Records User Actions Research Articles

UI Action Logger to Investigate Potential Robotic Process Automation Routines.

Robotic Process Automation (RPA) is a cost-effective technology that emulates human tasks, reduces errors and enhances business performance. However, identifying ideal processes for RPA implementation can be challenging. Process Mining is a strategy that leverages User Interface (UI) logs to delve into processes and generate "process maps." These logs record user actions during processes, necessitating the use of a tool such as UI Action Logger to capture and transmit them to a cloud-based application for logging. Subsequently, Process Mining frameworks like ProM utilize these logs to construct process models, aiding in the identification of repetitive processes suitable for RPA automation. This innovative study shifts the focus of process mining from event logs to UI logs, simplifying the detection of potential routines. Enriched UI logs are valuable for creating RPA bots, conducting in-depth process analysis, task mining, and training RPA bots through machine learning, and selecting processes for automation. In summary, UI Action Logger offers distinctive features, capturing user interactions at a coarse level conducive to RPA implementation.

FUNCTIONAL TEST AUTOMATION SYSTEM FOR UNITY APPLICATIONS

The tool for automatically executing and validating test sets of actions is not native to applications, which causes problems with recognizing interaction elements due to the abundance or, conversely, lack of GUI elements. This work describes the design and development of an internal tool that provides accurate recognition of interaction elements by decorating the input reading mechanisms of the Unity game engine. Previously, there were no solutions for Unity to automate success tests, testing the main flow of a use case, or other approaches for functional testing of applications, except through the mechanisms of the standard unit testing package. However, no matter how good the approach of using unit testing tools is, in order to cover all possible scenarios of actions within the project, you would have to either write your own test module for each of the aspects, or implement a complex universal system on its basis. The article's graceful workaround for the technical limitation of the standard Input class dramatically reduces the time required for the application testing phase. In addition to solving testing problems, such a form of recording user actions in a virtual environment can be used to generate training simulator scenarios, which will help to avoid the routine work of generating training tracks. So, immersion in a virtual biotechnology laboratory of an expert who can correctly pass all phases of the selected analysis (for example, ELISA) is enough to record the checkpoints of such a scenario for teaching students.

Анализ данных о поведении пользователей в системах электронного обучения

This article discusses modern e-learning systems that have the ability to record user actions, such as movement, use of interactive materials, registration for courses, their completion, and more. Analysis of user actions in learning management systems provides opportunities for personalization of educational trajectories. Based on the study of user behavior, it becomes possible to form recommendations for course developers to improve the content and structure, as well as recommendations for passing the course for students. This work examines the data contained in activity logs to obtain information, search for dependencies by filtering relevant logs, structuring information from them, and providing data in a form that is convenient for analysis and drawing conclusions. The paper considers data of the main types of events generated as a result of recording user actions in the training management system, and scenarios for using the results of analyzing this data.

A Keyword-Driven Tool for Testing Web Applications (KeyDriver)

In this article, we investigated the different types of keywords, base requirement, methodology, object repository, and various modules for the keyword-driven testing. These all are required to carry out a successful and efficient operation of keyword-driven testing. It is important to understand that keywords are not magic, but they can serve a good purpose. KeyDriver performs the automated functional testing of a Web application on the basis of keyword-driven testing. KeyDriver records user actions in the form of keywords and generates test scripts. In KeyDriver, mapping between keywords and corresponding labels is done, which increases the readability of test scripts. Keywords are stored in the object repository in the form of Excel files. The recorded test scripts are played back automatically for test result analysis. KeyDriver saves a lot of manual testing by automating the process of testing a Web application for various test cases. It also offers the reusability of keywords within the same Web application. It provides the reusability through parameterization of test scripts and creating multiple actions.

Modeling visitors' profiles

The time restrictions that apply in museum learning increase the need for adaptive and/or adaptable technologies. However, deriving a visitor's profile is not an easy task, since most common ways (asking direct questions, recording user actions) are either intrusive or time consuming. Observing the visitors' movement (visiting style) within the museum could provide valuable information regarding adaptivity. In the present study, issues of visiting style were explored and statistical significance was found once different factors were analyzed. Most importantly, there seems to be a connection between the way people move in a museum and the way they prefer to approach and process information cognitively. Environmental factors that can affect the expression of visiting style were also identified.

Identifying and recording user actions to enable automatic online assessment

This paper focuses on a system designed to identify and record user actions as they interact with various types of IT training software, and uses this information to provide an automated assessment of these activities in relation to users responding to set tests or exercises. The system has an intelligent inference engine enabling it to either automatically create test templates or analyse submitted tests. The existing prototype differs radically from other similar approaches in that it does not require any specific software platform to operate. Instead, it integrates seamlessly with standard existing business software such as Microsoft Word, PowerPoint or Excel. The present prototype operates on Windows XP and Vista and on the latest versions of Microsoft Office, but it can easily be expanded into other standard software, also used extensively in engineering education such as Matlab and Pspice. The aim of the presented system is to minimise the effort of tutors to set and evaluate tests.

Construction of interaction observation systems for collaboration analysis in groupware applications

Interaction observation systems for groupware applications capture and process all the actions performed by users engaged in workgroups. These actions are then stored in log documents that enable the work process carried out by the users to be analyzed and the interaction between users to be studied. This article proposes an approach, based on ontological models, which is devised to help the developer of an observation system for a groupware application to structure and record user actions. In order to achieve this aim, we present a specific ontology that shapes the collaborative work process of the users so as to obtain an XML-based log document that stores all the actions carried out by the users and facilitates the subsequent analysis of the system usage and users' behavior. This approach has been used to improve communication and collaboration capabilities in the COLLECE groupware application.

AppMonitor: A tool for recording user actions in unmodified Windows applications

This article describes AppMonitor, a Microsoft Windows-based client-side logging tool that records user actions in unmodified Windows applications. AppMonitor allows researchers to gain insights into many facets of interface interaction such as command use frequency, behavioral patterns prior to or following command use, and methods of navigating through systems and data sets. AppMonitor uses the Windows SDK libraries to monitor both low-level interactions, such as "left mouse button pressed" and "Ctrl-F pressed," as well as high-level "logical" actions, such as menu selections and scrollbar manipulations. The events recorded are configurable, allowing researchers to perform broad or targeted studies. No user input is required to manage logging, allowing participants to seamlessly conduct everyday work while their actions are monitored. The system currently supports logging in Microsoft Word and Adobe Reader; however, it could be extended for use with any Microsoft Windows-based application. To support other researchers wishing to create multilevel event loggers, we describe AppMonitor's underlying architecture and implementation, and provide a brief example of the data generated during our 4-month trial with six users.

A tutorial on creating logfiles for event-driven applications.

This paper describes the practical steps necessary to write logfiles for recording user actions in event-driven applications. Data logging has long been used as a reliable method to record all user actions, whether assessing new software or running a behavioral experiment. With the widespread introduction of event-driven software, the logfile must enable accurate recording of all the user's actions, whether with the keyboard or another input device. Logging is only an effective tool when it can accurately and consistently record all actions in a format that aids the extraction of useful information from the mass of data collected. Logfiles are often presented as one of many methods that could be used, and here a technique is proposed for the construction of logfiles for the quantitative assessment of software from the user's point of view.