238 research outputs found
Sponsored Article: Women In STEM: Interview with Anna Rafferty
No full textEncouraging diversity in the workplace has the potential to “change the trajectory of health for humanity” says Anna Rafferty, Director of Strategy at Johnson & Johnson Campus, Ireland. Promoting such representation, particularly in the area of STEM, has been one of the key aims of Johnson & Johnson’s WiSTEM2D undergraduate programme since its creation in 2016.
As a leader of this programme, Anna started her career with Johnson & Johnson in 2003 after graduating with a BSc in Biotechnology from the National University of Ireland, Galway, and later a Graduateship in Marketing from the Technological University of Dublin. She is now a central figure in the undergraduate WiSTEM2D programme in Ireland.
We spoke to Anna about the about the WiSTEM2D programme, the difficulties and challenges faced by women in STEM careers, and what she believes universities can do about it
Curation - space as an aesthetic property: Anna Rafferty
No full textThese films show examples of different approaches to display and its impact on the development of ideas. The presentation or curation of work should not necessarily be the last stage of creative practice. A viewers’ interpretation of an artwork can be drastically informed by its presentation - their first impression as they walk towards it, how their eyes are guided around it and move from one work to another. These considerations can become part of a works development, an artist making changes in order to manipulate the viewers’ experience. In this video Anna Rafferty describes her presentational approach
Connecting Instructors and Learning Scientists via Collaborative Dynamic Experimentation
No full textThe shift to digital educational resources provides new opportunities to advance psychology and education research, in tandem with improving instruction using theory and data. To realize this potential, this paper explores how randomized experiments can support mutually beneficial instructor-researcher collaborations. We developed the Collaborative Dynamic Experimentation (CDE) framework to address two key tensions. To enable researchers to embed experiments in online lessons while maintaining instructors' editorial control, Collaborative experiment authoring is needed. To enable instructors to use data for rapid improvement while maintaining statistically valid data for researchers, we apply an interpretable machine learning algorithm for Dynamic experimentation. We worked with an on-campus instructor to implement a proof-of-concept CDE system to experiment within their online calculus quizzes. The qualitative results from this deployment provided insight into how the CDE framework can facilitate alignment of research and practice
MOOClets
No full textRandomized experiments in online educational environments are ubiquitous as a scientific method for investigating learning and motivation, but they rarely improve educational resources and produce practical benefits for learners. We suggest that tools for experimentally comparing resources are designed primarily through the lens of experiments as a scientific methodology, and therefore miss a tremendous opportunity for online experiments to serve as engines for dynamic improvement and personalization. We present the MOOClet requirements specification to guide the implementation of software tools for experiments to ensure that whenever alternative versions of a resource can be experimentally compared (by randomly assigning versions), the resource can also be dynamically improved (by changing which versions are presented), and personalized (by presenting different versions to different people). The MOOClet specification was used to implement DEXPER, a proof-of-concept web service backend that enables dynamic experimentation and personalization of resources embedded in frontend educational platforms. We describe three use cases of MOOClets for dynamic experimentation and personalization of motivational emails, explanations, and problems
The MOOClet Framework: Unifying Experimentation, Dynamic Improvement, and Personalization in Online Courses
No full textHow can educational platforms be instrumented to accelerate the use of research to improve students' experiences? We show how modular components of any educational interface-e.g. explanations, homework problems, even emails-can be implemented using the novel MOOClet software architecture. Researchers and instructors can use these augmented MOOClet components for: (1) Iterative Cycles of Randomized Experiments that test alternative versions of course content; (2) Data-Driven Improvement using adaptive experiments that rapidly use data to give better versions of content to future students, on the order of days rather than months. A MOOClet supports both manual and automated improvement using reinforcement learning; (3) Personalization by delivering alternative versions as a function of data about a student's characteristics or subgroup, using both expert-authored rules and data mining algorithms. We provide an open-source web service for implementing MOOClets (www.mooclet.org) that has been used with thousands of students. The MOOClet framework provides an ecosystem that transforms online course components into collaborative micro-laboratories, where instructors, experimental researchers, and data mining/machine learning researchers can engage in perpetual cycles of experimentation, improvement, and personalization. © 2021 ACM
In Tune, BBC Radio 3: 'Berta Joncus in conversation with Sean Rafferty about her book Kitty Clive, or The Fair Songster'
No full textSean Rafferty presents a lively mix of music and arts news with live performance in the studio from mezzo-soprano Clara Mouriz with Jaume Santonja Espinós. The viol consort Fretwork join us too, and author Berta Joncus chats to Sean about her new book Kitty Clive, or The Fair Songster
Enhancing Online Problems Through Instructor-Centered Tools for Randomized Experiments
No full textDigital educational resources could enable the use of randomized experiments to answer pedagogical questions that instructors care about, taking academic research out of the laboratory and into the classroom. We take an instructorcentered approach to designing tools for experimentation that lower the barriers for instructors to conduct experiments. We explore this approach through DynamicProblem, a proof-ofconcept system for experimentation on components of digital problems, which provides interfaces for authoring of experiments on explanations, hints, feedback messages, and learning tips. To rapidly turn data from experiments into practical improvements, the system uses an interpretable machine learning algorithm to analyze students' ratings of which conditions are helpful, and present conditions to future students in proportion to the evidence they are higher rated. We evaluated the system by collaboratively deploying experiments in the courses of three mathematics instructors. They reported benefits in reflecting on their pedagogy, and having a new method for improving online problems for future students
[Photograph 2012.201.B1073.0273]
No full textPhotograph used for a story in the Daily Oklahoman newspaper. Caption: "Anna Sue Rafferty, spokeswoman for a group of Ponca City residents who favor a proposed settlement with Conoco, meets with reporters following Tuesday's court hearing.
The boldness of Betty the memoirs of Betty Margaret Rafferty, aged 14
No full textIt's summer 1913 and Betty Rafferty is fed up. Forced to leave school aged 14, Betty is considered lucky when she gets a job in a sweet shop. After all, her da and her older brother Eddie are both working hard down on the docks in all weathers. But Betty is bored at the shop, and looks with envy at her customers who attend the posh girls school on nearby Eccles Street. But life in Dublin becomes anything but boring when industrial unrest brings the city to a halt. Betty is shocked when her brother Eddie is badly injured by a police charge. The city becomes increasingly violent - and hungry. Betty has never seen anything like the violence and is horrified when employers start locking out workers who refuse to abandon the trade union. At the start of September a terrible tragedy strikes the tenement houses in Church Street, and Betty's friend Rosie loses both her mother and her sweet little brother FrancisFor ages 11 years
AXIS
No full textWhile explanations may help people learn by providing information about why an answer is correct, many problems on online platforms lack high-quality explanations. This paper presents AXIS (Adaptive eXplanation Improvement System), a system for obtaining explanations. AXIS asks learners to generate, revise, and evaluate explanations as they solve a problem, and then uses machine learning to dynamically determine which explanation to present to a future learner, based on previous learners' collective input. Results from a case study deployment and a randomized experiment demonstrate that AXIS elicits and identifies explanations that learners find helpful. Providing explanations from AXIS also objectively enhanced learning, when compared to the default practice where learners solved problems and received answers without explanations. The rated quality and learning benefit of AXIS explanations did not differ from explanations generated by an experienced instructor
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