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Check out our recent blog post on the TIDESS website!

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As part of the ACM SIGCHI 2018 conference, INIT Lab director Lisa Anthony helped co-organize a ‘special interest group’ (SIG) session on child-computer interaction. This SIG is organized by some of the child-computer interaction research community every year. This year, the topic was “Ubiquity and Big Data“: how do we design technology for children in an era of “big data” in which their online activities from an extremely early age may be being monitored, archived, evaluated, and judged? The issue is complex, since parents, schools, and other stakeholders may find beneficial reasons for monitoring and tracking their children’s activities, especially in cases of bullying, self-harm, or risky behaviors; but what are the last impacts of such technologies when the children grow up and already have a digital footprint not of their own making? How do we empower children to own their own online identities but still provide a safe space for growth and learning?

As a result of this SIG, many of the attendees of the event decided to write up a summary of the topics of discussion and submit it to the ACM interactions magazine. It has just recently appeared in the November-December 2018 issue, in the magazine’s forum on “Universal Interactions”. Check out the full article here (available in PDF or HTML format). The article presents the topics of discussion and some insights the SIG attendees came up with, especially the fact that education and transparency are critical values to keep in mind when pushing forward into this space. It is our hope that the article will launch further discussion and awareness of these topics among researchers, educators, designers, and parents.

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On May 29, I completed and passed my PhD dissertation proposal defense. The proposal defense process can vary widely among institutions and even among departments in the same institution, so in this post I outline the process I followed in the CISE department at UF.

The first step I followed was to create a document outlining my proposed work to help my committee understand my plans. There was no prescribed length or format for the document, but mine was around 60 pages. The document contained information about all the work I’ve done up to this point as a PhD student, as well as an outline of all the work I plan to do before graduating. Preparing the document requires a significant amount of work, so I would recommend planning on spending several months working on it before submitting. The document is a crucial part of the proposal process since your committee will use it as a guide to understand the details of your work that you don’t have time to cover in your presentation.

After completing the document, I sent it to my committee. The committee then had several weeks to review the document while I prepared for the next step, which was to give a 45 minute-long presentation about my prior work and my plans for my dissertation work, with 15 additional minutes for public questions.

The proposal defense itself was divided in to four stages. In the first phase, I gave my 45-minute presentation to my committee as well as members of the public who were interested in attending. In the second stage, which lasted around 15 minutes, both the public audience and my committee members asked questions. In the third stage, the public audience was asked to leave and my committee asked questions in private. This phase lasted around 30 minutes. I found that the questions my committee asked in this phase were more difficult and thorough since my committee wanted to be sure they understood my proposed work. For example, my committee asked not only what I planned to do but how I planned to implement specific parts of my dissertation work. In the final stage of the proposal defense, I was asked to leave the room while the committee deliberated on whether I had passed the proposal. The time taken by the committee to deliberate can vary, but for me it was in the range of 20 to 30 minutes. After my committee finished their discussion, I was brought back into the room and was very excited (and relieved) to learn that I had passed my proposal! My committee offered suggestions and feedback on ways to improve my proposed work. For example, some of my committee members suggested specific algorithms that I had not considered that may be useful for my work.

I am entering my fifth year in the PhD program at UF. Now that I’ve defended my proposal, my next major milestone will be my final dissertation defense, which I plan to complete in December 2019. The proposal process was long and difficult, but it provided me a valuable opportunity to crystallize my plans for my dissertation work. Preparing for my proposal forced me to take a more active role in generating ideas for future directions of my research, and now that I’ve passed my proposal I am expected to take more ownership of my work with less involvement from my advisor.

Based on my experience, here are some tips for preparing for your proposal:

* Read proposal documents from students who have already passed their proposal in your department and/or to help get an idea of the scope and formatting to use. I used previous students’ proposals working in a similar area to mine as a model for my document.

