{"id":{"repo_id":"cau-kiel","oai_identifier":"oai:macau.uni-kiel.de:macau_mods_00008118"},"canonical_url":"https://search.dev.ndltd.org/etd/cau-kiel/oai:macau.uni-kiel.de:macau_mods_00008118","repository":{"repo_id":"cau-kiel","name":"Christian-Albrechts Universität Kiel","base_url":"https://macau.uni-kiel.de/servlets/OAIDataProvider"},"display":{"title":"Adaptive Diagnostics of Programming Misconceptions","abstract":"Despite the growing relevance of programming education in recent years, there is still a lack of suitable, standardized assessments in the field. This shortcoming is especially present in the area of formative testing of novice programmers, where the focus is primarily on helping learners rather than on achieving performance-oriented outcomes. However, literature has shown that (many) learners encounter learning difficulties in the form of misconceptions during their learning process. Therefore, reliably and validly detecting them is a relevant task of assessment research. The detection would allow educators to plan further interventions to assist learners in overcoming their learning difficulties. My dissertation integrates findings from seven studies outlining a potential process for developing an adaptive assessment that employs item generation in the context of tracing elements of control flow. First, a static Rasch-scaled assessment is developed and evaluated for its effectiveness in detecting known misconceptions. Next, the selected item format is analyzed to understand its characteristics and the factors influencing item difficulty. Finally, the work describes and discusses the transition from the developed static Rasch-scaled assessment to an adaptive assessment that utilizes item generation, including an evaluation of the adaptive item selection process and the underlying item generator. The findings reveal that the selected item format can be used to detect misconceptions based on common patterns observed during the execution. A created test system can automatically analyze these patterns and provide programming educators with valuable insights into the cognitive processes of their learners. The developed adaptive assessment can decrease the time required to conduct a measurement by up to 49%. Moreover, switching from a static to an adaptive paradigm does not result in a significant loss of informativeness of the assessment.","abstract_html":"Despite the growing relevance of programming education in recent years, there is still a lack of suitable, standardized assessments in the field. This shortcoming is especially present in the area of formative testing of novice programmers, where the focus is primarily on helping learners rather than on achieving performance-oriented outcomes. However, literature has shown that (many) learners encounter learning difficulties in the form of misconceptions during their learning process. Therefore, reliably and validly detecting them is a relevant task of assessment research. The detection would allow educators to plan further interventions to assist learners in overcoming their learning difficulties. My dissertation integrates findings from seven studies outlining a potential process for developing an adaptive assessment that employs item generation in the context of tracing elements of control flow. First, a static Rasch-scaled assessment is developed and evaluated for its effectiveness in detecting known misconceptions. Next, the selected item format is analyzed to understand its characteristics and the factors influencing item difficulty. Finally, the work describes and discusses the transition from the developed static Rasch-scaled assessment to an adaptive assessment that utilizes item generation, including an evaluation of the adaptive item selection process and the underlying item generator. The findings reveal that the selected item format can be used to detect misconceptions based on common patterns observed during the execution. A created test system can automatically analyze these patterns and provide programming educators with valuable insights into the cognitive processes of their learners. The developed adaptive assessment can decrease the time required to conduct a measurement by up to 49%. Moreover, switching from a static to an adaptive paradigm does not result in a significant loss of informativeness of the assessment.","abstract_has_math":false,"creators":["Bastian, Morten"],"institution":"Christian-Albrechts-Universität zu Kiel","degree_name":null,"degree_level":"thesis.doctoral","degree_discipline":null,"degree_department":null,"school":null,"contributors":["Mühling, Andreas","Schulte, Carsten"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2026,"date_issued":"2026-03-12","date_published":"2026-03-12","updated_at":"2026-07-24T01:35:31Z","subjects":["assessment","programming education","tracing","misconceptions","computer science education","formative assessment"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://macau.uni-kiel.de/receive/macau_mods_00008118","outbound_label":"Repository record","outbound_source":"source_url"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Mühling, Andreas","Schulte, Carsten"]},{"key":"dc:creator","label":"Author","values":["Bastian, Morten"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:publisher","label":"Institution","values":["Universitätsbibliothek