the teacher. Formative evaluation of the school development process shows that the systemic prevention guidelines seem to improve learning and social progress of gifted pupils, including their self-regulation. Further development and implementation steps are discussed.

Learning for self-regulation: Improving instructional benefits for pupils, teachers, parents, schools, and society at large

Compulsory education laws oblige primary and secondary schools to give each pupil positive encouragement in, for example, social, emotional, cognitive, creative, and ethical respects. This is a fairly smooth process for most pupils, but it is not as easy to achieve with others. A pattern of pupil, home or family, and school variables turns out to be responsible for a long-term process that may lead to a pupil’s dropping out of education. A systemic approach will do much to introduce more clarity into the diagnosis, potential reduction and possible prevention of some persistent educational problems that express themselves in related phenomena, for example low school motivation and achievement; forced underachievement of high ability pupils; concentration of bullying and violent behaviour in and around some types of classes and schools; and drop-out percentages that are relatively constant across time. Such problems have a negative effect on pupils, teachers, parents, schools, and society alike. In this address, I would therefore like to clarify some of the systemic causes and processes that we have identified between specific educational and pupil characteristics. Both theory and practice can assist in developing, implementing, and checking better learning methods and coaching procedures, particularly for pupils at risk. This development approach will take time and require co-ordination, but it will result in much better processes and outcomes than we are used to. First, I will diagnose some systemic aspects of education that do not seem to optimise the learning processes and school careers of some types of pupils in particular. Second, I will specify cognitive, social, motivational, and self-regulative aspects of learning tasks and relate corresponding learning processes to relevant instructional and wider educational contexts. I will elaborate these theoretical notions into an educational design with systemic instructional guidelines and multilevel procedures that may improve learning processes for different types of pupils. Internet-based Information and Communication Technology, or ICT, also plays a major role here. Third, I will report on concrete developments made in prototype research and trials. The development process concerns ICT-based differentiation of learning materials and procedures, and ICT-based strategies to improve pupil development and learning. Fourth, I will focus on the experience gained in primary and secondary educational practice with respect to implementation. We can learn much from such practical experience, in particular about the conditions for developing and implementing the necessary changes in and around schools. Finally, I will propose future research. As I hope to make clear, theory-based development and implementation research can join forces with systemic innovation and differentiated assessment in educational practice, to pave the way for optimal “learning for self-regulation” for pupils, teachers, parents, schools, and society at large.

Validation of the self-regulated online learning questionnaire

Abstract The number of students engaged in Massive Open Online Courses (MOOCs) is increasing rapidly. Due to the autonomy of students in this type of education, students in MOOCs are required to regulate their learning to a greater extent than students in traditional, face-to-face education. However, there is no questionnaire available suited for this online context that measures all aspects of self-regulated learning (SRL). In this study, such a questionnaire is developed based on existing SRL questionnaires. This is the self-regulated online learning ques- tionnaire. Exploratory factor analysis (EFA) on the first dataset led to a set of scales differing from those theoretically defined beforehand. Confirmatory factor analysis (CFA) was conducted on a second dataset to compare the fit of the theoretical model and the exploratively obtained model. The exploratively obtained model provided much better fit to the data than the theoretical model. All models under investigation provided better fit when excluding the task strategies scale and when merging the scales measuring metacognitive activities. From the results of the EFA and the CFA it can be concluded that further development of the questionnaire is necessary.