* Give as many practice talks as you can with different people. Consider getting people outside of your own lab to make sure it is understandable to a more general audience. Even your committee will have diverse backgrounds and may not be familiar with some concepts related to your research. Practices also are a great time to get a feel for the types of questions you’re likely to get. When I prepared for my presentation, I gave practice talks to friends in other engineering departments to help evaluate how well I was able to explain my work.

* Prepare backup slides to help you answer questions you think you are likely to get.

* Ask your friends and labmates to attend your talk. It helps to see familiar faces and to know you have a lot of support while you’re giving your presentation.

* Bring food and/or coffee for the audience, especially your committee.

* Try not to get too stressed out during your presentation. Ultimately, everyone wants to see you succeed.

If you’re about to propose your dissertation, good luck!

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I just completed my qualifying exam and in this blog post, I will detail what I think I learned from the qualifying exam (quals) process. In the CISE department at UF, the qualifying exam is the first milestone used to assess the student’s ability to successfully complete the Ph.D. program. This exam involves a literature survey of the student’s field of research. For my qualifying exam, I wrote a survey paper titled “An Overview of the Effectiveness of Exertion Games (Exergames) for Children.” I focused on this topic since my research interest involves exertion games (games that promote physical activity) for children. Below are some of the major lessons I learned from the writing process.

  1. START EARLY: The process of writing the qualifying exam involves dedicating a large amount of time, so it is important to identify several semesters before when you would like to write the qualifying exam and inform your advisor and committee members about your decision. It is also important to identify the papers you would like to review and start reading these papers early.
  2. PLAN ACCORDINGLY: The semester I decided to write my qualifying exams, I also attended several conferences and took one class. I found out this was not ideal as this took away from the time I should have used to focus on my quals.
  3. IDENTIFY YOUR RESEARCH QUESTION/CONTRIBUTION: You should review prior surveys in your field of research to identify research questions that are novel. Identifying your research question/contribution would also ensure that your survey is focused and not too broad and will help in gathering papers that can help answer these research questions.
  4. IDENTIFY A METHODOLOGY: It is very essential that the papers reviewed in your survey were gathered using a systematic approach, as this will ensure that your survey is grounded and can be reproducible. Furthermore, it will help others understand why the papers in your survey are the only ones you selected. To ensure that your methodology is good, make sure you formulate your research questions/contribution, identify your inclusion and exclusion criteria, select your keywords, and identify the sources you want to focus on. To structure my methodology, I looked at methodologies employed in other surveys in the exergaming field and from quals written by my peers.
  5. STRUCTURE YOUR PAPER LIST: When creating your paper list, ensure that you have a preliminary structure to group these papers as this will help make sure your survey is on the right track. Furthermore, these groupings can be modified and transformed into sections in your survey.
  6. ORGANIZATION: I cannot overemphasize the importance of ensuring you organize your papers, as this makes the writing process easier. I organized my papers by creating an Excel table that details each paper, its findings, and its contributions. Organizing your papers not only helps to ensure that you are capturing the important points mentioned in each paper, but it also enables you to have a top-down view of all the papers to be reviewed so you can ensure that your survey properly answers the research questions.
  7. YOUR PEERS ARE A RESOURCE: For most students like me, the qualifying exam is most likely the first time you are writing a survey paper, which may seem overwhelming. A useful resource in this situation is your peers who have gone through this process. They know what you are experiencing since they have also been through the process. Hence, you should seek their advice on issues you are facing, look through their exams to familiarize yourself with the writing process, and send drafts so they can provide constructive feedback. By doing this, you will be able to address a lot of comments that would have been identified by your committee.
  8. HAVE A MAJOR TAKE-AWAY: This was one of the mistakes I initially made in my survey. I was trying to capture different ideas which made it difficult for my committee to understand the major takeaway from my survey. Furthermore, the structure of my survey made it more difficult, as it did not match the contribution I was emphasizing. Using the feedback from my committee as a guide, I identified the major idea I wanted readers to take-away from my survey and structured my survey around this idea. Once I did this, I found out that the writing process became easier.
  9. WRITING IS AN ITERATIVE PROCESS: I could remember when I first got the feedback from my committee stating “major reviews.” I felt really downcast because I thought I did not write a good enough paper and I had to rewrite my paper again. However, after speaking to my committee members and thoroughly studying my reviews, I came to the realization that writing is an iterative process and I did not write a bad paper, I just needed to make changes to make the contributions of my survey clearer. Therefore, it is important to realize that as this is the first-time writing a survey paper, you may not get it right the first time, so iterate on it as much as possible because at the end you would have an outstanding paper. Furthermore, one of the main goals of the qualifying exam is for students to be able to submit the survey paper to a journal, so this process will also help strengthen your submission and improve your chances of acceptance.

