Improved computation of individual ZPD in a distance learning system

This paper builds upon theoretical studies in the field of social constructivism. Lev Vygotsky is considered one of the greatest representatives of this research line, with his theory of the Zone of Proximal Development (ZPD). Our work aims at integrating this concept in the practice of a computer-assisted learning system. For each learner, the system stores a model summarizing the current Student Knowledge (SK). Each educational activity is specified through the deployed content, the skills required to tackle it, and those acquired, and is further annotated by the effort estimated for the task. The latter may change from one student to another, given the already achieved competence. A suitable weighting of the robustness (certainty) of student’s skills, stored in SK, and their combination are used to verify the inclusion of a learning activity in the student’s ZPD. With respect to our previous work, the algorithm for the calculation of the ZPD of the individual student has been optimized, by enhancing the certainty weighting policy, and a graphical display of the ZPD has been added. Thanks to the latter, the student can get a clear vision of the learning paths that he/she can presently tackle. This both facilitates the educational process, and helps developing the metacognitive ability self-assessment

Personalised Learning: Developing a Vygotskian Framework for E-learning

Personalisation has emerged as a central feature of recent educational strategies in the UK and abroad. At the heart of this is a vision to empower learners to take more ownership of their learning and develop autonomy. While the introduction of digital technologies is not enough to effect this change, embedding the affordances of new technologies is expected to offer new routes for creating personalised learning environments. The approach is not unique to education, with consumer technologies offering a 'personalised' relationship which is both engaging and dynamic, however the challenge remains for learning providers to capture and transpose this to educational contexts. As learners begin to utilise a range of tools to pursue communicative and collaborative actions, the first part of this paper will use analysis of activity logs to uncover interesting trends for maturing e-learning platforms across over 100 UK learning providers. While personalisation appeals to marketing theories this paper will argue that if learning is to become personalised one must ask what the optimal instruction for any particular learner is? For Vygotsky this is based in the zone of proximal development, a way of understanding the causal-dynamics of development that allow appropriate pedagogical interventions. The second part of this paper will interpret personalised learning as the organising principle for a sense-making framework for e-learning. In this approach personalised learning provides the context for assessing the capabilities of e-learning using Vygotsky’s zone of proximal development as the framework for assessing learner potential and development

INVESTIGATING AGENT AND TASK OPENNESS IN ADHOC TEAM FORMATION

When deciding which ad hoc team to join, agents are often required to consider rewards from accomplishing tasks as well as potential benefits from learning when working with others, when solving tasks. We argue that, in order to decide when to learn or when to solve task, agents have to consider the existing agents’ capabilities and tasks available in the environment, and thus agents have to consider agent and task openness—the rate of new, previously unknown agents (and tasks) that are introduced into the environment. We further assume that agents evolve their capabilities intrinsically through learning by observation or learning by doing when working in a team. Thus, an agent will need to consider which task to do or which team to join would provide the best situation for such learning to occur. In this thesis, we develop an auction-based multiagent simulation framework, a mechanism to simulate openness in our environment, and conduct comprehensive experiments to investigate the impact of agent and task openness. We propose several agent task selection strategies to leverage the environmental openness. Furthermore, we present a multiagent solution for agent-based collaborative human task assignment when finding suitable tasks for users in complex environments is made especially challenging by agent openness and task openness. Using an auction-based protocol to fairly assign tasks, software agents model uncertainty in the outcomes of bids caused by openness, then acquire tasks for people that maximize both the user’s utility gain and learning opportunities for human users (who improve their abilities to accomplish future tasks through learning by experience and by observing more capable humans). Experimental results demonstrate the effects of agent and task openness on collaborative task assignment, the benefits of reasoning about openness, and the value of non-myopically choosing tasks to help people improve their abilities for uncertain future tasks

Pedagogic approaches to using technology for learning: literature review

This literature review is intended to address and support teaching qualifications and CPD through identifying new and emerging pedagogies; "determining what constitutes effective use of technology in teaching and learning; looking at new developments in teacher training qualifications to ensure that they are at the cutting edge of learning theory and classroom practice and making suggestions as to how teachers can continually update their skills." - Page 4

EU–originated MOOCs, with focus on multi- and single-institution platforms

No abstract available

Building an Adaptive Culture where Collaborative Teaching Teams Leverage Data to Improve Student Achievement and Wellbeing

This Organizational Improvement Plan (OIP) seeks to open up the black box of classroom teaching to data informed collaborative inquiry by teachers for teachers using formative feedback as the model for instructional improvement. Teacher collective efficacy is developed through ongoing professional learning in collaborative teaching teams that use multiple measures of data to limit bias and improve equity of outcomes for students. Such a process is iterative, and the OIP envisions the combined use of adaptive leadership and distributed leadership approaches to support Kotter’s 8-step model for change implementation. The desired outcome is an adaptive and agile school culture where teachers are empowered to use data in collaborative teams. A distributed leadership team will develop a culture of collaborative inquiry and improve data literacy within teaching teams to create school level narratives of student achievement and growth. This OIP applies critical theory frameworks of empowerment and liberation to data generated in schools with the firm belief that teachers and students who generate data must be empowered to analyse and use such data for self-improvement. This shift from the evaluative use of data for school ranking to the use of data by collaborative teams of teacher leaders as formative feedback for self-improvement is an act of resistance to the colonial use of data in 21st century neoliberal accountability regimes. A successful implementation of this OIP seeks to return sense-making of knowledge back to teachers as professionals and students as partners in learning through data-informed, collaborative decision making