Learner-centered social support: enhancing online distance education for underserved rural high school students in the United States

Over the past decade, federal programs in the United States have largely addressed the well-documented problem of differences in basic access to technology between rural schools and their suburban and urban counterparts. Consequently, rural schools are better able to prepare their students for post-secondary education and the workplace where digital literacy is essential. As technology access improves, online distance education (ODE) is seen as a solution to significant challenges faced by rural schools, including a lack of highly-qualified teachers and declining population. However, ODE has high attrition rates, partly because participants’ social needs are often neglected. Additionally, students' success depends on their abilities to engage in self-regulated learning, effective time management and self-reflection, skills that many high school students are still developing. This paper describes an experimental research study funded by the U.S. Department of Education, currently underway in rural high schools across the U.S. The research adds to a growing body of work that attempts to expand understanding of the digital divide. Increasingly, schools realise that this is no longer an issue of mere access to equipment; education technology projects should incorporate strategies that ensure the success of previously marginalised communities. Our intervention, based on the APA’s Learner- Centered Principles, involves training on-site facilitators to provide social support for students involved in ODE. Preliminary findings indicate that the intervention group has a significantly lower dropout rate

Self-Directed Learning and the Impact of Leadership: Analyzing Keys for Success from a Covenental Perspective

The current state of education seems to beg for visionary changes to truly impact students and prepare them for the future. Self-directed learning models purport to do just that, by preparing students to be self-motivated, lifelong learners. While many educators seek to apply self-directed practices, research reveals that there are several obstacles that can hinder self-directed learning. Duby’s 2006 study of schools employing self-directed learning investigated how leaders successfully overcome these hindrances via specific leadership attitudes and behaviors that not only effectively overcame these obstacles, but are also reflected in the covenantal perspective of leadership. Using content analysis, this paper further explores the findings of Duby’s study of educational leaders, analyzing them within the covenantal construct developed by Fischer (2003), in order to better understand the relationship between effective leadership practice and the covenantal perspective. This study revealed intriguing similarities between particulars of the CFA model and the leadership practices exhibited in the self-directed learning schools. These similarities also present opportunities for future study, including whether visionary organizations are more apt to be motivated by covenantal principles and examining the type of for-profit organizations that are more apt to embody the tenets of CFA

Adaptive Guidance: Effects On Self-Regulated Learning In Technology-Based Training

Guidance provides trainees with the information necessary to make effective use of the learner control inherent in technology-based training, but also allows them to retain a sense of control over their learning (Bell & Kozlowski, 2002). One challenge, however, is determining how much learner control, or autonomy, to build into the guidance strategy. We examined the effects of alternative forms of guidance (autonomy supportive vs. controlling) on trainees’ learning and performance, and examined trainees’ cognitive ability and motivation to learn as potential moderators of these effects. Consistent with our hypotheses, trainees receiving adaptive guidance had higher levels of knowledge and performance than trainees in a learner control guidance. Controlling guidance had the most consistent positive impact on the learning outcomes, while autonomy supportive guidance demonstrated utility for more strategic outcomes. In addition, guidance was generally more effective for trainees with higher levels of cognitive ability and autonomy guidance served to enhance the positive effects of motivation to learn on the training outcomes

weSPOT: a cloud-based approach for personal and social inquiry

Scientific inquiry is at the core of the curricula of schools and universities across Europe. weSPOT is a new European initiative proposing a cloud-based approach for personal and social inquiry. weSPOT aims at enabling students to create their mashups out of cloud-based tools in order to perform scientific investigations. Students will also be able to share their inquiry accomplishments in social networks and receive feedback from the learning environment and their peers

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

weSPOT: A personal and social approach to inquiry-based learning

weSPOT is a new European initiative proposing a novel approach for personal and social inquiry-based learning in secondary and higher education. weSPOT aims at enabling students to create their mash-ups out of cloud based tools and services in order to perform scientific investigations. Students will also be able to share their inquiry accomplishments in social networks and receive feedback from the learning environment and their peers. This paper presents the research framework of the weSPOT project, as well as the initial inquiry-based learning scenarios that will be piloted by the project in real-life educational settings