To conclude, the qualifying exam writing process takes a lot of time but at the end in my view, it is worth it, because you learn a lot during the process. In my case, I gained an understanding of what has been done in the exergaming field and what is yet to be done, which helped to clarify my contributions on the FunFitTech project with respect to designing exergames for children. The qualifying exam process also helps you become a better writer and a more informed researcher in your field.

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I am pleased to be able to say that I was recently honored with the UF Herbert Wertheim College of Engineering Faculty Advising/Mentor of the Year Award for 2017-2018. This award focuses on undergraduate research and mentoring, an activity which I prioritize heavily in my research lab and other activities as a professor at UF. As a former undergraduate research student myself, I know the power of getting involved in research early. Before that opportunity came along, I really didn’t know what research was, or what career paths were available in this direction. After getting a taste of cutting-edge computer science research, I knew I wanted to remain part of the forward-thinking group of scientists that were helping push technology ahead. In my research lab, I have worked with many undergraduates, most of whom stay for multiple semesters and eventually lead their own research projects. For me, the best part of this award was getting to read the letters that students wrote to describe how they felt being involved in my lab and how the mentorship I provided helped them in their careers. Working with students, showing them the opportunities in research, and training the next generation of scientists is what this is all about, to me. Here’s a photo of the president of the University of Florida, Dr. Fuchs, presenting the award to me at the College awards ceremony, taken by a University photographer. Thank you for the honor!

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In the INIT Lab, we focus on natural user interaction for children. Many of these modalities, such as touch, gesture, and speech, involve some type of recognition process to understand what the user input is. To determine how accurate a recognizer is, there are several methods. One of these methods is using binary classifiers, as used in the MTAGIC project. Binary classification is classifying the elements of a set into two groups based on a classification rule. For example, classifying the outputs of a gesture recognizers to being recognized right or wrong is an example of the binary classification method. Word Error Rate (WER) is another method to determine the accuracy of a recognizer when the input is more complex. WER is commonly used as a metric for computing the performance of a speech recognition system (e.g., automatic speech recognition, or ASR). However, this method is useful in other contexts as well, such as handwriting, machine translation or other types of recognition.

The WER is derived from the Levenshtein Distance algorithm, calculated as the minimum edit distance between two strings. WER is used for both text and speech. In speech, it is defined as the minimum edit distance between an ASR hypothesis and the reference transcription. The formula for WER is as below, summing up the three types of errors (substitution, deletion, and insertion), over the length of the string:


In which:

  • S is the number of substitutions (misrecognition of one word for another),
  • D is the number of deletions (words missed by the recognition system),
  • I is the number of insertions (words introduced into the text output by the recognition system),
  • N is the number of words in the reference.

The intuition behind deletion and insertion is to think about what edits would one have to make to get from the reference to the hypothesis.

Accuracy can be computed as the inverse of WER:


WER is a useful metric to compute and compare the performance of different systems, as well as for evaluation of a system. However, it has some drawbacks that need to be considered. One problem is that this formula does not consider the effect that different types of errors may have on the outcome, i.e., some errors can be more disruptive, while other errors may be corrected more easily. Another problem is that this formula cannot distinguish a substitution error from a combined deletion plus insertion error. Therefore, the common belief that a lower word error rate shows more accuracy in recognition may not always be true, so further work and consideration may be needed to decide on the best metric based on the context.

