A Self-Regulated Learning Approach to Educational Recommender Design

Recommender systems, or recommenders, are information filtering systems prevalent today in many fields. One type of recommender found in the field of education, the educational recommender, is a key component of adaptive learning solutions as these systems avoid “one-size-fits-all” approaches by tailoring the learning process to the needs of individual learners. To function, these systems utilize learning analytics in a student-facing manner. While existing research has shown promise and explores a variety of types of educational recommenders, there is currently a lack of research that ties educational theory to the design and implementation of these systems. The theory considered here, self-regulated learning, is underexplored in educational recommender research. Self-regulated learning advocates a cyclical feedback loop that focuses on putting students in control of their learning with consideration for activities such as goal setting, selection of learning strategies, and monitoring of one’s performance. The goal of this research is to explore how best to build a self-regulated learning guided educational recommender and discover its influence on academic success. This research applies a design science methodology in the creation of a novel educational recommender framework with a theoretical base in self-regulated learning. Guided by existing research, it advocates for a hybrid recommender approach consisting of knowledge-based and collaborative filtering, made possible by supporting ontologies that represent the learner, learning objects, and learner actions. This research also incorporates existing Information Systems (IS) theory in the evaluation, drawing further connections between these systems and the field of IS. The self-regulated learning-based recommender framework is evaluated in a higher education environment via a web-based demonstration in several case study instances using mixed-method analysis to determine this approach’s fit and perceived impact on academic success. Results indicate that the self-regulated learning-based approach demonstrated a technology fit that was positively related to student academic performance while student comments illuminated many advantages to this approach, such as its ability to focus and support various studying efforts. In addition to contributing to the field of IS research by delivering an innovative framework and demonstration, this research also results in self-regulated learning-based educational recommender design principles that serve to guide both future researchers and practitioners in IS and education

Responsive Open Learning Environments at the Open University

Personal Learning Environments (PLEs) offer new opportunities for supporting personalized and self regulated learning both in formal and in informal education. The Open University in the UK is an early adopter of PLEs through a number of different initiatives, one of which is the European project ROLE (Responsive Open Learning Environments). This paper presents some of the lessons learned and best practices from the introduction of ROLE technologies within an informal learning test-bed at the Open University

Affective neuroscience, emotional regulation, and international relations

International relations (IR) has witnessed an emerging interest in neuroscience, particularly for its relevance to a now widespread scholarship on emotions. Contributing to this scholarship, this article draws on the subfields of affective neuroscience and neuropsychology, which remain largely unexplored in IR. Firstly, the article draws on affective neuroscience in illuminating affect's defining role in consciousness and omnipresence in social behavior, challenging the continuing elision of emotions in mainstream approaches. Secondly, it applies theories of depth neuropsychology, which suggest a neural predisposition originating in the brain's higher cortical regions to attenuate emotional arousal and limit affective consciousness. This predisposition works to preserve individuals' self-coherence, countering implicit assumptions about rationality and motivation within IR theory. Thirdly, it outlines three key implications for IR theory. It argues that affective neuroscience and neuropsychology offer a route towards deep theorizing of ontologies and motivations. It also leads to a reassessment of the social regulation of emotions, particularly as observed in institutions, including the state. It also suggests a productive engagement with constructivist and poststructuralist approaches by addressing the agency of the body in social relations. The article concludes by sketching the potential for a therapeutically-attuned approach to IR

A semantic framework for cloud learning environments

Cloud Learning Environments (CLEs) are gradually gaining ground over traditional Learning Management Systems (LMS) by facilitating the lone or collaborative study of user-chosen blends of content and courses from heterogeneous sources, including Open Educational Resources (OER). In this chapter, we describe the use of ontologies for modelling various aspects of the learning process within such an environment. In particular, we consider a semantic knowledge base as the core of the learning environment, facilitating learners in finding educational services on the cloud. We describe how different stakeholder clusters are involved in the creation and maintenance of this knowledge base, through collaborative ontology management techniques. Finally, we define the mechanisms for the evolution of this knowledge base and the constant updating of the associated cloud learning services

Yeast gene CMR1/YDL156W is consistently co-expressed with genes participating in DNA-metabolic processes in a variety of stringent clustering experiments

© 2013 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0/, which permits unrestricted use, provided the original author and source are credited.The binarization of consensus partition matrices (Bi-CoPaM) method has, among its unique features, the ability to perform ensemble clustering over the same set of genes from multiple microarray datasets by using various clustering methods in order to generate tunable tight clusters. Therefore, we have used the Bi-CoPaM method to the most synchronized 500 cell-cycle-regulated yeast genes from different microarray datasets to produce four tight, specific and exclusive clusters of co-expressed genes. We found 19 genes formed the tightest of the four clusters and this included the gene CMR1/YDL156W, which was an uncharacterized gene at the time of our investigations. Two very recent proteomic and biochemical studies have independently revealed many facets of CMR1 protein, although the precise functions of the protein remain to be elucidated. Our computational results complement these biological results and add more evidence to their recent findings of CMR1 as potentially participating in many of the DNA-metabolism processes such as replication, repair and transcription. Interestingly, our results demonstrate the close co-expressions of CMR1 and the replication protein A (RPA), the cohesion complex and the DNA polymerases α, δ and ɛ, as well as suggest functional relationships between CMR1 and the respective proteins. In addition, the analysis provides further substantial evidence that the expression of the CMR1 gene could be regulated by the MBF complex. In summary, the application of a novel analytic technique in large biological datasets has provided supporting evidence for a gene of previously unknown function, further hypotheses to test, and a more general demonstration of the value of sophisticated methods to explore new large datasets now so readily generated in biological experiments.National Institute for Health Researc

Action theory in Habermas and educational practices

In this paper I explore the potential for viewing education as an “unrestricted communication community” (Habermas 1990: 88), using categorisations from Habermas of different kinds of action as analytical tools for examining educational practices. For the paper, I pursue two main themes: 1) how the concept of communicative action in relation to the three forms of knowledge-constitutive interest (Habermas 1987) can be operationalised in educational discourse 2) how the distinguishing of communicative action and discourse ethics from other forms of action may be used to understand the interaction taking place in educational contexts to develop evaluative tools for examining teaching practices. The potential of this framework for encouraging critical reflection on teaching, on critical incidents in teaching, peer observation, or tutor observation of novice practitioners is also discussed in relation to the forms of reflexivity that Habermas identifies as necessary conditions of human freedom (1996). Taken together, these different constructs form a powerful framework for critically examining the truth and validity claims both explicitly made and implied in educational practices from the perspectives of the individual as well as the professional community to which the individual belongs. It is accepted that a rational, communicative action aimed at reaching consensus does not necessarily dominate either the school or the higher education institution’s normal mode of discourse. Thus, the paper also differentiates other forms of action, incorporating these into the overall critical framework

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Topic Maps as Indexing Tools in the Educational Sphere: Theoretical Foundations, Review of Empirical Research and Future Challenges

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