Kiel"]},{"key":"dc:type","label":"Dc Type","values":["PhDThesis"]},{"key":"thesis:degree_level","label":"Degree Level","values":["thesis.doctoral"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Christian-Albrechts-Universität zu Kiel"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["assessment","programming education","tracing","misconceptions","computer science education","formative assessment"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Despite the growing relevance of programming education in recent years, there is still a lack of suitable, standardized assessments in the field. This shortcoming is especially present in the area of formative testing of novice programmers, where the focus is primarily on helping learners rather than on achieving performance-oriented outcomes. However, literature has shown that (many) learners encounter learning difficulties in the form of misconceptions during their learning process. Therefore, reliably and validly detecting them is a relevant task of assessment research. The detection would allow educators to plan further interventions to assist learners in overcoming their learning difficulties. My dissertation integrates findings from seven studies outlining a potential process for developing an adaptive assessment that employs item generation in the context of tracing elements of control flow. First, a static Rasch-scaled assessment is developed and evaluated for its effectiveness in detecting known misconceptions. Next, the selected item format is analyzed to understand its characteristics and the factors influencing item difficulty. Finally, the work describes and discusses the transition from the developed static Rasch-scaled assessment to an adaptive assessment that utilizes item generation, including an evaluation of the adaptive item selection process and the underlying item generator. The findings reveal that the selected item format can be used to detect misconceptions based on common patterns observed during the execution. A created test system can automatically analyze these patterns and provide programming educators with valuable insights into the cognitive processes of their learners. The developed adaptive assessment can decrease the time required to conduct a measurement by up to 49%. Moreover, switching from a static to an adaptive paradigm does not result in a significant loss of informativeness of the assessment."]},{"key":"dc:format.medium","label":"Dc Format Medium","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Adaptive Diagnostics of Programming Misconceptions"]}]}],"canonical_facts":{"dc:contributor":["Mühling, Andreas","Schulte, Carsten"],"dc:creator":["Bastian, Morten"],"dc:description.abstract":["Despite the growing relevance of programming education in recent years, there is still a lack of suitable, standardized assessments in the field. This shortcoming is especially present in the area of formative testing of novice programmers, where the focus is primarily on helping learners rather than on achieving performance-oriented outcomes. However, literature has shown that (many) learners encounter learning difficulties in the form of misconceptions during their learning process. Therefore, reliably and validly detecting them is a relevant task of assessment research. The detection would allow educators to plan further interventions to assist learners in overcoming their learning difficulties. My dissertation integrates findings from seven studies outlining a potential process for developing an adaptive assessment that employs item generation in the context of tracing elements of control flow. First, a static Rasch-scaled assessment is developed and evaluated for its effectiveness in detecting known misconceptions. Next, the selected item format is analyzed to understand its characteristics and the factors influencing item difficulty. Finally, the work describes and discusses the transition from the developed static Rasch-scaled assessment to an adaptive assessment that utilizes item generation, including an evaluation of the adaptive item selection process and the underlying item generator. The findings reveal that the selected item format can be used to detect misconceptions based on common patterns observed during the execution. A created test system can automatically analyze these patterns and provide programming educators with valuable insights into the cognitive processes of their learners. The developed adaptive assessment can decrease the time required to conduct a measurement by up to 49%. Moreover, switching from a static to an adaptive paradigm does not result in a significant loss of informativeness of the assessment."],"dc:format.medium":["application/pdf"],"dc:publisher":["Universitätsbibliothek Kiel"],"dc:subject":["assessment","programming education","tracing","misconceptions","computer science education","formative assessment"],"dc:title":["Adaptive Diagnostics of Programming Misconceptions"],"dc:type":["PhDThesis"],"thesis:degree_level":["thesis.doctoral"],"thesis:institution_name":["Christian-Albrechts-Universität zu Kiel"]},"updated_at":"2026-07-24T01:35:31Z"}