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Integration of Computer Science Assessment into Learning Management Systems with JuezLTI Carrillo, Juan V. Sierra, Alberto Leal, José Paulo Queirós, Ricardo Pellicer, Salvador Primo, Marco programming interoperability automatic assessment programming exercises Computer science is a skill that will continue to be in high demand in the foreseeable future. Despite this trend, automated assessment in computer science is often hampered by the lack of systems supporting a wide range of topics. While there is a number of open software systems and programming exercise collections supporting automated assessment, up to this date, there are few systems that offer a diversity of exercises ranging from computer programming exercises to markup and databases languages. At the same time, most of the best-of-breed solutions force teachers and students to alternate between the Learning Management System - a pivotal piece of the e-learning ecosystem - and the tool providing the exercises. This issue is addressed by JuezLTI, an international project whose goal is to create an innovative tool to allow the automatic assessment of exercises in a wide range of computer science topics. These topics include different languages used in computer science for programming, markup, and database management. JuezLTI borrows part of its name from the IMS Learning Tools Interoperability (IMS LTI) standard. With this standard, the tool will interoperate with reference systems such as Moodle, Sakai, Canvas, or Blackboard, among many others. Another contribution of JuezLTI will be a pool of exercises. Interoperability and content are expected to foster the adoption of JuezLTI by many institutions. This paper presents the JuezLTI project, its architecture, and its main components. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Juan V. Carrillo and Alberto Sierra and José Paulo Leal and Ricardo Queirós and Salvador Pellicer and Marco Primo 2022 Is Part Of OASIcs, Volume 102, Third International Computer Programming Education Conference (ICPEC 2022) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/OASIcs.ICPEC.2022.9 urn:nbn:de:0030-drops-166130 https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICPEC.2022.9 eng https://creativecommons.org/licenses/by/4.0/legalcode