CALL FOR PAPER SUBMISSIONS FOR SPECIAL ISSUE OF TECHNOLOGY, INSTRUCTION, COGNITION AND LEARNING (TICL) ON ROLE OF DATA IN INSTRUCTIONAL PROCESSES Co-editor: Arnon Hershkovitz, Teachers College, Columbia University. Please send all submissions and enquiries to the co-editor by email, arnon.hershkovitz@xxxxxxxxx. *** Important Dates *** July 10, 2013 - Submission of extended abstracts (up to 1,000 words, including references) July 31, 2013 - Authors' notification (abstracts) September 30, 2013 - Submission of full papers November 30, 2013 - Authors' notification (full papers) March 2014 (expected) - Special issue publication *** Topics of interest *** This special issue is designed to discuss the role of data in instructional processes, from the point of view of either the instructor of the learner (or both). Relevant topics for this special issue include, but are not limited to the role of data in: * Feedback mechanisms to students/instructors * Reflective tools for students * Practical tools for instructors * Visualizations as a tool to improve learning/teaching * Advancements in learning/instructing support for ill-defined domains * Novel Learning Analytics or Educational Data Mining applications * Adaptive systems * Supporting meta-cognition, affect * Enabling human interventions in computer-based learning * Tools for supporting collaboration and/or social learning *** Aim of the Special Issue *** Following the explosion in data available about learning processes, Learning Analytics (LA) and Educational Data Mining (EDM) have established their status and are now widely recognized as legitimate and important disciplines for studying various topics in education. Data-driven studies have shed light on various aspects of technology-based learning and teaching processes, allowing new insights on classical theories, and enabling new advancements in many aspects of instructional processes. These insights and improvements have great potential (which in many cases is already fulfilled) to affect everyday technology-enhanced teaching and learning. Technology, Instruction, Cognition and Learning (TICL) is a journal primarily interested in issues in the intersection point of these four disciplines; its vision is to improve interdisciplinary communication and to promote scientific dialogue on fundamental issues and technological developments having important implications for future advances. As data-driven research had matured dramatically, and as much evidence have been gathered already regarding their importance in instructional processes, it is the purpose of this special issue to discuss the role of data in instruction from various - including criticizing - points of view. The editors are seeking papers that present and discuss data-driven advancements in technology-enhanced instruction (implemented for students, instructors, or both). Our focus is on empirical examination - from theoretical perspectives of instruction/learning - of the value of different implementations. Preliminary findings from state-of-the-art implementations are also encouraged. The optimal paper would analyze a given data-driven implementation based on a certain instructional theory (or a set of such theories), focusing on the benefits and challenges of this implementation, and on its contribution to both practice and theory. All disciplines and all age groups, as well as all research methods and all technology-based systems, are relevant for this special issue.