Understanding Hidden Memories of Recurrent Neural Networks

Recurrent neural networks (RNNs) have been successfully applied to various natural language processing (NLP) tasks and achieved better results than conventional methods. However, the lack of understanding of the mechanisms behind their effectiveness limits further improvements on their architectures. In this paper, we present a visual analytics method for understanding and comparing RNN models for NLP tasks. We propose a technique to explain the function of individual hidden state units based on their expected response to input texts. We then co-cluster hidden state units and words based on the expected response and visualize co-clustering results as memory chips and word clouds to provide more structured knowledge on RNNs' hidden states. We also propose a glyph-based sequence visualization based on aggregate information to analyze the behavior of an RNN's hidden state at the sentence-level. The usability and effectiveness of our method are demonstrated through case studies and reviews from domain experts.Comment: Published at IEEE Conference on Visual Analytics Science and Technology (IEEE VAST 2017

The Art and Science of Data-Driven Journalism

Journalists have been using data in their stories for as long as the profession has existed. A revolution in computing in the 20th century created opportunities for data integration into investigations, as journalists began to bring technology into their work. In the 21st century, a revolution in connectivity is leading the media toward new horizons. The Internet, cloud computing, agile development, mobile devices, and open source software have transformed the practice of journalism, leading to the emergence of a new term: data journalism. Although journalists have been using data in their stories for as long as they have been engaged in reporting, data journalism is more than traditional journalism with more data. Decades after early pioneers successfully applied computer-assisted reporting and social science to investigative journalism, journalists are creating news apps and interactive features that help people understand data, explore it, and act upon the insights derived from it. New business models are emerging in which data is a raw material for profit, impact, and insight, co-created with an audience that was formerly reduced to passive consumption. Journalists around the world are grappling with the excitement and the challenge of telling compelling stories by harnessing the vast quantity of data that our increasingly networked lives, devices, businesses, and governments produce every day. While the potential of data journalism is immense, the pitfalls and challenges to its adoption throughout the media are similarly significant, from digital literacy to competition for scarce resources in newsrooms. Global threats to press freedom, digital security, and limited access to data create difficult working conditions for journalists in many countries. A combination of peer-to-peer learning, mentorship, online training, open data initiatives, and new programs at journalism schools rising to the challenge, however, offer reasons to be optimistic about more journalists learning to treat data as a source

Sensemaking with learning analytics visualizations: Investigating dashboard comprehension and effects on learning strategy

In the provision of just-in-time feedback, student-facing learning analytics dashboards (LADs) are meant to aid decision-making during the process of learning. Unlike summative feedback received at its conclusion, this formative feedback may help learners pivot their learning strategies while still engaged in the learning activity. To turn this feedback into actionable insights however, learners must understand LADs well enough to make accurate judgements of learning with them. For these learners, LADs could become an integral part of their self-regulatory learning strategy. This dissertation presents a multifaceted examination of learners’ sensemaking processes with LADs designed to support self-regulatory learning. The in-situ studies detailed therein examine learners’ understanding of the data visualized in LADs and the effects of this understanding on their performance-related mental models. Trace data, surveys, semi-structured in-depth qualitative interviews, and retrospective cued recall methods were used to identify why, when, and how learners used LADs to guide their learning. Learners’ qualitative accounts of their experience explained and contextualized the quantitative data collected from the observed activities. Learners preferred less complex LADs, finding them more useful and aesthetically appealing, despite lower gist recall with simpler visualizations. During an early investigation of how LADs were used to make learning judgments in situ, we observed learners’ tendency to act upon brief LAD interactions. This inspired us to operationalize gist as a form of measurement, describing learners’ ability to make sense of a LAD after a brief visual interrogation. Subsequent comparisons of the accuracy and descriptiveness of learners’ gist estimates to those of laypeople repeatedly showed that laypeople were more apt than learners to produce accurate and complete gist descriptions. This dissertation culminates in a final study examining the evolution of learners’ mental models of their performance due to repeated LAD interaction, followed by a discussion of the contextual factors that contributed to what was observed. Trends observed across this work suggest that learners were more apt to “get the gist” with LAD after repeated interaction. This dissertation contributes a novel method for evaluating learners’ interpretation of LADs, while our findings offer insight into how LADs shape learners’ sensemaking processes

