An assessment of warm fog: Nucleation, control, and recommended research

A state-of-the-art survey is given of warm fog research which has been performed up to, and including, 1974. Topics covered are nucleation, growth, coalescence, fog structures and visibility, effects of surface films, drop size spectrum, optical properties, instrumentation, liquid water content, condensation nuclei. Included is a summary of all reported fog modification experiments. Additional data is provided on air flow, turbulence, a summary of recommendations on instruments to be developed for determining turbulence, air flow, etc., as well as recommendations of various fog research tasks which should be performed for a better understanding of fog microphysics

Interaction between water vapor and pure silver iodide in the vicinity of saturation, The

January 1971.Includes bibliographical references.Sponsored by the National Science Foundation GA-11309

Enhancing the ethical use of learning analytics in Australian higher education

Ensuring the ethical use of data about students is an important consideration in the use of learning analytics in Australian higher education. In early 2019 a discussion paper was published by a group of learning analytics specialists in the sector to help promote the conversation around the key ethical issues institutions need to address in order to ensure the ethical use of learning analytics. This panel session will explore these ethical issues in more detail and update the conversation with new perspectives and provocations. The panel will include authors of the discussion paper and structured so the audience will have an active role in considering the key issues and advancing the ongoing conversations about these important issues

Enriching Pre-Clinical Education with Near-Peer Learning Experiences

The purpose of this mixed methods study was to examine the outcomes of two instructional methodologies (traditional and peer-assisted learning; PAL) used in a clinical methods course for undergraduate speech-language pathology (SLP) students. The sample included 53 undergraduate SLP students (near-peer learners) as well as 27 graduate SLP students and 7 clinical fellows (near-peer tutors). Traditional instruction was used during the first half of the course and PAL was added during the second half. The undergraduate SLP students’ weekly written reflections and grades (mid-term and final) were collected for analysis. Students demonstrated a preference for peer- and near-peer learning experiences and commented positively on learning via stories throughout the course. They exhibited more positive attitudes during PAL instruction. Further, students reported less clinical confidence and more confusion as the course progressed and they learned more about the demands and expectations for clinical practice. Implications and recommendations for SLP students’ clinical training are discussed

The Potential for Student Performance Prediction in Small Cohorts with Minimal Available Attributes

The measurement of student performance during their progress through university study provides academic leadership with critical information on each student’s likelihood of success. Academics have traditionally used their interactions with individual students through class activities and interim assessments to identify those “at risk” of failure/withdrawal. However, modern university environments, offering easy on-line availability of course material, may see reduced lecture/tutorial attendance, making such identification more challenging. Modern data mining and machine learning techniques provide increasingly accurate predictions of student examination assessment marks, although these approaches have focussed upon large student populations and wide ranges of data attributes per student. However, many university modules comprise relatively small student cohorts, with institutional protocols limiting the student attributes available for analysis. It appears that very little research attention has been devoted to this area of analysis and prediction. We describe an experiment conducted on a final-year university module student cohort of 23, where individual student data are limited to lecture/tutorial attendance, virtual learning environment accesses and intermediate assessments. We found potential for predicting individual student interim and final assessment marks in small student cohorts with very limited attributes and that these predictions could be useful to support module leaders in identifying students potentially “at risk.”.Peer reviewe

Weather modification by carbon dust absorption of solar energy

July, 1974.Includes bibliographical references

Completing the loop: Returning learning analytics to teachers

This paper provides an outline of an Australian Government Office of Learning and Teaching project that aims to investigate and then develop ways in which learning analytics data can be more usefully harnessed by academic teachers in higher education. Fundamental to this project is linking the learning design of online tasks provided to students with the learning analytic affordances of the technology-based tools that support them. The paper provides an outline of the background to the project, including its conceptual underpinnings, and sets out the program of research and development. The expected outcomes of the project are discussed

Loop: A learning analytics tool to provide teachers with useful data visualisations

One of the great promises of learning analytics is the ability of digital systems to generate meaningful data about students’ learning interactions that can be returned to teachers. If provided in appropriate and timely ways, such data could be used by teachers to inform their current and future teaching practice. In this paper we showcase the learning analytics tool, Loop, which has been developed as part of an Australian Government Office of Learning and Teaching project. The project aimed to develop ways to deliver learning analytics data to academics in a meaningful way to support the enhancement of teaching and learning practice. In this paper elements of the tool will be described. The paper concludes with an outline of the next steps for the project including the evaluation of the effectiveness of the tool