{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/99347"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/99347","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Applying Curricular Alignment to Improve the Effectiveness of CS Education","abstract":"According to Fossati and Guzdail, many CS instructors rely on their intuition, feedback from students and anecdotal advice from other instructors to make course improvements. Guzdail noted that: \"Computing educators' practice would dramatically improve if we drew on evidence, rather than intuition\". This means that Computer Science instructors may benefit from processes and tools that help them make informed changes to their curriculum. An evidence-based approach to course improvement is curriculum alignment, which evaluates the degree which the learning objectives, course content, and assessment methods are in agreement with each other. This provides instructors with a detailed view of their course and areas that need improvement. Current alignment processes are impractical for a course instructor to apply, requiring a panel of experts and training on the process. In this research, I developed a computer-assisted alignment process (CAAP) that uses the concept of traceability from software engineering, to define a process that is applicable by a single course instructor limiting the need for a panel of experts. In an initial application CAAP took 75 hours to apply, consequently a prototype alignment tool (AlignET) was designed to automates the new alignment process providing instructors with results they can use to make course improvements. I evaluated the practicality of AlignET by conducting collective case studies with four participants. Observations and interviews were used to collect data. AlignET reduced the time to complete CAAP to less than 11 hours and the participants identified course improvements, gaps in their instructional methods, and learning objectives they emphasized more than others. The findings from the case study presented key improvements to AlignET.","abstract_html":"According to Fossati and Guzdail, many CS instructors rely on their intuition, feedback from students and anecdotal advice from other instructors to make course improvements. Guzdail noted that: "Computing educators' practice would dramatically improve if we drew on evidence, rather than intuition". This means that Computer Science instructors may benefit from processes and tools that help them make informed changes to their curriculum. An evidence-based approach to course improvement is curriculum alignment, which evaluates the degree which the learning objectives, course content, and assessment methods are in agreement with each other. This provides instructors with a detailed view of their course and areas that need improvement. Current alignment processes are impractical for a course instructor to apply, requiring a panel of experts and training on the process. In this research, I developed a computer-assisted alignment process (CAAP) that uses the concept of traceability from software engineering, to define a process that is applicable by a single course instructor limiting the need for a panel of experts. In an initial application CAAP took 75 hours to apply, consequently a prototype alignment tool (AlignET) was designed to automates the new alignment process providing instructors with results they can use to make course improvements. I evaluated the practicality of AlignET by conducting collective case studies with four participants. Observations and interviews were used to collect data. AlignET reduced the time to complete CAAP to less than 11 hours and the participants identified course improvements, gaps in their instructional methods, and learning objectives they emphasized more than others. The findings from the case study presented key improvements to AlignET.","abstract_has_math":false,"creators":["Elsherbiny, Noha Ibrahim Mohamed"],"institution":"Virginia Tech","degree_name":"Doctor of Philosophy","degree_level":"doctoral","degree_discipline":"Computer Science and Applications","degree_department":"Computer Science","school":null,"contributors":[],"advisors":[],"committee_chairs":["Edwards, Stephen H."],"committee_members":["Perez-Quinonez, Manuel A.","Shaffer, Clifford A.","McCrickard, D. 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In an initial application CAAP took 75 hours to apply, consequently a prototype alignment tool (AlignET) was designed to automates the new alignment process providing instructors with results they can use to make course improvements. I evaluated the practicality of AlignET by conducting collective case studies with four participants. Observations and interviews were used to collect data. AlignET reduced the time to complete CAAP to less than 11 hours and the participants identified course improvements, gaps in their instructional methods, and learning objectives they emphasized more than others. 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In an initial application CAAP took 75 hours to apply, consequently a prototype alignment tool (AlignET) was designed to automates the new alignment process providing instructors with results they can use to make course improvements. I evaluated the practicality of AlignET by conducting collective case studies with four participants. Observations and interviews were used to collect data. AlignET reduced the time to complete CAAP to less than 11 hours and the participants identified course improvements, gaps in their instructional methods, and learning objectives they emphasized more than others. 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