<?xml version='1.0' encoding='UTF-8'?><metadata xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns="http://dublincore.org/documents/dcmi-terms/"><dcterms:title>Informatics Lesson Plans. Area B. Lesson Plans and Tasks for Grades 9–10 (I–II Gymnasium) Classes</dcterms:title><dcterms:identifier>https://hdl.handle.net/21.12137/KJP7UF</dcterms:identifier><dcterms:creator>Burbaitė, Renata</dcterms:creator><dcterms:creator>Klizienė, Irina</dcterms:creator><dcterms:creator>Augustinienė, Aldona</dcterms:creator><dcterms:creator>Jakštienė, Vitalija</dcterms:creator><dcterms:creator>Kubiliūnas, Ramūnas</dcterms:creator><dcterms:publisher>Lithuanian Data Archive for SSH (LiDA)</dcterms:publisher><dcterms:issued>2025-11-21</dcterms:issued><dcterms:modified>2026-03-20T11:53:39Z</dcterms:modified><dcterms:description>&lt;p>This dataset contains lesson plans and tasks for grades 9–10 (I–II gymnasium) classes in Area B (Algorithms and programming) from the teaching guide "Informatics Lesson Plans: Ideas and Scenarios for Grades 5–12".&lt;/p>
&lt;p>Authors of lesson plans and tasks: Olga Bielko, Deividas Urbonas, Rasa Vilimienė-Jurkė, Jolita Lazauskienė.&lt;/p>
&lt;p> Area B. The lesson plans and tasks for grades 9–10 (I–II gymnasium) classes are characterised by thematic and methodological consistency in lesson content and a focus on developing higher-level programming skills. The lesson topics demonstrate a targeted deeper learning process – from working with external data to systematic program design.&lt;p>
Lesson plans and tasks
&lt;ol>
&lt;li>Use of external data. Keeping initial data in text files. Reading from a file (linear and conditional algorithms) (Olga Bielko)&lt;/li>
&lt;li>Use of external data. Saving results in text files. Writing to a file (linear and conditional algorithms) (Olga Bielko)&lt;/li>
&lt;li>Use of external data. Storage of initial data in text files. Reading from a file and writing results to a file (loops) (Olga Bielko)&lt;/li>
&lt;li>FOR loops (Deividas Urbonas)&lt;/li>
&lt;li>The importance of subroutines in programming (Rasa Vilimienė-Jurkė)&lt;/li>
&lt;li>Subroutines when a value is passed as a parameter (Rasa Vilimienė-Jurkė)&lt;/li>
&lt;li>Solving problems using subroutines when a value is passed as a parameter (Rasa Vilimienė-Jurkė)&lt;/li>
&lt;li>Introduction to software design (Jolita Lazauskienė)&lt;/li>
&lt;li>Breaking software design tasks into component parts (Jolita Lazauskienė)&lt;/li>
&lt;li>Program design: practical study (Jolita Lazauskienė)&lt;/li>
&lt;/ol>
&lt;p>&lt;a href=https://lida.dataverse.lt/dataverse/InstitutionData_HiEd_KTU_EdTech_EduIPM_TopicB target="_blank"> All lesson plans and tasks for Area B&lt;/a>&lt;/p>
&lt;p>Lesson plans and tasks were prepared as a part of the project "Digital Transformation of Education ("EdTech") (No. 10-004-P-0001)", implemented under the Economic Recovery and Resilience Plan "Next Generation Lithuania", funded by the European Union's Economic Recovery and Resilience Instrument "NextGenerationEU".&lt;/p></dcterms:description><dcterms:subject>Computer and Information Science</dcterms:subject><dcterms:subject>Social Sciences</dcterms:subject><dcterms:subject>education science</dcterms:subject><dcterms:subject>educational methods</dcterms:subject><dcterms:subject>information technology training</dcterms:subject><dcterms:subject>computer science education</dcterms:subject><dcterms:subject>teacher training</dcterms:subject><dcterms:subject>students</dcterms:subject><dcterms:subject>schoolchildren</dcterms:subject><dcterms:language>English</dcterms:language><dcterms:language>Lithuanian</dcterms:language><dcterms:IsSupplementTo>Burbaitė, R., Klizienė, I., Augustinienė,  A., Jakštienė, V., &amp; Kubiliūnas, R. (2025). Informatikos pamokų modeliavimas: 5–12 klasės pamokų idėjos ir scenarijai. Mokomoji knyga. Kaunas: Technologija., doi, 10.5755/e01.9786090219331, https://doi.org/10.5755/e01.9786090219331</dcterms:IsSupplementTo><dcterms:date>2025-09-05</dcterms:date><dcterms:contributor>Kubiliūnas, Ramūnas (Research Group – Smart Educational Technologies and Their Application, Faculty of Informatics, Kaunas University of Technology, Lithuania [ORCID: 0009-0006-5050-8007])</dcterms:contributor><dcterms:contributor>Žvaliauskas, Giedrius (Center for Data Analysis and Archiving (DAtA), Faculty of Social Sciences, Arts and Humanities, Kaunas University of Technology, Lithuania [ORCID: 0000-0001-8970-0756])</dcterms:contributor><dcterms:dateSubmitted>2025-09-05</dcterms:dateSubmitted><dcterms:temporal>2022-09</dcterms:temporal><dcterms:temporal>2024-06</dcterms:temporal><dcterms:type>Other social science data</dcterms:type><dcterms:source>&lt;a href="https://vocabularies.cessda.eu/vocabulary/DataSourceType?code=ProcessesWorkflows" target="_blank"> Processes: Workflow(s)&lt;/a> (DDI Alliance CV for Data Source Type)</dcterms:source><dcterms:spatial>Lithuania</dcterms:spatial><dcterms:rights>&lt;p>The data is available to the users of the LiDA Dataverse repository under the &lt;a href="https://creativecommons.org/licenses/by-sa/4.0" target="_blank">Creative Commons Attribution-ShareAlike 4.0 International licence (CC BY-SA 4.0)&lt;/a>, if not indicated otherwise. Individuals and organizations wishing to use data licensed differently must apply for access to the specific data (in written form or by email: &lt;a href="mailto:data@ktu.lt">data@ktu.lt&lt;/a>). Regardless of the data access restrictions, everyone can browse and use all the descriptions of the data stored in the LiDA Dataverse repository (metadata, including fieldwork resources, research instruments and other data collection information) as well as other information under the &lt;a href="https://creativecommons.org/licenses/by-sa/4.0" target="_blank">Creative Commons Attribution-ShareAlike 4.0 International licence (CC BY-SA 4.0)&lt;/a>.&lt;/p>
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