I am a 2nd year Ph.D. student majoring in Human-Centered Computing in the CISE department of the University of Florida. I believe studying and implementing WER has helped me improve my understanding of methods of recognition, especially in the context of ASR or other natural interaction technologies. It has also helped me learn the reasons behind the WER formulation, and its drawbacks. I am looking forward to a deeper investigation of WER and its implementation using Levenshtein distance algorithm.


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Last spring, I participated in a project in a game design course. The project involved transforming a board game, previously designed by the University of Florida Center for Aquatic and Invasive Plants, to a mobile game. The objective of the project was for children to learn about the effects of invasive species on their real-world environment. At the end of the course, we submitted a work in progress paper discussing our design process. Our work in progress paper titled, “From Board Game to Digital Game: Designing a Mobile Game for Children to Learn about Invasive Species,” was accepted at CHI PLAY 2017, an international conference that combines all areas of play, games, and human-computer interaction (HCI). The paper focused on the design of a mobile strategy game that teaches children about the differences between native, non-native, and invasive species, and the mechanisms used to control invasive species. Here is the abstract:

Invasive species are species that cause economic and ecological harm and/or harm to human health. One challenge to managing invasive species is the lack of awareness about these species and the threats they pose. To mitigate this problem, the University of Florida Center for Aquatic and Invasive Plants developed a classroom board game for children to learn about trade-offs in managing invasive species. The game is effective in increasing knowledge about invasive species and promoting collaborative discussions. However, this board game is only accessible within the classroom. We created a mobile digital game that expands on the goals of the board game. In this paper, we discuss the design of the board and digital versions of the game, and provide some guidelines for designing digital learning games that address real-world problems that have no optimal solution, like the management of invasive species. Future work will evaluate the effectiveness of the digital game in enhancing children’s knowledge about invasive species.

We will post the camera-ready version of the paper soon. This year’s CHI PLAY conference will be held in Amsterdam, Netherlands, and I will be presenting a poster at the conference.

I am a 3rd year PhD student working on whole body interaction and movement based games for children. I am looking forward to attending the talks and sessions at the CHI PLAY conference. I believe these talks will help improve my understanding on creating better technologies for children.

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The main purpose of the Kids Application survey project is to help generate constructive recommendations for designing touchscreen interfaces specifically tailored towards kids. In our current study, we are taking inspiration by surveying interfaces of existing kid’s applications and are trying to decipher common interface/design patterns. We are presently in the process of creating categories for different aspects like Graphics, Gestures, etc. commonly found in kid’s applications which would help us understand interface patterns. These patterns would later help in drafting the analysis that would serve as a useful tool for developers to make more relevant kids application interfaces. We will be running our study on most downloaded kid’s applications (compatible with iPad/iPod Touch/iPhone/Android) under different categories.

I am a Master’s Student at University of Florida studying computer science. This qualitative analysis process has helped me gain a good understanding in conducting research. We are targeting to collect patterns from 100 applications. The next phase of project would include coding the patterns encountered from the analyzed data.

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One of the main goals of the INIT Lab is to build more natural user interfaces for children. A source of inspiration for our work is looking at existing applications and interfaces and learning what works and what does not work for kids. We are currently working on creating a definitive list of which currently available mobile apps are the most popular among children (and therefore being used a lot). Although services like the iOS App Store and the Google Play Store provide a list of the most downloaded apps for each category, they give no indication of how long each app is used after being downloaded. In addition to this, it is impossible to know if a child or an adult downloaded an app, even if it is in a category for children. We are working on an online survey for parents that aims to determine what current mobile apps children are using the most. With this information and our analysis of it, developers will be able to model the user interface of their mobile applications after ones that they know work well with children.

I am a first year undergraduate student at the University of Florida studying Computer Science. Working on the Apps for Kids project has been an excellent opportunity, and has allowed me to gain valuable experience in conducting research. In particular, I have learned a great deal about how to design intuitive surveys that collect meaningful data.

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