Towards a Universal Toolkit Model for Structures

Abstract. Model-based toolkit widgets have the potential for (i) increasing automation and (ii) making it easy to substitute a user-interface with another one. Current toolkits, however, have focused only on the automation benefit as they do not allow different kinds of widgets to share a common model. Inspired by programming languages, operating systems and database systems that support a single data structure, we present here an interface that can serve as a model for not only the homogeneous model-based structured-widgets identified so far -tables and trees -but also several heterogeneous structured-widgets such as forms, tabbed panes, and multi-level browsers. We identify an architecture that allows this model to be added to an existing toolkit by automatically creating adapters between it and existing widget-specific models. We present several full examples to illustrate how such a model can increase both the automation and substitutability of the toolkit. We show that our approach retains model purity and, in comparison to current toolkits, does not increase the effort to create existing model-aware widgets

Predicting Students’ Cell and Assignment Completion Times in Jupyter

In beginning computer science courses, students are often overwhelmed by the complex and novel way of problem-solving. Having a good expectation of how long the task is going to take is not easy even for students with much experience in programming. Without knowing their progress, beginners may become discouraged, have poor efficiency, miss deadlines, fail the course, and even drop out of the program. In this paper, I introduce a way to predict student time spent on Jupyter assignments by training models with collected student logs. The key idea of this project is that the student’s future relative progress can be deduced by the student’s past relative progress and problems together with information on other students. I develop a toolkit used for creating and troubleshooting prediction schemes. I present two ways of prediction: Assignment-based binary classification, and Cell-based ternary completion time. These two approaches have satisfactory results but still have room for improvement. I also evaluate an adaptation of an existing prediction scheme and compare the results. The video of the oral presentation of this thesis is available at (https://youtu.be/2qiuRLjfF-Y)Bachelor of Scienc

Composable collaboration infrastructures based on programming patterns

In general, collaboration infrastructures have supported sharing of an object based on its logical structure. However, current implementations assume an implicit binding between this logical structure and particular system-defined abstractions. We present a new composable design based on programming patterns that eliminates this binding, thereby increasing the range of supported objects and supporting extensibility

Special Issue: ECSCW 2018: The 16th European Conference on Computer-Supported Cooperative Work, The International Venue on Practice-centred Computing and the Design of Cooperation Technologies

International audienc

Designing and Implementing Multi-User Applications: A Case Study

this paper, we describe the user interface and implementation of the application, give the rationale for our design choices, describe our experience with the tools and techniques used in the implementation, and present conclusions and directions for future work. Key Words: CSCW, distributed objects, groupware, office automation, mail systems, user interfaces, views. INTRODUCTIO

An Inheritance Model for Supporting Flexible Displays of Data Structures

We have designed an inheritance model that reduces...This paper motivates, describes, and illustrates our method of grouping values and arranging the value groups in inheritance hierarchies