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This article describes the process of developing a career advice 3D adventure game for applicants interested in working in IT departments. The game is based on a 3D representation of the computer science and information technologies department at the Kharkiv Aviation Institute. The quest challenges are designed to measure applicants' and first-year students' digital competency. The theoretical foundation, software tools, development stages, implementation obstacles, and gaming application scenario were all used in the article. The game scenario includes a virtual tour of a 3D university department. In terms of how closely the game resembles real-life stuff, applicants can examine the department's equipment and classrooms. The team used C# and C++, Unity 3D, and Source Engine to create the game application. We used Hammer Editor, Agisoft PhotoScan Pro, and photogrammetry technology to model objects for realistic gaming. Based on the Digital Competence Framework for Citizens (DigComp 2.2), players can assess their digital competences in a variety of ways, including a test activity, a puzzle, assembling a computer, and putting up an IT-specialist firm. The experiment conducted at the online open house day 2020 demonstrated the efficiency of the 3D quest game. A 3D quest was rated as a more modern and appealing kind of involvement by the candidates. According to the 3D quest findings, applicants displayed an average degree of digital competence, with certain specific item challenges graded at 0.5. Several psychometric item parameters were thoroughly examined in order to increase the item's quality.

This article analyzes the ways to apply Learning Analytics, Cloud Technologies, and Big Data in the field of education on the international level. This paper provides examples of international analytical researches and cloud technologies used to process the results of those researches. It considers the PISA research methodology and related tools, including the IDB Analyzer application, free R intsvy environment for processing statistical data, and cloud-based web application PISA Data Explorer. The paper justifies the necessity of creating a stand-alone web application that supports Ukrainian localization and provides Ukrainian researchers with rapid access to well-structured PISA data. In particular, such an application should provide for data across the factorial features and indicators applied at the country level and demonstrate the Ukrainian indicators compared to the other countries’ results. This paper includes a description of the application core functionalities, architecture, and technologies used for development. The proposed solution leverages the shiny package available with R environment that allows implementing both the UI and server sides of the application. The technical implementation is a proven solution that allows for simplifying the access to PISA data for Ukrainian researchers and helping them utilize the calculation results on the key features without having to apply tools for processing statistical data.