This presentation has three parts: Analyzing different Perspectives on Personalization and Learning in Formal Education and VLE Discussion a Conceptual Framework for providing Personalized Feedback Presentation of a Prototype for providing personalized Feedback in Moodle
Outline of Part 1
If Educators speak of Personalization they usually refer to the following three concepts Constructivism Self-regulated Learning Reflective Thinking Constructivism refers to the relevance of interacting with an environment for creating coherent models of this environment Reflective Thinking refers to the cognitive processes that are related to understanding and generalization SRL refers to control processes that link interactions and cognitive processes in terms of goal setting and decision making
All three educational concepts are closely related to motivation. In the literature, motivation depends on The ability of learners to control their own learning processes The insight of learners to the personal value of performing a task (self-determination) The estimation of learners of being able to successfully perform a task (self-efficacy)
The three key factors of motivation appear to be dependent on and to be influenced by the learners’ perception of the following dimensions: Participation Reflection Ownership Regulation Diversity Participation refers to the extent to which learners are able to contribute to learning processes, be it in classes of in group work. This dimension is related to controllability and self-efficacy factors of motivation. Reflection refers to which extent learners are encouraged to reason about their experiences. This dimension is related to controllability factor of motivation Ownership refers to which extent learners can identify themselves with their own learning processes and take responsibility for them. This dimension is related to the task value factor of motivation. Regulation refers to which extent learners can control the different aspects of their learning activities. This is a direct consequence of the controllability factor of motivation Diversity refers to the freedom of choosing different approaches and learning paths to achieve learning goals. This dimension integrates controllability, self-efficacy and task value factors of motivation.
In virtual learning environments the motivational factors are constrained by the access to relevant information. This is part of the controllability factor of motivation and has been analysed extensively by Jon Dron. In VLEs four levels of control can get distinguished: System control Organizational control Teacher control Learner control System control refers to constraints of the system in use. These constraints are due to design decisions of system developers. These constraints are shared by all instances of one VLE Organizational Control refers to the constraints that are related to one organisational regulations and management decisions. These constraints are particular to one instance of a VLE, although these constraints are not necessarily reinforced by the system. Teacher control refers to the constraints that are related to the instructional design and the didactics that were chosen by teachers. These constraints are only related to one particular course in a VLE. (The specifications IMS Learning Design and IMS Simple Sequencing focus at his level) Learner control refers to what is actually available and controllable by learners. This includes accessing learning resources, taking assessment, contributing to discussion forums, or access to system information.
The discussion related to personal versus virtual learning environments the emphasis lies on the levels Teacher control vs. Learner control. However, most restrictions in all kinds of PLEs and VLEs is constrained by the system design of the environment in use. This includes the decision that particular information is only available to specific roles of a system. In the context of formal learning organizational decisions regulate how and to what extent an instance of a VLE can be used. This includes aspects such as “corporate identity”, “privacy” and “data security” but also the availability of components of a VLE. These decisions are often taken by system administrators and technical advisors . Teachers then have only control about what tools they choose for their course and what learning material they choose to use. Interestingly many teachers choose to go what has been defaulted by the system or the organization. Learners are usually considered only to participate to courses, but not to control parts of their learning environment.
The goal of linking personalization and learning is to enrich learning experiences and to improve the learning efficiency of the individual learner. From the previous remarks three aspects are important to consider: Learning is an active process of each learner. Therefore, learners must not be considered as recipients rather than actors that participate in and contribute to the social process of teaching and learning. Because learning is a personal process of each student in a course or class, learners require a certain amount of autonomy over their personal learning experiences. In order to become active, it is important to focus the learner’s perception and awareness on relevant aspects of the learning process.
Given to these remarks, personalisation in VLEs can be defined as one approach to enable learners for taking control over the ways how learners construct knowledge and develop their competences. This does not necessarily implies that learners to have all the control in a virtual learning environment, but they need the room for developing their autonomous decisions and managing their tasks.
Given to the educational concepts, learning is an interactive process between an actor (the learner) with a system (the learning environment). For our research we apply and extended model for motivation and self-regulation proposed by Butler & Winne. The extension has been influenced by the ideas of context aware and adaptive systems. From the perspective of this model the personalization problem is related to the following question. how to arrange and influence the interaction between the actor with the system from the system side? Our previous research suggests a four level information processing pipeline at the system side. The sensor layer capturers the interactions of an actor with the system. This can include all possible types of actions that an actor can perform with a system The semantic layer selects, combines and focuses on particular aspects of the captured actions. This process is often referred to as semantic enrichment. The control layer refers to the arrangement and integration of selected information. Arrangement puts different sets of information into relation. Integration uses the selected information to infer further intelligence. Rule based engines (such as IMS LD run time engines) operate at the Arrangement level. Self-adaptive systems (such as Recommender Systems) operate at the level of integration. The indicator layer is responsible for the appropriate presentation mode for the interaction with the actor.
One way of supporting self-regulation in learning is providing feedback through mirroring. This technique provides a selected perspective on the learners actions as it has been perceived by the system.
In interactive systems mirroring approaches can be distinguished regarding their interactivity and their responsiveness. Interestingly, no VLE and PLE makes information available to the learners.
The following slides present a prototype of a mirroring plug-in for the moodle VLE. This prototype is a non-interactive approach using selected aspects of live tracking data of the moodle system (direct responsiveness)
The plug-in allows to arrange and to visualize different tracking information to the learners. We call these visualizations “activity indicators”. This allows the learners to inspect their learning activities from different perspectives.
The first indicator is a time tracking visualization. This indicator shows the time a learner has spent in the course. This information is not the absolute time a learner has effectively spent with the course rather than the estimated time that can be inferred from moodle’s system logs.
The second indicator arranges the number of actions that were performed by a learner and puts this information in relation to the average actions of the other participants in the course. The two numbers are visualised as bar charts so the students can compare their action with the rest of the group. By default the maximum of both charts is the number of actions that the teacher has predefined as a minimum requirement. If the learners proceed to be active in the course beyond this “yard stick”, this reference point turn into a marker that will move towards the left the more actions are performed. This allows learners to inspect their personal actions in relation to other participants in a course.
Personalisation Of Learning In Virtual Learning Environments
Personalisation of Learning in Virtual Learning Environments Dominique Verpoorten, Christian Glahn Milos Kravcik, Stefaan Ternier & Marcus Specht Open University of the Netherlands ECTEL’09 1 October 2009, Nice, FR
Personalisation and Learning Control Motivation Educational Concepts Dimensions
Thank you <ul><li>Christian Glahn </li></ul><ul><li>CELSTEC </li></ul><ul><li>Open University of the Netherlands </li></ul><ul><li>christian DOT glahn AT ou DOT nl </li></ul><ul><li>http://moodle.org/mod/data/view.php?d=13&rid=2582 </li></ul><ul><li>http://www.slideshare.com/phish108 </li></ul>