Programming Assessments
A curated list of assessments, classifications and papers regarding programming asssessments
Visit http://www.barkmin.eu/programming-assessments/ for more details.
Contents
Assessments
Classifications
Papers
- Ahadi et.al (2013): Geek Genes, Prior Knowledge, Stumbling Points and Learning Edge Momentum: Parts of the One Elephant?
- Ahadi et.al (2019): ArAl: An Online Tool for Source Code Snapshot Metadata Analysis
- Alvarado et.al (2018): The Persistent Effect of Pre-College Computing Experience on College CS Course Grades
- Bari et.al (2019): {{EvoParsons}}: Design, Implementation and Preliminary Evaluation of Evolutionary {{Parsons}} Puzzle
- Barkmin (2020): Competency Structure Model for Programming for the Transition from School to University
- Blanchard et.al (2019): Effects of Code Representation on Student Perceptions and Attitudes Toward Programming
- Bockmon et.al (2019): (Re)Validating Cognitive Introductory Computing Instruments
- Bockmon et.al (2020): A CS1 Spatial Skills Intervention and the Impact on Introductory Programming Abilities
- Caceffo et.al (2016): Developing a Computer Science Concept Inventory for Introductory Programming
- Clifton (1995): Self-Assessment Procedure XXIII: Programming Languages
- Dierbach et.al (2005): Experiences with a CS0 Course Targeted for CS1 Success
- Fronza et.al (2019): An Exploration of Cognitive Shifting in Writing Code
- Izu et.al (2019): Fostering Program Comprehension in Novice Programmers - Learning Activities and Learning Trajectories
- Izu et.al (2020): Assessing CS1 Design Skills with a String Manipulation Task
- Jacková et.al (2019): Introductory Programming Exams and Their Benchmarking in Slovakia
- Joyner (2018): Toward CS1 at Scale: Building and Testing a MOOC-for-Credit Candidate
- Joyner (2018): Intelligent Evaluation and Feedback in Support of a Credit-Bearing MOOC
- Joyner et.al (2019): Replicating and Unraveling Performance and Behavioral Differences between an Online and a Traditional CS Course
- Liao et.al (2019): A Robust Machine Learning Technique to Predict Low-Performing Students
- Lister (2005): One Small Step toward a Culture of Peer Review and Multi-Institutional Sharing of Educational Resources: A Multiple Choice Exam for First Semester Programming Students
- Lodi (2019): Does Studying CS Automatically Foster a Growth Mindset?
- Luxton-Reilly et.al (2018): Developing Assessments to Determine Mastery of Programming Fundamentals
- Morrison (2017): Dual Modality Code Explanations for Novices: Unexpected Results
- Parker et.al (2016): Replication, Validation, and Use of a Language Independent CS1 Knowledge Assessment
- Parker et.al (2018): Socioeconomic Status and Computer Science Achievement: Spatial Ability as a Mediating Variable in a Novel Model of Understanding
- Patitsas et.al (2019): Evidence That Computer Science Grades Are Not Bimodal
- Porter et.al (2019): BDSI: A Validated Concept Inventory for Basic Data Structures
- Rosenstein et.al (2020): Identifying the Prevalence of the Impostor Phenomenon Among Computer Science Students
- Sheard et.al (2014): Benchmarking a Set of Exam Questions for Introductory Programming
- Simon et.al (2016): Benchmarking Introductory Programming Exams: Some Preliminary Results
- Somerville et.al (2020): Addressing Mixed Levels of Prior Knowledge by Individualising Learning Pathways in a Degree Apprenticeship Summer School
- Timmermann et.al (2016): Evidence-based re-design of an introductory course “programming in C”
- Xhakaj et.al (2018): Towards {{Improving Introductory Computer Programming}} with an {{ITS}} for {{Conceptual Learning}}
- Xie et.al (2019): An Item Response Theory Evaluation of a Language-Independent CS1 Knowledge Assessment
- Xie et.al (2020): The Effect of Informing Agency in Self-Directed Online Learning Environments
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