311,612 research outputs found

    An Online Tutor for Astronomy: The GEAS Self-Review Library

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    We introduce an interactive online resource for use by students and college instructors in introductory astronomy courses. The General Education Astronomy Source (GEAS) online tutor guides students developing mastery of core astronomical concepts and mathematical applications of general astronomy material. It contains over 12,000 questions, with linked hints and solutions. Students who master the material quickly can advance through the topics, while under-prepared or hesitant students can focus on questions on a certain topic for as long as needed, with minimal repetition. Students receive individual accounts for study and course instructors are provided with overview tracking information, by time and by topic, for entire cohorts of students. Diagnostic tools support self-evaluation and close collaboration between instructor and student, even for distance learners. An initial usage study shows clear trends in performance which increase with study time, and indicates that distance learners using these materials perform as well as or better than a comparison cohort of on-campus astronomy students. We are actively seeking new collaborators to use this resource in astronomy courses and other educational venues.Comment: 15 pages, 9 figures; Vogt, N. P., and A. S. Muise. 2015. An online tutor for general astronomy: The GEAS self-review library. Cogent Education, 2 (1

    High-resolution temporal profiling of transcripts during Arabidopsis leaf senescence reveals a distinct chronology of processes and regulation

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    Leaf senescence is an essential developmental process that impacts dramatically on crop yields and involves altered regulation of thousands of genes and many metabolic and signaling pathways, resulting in major changes in the leaf. The regulation of senescence is complex, and although senescence regulatory genes have been characterized, there is little information on how these function in the global control of the process. We used microarray analysis to obtain a highresolution time-course profile of gene expression during development of a single leaf over a 3-week period to senescence. A complex experimental design approach and a combination of methods were used to extract high-quality replicated data and to identify differentially expressed genes. The multiple time points enable the use of highly informative clustering to reveal distinct time points at which signaling and metabolic pathways change. Analysis of motif enrichment, as well as comparison of transcription factor (TF) families showing altered expression over the time course, identify clear groups of TFs active at different stages of leaf development and senescence. These data enable connection of metabolic processes, signaling pathways, and specific TF activity, which will underpin the development of network models to elucidate the process of senescence

    Effective online interaction: mapping course design to bridge from research to practice

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    Quantitative and qualitative research of a case study course confirmed that the course achieved a highly interactive learning experience, associated with more effective student support and high student retention. Computer conferencing achieved high participation from the beginning and evidence of dialogue and argumentation within online tutor groups. This was achieved not by active tutor moderation but by a sequence of structured tasks. Compendium mind mapping software has been used to represent the design of this sequence of tasks and this has refined interpretation of the research findings. The positive outcomes identified relate not purely to computer conferencing but to an integration of individual and group tasks feeding forward into a well-designed assignment. The usability of case study data relates to the ability of practitioners to compare their own context with that of the case. The visual representation of the design of the task sequence is providing a better bridge from the research to the practice context than the use of general description of findings alone. This is particularly important in an area which has generated a range of sometimes conflicting findings, with weak links to the challenges of course design

    Dialogue as Data in Learning Analytics for Productive Educational Dialogue

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    This paper provides a novel, conceptually driven stance on the state of the contemporary analytic challenges faced in the treatment of dialogue as a form of data across on- and offline sites of learning. In prior research, preliminary steps have been taken to detect occurrences of such dialogue using automated analysis techniques. Such advances have the potential to foster effective dialogue using learning analytic techniques that scaffold, give feedback on, and provide pedagogic contexts promoting such dialogue. However, the translation of much prior learning science research to online contexts is complex, requiring the operationalization of constructs theorized in different contexts (often face-to-face), and based on different datasets and structures (often spoken dialogue). In this paper, we explore what could constitute the effective analysis of productive online dialogues, arguing that it requires consideration of three key facets of the dialogue: features indicative of productive dialogue; the unit of segmentation; and the interplay of features and segmentation with the temporal underpinning of learning contexts. The paper thus foregrounds key considerations regarding the analysis of dialogue data in emerging learning analytics environments, both for learning-science and for computationally oriented researchers
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