Applying science of learning in education: Infusing psychological science into the curriculum

The field of specialization known as the science of learning is not, in fact, one field. Science of learning is a term that serves as an umbrella for many lines of research, theory, and application. A term with an even wider reach is Learning Sciences (Sawyer, 2006). The present book represents a sliver, albeit a substantial one, of the scholarship on the science of learning and its application in educational settings (Science of Instruction, Mayer 2011). Although much, but not all, of what is presented in this book is focused on learning in college and university settings, teachers of all academic levels may find the recommendations made by chapter authors of service. The overarching theme of this book is on the interplay between the science of learning, the science of instruction, and the science of assessment (Mayer, 2011). The science of learning is a systematic and empirical approach to understanding how people learn. More formally, Mayer (2011) defined the science of learning as the “scientific study of how people learn” (p. 3). The science of instruction (Mayer 2011), informed in part by the science of learning, is also on display throughout the book. Mayer defined the science of instruction as the “scientific study of how to help people learn” (p. 3). Finally, the assessment of student learning (e.g., learning, remembering, transferring knowledge) during and after instruction helps us determine the effectiveness of our instructional methods. Mayer defined the science of assessment as the “scientific study of how to determine what people know” (p.3). Most of the research and applications presented in this book are completed within a science of learning framework. Researchers first conducted research to understand how people learn in certain controlled contexts (i.e., in the laboratory) and then they, or others, began to consider how these understandings could be applied in educational settings. Work on the cognitive load theory of learning, which is discussed in depth in several chapters of this book (e.g., Chew; Lee and Kalyuga; Mayer; Renkl), provides an excellent example that documents how science of learning has led to valuable work on the science of instruction. Most of the work described in this book is based on theory and research in cognitive psychology. We might have selected other topics (and, thus, other authors) that have their research base in behavior analysis, computational modeling and computer science, neuroscience, etc. We made the selections we did because the work of our authors ties together nicely and seemed to us to have direct applicability in academic settings

Affective learning: improving engagement and enhancing learning with affect-aware feedback

This paper describes the design and ecologically valid evaluation of a learner model that lies at the heart of an intelligent learning environment called iTalk2Learn. A core objective of the learner model is to adapt formative feedback based on students’ affective states. Types of adaptation include what type of formative feedback should be provided and how it should be presented. Two Bayesian networks trained with data gathered in a series of Wizard-of-Oz studies are used for the adaptation process. This paper reports results from a quasi-experimental evaluation, in authentic classroom settings, which compared a version of iTalk2Learn that adapted feedback based on students’ affective states as they were talking aloud with the system (the affect condition) with one that provided feedback based only on the students’ performance (the non-affect condition). Our results suggest that affect-aware support contributes to reducing boredom and off-task behavior, and may have an effect on learning. We discuss the internal and ecological validity of the study, in light of pedagogical considerations that informed the design of the two conditions. Overall, the results of the study have implications both for the design of educational technology and for classroom approaches to teaching, because they highlight the important role that affect-aware modelling plays in the adaptive delivery of formative feedback to support learning

Learning and Work: Professional Learning Analytics

Learning for work takes various forms, from formal training to informal learning through work activities. In many work settings, professionals collaborate via networked environments leaving various forms of digital traces and “clickstream” data. These data can be exploited through learning analytics (LA) to make both formal and informal learning processes traceable and visible to support professionals with their learning. This chapter examines the state-of-the-art in professional learning analytics (PLA) by considering how professionals learn, putting forward a vision for PLA, and analyzing examples of analytics in action in professional settings. LA can address affective and motivational learning issues as well as technical and practical expertise; it can intelligently align individual learning activities with organizational learning goals. PLA is set to form a foundation for future learning and work