Reshaping the Museum of Zoology in Rome by Visual Storytelling and Interactive Iconography

This article summarizes the concept of a new immersive and interactive setting for the Zoology Museum in Rome, Italy. The concept, co-designed with all the museum’s curators, is aimed at enhancing the experiential involvement of the visitors by visual storytelling and interactive iconography. Thanks to immersive and interactive technologies designed by Centro Studi Logos, developed by Logosnet and known as e-REALâ and MirrorMeä, zoological findings and memoirs come to life and interact directly with the visitors in order to deepen their understanding, visualize stories and live experiences, and interact with the founder of the Museum (Mr. Arrigoni degli Oddi) who is now a virtualized avatar, or digital human, able to talk with the visitors. All the interactions are powered through simple hand gestures and, in a few cases, vocal inputs that transform into recognized commands from multimedia systems

Usability and Usage of Interactive Features in an Online Ebook for CS Teachers

There are too few secondary school computing teachers to meet international needs for growing secondary school computing education. Our group has created an ebook to help prepare secondary teachers to teach the programming and big data concepts in the new AP Computer Science Principles course. The ebook was designed using principles from educational psychology, specifically worked examples and cognitive load. The ebook interleaves worked examples and interactive practice activities, which we believe will lead to more efficient and effective learning than more typical approaches to learning programming. This paper reports the results from initial studies of our ebook. First, we conducted a usability study comparing three different ebook platforms. Next, we conducted a study of teacher use of the ebook. Ten teachers worked through the first eight chapters of the ebook at their own pace. Five of the ten teachers completed the first eight chapters which is a 50% completion rate. Significantly, teachers who used more of the interactive features in the ebook did better on the post-tests and reported higher confidence in their ability to teach the material than teachers who used few of the interactive features

Social Worked-Examples Technique to Enhance Student Engagement in Program Visualization

يعد تعلم البرمجة من بين أهم التحديات في تعليم علوم الكمبيوتر. حاليا، يتم استخدام تصوير البرامج ) PV ( كأداة للتغلب علىمعدلات الفشل والتسرب العالية في مادة اساسيات البرمجة. ومع ذلك، هناك مخاوف متزايدة بشأن فعالية أدوات تصوير البرامج الحالية استناداالى النتائج المختلطة المستمدة من الدراسات المختلفة. تعتبر مشاركة الطلاب أيضًا عاملاً حيويًا في بناء PV ناجحًا، كما تعد أيضًا جزءًا مهمًامن عملية التعلم بشكل عام. تم إدخال العديد من التقنيات لتعزيز المشاركة في أدوات تصوير البرامج؛ ومع ذلك، فإن مشاركة الطلاب في PVلا يزال يمثل تحديًا كبيراً. استخدمت هذه الورقة ثلاث نظريات مختلفة: البنيوية، والبناء الاجتماعي، والحمل المعرفي لاقتراح تقنية لتعزيزمشاركة الطلاب في استخدام أدوات تصوير البرامج. تعمل تقنية الأمثلة المكتملة الاجتماعية ) SWE ( على تحويل المثال المكتمل التقليدي إلىنشاط اجتماعي ، حيث يتم التركيز بشكل أكبر على دور التعاون في بناء معرفة الطلاب. حددت هذه الدراسة ثلاثة مبادئ يمكن أن تعززمشاركة الطلاب من خلال تقنية SWE : التعلم النشط والتعاون الاجتماعي والأنشطة ذاتس التحميل المنخفض.Learning programming is among the top challenges in computer science education. A part of that, program visualization (PV) is used as a tool to overcome the high failure and drop-out rates in an introductory programming course. Nevertheless, there are rising concerns about the effectiveness of the existing PV tools following the mixed results derived from various studies. Student engagement is also considered a vital factor in building a successful PV, while it is also an important part of the learning process in general. Several techniques have been introduced to enhance PV engagement; however, student engagement with PV is still challenging. This paper employed three theories—constructivism, social constructivism and cognitive load to propose a technique for enhancing student engagement with program visualisation. The social worked-examples (SWE) technique transforms the traditional worked-example into a social activity, whereby a greater focus is placed on the collaboration role in constructing students’ knowledge. This study identified three principles that could enhance student engagement through the SWE technique: active learning, social collaboration and low-load activity